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Personal growth initiative across the life span: a systematic review protocol of quantitative studies using the Personal Growth Initiative Scale-II

• Katleen Verdoodt   ORCID: orcid.org/0000-0002-9572-8605 1 ,
• Marianne Simons 1 ,
• Natascha de Hoog 1 ,
• Jennifer Reijnders 1 &
• Nele Jacobs 1 , 2  

Systematic Reviews volume  13 , Article number:  127 ( 2024 ) Cite this article

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Personal Growth Initiative (PGI) a multi-dimensional construct, conceptualised as a skill set that helps individuals to intentionally grow is considered an important construct throughout the life span. Coping with the challenges, transitions, experiences and stressors of life requires an active growth orientation. In previous empirical research, the construct has been measured by either the PGIS-I or PGIS-II, of which only the latter takes account of the theoretically established multi-dimensionality of the construct. This paper describes the protocol for conducting a systematic review of published peer-reviewed empirical research articles on the multi-dimensional construct of PGI. The aim of this review is threefold: (1) to better understand the multi-dimensional construct PGI in different contexts and populations, (2) to improve our understanding of the reliability and validity of the PGIS-II in various research populations and (3) to obtain an overview of its associations with relevant psychosocial factors.

For the development of this protocol, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) reporting guidelines were used. Four databases and one registry will be searched using a predetermined search strategy for relevant studies. Studies will be screened, by two reviewers independently, against the established inclusion criteria. During the data extraction process, the quality of the included studies will be assessed using the Quality Assessment for Survey Studies in Psychology (Q-SSP). The collected data will then be analysed and reported in both narrative and tabular form according to the PRISMA 2020 statement guidelines and flow diagram.

The findings of this study will increase our understanding of the dynamics of PGI throughout the lifespan, its associations with other psychosocial factors and the psychometric properties of the PGIS-II. It will also clarify where additional research is needed. The objectives of the proposed review can provide a basis for the development of practical applications and interventions.

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PROSPERO CRD42022377342.

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From a lifespan perspective, personal growth is considered to be essential for a well-functioning individual [ 1 ] and found to be a key element for maintaining and enhancing well-being and positive psychological functioning throughout the different life stages [ 2 , 3 ]. Growth can occur without the awareness of the individual, which is often the case in biological growth processes, or entail a conscious process as a result of an important life event [ 4 ]. Intentional growth occurs when the individual is not only aware of the changes but also takes active action to achieve growth [ 5 ]. The concept of Personal Growth Initiative (PGI), related to the latter, is described as conscious and active involvement in personal growth processes [ 1 ] and is considered to be a multi-dimensional construct composed of cognitive and behavioural components [ 1 , 6 ]. The cognitive component entails knowledge, beliefs, attitudes and values that foster personal growth. The implementation of the cognitive component in conjunction with decisions to actively make changes constitute the behavioural component [ 7 ]. PGI can be seen as a range of skills that assist individuals to engage in self-change across different life domains [ 6 ].

To further empirically explore the concept of PGI, Robitschek [ 1 ] developed the Personal Growth Initiative Scale (PGIS). Although the observed psychometric properties were sufficient, the original PGIS has two major shortcomings. First, not all items included are intrinsic to intentional personal growth [ 8 ]. Second, PGI is measured as a one-dimensional construct [ 1 ] and, consequently, no distinction is made between the previously established cognitive and behavioural components of the concept [ 8 ]. Subsequently, Robitschek et al. [ 8 ] developed the multi-dimensional Personal Growth Initiative Scale-II (PGIS-II), which to the best of our knowledge, currently remains the only scale that measures PGI as a multi-dimensional construct. The scale has four correlated factors, namely: readiness for change, planfulness, using resources and intentional behaviour. The cognitive component comprises readiness for change and planfulness. The behavioural component is constituted by using resources and intentional behaviour. With its multifactor structure, this scale provides a more profound measurement of PGI. The influence of each factor on growth efforts can be determined, as can the relationship with psychosocial factors. In addition to individual differences, population-level variations may also occur [ 8 ]. Cultural background can be influential as there are cultural differences in growth motivation and psychological desire to grow [ 6 ].

The PGI concept was developed from counselling practice and is consistent with the humanistic view of personal growth as a way of approaching life [ 1 ]. Active interest in self-change, therefore, differs from the recognition that change is inherent to human development [ 8 ]. PGI shows similarities with the tendency toward self-actualization by focusing on growth orientation but emphasises the individual’s active and intentional involvement in changing and developing as a person. PGI skills can be present throughout the entire course of life [ 6 ]. By encouraging active growth in various life domains [ 8 ] and providing the skills needed for a productive and fulfilling life [ 1 ], PGI contributes to the optimal functioning of the individual and belongs to the essence of eudemonic well-being [ 9 ] where the actualisation of human potential is key [ 10 ]. As such, research has shown that higher levels of PGI are associated with greater well-being [ 9 , 11 ] and PGI has proven to be an antecedent of well-being [ 1 ]. Meanwhile, positive relationships have also been found with other psychosocial factors such as assertiveness [ 8 ], life satisfaction [ 12 , 13 ] and positive affect [ 12 ].

In summary, PGI is an important construct throughout the life course. Coping with the challenges, transitions, experiences and stressors of life requires an active growth orientation [ 8 ]. A systematic review of research on PGI, as a multi-dimensional construct, may contribute to a better understanding of the dynamics of PGI across the lifespan.

A previous review conducted in 2016 [ 14 ] included many studies using the PGI-I scale, studying PGI as a one-dimensional rather than a multi-dimensional construct. The variation in research populations of the studies included in this review was limited, as most of the studies of personal growth during the period covered by this review involved student populations [ 14 , 15 ]. The current paper describes a protocol for a systematic review that focuses on studies that measured PGI as a multi-dimensional construct and thus covers the period from 2012, when the PGIS-II was developed, to the present day. According to Weigold et al. [ 16 ], several more recent studies have addressed population diversification, finding associations between PGI, well-being and related factors in varying life stages and across populations. As a result, this review may provide a better understanding of the dynamics of PGI over the course of life.

Study objectives

The aim of this review is to better understand the multi-dimensional construct PGI across the life span and in different populations, its measurement and its importance for mental well-being. To achieve this, three objectives were formulated. The first objective, exploring the different research populations in which PGI has been studied, will help to better understand the dynamics of PGI throughout the lifespan. The second objective concerns the psychometric characteristics of the PGIS-II and will improve our understanding of the reliability and validity of this scale in various research populations. The third objective, examining the associations found with psychological factors and well-being, will also enhance the understanding of PGI as a construct across the life course. This will complement findings from the earlier mentioned review [ 14 ], which included several early studies using the PGIS-II and found some evidence for the stability of the four-factor structure of the PGIS-II, albeit inconsistently.

Corresponding with the formulated objectives, the proposed systematic review will address the following questions:

In which different contexts and populations has PGI been studied?

What are the psychometric properties of the PGIS-II in different research populations?

What psychosocial factors have been found to be related to PGI across the lifespan?

Although several psychosocial factors have been identified in the earlier review [ 14 ] and meta-analysis [ 16 ] among student populations, such as self-efficacy [ 17 ], psychological adjustment [ 17 ], depressive symptoms and rumination [ 18 ], the psychosocial factors will not be specified in advance in this protocol. More recent studies including other research populations may focus on a variety of psychosocial factors, which may have not yet been addressed in previous research. In the next section, the method of the proposed systematic review is discussed in more detail.

Protocol design

This systematic review protocol uses the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) reporting guidelines [ 19 ] as the conceptual framework (see Additional file 1).

Eligibility criteria

The systematic review will include quantitative peer-reviewed studies using the PGIS-II scale and published in the English language from 2012. All ages, across populations and settings, will be included to provide a lifespan perspective on PGI as measured with the PGIS-II. Studies will be excluded if (a) the full text is not available (b) no sufficient details are provided about the intended population (e.g. age, gender, cultural background,…) or the psychometric qualities of the scale or correlations with psychosocial factors are missing (authors will be contacted in case of insufficient details). The number of excluded studies will be recorded at each stage with the reason for exclusion.

To answer the first research question, reported data contains the general characteristics of the included studies and details of the population being studied such as age, gender, type of respondents (e.g. general population, students,..), and cultural background. To answer the second research question, the data items of interest comprise the identified factor structure with fit indices and the internal consistency and test–retest reliability of both the total scale and the subscales. Data in validation studies concerning correlations with other constructs and measurement scales will provide evidence for the concurrent, convergent and discriminant validity of the PGIS-II. Also, data regarding measurement invariance of the scale across samples will be captured. Finally, the data items of interest for the third research question consist of all reported psychosocial factors (e.g. well-being, life satisfaction, psychological distress,…) and their correlations with the overall PGI score and the PGI dimensions.

Search strategy

An extensive search will be performed in the following databases and registers: EBSCO host, PubMed and Web of Science. Two publisher databases will also be searched, namely ScienceDirect and Wiley online library. Additional snowball and citation searches will be performed on the reference lists of the eligible studies. New identified articles that meet the eligibility criteria will also be included. The published literature will be systematically searched using predefined search terms combined with the Boolean operator “OR”. The search terms for the title, abstract and body text are ‘Personal Growth Initiative’ and ‘PGIS-II’. A preliminary search of the literature in the Pubmed database revealed that the search term 'PGI' produced an excess of irrelevant results. Apparently, the abbreviation PGI has different meanings and is also used in medical research literature. Consequently, it will not be used in the final searches. The elaborated search strategy for the PubMed database in (Table 1 ) will be adapted for use in the other databases and registries.

Study screening and selection

The results of the systematic searches will be transferred to Zotero [ 20 ], an open-source bibliographic software manager, where duplicates will be discarded. Studies will then be screened for eligibility based on title and abstract according to the inclusion and exclusion criteria. All identified studies will also be screened independently by a second reviewer. Discrepancies will be cleared through discussion or third-party consultation. Next, the full text of the potentially eligible studies will be examined. Finally, the reference list of the included studies will be checked to find additional studies. To include these additional studies the full text will be screened by the two reviewers. The screening process will be presented according to the PRISMA flow diagram [ 21 ].

Data collection process

Two reviewers will perform data extraction using a Microsoft Excel data extraction sheet developed for this review. A codebook provides guidance for completing the extraction sheet. Before starting the final data extraction, a trial will be conducted to check for consistency among the reviewers. Discrepancies between the reviewers will be resolved through discussion or third-party consultation. To finalise the data extraction, the reviewers will compare the completed datasheets and produce a definitive datasheet by mutual agreement. The extracted data will include title, author, year, country, characteristics of the research populations, psychometric qualities and factor structure of the PGIS-II and significant correlations with examined psychosocial factors. The data extraction sheet can be refined by the reviewers, during the data extraction, to ensure the suitability and usability of all the fields.

Risk of bias in individual studies

To assess the quality of the included studies, the Quality Assessment for Survey Studies in Psychology (Q-SSP) [ 22 ] will be used. The Q-SSP is a 20-item checklist that offers the possibility of assessing the methodological quality of the key elements of a survey study. A separate tab in the Excel file for data extraction is provided for the quality assessment. To ensure sufficient quality of the included studies, 70% is adopted as the threshold for the current review, which is in line with the guidelines of the Q-SSP checklist (Protogerou and Hagger, 2020) If the quality is considered to be inferior, the reason will be stated in the comments on the datasheet. Methodological limitations that have been identified will be considered in the discussion of the results and conclusions. The quality of the included studies will be rated independently by two reviewers. Inter-rater reliability will be checked for consistency and discrepancies will be cleared through discussion or third-party consultation.

Data synthesis, presentation and dissemination of findings

The objective of this systematic review is to provide a comprehensive overview of the studies on PGI using the PGIS-II as a measurement, the populations in which it is measured, the psychometric qualities of the scale and the relationships found with psychosocial factors. Therefore, a synthesis of the results will be reported in both narrative and tabular form. To write up the final systematic review the PRISMA 2020 statement guidelines and flow diagram [ 19 ] to report on the search findings will be followed. The review will be submitted for publication in an international peer-reviewed journal.

Throughout the life course, personal growth can be considered an important component of optimal functioning and well-being. The earlier review, discussed in the introduction [ 14 ], has provided a useful starting point for a better understanding of the concept of PGI and the contribution of PGI skills to intentional growth moments. A previously conducted meta-analysis [ 16 ] has shed light on several psychosocial factors related to PGI. The current review explicitly focuses on PGI as a multi-dimensional construct and hopes to include studies that vary in research populations, in order to clarify the extent to which PGI has been studied across different life stages and cultural backgrounds and where additional research is needed. The stability of the multifactorial measurement scale when used across populations also merits additional attention. In addition, the objectives of the proposed review may also provide a basis for the development of practical applications and interventions. Uncovering associations between PGI and other factors, throughout different life stages, can help design targeted interventions to promote PGI.

By using the PRISMA guidelines [ 19 , 21 ] to shape this protocol, a solid framework for research was created. However, by including only peer-reviewed studies, publication bias is a risk. Consequently, such bias can be seen as a limitation of this review.

Availability of data and materials

Not applicable.

Abbreviations

Personal Growth Initiative

Personal Growth Initiative Scale-II

Preferred Reporting Items for Systematic Reviews and Meta-Analyses–Protocols

PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews

International prospective register of systematic reviews

Quality Assessment for Survey Studies in Psychology

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Katleen Verdoodt, Marianne Simons, Natascha de Hoog, Jennifer Reijnders & Nele Jacobs

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KV, MS and JR prepared the first draft of the systematic review protocol. Each of the authors delivered critical revisions and approved the final manuscript.

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Verdoodt, K., Simons, M., de Hoog, N. et al. Personal growth initiative across the life span: a systematic review protocol of quantitative studies using the Personal Growth Initiative Scale-II. Syst Rev 13 , 127 (2024). https://doi.org/10.1186/s13643-024-02546-9

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Personal Growth and Well-Being in the Time of COVID: An Exploratory Mixed-Methods Analysis

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The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The physical distancing measures necessitated by COVID-19 have resulted in a severe withdrawal from the patterns of daily life, necessitating significantly reduced contact with other people. To many, such withdrawal can be a major cause of distress. But, to some, this sort of withdrawal is an integral part of growth, a pathway to a more enriching life. The present study uses a sequential explanatory QUAN-qual design to investigate whether people who felt that their lives had changed for the better after being forced to engage in physical distancing, what factors predicted such well-being, and how they spent their time to generate this sense of well-being. We invited 614 participants who reported closely following physical distancing recommendations to complete a survey exploring this topic. Our analyses, after controlling for all other variables in the regression model, found a greater positive association between presence of meaning in life, coping style, and self-transcendent wisdom and residualized current well-being accounting for retrospective assessments of well-being prior to physical distancing. An extreme-case content analysis of participants' personal projects found that participants with low self-transcendent wisdom reported more survival-oriented projects (e.g., acquiring groceries or engaging in distracting entertainments), while participants reporting high self-transcendent wisdom reported more projects involving deepening interactions with other people, especially family. Our findings suggest a more nuanced pathway from adversity to a deeper sense of well-being by showing the importance of not merely coping with adversity, but truly transcending it.

The physical distancing measures necessitated by the COVID-19 pandemic have resulted in a massive withdrawal from the habitual patterns of daily life and in significantly less contact with other people. To many, such withdrawal can lead to disconnection and loneliness, a major cause of stress, anxiety, depressive symptoms, self-harm, and suicidal ideation (Goldsmith et al., 2002 ; Cacioppo et al., 2006 ; Meltzer et al., 2013 ). Research on the effects of current lockdown and physical distancing protocols has already begun to ring alarm bells. Physical distancing policies have been found to have overall negative effects on the mental health of young adults in China, exacerbated by a steady stream of dire news about the pandemic (Chen et al., 2020 ). Participant samples from California and the UK have reported feeling more hopeless and less engaged than a comparison group of first-time incarcerated inmates (Dhami et al., 2020 ). Furthermore, increased rates of substance use have also been seen as result of loneliness and isolation as individuals are using substances to cope with the emotional impact of the pandemic (Czeisler et al., 2020 ). Loneliness affects people of all ages, genders, and socioeconomic status. A study that examined loneliness as a predictor of mental health outcomes found that individuals experienced an increase in mental health symptom severity and decreased recovery and quality of life scores (Wang et al., 2020 ). Such effects appear to be heightened among already vulnerable population, with loneliness being found to be particularly detrimental to the mental health of certain vulnerable societal groups such as seniors, migrants, asylum seekers and those in the LGBT population (Eres et al., 2020 ); often the same populations most at risk as a result of the current pandemic.

Prior to the pandemic, North America was already beginning to demonstrate a worrying culture of disconnection, with people feeling increasingly isolated. The meteoric rise in single-person households over the past decade was accompanied by an increase in feelings of loneliness and disconnection (Snell, 2017 ), along with a marked increase in major depressive episodes among those born in both the 1990's and 1950's (Twenge et al., 2019 ). Religious institutions, formerly a major source of interpersonal connection and meaning-making (Park et al., 2013 ), have seen a steady decline in membership, which Eberstadt ( 2013 ) directly ties to more people living alone. While loneliness and disconnection were already a topic of concern, the pandemic, fueling further separation of family units and closure of churches in many parts of the world, is likely to have exacerbated an already worrying trend. Or has it?

While loneliness is well-known to have negative impacts on many aspects of mental and physical health, solitude, or at least some form of withdrawal from mundane activities, is a necessary part of achieving higher forms of development in many religious and spiritual traditions, from the Desert Fathers of Christianity to the Sannyasis of Hinduism. The Buddhist Dhammapadda, likewise, uses the image of the elephant walking alone through the jungle to symbolize the often-solitary path of the aspirant in search of enlightenment. Modern qualitative research with spiritual aspirants (Thomas, 1991 ; Durà-Vilà and Leavey, 2017 ) finds that they consider solitude an integral part of their pursuit of wisdom, a way for them to engage in uninterrupted reflection and meditation. Barbour ( 2004 , 2013 ) has argued that aloneness is an intrinsically spiritual value; seeking separation from the ordinary rhythms of societal life is a time-honored way to open oneself up to greater sources of connection and meaning. Averill and Sundararajan ( 2014 ) argue that the spiritual value of solitude comes from a relational soft reset, allowing one to focus on cultivating one's relationships with higher or greater sources of meaning. Solitude is often pursued as a strategy for affective self-regulation, a way to recover from intense emotional experiences (Nguyen et al., 2018 ).

The benefits of solitude for personal and spiritual growth, however, make two key assumptions: that solitude is both voluntary and used constructively. This is particularly clear in studies of aloneness in children: while self-determined solitude is consistently associated with positive developmental outcomes, non-self-determined solitude is associated with greater loneliness and its accompanying long-term problems (Galanaki, 2013 ; van Zyl et al., 2018 ; Corsano et al., 2020 ). Regarding the use of solitude, Lay et al. ( 2019 ) found that trait self-reflection, by definition involuntary, was more strongly associated with negative solitude experiences than positive, suggesting a greater opportunity for moments of despair when forced to be alone with one's thoughts. However, Weststrate ( 2019 ) found that deliberate exploratory reflection on one's life is a vital component in developing wisdom and a meaningful life.

As humans are inherently relational creatures, involuntary solitude may open up greater opportunities for individuals to experience an existential vacuum [see Frankl ( 1963 ), Garfield ( 1973 ), Reker et al. ( 1987 )]. Weinstein et al. ( 2012 ) observe that the notion of existential vacuum in existential psychology, as well as the phenomenon of pervasive motivation in literature on self-determination theory, are associated with a sort of epistemological loneliness, a feeling of being mentally alone. Without strong relationships in place, or the capacity to build them, the sense of aloneness can become unbearable. Those who do have such strong relationships with others, or with greater things, likely have less cause for concern. People with stronger relationships tend to weather involuntary solitude better (Pauly et al., 2018 ), as do those who have built a healthy relationship with solitude itself, by being more likely to seek it out (Lay et al., 2019 ). Lay et al. ( 2019 ) also found that greater social self-efficacy was another good predictor of positive experiences of solitude, which helps reconcile Wei ( 2020 ) finding that introverts are suffering more than expected under lockdown conditions in the United States. It takes a good deal of self-confidence to be alone; under present conditions, an aptitude for it may not be enough.

As a result of COVID-19, humanity is currently experiencing involuntary solitude on an unprecedented scale. However, as per the tenets of existential positive psychology (Wong, 2020 ), times of such great suffering also provide the greatest opportunities for growth. Looking to history, we have some reason to be optimistic—or perhaps tragically optimistic (Wong and McDonald, 2002 ; Leung, 2019 ). Loneliness became an important factor during the 2003 SARS epidemic, as well, but resulted in increased social cohesion due to the detrimental impact of isolation (Lau et al., 2005 ; Saltzman et al., 2020 ). Even in the early stages of the pandemic, during the spring and summer of 2020, a large-scale narrative inquiry conducted in Italy found that some participants were already beginning to represent the pandemic as a time for re-evaluation of personal and social priorities, not just as a crisis (Venuleo et al., 2020 ).

According to the MORE Wisdom Model (Weststrate and Glück, 2017 ; Weststrate, 2019 ; Glück, in press ), “critical life experiences”—typically disruptive to life as usual—are important to fostering the development of wisdom, when accompanied by the exploratory reflective processing. This is very much in line with prominent models of post-traumatic growth, most notably the model championed by Tedeschi and Calhoun ( 1996 , 2004 ; Blevins and Tedeschi, in press ), according to which post-traumatic growth is a process of self-transformation involving the reconstruction of an individual's basic assumptions about how life ought to be lived to promote future flourishing. Paradoxically, post-traumatic growth involves: a greater appreciation for one's life, a newfound sense of personal strength, improved relationships, and consequently, greater wisdom. Indeed, with the right perspective, adverse events causing suffering can be transformed in the moment, potentially ameliorating the negative effect during, rather than after, the ongoing traumatic event (Leung, 2019 ; Mead et al., 2020 ; Wong, 2020 ).

Thus, the isolation caused by the pandemic gives us cause for both concern and optimism. On the one hand, such isolation can and does impact most people negatively. On the other hand, strong relationships can help people weather such times of suffering, and such disruptions offer the opportunity to take stock of one's world and re-evaluate one's priorities. As per PP2.0 (Wong, 2020 ), if one is able to take this time of suffering and necessary solitude, affirm it, and use it to grow, one can come to experience greater meaning and well-being than before such trials—an understanding that has a long history in philosophy and clinical psychology (Halling and Nill, 1995 ). If anyone is lucky enough to feel that they have grown as a result of the current pressures to self-isolate, it is likely people who have focused on the key things in life: forging connections and finding meaning. If this is how some people have been spending this time, they have spent this time wisely.

The present exploratory mixed-methods study began with these two questions: (1) How do North Americans feel they have been doing since the introduction of physical distancing measures, and (2) how are they spending their time? Using an explanatory QUAN-qual design, this paper describes and elucidates our finding that it is the relationships we build, and the things we care about, that lead to a life of flourishing, even in the face of global suffering.

This study was approved by the Research Ethics Board at the University of Toronto. Workers on Amazon's Mechanical Turk chose to participate in our human intelligence task which was advertised as a study on coping with the COVID-19 pandemic. Workers were directed to a link to participate in our online survey, hosted on Qualtrics. All participants gave informed consent before starting the survey. In part one, a screening was made in which participants indicated the extent of their engagement in physical distancing practices before completing a series of measurements in which they were instructed to respond while reflecting on their life prior to physical distancing. These included instruments on well-being, personal wisdom, presence and search for meaning, coping styles, negative emotion, and alienation.

Participants who reported closely following physical distancing recommendations were invited to complete a second stage of the survey, in which participants completed many of the same measures for a second time, this time reflecting on their life and experiences as they were at the time of completion (see Table 1 for list of measures completed in each section of the survey). They also completed additional measures of self-transcendent wisdom and engagement in personal projects. This two-stage design and broad array of measurements were intended to capture participants' experiences of physical distancing, their motivations for doing so, how they felt life has changed under distanced conditions, and why. Participants were not aware that their responses from the pre-physical distancing measures would be compared with their responses on the later set of measures related to the current time of completion.

List of measures completed in each section of the survey.

Participants

Data was collected from mid-April to end-of-July, 2020, through a two-part online survey distributed via Amazon's Mechanical Turk platform to residents of Canada and the U.S.A. To ensure the quality of our data, we implemented many approaches in the collection of our responses from Amazon's Mechanical Turk platform and screened participant data for problematic responses. On Mechanical Turk, workers were required to have a “human intelligence task” (HIT) approval rating ≥90, later upgraded to ≥95, along with having ≥100 HITs previously approved. We also included two attention checks (e.g., “select _ for this item”), one in each half of the survey. Workers who failed all attention checks that they came across were excluded from the study (n.b., individuals who did not pass the pre-established physical distancing cut-off score only encountered one attention check). IP duplications in submitted responses were screened and examined 1 . Open-ended questions within the Personal Projects Analysis Workbook (measure detailed in the following section) were assessed by two graduate coders for problematic responses, and cases that contain copy-paste responses or answers that did not relate to the prompt were removed from the study. Lastly, participants who scored the same responses for all items across several measurements (i.e., having standard deviations equal to 0 across several measurements) were removed before data analysis.

The final sample of physically-distanced participants consists of 274 Americans and 340 Canadians ( N = 614), with 279 females and 334 males with a mean age of 35 (see Table 2 ). Of these participants, 50% had a bachelor's degree or equivalent. Most household income were between C$40,000 and C$60,000. The mean number of children participants had was 0.78 ( Table 2 ).

Demographics ( N = 614).

Physical Distancing

Participants were asked how much they were participating in physical distancing measures by staying home, avoiding visiting others or having others visit them at home, avoiding religious gatherings and other social events, limiting trips to the grocery stores, or outdoor activities, and maintaining a safe distance from people who have traveled, in stores, or showing COVID-related symptoms; also whether they were canceling travel plans, quarantining after travel, self-isolating due to symptoms or close contact with people who had then, and generally following public health guidance about COVID as much as possible. Participants rated the extent to which they did so on a scale from 0 (Not at all) to 10 (To my best ability). Participants who scored an average of eight or above on all items were permitted to fill out additional questionnaires, as we were only interested in those who were physically distancing most of the time. Only participants who scored an average of eight or above on our measure of physical distancing are included in the present study.

Religiosity and Spirituality

Participants were asked to rate on a scale from 0 (Not at all religious/spiritual) to 10 (Very religious/spiritual) how religious or spiritual they were, in order to measure both the degree of religiosity and the degree of spirituality separately.

The Brief COPE Inventory (Carver, 1997 ) was used to measure coping styles used after physical distancing was enacted. This measure consists of 28 items with 14 subscales: (1) self-distraction (e.g., “I've been turning to work or other activities to take my mind off things”), (2) active coping (e.g., “I've been concentrating my efforts on doing something about the situation I'm in”), (3) denial (e.g., “I've been saying to myself "this isn't real”), (4) substance use (e.g., “I've been using alcohol or other drugs to make myself feel better”), (5) emotional support (e.g., “I've been getting emotional support from others”), (6) instrumental support (e.g., “I've been getting help and advice from other people”), (7) behavioral disengagement (e.g., “I've been giving up trying to deal with it”), (8) venting (e.g., “I've been saying things to let my unpleasant feelings escape”), (9) positive reframing (e.g., “I've been trying to see it in a different light, to make it seem more positive”), (10) planning (e.g., “I've been trying to come up with a strategy about what to do”), (11) humor (e.g., “I've been making jokes about it”), (12) acceptance (e.g., “I've been accepting the reality of the fact that it has happened”), (13) religion (e.g., “I've been trying to find comfort in my religion or spiritual beliefs”), and (14) self-blame (e.g., “I've been criticizing myself”). Each item is rated on a 4-point Likert scale, ranging from 1 (I haven't been doing this at all) to 4 (I've been doing this a lot). In our study, overall Cronbrach's alpha was good (Alpha = 0.84).

Personal Wisdom

The 12-item Abbreviated Three-Dimensional Wisdom Scale (3D-WS-12; Thomas et al., 2017 ) was used to measure personal wisdom. This scale selects items from Ardelt's ( 2003 ) original scale, which includes three dimensions: cognitive (e.g., “I try to anticipate and avoid situations where there is a likely chance I will have to think in depth about something”), compassionate (“Sometimes I feel a real compassion for everyone”), and reflective (e.g., “I either get very angry or depressed if things go wrong”). Scores were rated on a 5-point Likert scale, ranging from 1 (Definitely true of myself) to 5 (Not true of myself). Total scores are calculated by taking the mean of all items on the scale. Cronbach's alpha for the 3D-WS-12 was good (Alpha = 0.81).

Social Support

To measure participants' perceptions of social support, we used the Multidimensional Scale of Perceived Social Support (MSPSS; Zimet et al., 1988 ). This measure consists of 12 items and three subscales: (1) Significant other (e.g., There is a special person who is around when I am in need), (2) Family, (e.g., I can talk about my problems with my family), and (3) Friends (e.g., My friends really try to help me). All items were answered on a 7-point Likert scale ranging from 1 (Very strongly disagree) to 7 (Very strongly agree). Total scores are calculated by taking the mean across the raw score from each item. Cronbach's alpha for the MSPSS was excellent (Alpha = 0.94).

The PERMA-profiler (Butler and Kern, 2016 ), was administered to measure participants' well-being. The PERMA-profiler assesses well-bring across five subscales, also known as the five pillars of well-being: positive emotion, engagement, relationships, meaning, and accomplishment. The final well-being score is the mean across all PERMA subscale items. To determine if participants perceived their well-being as being different during and prior to physical distancing, participants completed both retrospective and current versions of the measure. Total scores and subscale scores were calculated for both pre-pandemic and current moment. Cronbach's alpha for the well-being subscale of the PERMA pre-pandemic and at the current moment were excellent at 0.96. The PERMA also includes as negative emotion subscale, whose Cronbach's alphas were good at 0.83 (pre-pandemic) and 0.85 (at the current moment). The loneliness subscale contains only one item, so Cronbach's alpha cannot be computed.

Meaning in Life

The Meaning in Life Questionnaire (MLQ; Steger et al., 2006 ) was used to measure both search for, and presence of, meaning in life before physical distancing (pre-pandemic) and once physical distancing had been enacted (at the current moment during the pandemic). The measure consists of 10 items, such as “I am looking for something that makes my life feel meaningful” (search for meaning, 5 items) and “I understand my life's meaning” (presence of meaning, 5 items). Participants rated these items on a 7-point Likert scale, ranging from 1 (absolutely untrue) to 7 (absolutely true). To determine if participants perceived their experienced sense of meaning in life as being different during and prior to physical distancing, participants completed both retrospective and current versions of the measure Total scores for search and presence of meaning were calculated separately and scores for pre-pandemic, current moment, and a pre-post difference score were calculated for each subscale. Cronbach's alpha for the search for meaning at 0.94 (pre-pandemic) and 0.95 (at the current moment), and presence of meaning at 0.94 (pre-pandemic) and 0.90 (at the current moment), were all excellent.

Self-Transcendent Wisdom

The Adult Self-Transcendence Inventory (ASTI; Levenson et al., 2005 ) was used to measure wisdom as self-transcendence since the beginning of physical distancing (self-reported at the present moment). The ASTI broadly defines self-transcendence as decreased egoic self-saliency and increased sense of connectedness. It consists of 29 items with six subscales (Koller et al., 2017 ). Five subscales measure self-transcendent wisdom: (1) Self-Knowledge and Integration (e.g., “Since physical distancing was enacted, I have better sense of humor about myself”); (2) Peace of Mind (e.g., “Since physical distancing was enacted, I am more often engaged in quiet contemplation”); (3) Non-Attachment (e.g., “Since physical distancing was enacted, I have become less concerned about other people's opinions of me”); (4) Self-Transcendence (e.g., “Since physical distancing was enacted, I feel that my individual life is a part of a greater whole”); and (5) Presence in the Here-and-Now and Growth (e.g., “Since physical distancing was enacted, I find more joy in life”). Participants rated on a 4-point Likert scale, ranging from 1 (Disagree strongly) to 4 (Agree strongly). Total scores were calculated by taking the mean of all individual items in the self-knowledge and self-integration, peace of mind, non-attachment, self-transcendence, and presence in the here-and-now and growth subscales, as recommended for measuring overall self-transcendent wisdom. The 6th scale, Alienation (e.g., “Since physical distancing was enacted, I feel that my life has less meaning”), was treated as an individual subscale in all analyses, following Koller et al. ( 2017 ). Cronbach's alpha for the total score was excellent (Alpha = 0.94), and for alienation was acceptable (Alpha = 0.65). Unlike our other measures, the ASTI is designed to assess the difference between the present moment and some previously specified time. As such, participants only filled out a single version of the ASTI.

Personal Projects

Finally, the Personal Projects Analysis Workbook (PPAW; Little, 1983 ) Module 1 was used to solicit participants' personal projects; that is, their most important goals and activities. Personal projects analysis conceptualizes the individual as collections of ongoing personal projects, as opposed to collections of personality traits. The PPAW Module 1 invites participants to list as many ongoing projects as comes to their mind—from the immediately utilitarian (e.g., “Mow the lawn”) to the most abstract (e.g., “Clarify my philosophy of life”). In separate sections of the survey, participants were asked to generate separate lists of personal projects both prior to and during physical distancing.

Analytic Strategy

Latent profile analysis.

To reduce the number of variables in later regression analyses, we conducted a latent profile analysis (LPA) on the 14 coping subscales from the Brief COPE (self-distraction, active coping, denial, substance use, emotional support, instrumental support, behavioral disengagement, venting, positive reframing, planning, humor, acceptance, religion, and self-blame) to identify latent subgroups of individuals who engaged in physical distancing, using the tidy LPA package in R (Berlin et al., 2014 ; Rosenberg et al., 2018 ). Mean differences were tested across the latent profiles.

Four different models containing from 1 to 7 profiles were evaluated using the Bayesian Information Criterion (BIC) and Akaike Information Criterion (AIC) fit indices (Schwarz, 1978 ). Lower values for the AIC and BIC indicate better model fit and demonstrate the fewest parameters among a set of non-hierarchical models. The BIC is preferable in determining the best model fit over the other fit statistics (Nylund et al., 2007 ). Moreover, a bootstrap likelihood ratio test (BLRT) examined the statistical significance for model comparisons, by comparing the neighboring models as the number of classes decrease (McLachlan and Peel, 2000 ). A significant p -value for this test also indicates better model fit as profiles are added. To assess the certainty with which participants were classified into latent profiles, the entropy value was also considered, since it provides information regarding the accuracy of the models, with a range from 0 to 1. An entropy value of 0.80 or above is preferred and indicates an accuracy of >90% (Berlin et al., 2014 ). The best fitting model was chosen based on these criteria. See Table 2 for sample mean and standard deviations of the coping variables.

Multiple Linear Regression

Multiple linear regression models were used to explore the relationship between coping styles, personal wisdom, social support, self-transcendent wisdom, religiosity, spirituality, health, meaning in life, negative emotions, loneliness, alienation, and well-being. In particular, we are interested in investigating how these variables affected: (1) participants' retrospective pre-physical distancing well-being, and (2) the variance in reported current well-being (at the time of data collection) not explained by its pre-distancing level.

Descriptive statistics of the outcome and predictor variables are presented in Table 3 . In preparation for multiple regression analyses, study variables were mean-centered by subtracting total sample mean from subscale or total scores. For variables where retrospective pre-physical distancing ratings were available (i.e., well-being, health, presence of and search for meaning in life, negative emotion, loneliness), unstandardized residuals were computed by regressing “during-physical distancing” scores on their respective pre-physical distancing values, to parse out the contribution of the baseline pre-physical distancing condition from change in performance during physical distancing and to mitigate multicollinearity ( Table 4 ).

Descriptive statistics of study variables ( N = 614).

Predicting current levels of performance with retrospective pre-physical distancing levels.

Nested robust multiple linear regressions were conducted in Stata/IC 16. Coping profiles obtained from the LPA were transformed into dummy variables, using the profile of participants who mainly used adaptive coping strategies as the reference group. Examinations of the correlation table (see Appendix A ) and scatter plots suggested possible interaction effects between coping profiles and self-transcendent wisdom; therefore, a side-by-side comparison was made between models with and without the interaction terms. Additional F -tests were carried out to examine the statistical significance of the slopes of the predictor variable self-transcendent wisdom for people belonging to each coping profile. Paired-sample t -tests and one-way ANOVA analyses were conducted to explore possible group differences by nation, gender, educational level, marital status, religious affiliation, and annual household income in 2019 (See Appendix B for details). All models controlled for the main effects of nation, gender, educational level, marital status, religious affiliation, and household income prior to physical distancing (i.e., 2019).

Personal Projects Analysis

To elaborate on possible reasons for any changes in experience, we used personal projects analysis (Little, 1983 ) to examine how participants spent their time both before and after physical distancing measures went into effect. With the results of the regression analysis suggesting an important role of self-transcendent wisdom, we conducted an extreme cases analysis of the personal projects of the participants with the highest ( n = 76) and lowest ( n = 76) self-transcendent wisdom scores, ~25% of the total sample. Logistic regressions were employed to explore the effects of demographic characteristics on high-low self-transcendence group membership. The first and fourth authors, coding independently, content-coded participants' personal projects. The first author is a researcher in humanistic psychology with previous experience using the Personal Projects Analysis Workbook (Kim et al., 2020 ), while the fourth author has previous experience coding life narrative research. Personal projects were sorted into categories established by previous research in personal projects analysis (Little and Gee, 2007 ). Discrepancies were resolved via discussion between the authors.

After comparing fit indices and entropy levels across all four models (see Table 5 ), a four-profile model was chosen to best classify coping strategies of participants who were physically distancing (see Figure 1 and Table 6 ). Each profile has been named after its most prominent form of coping, or, in the case of Profile 4, a core feature.

Fit statistics for LPA (Model 3: equal variances and equal covariances).

The selected model is bolded .

The four latent profiles of coping mechanisms among individuals who are physically distancing. Profile 1: religious coping ( n = 144), Profile 2: substance use ( n = 46), Profile 3: average ( n = 373), Profile 4: disengagement ( n = 51).

Mean differences between profiles by coping mechanisms.

z-standardized mean difference from sample mean.

Profile 1: Religious (23.5%) consisted of individuals who engaged in greater religious coping, z = 1.42, greater adaptive coping strategies (e.g., active coping, z = 0.43), and less maladaptive strategies (e.g., substance use, z = −0.32).

Profile 2: Substance Use (7.49%) consisted of individuals who engaged in greater maladaptive strategies (e.g., substance use, z = 2.42 and self-blame, z = 0.29) and less adaptive coping strategies (e.g., active coping, z = −0.26) and religious coping, z = −0.45.

Profile 3: Average (60.75%) consisted of participants who engaged in both adaptive and maladaptive strategies; they also engaged in very low levels of religious coping (z = −0.59).

Profile 4: Disengagement (8.31%) engaged in more behavioral disengagement, z = 1.46, substance use, z = 1.23, denial, z = 2.67, self-blame, z = 1.08, some adaptive strategies at higher levels (e.g., instrumental support, z = 0.45), and religious coping at higher levels, z = 0.69, but with less acceptance (z = −0.36).

These results suggest individuals engaged in both adaptive and maladaptive coping strategies. However, they also show that a small group of individuals were coping relatively well with the pandemic (23.5%). These profile memberships were used for subsequent analysis as the entropy level was high (0.95).

Nested robust multiple linear regressions were used to predict both retrospectively reported pre-physical distancing well-being and current well-being not accounted for by pre-physical distancing levels. Regression models are presented in Table 7 . Studentized residuals from models 2, 3, 4, 6, and 7 were normally distributed. While the removal of responses with outstanding studentized residual, leverage, or Cook's d slightly increased the amount of variance explained by the predictor variables, the models largely remained the same. Therefore, these responses have been kept in the regression analyses table.

Predictive models of participants' reported levels of well-being (variables were mean-centered).

Models 1 and 5 were baseline models examining the main effects of nation, gender, household income in 2019, religious affiliation, educational level, and marital status on participants' pre-physical distancing well-being as well as the amount of variance in current well-being not explained by its pre-physical distancing level. Both models were significant, F m 1 (6,597) = 17.79, p < 0.001, F m 5 (6,597) = 2.50, p = 0.0 2, but only about 15 and 2% of the variance in pre-physical distancing well-being and the unstandardized residuals of current well-being respectively were accounted for.

Models 2 and 3 aimed to predict pre-physical distancing well-being using slightly different approaches. In Model 2, we predicted pre-physical distancing well-being using pre-physical distancing levels of negative emotion, loneliness, health, presence of and search for meaning in life, as well as constructs hypothesized to be largely stable over time (i.e., coping profiles, wisdom, social support, religiosity, and spirituality). However, since our pre-physical distancing well-being was a retrospective measure that might be significantly affected by current levels of performance, Model 3 examined the effects of current levels of negative emotion, loneliness, health, presence of and search for meaning in life, represented by unstandardized residuals, as well as difference measures of self-transcendence and alienation measured by ASTI.

As shown in Table 7 , both Model 2 and 3 significantly predicted pre-physical distancing well-being, F m 2 (18,585) = 106.73, p < 0.001, F m 3 (26,577) = 85.98, p < 0.001. Model 2 explained significantly more variance than the baseline model, F change (2−1) (12,585) = 134.92, p < 0.001, and Model 3 explained significantly more variance than Model 2, F change (3−2) (8,577) = 10.89, p < 0.001, but only for an additional 3.16% of the variance. Furthermore, among the additional predictors added in Model 3, only ASTI and the residualized current well-being turned out to be significant. The significance main effect of ASTI may be explained by the fact that it was a change score, thus had the pre-physical distancing level of self-transcendent wisdom already embedded within it. The unstandardized residuals of current well-being were negatively associated with retrospective pre-physical distancing well-being. Overall, after controlling for the other variables in Models 2 and 3, pre-physical distancing well-being was positively associated with personal wisdom, social support, and retrospective pre-physical distancing levels of presence of meaning in life and health, and was negatively associated with pre-physical distancing negative emotions and loneliness.

Before entering the interaction terms between coping profiles and ASTI, controlling for all other variables in the models, belonging to coping Profile 4 “Disengagement” was associated with higher pre-physical distancing well-being. Model 4 explored the interaction terms, F m 4 (29,574) = 78.20, p < 0.001. While the additional explanation power of Model 4 over Model 3 was only 0.34%, this change was significant, F change (4−3) (3,574) = 2.93, p = 0.03. Model 4 revealed a significant interaction effect between ASTI and Disengagement membership (see Figure 2A ). F -tests were conducted to see (1) whether the slopes of the regression lines in Figure 2A were significantly different from zero, and (2) whether the slopes of these lines were significantly different from one another. Results are presented in Table 8 . The slopes of ASTI for all coping profiles were significant, and significantly different from one another as demonstrated by the significant R 2 change between Model 3 and 4. The slope of the regression line for people with a Disengagement profile was significantly steeper than those with a Religious coping profile or used an average level of all coping strategies (Profile 3).

The effects of self-transcendent wisdom on self-reported levels of well-being for people belonging to different coping profiles (variables were mean-centered). For illustrative purposes, (A,B) were created for an individual that fell into the median categories for all demographic variables (Canadian, male, Christian, married, or living with a partner, had a Bachelor's degree or equivalent, and lived in a household the annual income of which was between C$40–60k in 2019) and scored the mean values for all continuous predictors except for ASTI (i.e., unstandardized residuals = 0).

F-tests for significant non-zero slopes and significant differences between the slopes of pre-physical distancing well-being on ASTI by each coping profile.

Model 6 aimed to improve on the baseline Model 5 (discussed above) by adding pre-physical distancing and residualized current levels of negative emotion, loneliness, presence of and search for meaning in life, and health, as well as coping profiles, wisdom, social support, religiosity, spirituality, self-transcendent wisdom, alienation, and pre-physical distancing well-being, in the prediction of residualized current well-being. Model 6 explained 61.47% of the variance in the unstandardized residuals of current well-being, F m 6 (26,577) = 25.01, p < 0.001, representing a significant R 2 change compared to Model 5, F change (6−5) (20,577) = 30.47, p < 0.001. Model 7 further added the interaction terms between coping profiles and ASTI and explained 62.47% of the variance in the dependent variable, F m 7 (29,574) = 23.36, p < 0.001. While quite small, this R 2 change was also significant, F change (7−6) (3,574) = 2.91, p = 0.03.

Predicting variance in current well-being not accounted for by pre-physical distancing levels, after controlling for other variables, we observed significant positive main effects of social support, pre-physical distancing and residualized current presence of meaning in life, residualized current health, and ASTI, as well as significant negative main effects from residualized current negative emotion and loneliness, alienation, and retrospective pre-physical distancing well-being. The effects of the interaction terms are illustrated in Figure 2B , and the results of F -tests are shown in Table 8 . The slopes for ASTI were significant for all coping profiles, and significantly different from one another as demonstrated by the significant R 2 change between Model 6 and 7. The slope of the regression line for people with a Disengagement profile was significantly steeper than those with a Religious coping profile or an average level of all coping strategies (Profile 3). The slope of the regression line for people with a Substance Use profile was significantly steeper than with a Religious coping profile.

Extreme Case Analysis of High and Low Transcenders

Since self-transcendent wisdom plays such an important role in maintaining and improving well-being, we decided to further examine the individuals with particularly high and low self-reported transcendence. Using logistic regressions, we explored the effects of demographic characteristics (i.e., country, age, gender, annual household income in 2019, religious affiliation, marital status, and highest level of education) on whether one fell into the top and bottom 10% based on their scores on ASTI ( n = 76 participants, per group).

As shown in Table 9 , ASTI extreme group membership is significantly associated with religious affiliation. In particular, whether or not one adjusts for the effects of other demographic characteristics, the odds of being in the high-ASTI group for Christians were 2.94, those for Atheists were 0.30, those for Agnostics were 0.36, and were 1.30 for all others. Due to the more restricted sample size ( n = 152), we were not able to compare the relative odds of being a Muslim, Buddhist, or Hindu.

Predicting memberships in the high and low ASTI groups by demographics.

Qualitative Results

Each personal project reported was categorized as one of nine possible types: Academic, Work, Health, Recreational, Interpersonal, Intrapersonal, Maintenance, Creative, and Other. All categories come from the established work on personal projects analysis (Little and Gee, 2007 ), except for “Creative” projects, added to classify projects that were neither academic, work, or recreational. “Other” projects did not fit cleanly within any existing category, nor align with other idiosyncratic items to suggest a new category, and were excluded from the present analysis. To highlight the prevalence the particular types of projects among participants before and during physical distancing, Figure 3 and Tables 10 , ​ ,11 11 report the number of participants with high or low self-transcendent wisdom who reported at least one project of the listed type. In what follows, we present only those categories that differ substantially between groups.

(A) Personal projects reported by participants low in self-transcendent wisdom and (B) high in self-transcendent wisdom.

Examples of pre and current project for the low self-transcendence group.

Note: The pre-physical distancing and current lists are not from the same participants .

Examples of pre and current project for the high self-transcendence group.

Recreational Projects

Both the high and low self-transcendent wisdom group participants placed greater emphasis on recreational projects at the time of data collection than they did reflecting on their projects prior to physical distancing, as seen in Figure 3 . The low-transcendence group emphasized recreational pursuits that appeared more escapist in nature (e.g., playing video games, “binge” watching television series), whereas the high self-transcendent wisdom group emphasized reading books—often phrased as “catching up” on a pre-existing reading list. Where the high self-transcendent wisdom group also reported watching shows or playing games, it was often in the context of watching with family, or playing online games with friends. With such an emphasis, such projects were instead counted as interpersonal projects, reported below. Absent any mention of friends or family being involved in electronic entertainment, we theorize that playing video games and watching television series allowed participants to mimic missing social relationships through immersion in narratives, as well as being an accessible and understandable form of escapism (Hilgard et al., 2013 ; Blasi et al., 2019 ). While there is likely also an escapist element in reading projects, reading suggests exercising the mind and the imagination, rather than turning to more sensory distractions for fun. The emphasis on more sensory, concrete, or immediate projects is a recurring theme amongst projects of participants with the lowest levels of self-transcendent wisdom.

Interpersonal Projects

Participants with high self-transcendent wisdom placed greater emphasis on projects involving deepening interactions with other people, especially family. Prior projects involving family are maintained, or participants mention transitioning toward making their current projects more focused on spending time with their family, friends, or significant others. Participants with low self-transcendent wisdom had difficulty maintaining their interpersonal projects across pre-physical distancing and current lists: For example, dating and spending time with friends dropped off their current list. We can particularly see this with projects involving electronic media. For participants with high self-transcendent wisdom, projects involving watching television or playing videos games emphasize sharing an experience, and are therefore coded as “Interpersonal” projects. Those with higher levels of self-transcendent wisdom appeared to prioritize deepening the connections they have, while those with lower reported levels of self-transcendent wisdom appear to retreat from others, engaging with projects that are accomplished alone, or are immediately salient.

Intrapersonal Projects

Intrapersonal projects cover activities that attempt to change or develop oneself (e.g., active self-care, personal growth, and spirituality). While participants with high self-transcendent wisdom reported more intrapersonal projects prior to physical distancing than participants with low self-transcendent wisdom, we see a spike in these projects among latter group during physical distancing that focus on managing negative emotions, particularly anger. Given the association between self-transcendent wisdom and feelings of interconnectedness and personal growth, it makes sense that the projects of those with higher levels of self-transcendent involve identifying ways to feel more content, happy and well, through e.g., meditation and self-care, during a global pandemic that generates an unprecedent level of anxiety and stress about the future. The projects of those low in self-transcendent wisdom, on the other hand, again, emphasize something immediate and visceral; in this case, anger management.

Maintenance

Across both groups of participants, a qualitatively noticeable difference was noted for participants with low, as compared to high, self-transcendent wisdom, toward very basic forms of survival projects during physical distancing. Projects such as grocery shopping, cooking , and cleaning were far more central for participants with low self-transcendent wisdom, particularly in comparison with the projects they listed having prior to physical distancing. As was the case with “Recreational” projects, participants with high self-transcendent wisdom emphasized interpersonal interactions even in their maintenance projects. The most common example of this was cooking with family . Rather than just mentioning the project of cooking, they specifically noted that were doing the task with family. This emphasis on spending time with others during what would otherwise be routine task moved such projects to the “Interpersonal” projects section.

Creative Projects

We created the category of “Creative” projects as distinct from “Academic,” “Work,” and “Recreational” projects in order to capture artistic projects, musical projects, or in some cases, learning languages, that lacked an emphasis on formal schooling, earning money, or hedonic fun. Creative projects instead emphasized making things or mastering skills. Prior to physical distancing, participants in both groups reported similar projects. The most common of these projects were what one would traditionally categorize as creative pursuits, such as painting, writing, or playing an instrument. During physical distancing, however, projects began to diverge. For low transcendence participants, even creative projects retain some element of a utilitarian goal: preparing food with a new recipe, for instance, or redecorating personal spaces. Creative projects among high-transcendence participants, on the other hand, tended to emphasize creation for creation's sake, with more emphasis on languages, fine arts, crafts, or even puzzles. Once again, participants with lower self-transcendent wisdom focused on concrete, tangible projects that often have a clear goal or result, while participants with higher self-transcendent wisdom focused on projects that appear more open-ended, abstract, and typically involve others.

Overall, by examining the participants with the lowest and highest self-transcendent wisdom we see a pattern of change in pre-pandemic to current personal project lists. Examples of personal project responses that display a pattern of transformation are displayed in Table 12 . The first and third example are participants with high self-transcendent wisdom, whereas the second example is a participant with low self-transcendent wisdom. Participants with high self-transcendent wisdom appeared to be more successful in staying connected with other people and larger causes. They often found new ways to spend their energy, either by connecting at a more local level or, in the case of one memorable participant displayed in Table 12 , radically scaling up their circle of concerns to new heights of political activism. Participants with low self-transcendent wisdom, by contrast, appeared to withdraw rather than venture outwards. While some managed to adjust to a world in which connections must be either immediately local or radically global, overall the projects of the lowest scoring participants seem to have been, for lack of a better word, crushed.

Exemplar participants pre-current personal project lists.

The analyses described above focused on determining predictors of two main variables: (1) retrospective perceptions of well-being before the beginning of physical distancing, and (2) the residuals between participants' retrospective well-being and participants' perceived well-being since the enactment of physical distancing measures, which we used to provide an estimate of change in perceived well-being since physical distancing began. Before we move to a general discussion, it is worth noting our overall approach to the interpretation of these data. Due to the retrospective nature of the data collection, we interpret these data used as representing idiographic participant self-understanding of change over time, as it seems to them at the time of data collection, rather than “objective” differences between present and past states of being. While psychology has historically emphasized nomothetic analyses of experience (Munsterberg, 1899 ), idiographic approaches to data championed by Allport ( 1942 ) or more recently Lundh ( 2015 ) are particularly applicable to the study of events which are, incontestably, historical in nature, like the present pandemic. Indeed, computer-assisted textual analysis has revealed narrative patterns consistent with the quantitative and qualitative findings from our study, namely, that one is either experiencing the current pandemic as a time for vital re-evaluation of priorities, or as a fight for survival (Venuleo et al., 2020 ).

In terms of quantitative findings, controlling for all other variables in the model, we observed a greater association between nationality, gender, personal wisdom, disengagement coping profile, retrospective health, loneliness, negative emotions, and meaning in life and participants' retrospective well-being than for other factors. Residualized current perceived health, negative emotions, loneliness, and alienation demonstrated the greatest association with residualized current well-being, again controlling for all other variables. The interaction between Disengaged coping and self-transcendent wisdom, as well as self-transcendent wisdom on its own, was strongly associated with both retrospective and residual well-being, as was retrospective meaning in life and social support. Controlling for all other variables, residualized current well-being is negatively associated retrospective pre-physical distanced well-being.

Many of these results are in line with past findings, both during and prior to the pandemic. For instance, personal wisdom (Grossmann et al., 2013 ; Ardelt, 2019 ), health (Aneshensel et al., 1984 ; Hayes and Ross, 1986 ; Hsieh and Waite, 2019 ; Park and Adler, 2003 ), and social support (Turner, 1981 ; Thoits, 1985 ; Portero and Oliva, 2007 ; Hyde et al., 2011 ) are known to be predictive of well-being. Personal wisdom in particular has been previously found to be a protective factor for psychological well-being during the COVID-19 pandemic (Pellerin and Raufaste, 2020 ), though it does not appear to impact residualized current well-being in the present sample. The coping responses from our participants also align with those who have experienced similar outbreaks (Chew et al., 2020 ; Rajkumar, 2020 ). Although some strategies (e.g., distraction) may be deemed maladaptive, evidence suggests their short-term efficacy in dealing with uncontrollable situations (Janson and Rohleder, 2017 ), explaining the existence of the Disengaged coping profile. While recent research by Park et al. ( 2020 ) also found evidence that demographic factors (e.g., age and socio-economic status) may predict differential coping responses with the pandemic, only nationality and gender appear to play a role in the models presented here. Of the two, Canada has had significantly fewer cases of COVID-19 relative to its population than the United States, as well as more centralized support from the federal government, while the pandemic is well-known to have had a disproportionate impact on women relative to men (Alon et al., 2020 ). In summary, there do not appear to be any surprises in predictors of current well-being.

In line with previous findings that strong interpersonal relationships predict more positive experiences of solitude (Pauly et al., 2018 ), our qualitative analyses found that participants with high self-transcendent wisdom strongly emphasized how their projects during times of physical distancing helped connect them to friends, family, and community. Previous research examining the presence of meaning in life have consistently found that meaning relates to connectedness , whether through existential mattering (Costin and Vignoles, 2020 ), relationships of mutual care and trust (Wong, 2020 ), or an overall sense of coherence (Park, 2010 ). Good relationships with others are also consistently placed among the most important aspects of what it means to live a good life the world over (Tafarodi et al., 2012 ; Bonn and Tafarodi, 2013 ). As such, the finding that the participants who are relatively thriving during periods of physical distancing have managed to center and maintain these relationships is consistent with several models of a good, meaningful life. The finding that participants with low self-transcendent wisdom have found it apparently difficult to maintain such relationships and seem to be slipping into escapism and self-distraction is consonant with the narratives of “global crisis” and “surviving a war” identified by Venuleo et al. ( 2020 ) as most frequent amongst people experiencing greater instability during lockdown measures in Italy. Combined with our quantitative findings that loneliness and alienation demonstrated negative associations with perceived well-being, such findings further evidence for the importance of strong, resilient relationships to weathering misfortune, particularly on misfortune on such a magnified scale.

That participants with the highest self-transcendent wisdom were more likely to be religious is an interesting finding, and one for which the framework of existential positive psychology provides some context. While it might be too strong a claim that religion itself is necessary, Wong's ( 2020 ) model of existential meaning emphasizes the importance of faith and concern for greater things in cultivating meaning, which religious participants could be reasonably expected to experience more strongly than non-religious participants. Religion is also known to have strong anxiolytic effects (Kay et al., 2010 ; Newton and McIntosh, 2010 ). Interestingly, self-transcendent wisdom, otherwise an important factor in predicting change in well-being, was had a reduced impact for participants with a Religious coping profile.

Self-transcendence is defined as decreased egoic self-salience and increased feelings of connectedness to something larger than oneself (Kitson et al., 2020 ). A sense of connectedness can provide an anchor point for coping (Frydenberg and Lewis, 2009 ), and strengthening that sense of connectedness underlies both self-transcendence (Kitson et al., 2020 ) and cultivation of meaning in life (George and Park, 2016 ; Costin and Vignoles, 2020 ). In developmental research, self-transcendence is related to—and perhaps a precondition for— developing wisdom (Aldwin et al., 2019 ), with the Adult Self-Transcendence Inventory being designed to evaluate such self-transcendent wisdom. Based on our findings, it appears that self-transcendent wisdom contributes to current well-being over and above coping style and predicts change in well-being for people using all coping styles, except for those using mainly Religious coping.

That self-transcendent wisdom seemed to have a stronger contribution to variance in well-being over coping for Profiles 2 (Substance Use) and 4 (Disengagement) than for Profiles 1 (Religious) and 3 (Average) is somewhat surprising. Perhaps wiser people have a deeper understanding of negative emotions as not necessarily bad or maladaptive; used appropriately, they can help signal the need to engage adaptive strategies for psychological safety or strategies that can generate psychological growth (Webster, in press ). Likewise, even avoidance coping may be adaptive in certain clinical contexts [see Hofmann and Hay ( 2018 )].

A decreased acceptance of ongoing negative events might also have played a role. Previous research in mindfulness has found that the “non-judgmental acceptance” component of mindfulness is negatively associated with both intuition (Remmers et al., 2014 ) and wise reasoning (Kim et al., 2020 ), suggesting that acceptance may circumvent the exploratory processing needed to achieve greater well-being (Weststrate, 2019 ). Pellerin and Raufaste ( 2020 ) similarly find that in the current pandemic climate, peaceful disengagement actually predicts a decline in well-being over time. Wiser individuals are particularly good at managing the sense of uncertainty and uncontrollability that necessarily comes with adverse experiences (Glück et al., 2018 ; Glück, in press ). According to Glück et al.'s ( 2018 ) MORE model, wise individuals can sustain a higher level of negative emotions when trying to understand the complexity of a situation. Therefore, their use of different types of coping strategies can help maximize their well-being (Glück, in press ).

However, for participants who already had adaptive coping mechanisms, their existing strategies probably accounted for most of the added benefit of self-transcendent wisdom, although self-transcendent wisdom still played a role in predicting their well-being. Coping strategies appear to be important for well-being in daily life (Ben-Zur, 2009 ), as well as for helping to maintain a baseline functioning during stressful events (Park and Adler, 2003 ). However, self-transcendent wisdom is the more robust indicator, when comparing coping and self-transcendence as indicators of well-being (McCarthy et al., 2013 ). Additionally, the use of Religious coping may overlap sufficiently with self-transcendent wisdom in motivating attention to concerns beyond the self so as to reduce any apparent impact.

Interestingly, self-transcendence was not a significant predictor of well-being in a previous study of protective factors during the COVID-19 pandemic. Pellerin and Raufaste ( 2020 ) found that self-transcendence was only related to well-being when all other potential psychological resources (i.e., personal wisdom, self-efficacy, optimism, hope, and gratitude) were not controlled for; thus, they consider self-transcendence a meta-resource that affords the development of other resources, or perhaps this reflects a floor effect: an individual may need higher self-transcendence in order to see a benefit. Our findings suggest that it is not greater self-transcendence, but rather a more holistic approach to it that is needed to see results. While Pellerin and Raufaste ( 2020 ) used only the self-transcendence ASTI subscale in their research, to specifically target self-transcendence as an independent variable, our study used all five subscales to measure self-transcendent wisdom in its full spectrum. Our findings also suggest that self-transcendent wisdom may make the biggest contribution when an individual lacks healthy, adaptive coping strategies. Participants with adaptive coping skills could simply apply what they already know to the present situation. Without such skills, however, self-transcendent wisdom may make the difference between a traumatic experience and a transformative one.

In the philosophical literature on self-transformation, a distinction is made between self-transformation and self-cultivation (Callard, 2018 ). Unlike self-transformation, self-cultivation involves no radical shift in values, but instead refines their ability to apply existing values. After self-cultivation, one is simply a more effective version of the same person they were before. Self-transformation, on the other hand, involves a radical shift in values (Paul, 2014 ). Sometimes, transformation is a consequence of unexpected situations, like unplanned parenthood. At other times, self-transformation is an active pursuit, as for spiritual aspirants, or in the best traditions of liberal education (Callard, 2017 ). In both cases, a person may be unrecognizable to their past self after self-transformation; their priorities, values, and approach to life may come to be entirely different than those they held before. In our current sample, participants with an adaptive coping profile seem to be engaged in self-cultivation —using and refining what they already know to be good for them—while participants with other coping profiles seek self-transformation.

Although the pandemic has severely affected every area of public life, it has also deepened some individuals' connections to others and complexified their worldview, which could potentially allow post-traumatic growth (PTG), defined as positive psychological change following trauma that results in a greater appreciation for life, increased personal strength, spiritual growth, more meaningful relationships, and the recognition of new possibilities (Tedeschi and Calhoun, 1996 ). Traumatic events that trigger PTG are often described as “seismic” (Blevins and Tedeschi, in press ), disrupting someone's entire way of life and potentially their existing coping strategies. For many people, the COVID-19 pandemic qualifies as a seismic event, given that it not only provokes a health scare, but interrupts the familiar rhythms and patterns of daily life, is impossible to escape, and has made common means of self-distraction like travel or simply going to a pub life-threatening. It has therefore, forced many people to begin to examine alternative ways of life.

Among the participants high in self-transcendent wisdom, we see evidence of such a shift in priorities. Projects oriented around family or immediate communities of friends become more prevalent during physical distancing than they were before. Intrapersonal projects, aimed at some sort of personal change, also become more focal: meditation, yoga, and contemplation on a good life become projects among participants with high self-transcendent wisdom. Memorably, one person showed a newfound commitment to political activism, possibly spurred by the surge in racial justice protests that began during the time of data collection. These projects closely match the pattern of activities that Calhoun et al. ( 2010 ) argue best facilitate PTG: reassessing one's goals, strengths, and priorities, sociocultural influences (such as social support and role models), and strategies to manage ongoing stress. They also closely match the conditions that Callard ( 2018 ) argues are ideal for supporting intentional self-transformation: ideals, a supportive community, and a sense that such transformation will be meaningful. Previous evidence following the SARS epidemic found that some individuals reported experiencing positive life transformations, similar to PTG (Lau et al., 2006 ). Blevins and Tedeschi ( in press ) suggest that PTG reflects an ability for people to respond well to adversity and experience positive changes following the attempt to make sense of a disrupted world. Similar themes to PTG and the conditions for self-transformation have been identified by existential positive psychology in positioning confrontation with periods of suffering as opportunities for cultivating a greater sense of meaning (Wong, 2020 ). The COVID-19 pandemic has severely disrupted our own worldviews and requires this sense of reconstruction to cope with our new reality.

To use an analogy, the relationship between adaptive coping and self-transcendent wisdom may be compared to boiling water. As one heats a pot of water, at some point, when the liquid water has no more capacity to disperse energy, it turns to steam. People with existing adaptive coping strategies are analogous to a larger pot of water, which takes more heat and longer exposure to boil. Those without such strategies, however, are analogous to smaller pots; the heat represented by the current disruption to daily life is enough to require them not just to cope, but to change.

Limitations

Like all studies, our study has limitations. The most salient of these is that it captures a single moment in time, representing the experience of North Americans in the early summer of 2020. It is possible that some of our findings might differ were the same questions to be asked of a different sample, or even of the same sample now, in the second winter wave of the pandemic. Another limitation of the present study is that our “baseline” measures from before the pandemic are retrospective, not pre-recorded. While this might open our study up to recency and saliency biases, we feel that this concern is balanced out by the strengths of this retrospective method: a high self-rating of well-being now may be far more meaningful than such a rating a year ago. Importantly, our interest in the present study was predominately idiographic, rather than nomothetic. Our findings should be interpreted as presenting participants' self-understanding of their life and experiences of change during a period of physical distancing and how that has changed, rather than as impersonal objective measures at two points in time. While some researchers were fortunate enough to have baseline measures for their participants that pre-dated the pandemic [see Hamza et al. ( 2020 )], the methods of the present study relied on participant self-understanding in the moment of data collection. Relatedly, it must be remembered that our study is exploratory, not confirmatory. We began this study to investigate a broad assortment of possible influences on how North Americans were spending their time during social distancing as compared to before such measures were enacted, and how this relates to their reported sense of well-being. Our findings, however, repeat a fairly consistent theme in the positive, existential, narrative, and phenomenological psychologies of well-being: feeling connected to others is vital to experiencing a meaningful life.

Conclusions

The present study used a broad range of measures to explore contributing factors to participants' well-being during physical distancing resulting from the COVID-19 pandemic. In particular, we used retrospective comparison to examine perceived changes in well-being prior to the pandemic, and how they contributed to a change in well-being at the time of the study. We found that self-transcendent wisdom and perceived meaning in life demonstrated the strongest positive associations with change in perceived well-being when controlling for all other variables. Analysis of the personal projects of participants reporting the highest levels of self-transcendent wisdom revealed a pattern consistent with models of PTG and aspirational self-transformation. Our findings suggest that while most participants experienced a decline in well-being, for understandable reasons (e.g., loneliness, negative emotions, and alienation), higher levels of self-transcendent wisdom were associated with positive changes in well-being during physical distancing as compared to before—especially for participants with merely average coping mechanisms, or who belonged to the Substance Use coping profile. Our findings suggest ways to avoid having the COVID-19 pandemic become the traumatic event of a generation, but instead a genuine watershed moment for growth.

Data Availability Statement

Ethics statement.

The studies involving human participants were reviewed and approved by University of Toronto Research Ethics Board. The participants provided their written informed consent to participate in this study.

Author Contributions

JK, MM, ZF, and SM designed the study and contributed to writing the manuscript. JK provided theoretical framing and performed qualitative analysis. MM, MA, and RA performed latent profile analysis and data visualization. ZF performed descriptive statistics, multiple regression analysis, and data visualization. SM provided the original concept for the study, performed qualitative analysis, and data visualization. MF provided funding, resources, supervision for the study, and reviewed the manuscript. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

1 There are 23 responses that came from 11 IP addresses. After examining these responses closely we decided to keep them because it is more likely that responses from the same IP originated from the same household.

Funding. This project was funded by a University of Toronto Faculty Research grant to MF.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2021.648060/full#supplementary-material

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Does Personal Growth Benefit a Relationship?

New research examines the potential impact of shared and unshared experiences..

Posted March 20, 2021 | Reviewed by Matt Huston

• Recent studies showed an association between experiences of personal growth on a given day and the passion individuals felt in their relationship.
• The studies also add to the evidence that growth experiences shared by a couple can strengthen a relationship.
• Chronically high individual growth, however, may be associated with lower feelings of passion in one's relationship.

There’s some truth to the old proverb that “familiarity breeds contempt.” When we first enter into an intimate relationship, everything is exciting because everything is new. You’re getting to know your partner, and they’re getting to know you. On top of that, each of you is also changing as you adapt to the new relationship.

Over the years, we get to know our intimate partner better than any other person, and this is when the excitement in the relationship often starts to wane. What was once new and exciting can become old and boring .

But this doesn’t mean that romantic passion is destined to fizzle out over time. Plenty of research shows that couples can maintain excitement in their relationship by jointly engaging in novel experiences that promote personal growth. This could be taking a ballroom dance class, traveling, gardening—really any activity that the couple enjoys doing together and that entails some sort of novelty or challenge to overcome.

As we step out into the world, we learn new things, we meet new people, and we have experiences we never imagined. All this leads to personal growth. Because the partners are engaged in these activities together, they’re also growing together, and this is what fuels the flame of passion in a happy marriage .

Research shows that personal growth is important at the individual level as well. When we learn something new, our sense of competence increases. That is, we get a renewed can-do confidence that derives from overcoming challenges.

But what happens when personal growth takes place outside of the relationship? When one partner has new experiences that the other partner hasn’t shared, does this lead to an increase or decrease in relationship quality? These are the questions that Durham University (United Kingdom) psychologist Kathleen Carswell and her colleagues explored in a paper they recently published in the Journal of Personality and Social Psychology .

Shared Experiences, Personal Experiences, and Romantic Passion

The researchers reported on three studies that looked at the relation between personal growth and relationship quality. Two of these were daily diary studies in which each participant reported on experiences of self-expansion—involving elements like a sense of novelty, excitement, greater perspective, and expanded sense of self—either as an individual or with one's partner. Each person also indicated their current level of relationship passion.

The third study looked at couples who had recently relocated to a new city in a career move for one of the partners. The researchers speculated that the partner who’d moved for their career should be experiencing a degree of personal growth, at least as far as their job was concerned. Meanwhile, the sacrificing partner could be experiencing personal setbacks, career- wise anyway.

Consistent with previous findings, the researchers found that people who reported higher relational self-expansion tended to report greater passion in their relationship. But with regard to experiences partners had on their own, the implication for the relationship was more complicated.

On a given day, if one partner showed an increase in their personal growth experiences, they also tended to report greater passion in the relationship. Although the data don’t show us why this is the case, we can speculate.

Prior research shows that intimacy grows through the sharing of personal information. As two people reveal things about themselves that are generally not known to others, they develop a sense of closeness. When our partner comes home at the end of the day and shares an interesting experience they had, we learn something new about them, and this leads to an increase in intimacy. Additionally, their good mood can be infectious, boosting our own sense of relationship quality as well. Thus, when one partner experiences personal growth on a given day, this can lead to a boost in intimacy and relationship quality for both partners.

However, the results also suggest that when one partner engages in a prolonged period of personal growth that doesn’t include the other partner, it can cause problems in the relationship. As the researchers report, "more chronic personal self-expansion was associated with lower romantic passion." In the short run, personal growth leads to an increased sense of competence, and hence to a boost in mood. But over time, the psychological benefits of this continued personal growth may be lost as these couples experience less satisfaction with their relationship. In other words, they may feel themselves growing apart.

The Implications for Romantic Relationships

There are some important lessons to take home from this research. First, it backs up previous research suggesting that long-term couples grow together by engaging in shared novel experiences. This is the rationale behind the standard prescription for struggling couples to go on “date nights.”

The research also reaffirms the general finding that personal growth yields psychological benefits for the individual. As we meet and overcome challenges, our sense of self-competence also increases. This makes us more confident in our abilities, which boosts our mood.

Finally, it seems that one partner's long-term personal growth may have a negative impact on the relationship: "...consistently growing outside of the relationship in ways that are not shared with a romantic partner may reduce feelings of closeness and connection, and ultimately passion." In a sense, our once-intimate partner may become someone we feel as if we no longer know.

Of course, this doesn’t mean that we should avoid personal growth outside the relationship. That is unavoidable as we grow in our careers and our interactions with other people. However, the results of this study do suggest that we need to supplement our own individual development with shared experiences with our partners, as these are what will keep us growing together rather than apart.

Facebook image: Kamil Macniak/Shutterstock

Carswell, K. L., Muise, A., Harasymchuk, C., Horne, R. M., Visserman, M. L., & Impett, E. A. (2021, January 25). Growing desire or growing apart? Consequences of personal self-expansion for romantic passion. Journal of Personality and Social Psychology . Advance online publication. http://dx.doi.org/10.1037/pspi0000357

David Ludden, Ph.D. , is a professor of psychology at Georgia Gwinnett College.

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At any moment, someone’s aggravating behavior or our own bad luck can set us off on an emotional spiral that threatens to derail our entire day. Here’s how we can face our triggers with less reactivity so that we can get on with our lives.

• Emotional Intelligence
• Gaslighting
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• Neuroscience

ORIGINAL RESEARCH article

Personal growth and well-being in the time of covid: an exploratory mixed-methods analysis.

• Department of Applied Psychology and Human Development, Ontario Institute for Studies in Education, University of Toronto, Toronto, ON, Canada

The physical distancing measures necessitated by COVID-19 have resulted in a severe withdrawal from the patterns of daily life, necessitating significantly reduced contact with other people. To many, such withdrawal can be a major cause of distress. But, to some, this sort of withdrawal is an integral part of growth, a pathway to a more enriching life. The present study uses a sequential explanatory QUAN-qual design to investigate whether people who felt that their lives had changed for the better after being forced to engage in physical distancing, what factors predicted such well-being, and how they spent their time to generate this sense of well-being. We invited 614 participants who reported closely following physical distancing recommendations to complete a survey exploring this topic. Our analyses, after controlling for all other variables in the regression model, found a greater positive association between presence of meaning in life, coping style, and self-transcendent wisdom and residualized current well-being accounting for retrospective assessments of well-being prior to physical distancing. An extreme-case content analysis of participants' personal projects found that participants with low self-transcendent wisdom reported more survival-oriented projects (e.g., acquiring groceries or engaging in distracting entertainments), while participants reporting high self-transcendent wisdom reported more projects involving deepening interactions with other people, especially family. Our findings suggest a more nuanced pathway from adversity to a deeper sense of well-being by showing the importance of not merely coping with adversity, but truly transcending it.

The physical distancing measures necessitated by the COVID-19 pandemic have resulted in a massive withdrawal from the habitual patterns of daily life and in significantly less contact with other people. To many, such withdrawal can lead to disconnection and loneliness, a major cause of stress, anxiety, depressive symptoms, self-harm, and suicidal ideation ( Goldsmith et al., 2002 ; Cacioppo et al., 2006 ; Meltzer et al., 2013 ). Research on the effects of current lockdown and physical distancing protocols has already begun to ring alarm bells. Physical distancing policies have been found to have overall negative effects on the mental health of young adults in China, exacerbated by a steady stream of dire news about the pandemic ( Chen et al., 2020 ). Participant samples from California and the UK have reported feeling more hopeless and less engaged than a comparison group of first-time incarcerated inmates ( Dhami et al., 2020 ). Furthermore, increased rates of substance use have also been seen as result of loneliness and isolation as individuals are using substances to cope with the emotional impact of the pandemic ( Czeisler et al., 2020 ). Loneliness affects people of all ages, genders, and socioeconomic status. A study that examined loneliness as a predictor of mental health outcomes found that individuals experienced an increase in mental health symptom severity and decreased recovery and quality of life scores ( Wang et al., 2020 ). Such effects appear to be heightened among already vulnerable population, with loneliness being found to be particularly detrimental to the mental health of certain vulnerable societal groups such as seniors, migrants, asylum seekers and those in the LGBT population ( Eres et al., 2020 ); often the same populations most at risk as a result of the current pandemic.

Prior to the pandemic, North America was already beginning to demonstrate a worrying culture of disconnection, with people feeling increasingly isolated. The meteoric rise in single-person households over the past decade was accompanied by an increase in feelings of loneliness and disconnection ( Snell, 2017 ), along with a marked increase in major depressive episodes among those born in both the 1990's and 1950's ( Twenge et al., 2019 ). Religious institutions, formerly a major source of interpersonal connection and meaning-making ( Park et al., 2013 ), have seen a steady decline in membership, which Eberstadt (2013) directly ties to more people living alone. While loneliness and disconnection were already a topic of concern, the pandemic, fueling further separation of family units and closure of churches in many parts of the world, is likely to have exacerbated an already worrying trend. Or has it?

While loneliness is well-known to have negative impacts on many aspects of mental and physical health, solitude, or at least some form of withdrawal from mundane activities, is a necessary part of achieving higher forms of development in many religious and spiritual traditions, from the Desert Fathers of Christianity to the Sannyasis of Hinduism. The Buddhist Dhammapadda, likewise, uses the image of the elephant walking alone through the jungle to symbolize the often-solitary path of the aspirant in search of enlightenment. Modern qualitative research with spiritual aspirants ( Thomas, 1991 ; Durà-Vilà and Leavey, 2017 ) finds that they consider solitude an integral part of their pursuit of wisdom, a way for them to engage in uninterrupted reflection and meditation. Barbour (2004 , 2013) has argued that aloneness is an intrinsically spiritual value; seeking separation from the ordinary rhythms of societal life is a time-honored way to open oneself up to greater sources of connection and meaning. Averill and Sundararajan (2014) argue that the spiritual value of solitude comes from a relational soft reset, allowing one to focus on cultivating one's relationships with higher or greater sources of meaning. Solitude is often pursued as a strategy for affective self-regulation, a way to recover from intense emotional experiences ( Nguyen et al., 2018 ).

The benefits of solitude for personal and spiritual growth, however, make two key assumptions: that solitude is both voluntary and used constructively. This is particularly clear in studies of aloneness in children: while self-determined solitude is consistently associated with positive developmental outcomes, non-self-determined solitude is associated with greater loneliness and its accompanying long-term problems ( Galanaki, 2013 ; van Zyl et al., 2018 ; Corsano et al., 2020 ). Regarding the use of solitude, Lay et al. (2019) found that trait self-reflection, by definition involuntary, was more strongly associated with negative solitude experiences than positive, suggesting a greater opportunity for moments of despair when forced to be alone with one's thoughts. However, Weststrate (2019) found that deliberate exploratory reflection on one's life is a vital component in developing wisdom and a meaningful life.

As humans are inherently relational creatures, involuntary solitude may open up greater opportunities for individuals to experience an existential vacuum [see Frankl (1963) , Garfield (1973) , Reker et al. (1987) ]. Weinstein et al. (2012) observe that the notion of existential vacuum in existential psychology, as well as the phenomenon of pervasive motivation in literature on self-determination theory, are associated with a sort of epistemological loneliness, a feeling of being mentally alone. Without strong relationships in place, or the capacity to build them, the sense of aloneness can become unbearable. Those who do have such strong relationships with others, or with greater things, likely have less cause for concern. People with stronger relationships tend to weather involuntary solitude better ( Pauly et al., 2018 ), as do those who have built a healthy relationship with solitude itself, by being more likely to seek it out ( Lay et al., 2019 ). Lay et al. (2019) also found that greater social self-efficacy was another good predictor of positive experiences of solitude, which helps reconcile Wei (2020) finding that introverts are suffering more than expected under lockdown conditions in the United States. It takes a good deal of self-confidence to be alone; under present conditions, an aptitude for it may not be enough.

As a result of COVID-19, humanity is currently experiencing involuntary solitude on an unprecedented scale. However, as per the tenets of existential positive psychology ( Wong, 2020 ), times of such great suffering also provide the greatest opportunities for growth. Looking to history, we have some reason to be optimistic—or perhaps tragically optimistic ( Wong and McDonald, 2002 ; Leung, 2019 ). Loneliness became an important factor during the 2003 SARS epidemic, as well, but resulted in increased social cohesion due to the detrimental impact of isolation ( Lau et al., 2005 ; Saltzman et al., 2020 ). Even in the early stages of the pandemic, during the spring and summer of 2020, a large-scale narrative inquiry conducted in Italy found that some participants were already beginning to represent the pandemic as a time for re-evaluation of personal and social priorities, not just as a crisis ( Venuleo et al., 2020 ).

According to the MORE Wisdom Model ( Weststrate and Glück, 2017 ; Weststrate, 2019 ; Glück, in press ), “critical life experiences”—typically disruptive to life as usual—are important to fostering the development of wisdom, when accompanied by the exploratory reflective processing. This is very much in line with prominent models of post-traumatic growth, most notably the model championed by Tedeschi and Calhoun (1996 , 2004 ; Blevins and Tedeschi, in press) , according to which post-traumatic growth is a process of self-transformation involving the reconstruction of an individual's basic assumptions about how life ought to be lived to promote future flourishing. Paradoxically, post-traumatic growth involves: a greater appreciation for one's life, a newfound sense of personal strength, improved relationships, and consequently, greater wisdom. Indeed, with the right perspective, adverse events causing suffering can be transformed in the moment, potentially ameliorating the negative effect during, rather than after, the ongoing traumatic event ( Leung, 2019 ; Mead et al., 2020 ; Wong, 2020 ).

Thus, the isolation caused by the pandemic gives us cause for both concern and optimism. On the one hand, such isolation can and does impact most people negatively. On the other hand, strong relationships can help people weather such times of suffering, and such disruptions offer the opportunity to take stock of one's world and re-evaluate one's priorities. As per PP2.0 ( Wong, 2020 ), if one is able to take this time of suffering and necessary solitude, affirm it, and use it to grow, one can come to experience greater meaning and well-being than before such trials—an understanding that has a long history in philosophy and clinical psychology ( Halling and Nill, 1995 ). If anyone is lucky enough to feel that they have grown as a result of the current pressures to self-isolate, it is likely people who have focused on the key things in life: forging connections and finding meaning. If this is how some people have been spending this time, they have spent this time wisely.

The present exploratory mixed-methods study began with these two questions: (1) How do North Americans feel they have been doing since the introduction of physical distancing measures, and (2) how are they spending their time? Using an explanatory QUAN-qual design, this paper describes and elucidates our finding that it is the relationships we build, and the things we care about, that lead to a life of flourishing, even in the face of global suffering.

This study was approved by the Research Ethics Board at the University of Toronto. Workers on Amazon's Mechanical Turk chose to participate in our human intelligence task which was advertised as a study on coping with the COVID-19 pandemic. Workers were directed to a link to participate in our online survey, hosted on Qualtrics. All participants gave informed consent before starting the survey. In part one, a screening was made in which participants indicated the extent of their engagement in physical distancing practices before completing a series of measurements in which they were instructed to respond while reflecting on their life prior to physical distancing. These included instruments on well-being, personal wisdom, presence and search for meaning, coping styles, negative emotion, and alienation.

Participants who reported closely following physical distancing recommendations were invited to complete a second stage of the survey, in which participants completed many of the same measures for a second time, this time reflecting on their life and experiences as they were at the time of completion (see Table 1 for list of measures completed in each section of the survey). They also completed additional measures of self-transcendent wisdom and engagement in personal projects. This two-stage design and broad array of measurements were intended to capture participants' experiences of physical distancing, their motivations for doing so, how they felt life has changed under distanced conditions, and why. Participants were not aware that their responses from the pre-physical distancing measures would be compared with their responses on the later set of measures related to the current time of completion.

Table 1 . List of measures completed in each section of the survey.

Participants

Data was collected from mid-April to end-of-July, 2020, through a two-part online survey distributed via Amazon's Mechanical Turk platform to residents of Canada and the U.S.A. To ensure the quality of our data, we implemented many approaches in the collection of our responses from Amazon's Mechanical Turk platform and screened participant data for problematic responses. On Mechanical Turk, workers were required to have a “human intelligence task” (HIT) approval rating ≥90, later upgraded to ≥95, along with having ≥100 HITs previously approved. We also included two attention checks (e.g., “select _ for this item”), one in each half of the survey. Workers who failed all attention checks that they came across were excluded from the study (n.b., individuals who did not pass the pre-established physical distancing cut-off score only encountered one attention check). IP duplications in submitted responses were screened and examined 1 . Open-ended questions within the Personal Projects Analysis Workbook (measure detailed in the following section) were assessed by two graduate coders for problematic responses, and cases that contain copy-paste responses or answers that did not relate to the prompt were removed from the study. Lastly, participants who scored the same responses for all items across several measurements (i.e., having standard deviations equal to 0 across several measurements) were removed before data analysis.

The final sample of physically-distanced participants consists of 274 Americans and 340 Canadians ( N = 614), with 279 females and 334 males with a mean age of 35 (see Table 2 ). Of these participants, 50% had a bachelor's degree or equivalent. Most household income were between C$40,000 and C$60,000. The mean number of children participants had was 0.78 ( Table 2 ).

Table 2 . Demographics ( N = 614).

Physical Distancing

Participants were asked how much they were participating in physical distancing measures by staying home, avoiding visiting others or having others visit them at home, avoiding religious gatherings and other social events, limiting trips to the grocery stores, or outdoor activities, and maintaining a safe distance from people who have traveled, in stores, or showing COVID-related symptoms; also whether they were canceling travel plans, quarantining after travel, self-isolating due to symptoms or close contact with people who had then, and generally following public health guidance about COVID as much as possible. Participants rated the extent to which they did so on a scale from 0 (Not at all) to 10 (To my best ability). Participants who scored an average of eight or above on all items were permitted to fill out additional questionnaires, as we were only interested in those who were physically distancing most of the time. Only participants who scored an average of eight or above on our measure of physical distancing are included in the present study.

Religiosity and Spirituality

Participants were asked to rate on a scale from 0 (Not at all religious/spiritual) to 10 (Very religious/spiritual) how religious or spiritual they were, in order to measure both the degree of religiosity and the degree of spirituality separately.

The Brief COPE Inventory ( Carver, 1997 ) was used to measure coping styles used after physical distancing was enacted. This measure consists of 28 items with 14 subscales: (1) self-distraction (e.g., “I've been turning to work or other activities to take my mind off things”), (2) active coping (e.g., “I've been concentrating my efforts on doing something about the situation I'm in”), (3) denial (e.g., “I've been saying to myself "this isn't real”), (4) substance use (e.g., “I've been using alcohol or other drugs to make myself feel better”), (5) emotional support (e.g., “I've been getting emotional support from others”), (6) instrumental support (e.g., “I've been getting help and advice from other people”), (7) behavioral disengagement (e.g., “I've been giving up trying to deal with it”), (8) venting (e.g., “I've been saying things to let my unpleasant feelings escape”), (9) positive reframing (e.g., “I've been trying to see it in a different light, to make it seem more positive”), (10) planning (e.g., “I've been trying to come up with a strategy about what to do”), (11) humor (e.g., “I've been making jokes about it”), (12) acceptance (e.g., “I've been accepting the reality of the fact that it has happened”), (13) religion (e.g., “I've been trying to find comfort in my religion or spiritual beliefs”), and (14) self-blame (e.g., “I've been criticizing myself”). Each item is rated on a 4-point Likert scale, ranging from 1 (I haven't been doing this at all) to 4 (I've been doing this a lot). In our study, overall Cronbrach's alpha was good (Alpha = 0.84).

Personal Wisdom

The 12-item Abbreviated Three-Dimensional Wisdom Scale (3D-WS-12; Thomas et al., 2017 ) was used to measure personal wisdom. This scale selects items from Ardelt's (2003) original scale, which includes three dimensions: cognitive (e.g., “I try to anticipate and avoid situations where there is a likely chance I will have to think in depth about something”), compassionate (“Sometimes I feel a real compassion for everyone”), and reflective (e.g., “I either get very angry or depressed if things go wrong”). Scores were rated on a 5-point Likert scale, ranging from 1 (Definitely true of myself) to 5 (Not true of myself). Total scores are calculated by taking the mean of all items on the scale. Cronbach's alpha for the 3D-WS-12 was good (Alpha = 0.81).

Social Support

To measure participants' perceptions of social support, we used the Multidimensional Scale of Perceived Social Support (MSPSS; Zimet et al., 1988 ). This measure consists of 12 items and three subscales: (1) Significant other (e.g., There is a special person who is around when I am in need), (2) Family, (e.g., I can talk about my problems with my family), and (3) Friends (e.g., My friends really try to help me). All items were answered on a 7-point Likert scale ranging from 1 (Very strongly disagree) to 7 (Very strongly agree). Total scores are calculated by taking the mean across the raw score from each item. Cronbach's alpha for the MSPSS was excellent (Alpha = 0.94).

The PERMA-profiler ( Butler and Kern, 2016 ), was administered to measure participants' well-being. The PERMA-profiler assesses well-bring across five subscales, also known as the five pillars of well-being: positive emotion, engagement, relationships, meaning, and accomplishment. The final well-being score is the mean across all PERMA subscale items. To determine if participants perceived their well-being as being different during and prior to physical distancing, participants completed both retrospective and current versions of the measure. Total scores and subscale scores were calculated for both pre-pandemic and current moment. Cronbach's alpha for the well-being subscale of the PERMA pre-pandemic and at the current moment were excellent at 0.96. The PERMA also includes as negative emotion subscale, whose Cronbach's alphas were good at 0.83 (pre-pandemic) and 0.85 (at the current moment). The loneliness subscale contains only one item, so Cronbach's alpha cannot be computed.

Meaning in Life

The Meaning in Life Questionnaire (MLQ; Steger et al., 2006 ) was used to measure both search for, and presence of, meaning in life before physical distancing (pre-pandemic) and once physical distancing had been enacted (at the current moment during the pandemic). The measure consists of 10 items, such as “I am looking for something that makes my life feel meaningful” (search for meaning, 5 items) and “I understand my life's meaning” (presence of meaning, 5 items). Participants rated these items on a 7-point Likert scale, ranging from 1 (absolutely untrue) to 7 (absolutely true). To determine if participants perceived their experienced sense of meaning in life as being different during and prior to physical distancing, participants completed both retrospective and current versions of the measure Total scores for search and presence of meaning were calculated separately and scores for pre-pandemic, current moment, and a pre-post difference score were calculated for each subscale. Cronbach's alpha for the search for meaning at 0.94 (pre-pandemic) and 0.95 (at the current moment), and presence of meaning at 0.94 (pre-pandemic) and 0.90 (at the current moment), were all excellent.

Self-Transcendent Wisdom

The Adult Self-Transcendence Inventory (ASTI; Levenson et al., 2005 ) was used to measure wisdom as self-transcendence since the beginning of physical distancing (self-reported at the present moment). The ASTI broadly defines self-transcendence as decreased egoic self-saliency and increased sense of connectedness. It consists of 29 items with six subscales ( Koller et al., 2017 ). Five subscales measure self-transcendent wisdom: (1) Self-Knowledge and Integration (e.g., “Since physical distancing was enacted, I have better sense of humor about myself”); (2) Peace of Mind (e.g., “Since physical distancing was enacted, I am more often engaged in quiet contemplation”); (3) Non-Attachment (e.g., “Since physical distancing was enacted, I have become less concerned about other people's opinions of me”); (4) Self-Transcendence (e.g., “Since physical distancing was enacted, I feel that my individual life is a part of a greater whole”); and (5) Presence in the Here-and-Now and Growth (e.g., “Since physical distancing was enacted, I find more joy in life”). Participants rated on a 4-point Likert scale, ranging from 1 (Disagree strongly) to 4 (Agree strongly). Total scores were calculated by taking the mean of all individual items in the self-knowledge and self-integration, peace of mind, non-attachment, self-transcendence, and presence in the here-and-now and growth subscales, as recommended for measuring overall self-transcendent wisdom. The 6th scale, Alienation (e.g., “Since physical distancing was enacted, I feel that my life has less meaning”), was treated as an individual subscale in all analyses, following Koller et al. (2017) . Cronbach's alpha for the total score was excellent (Alpha = 0.94), and for alienation was acceptable (Alpha = 0.65). Unlike our other measures, the ASTI is designed to assess the difference between the present moment and some previously specified time. As such, participants only filled out a single version of the ASTI.

Personal Projects

Finally, the Personal Projects Analysis Workbook (PPAW; Little, 1983 ) Module 1 was used to solicit participants' personal projects; that is, their most important goals and activities. Personal projects analysis conceptualizes the individual as collections of ongoing personal projects, as opposed to collections of personality traits. The PPAW Module 1 invites participants to list as many ongoing projects as comes to their mind—from the immediately utilitarian (e.g., “Mow the lawn”) to the most abstract (e.g., “Clarify my philosophy of life”). In separate sections of the survey, participants were asked to generate separate lists of personal projects both prior to and during physical distancing.

Analytic Strategy

Latent profile analysis.

To reduce the number of variables in later regression analyses, we conducted a latent profile analysis (LPA) on the 14 coping subscales from the Brief COPE (self-distraction, active coping, denial, substance use, emotional support, instrumental support, behavioral disengagement, venting, positive reframing, planning, humor, acceptance, religion, and self-blame) to identify latent subgroups of individuals who engaged in physical distancing, using the tidy LPA package in R ( Berlin et al., 2014 ; Rosenberg et al., 2018 ). Mean differences were tested across the latent profiles.

Four different models containing from 1 to 7 profiles were evaluated using the Bayesian Information Criterion (BIC) and Akaike Information Criterion (AIC) fit indices ( Schwarz, 1978 ). Lower values for the AIC and BIC indicate better model fit and demonstrate the fewest parameters among a set of non-hierarchical models. The BIC is preferable in determining the best model fit over the other fit statistics ( Nylund et al., 2007 ). Moreover, a bootstrap likelihood ratio test (BLRT) examined the statistical significance for model comparisons, by comparing the neighboring models as the number of classes decrease ( McLachlan and Peel, 2000 ). A significant p -value for this test also indicates better model fit as profiles are added. To assess the certainty with which participants were classified into latent profiles, the entropy value was also considered, since it provides information regarding the accuracy of the models, with a range from 0 to 1. An entropy value of 0.80 or above is preferred and indicates an accuracy of >90% ( Berlin et al., 2014 ). The best fitting model was chosen based on these criteria. See Table 2 for sample mean and standard deviations of the coping variables.

Multiple Linear Regression

Multiple linear regression models were used to explore the relationship between coping styles, personal wisdom, social support, self-transcendent wisdom, religiosity, spirituality, health, meaning in life, negative emotions, loneliness, alienation, and well-being. In particular, we are interested in investigating how these variables affected: (1) participants' retrospective pre-physical distancing well-being, and (2) the variance in reported current well-being (at the time of data collection) not explained by its pre-distancing level.

Descriptive statistics of the outcome and predictor variables are presented in Table 3 . In preparation for multiple regression analyses, study variables were mean-centered by subtracting total sample mean from subscale or total scores. For variables where retrospective pre-physical distancing ratings were available (i.e., well-being, health, presence of and search for meaning in life, negative emotion, loneliness), unstandardized residuals were computed by regressing “during-physical distancing” scores on their respective pre-physical distancing values, to parse out the contribution of the baseline pre-physical distancing condition from change in performance during physical distancing and to mitigate multicollinearity ( Table 4 ).

Table 3 . Descriptive statistics of study variables ( N = 614).

Table 4 . Predicting current levels of performance with retrospective pre-physical distancing levels.

Nested robust multiple linear regressions were conducted in Stata/IC 16. Coping profiles obtained from the LPA were transformed into dummy variables, using the profile of participants who mainly used adaptive coping strategies as the reference group. Examinations of the correlation table (see Appendix A ) and scatter plots suggested possible interaction effects between coping profiles and self-transcendent wisdom; therefore, a side-by-side comparison was made between models with and without the interaction terms. Additional F -tests were carried out to examine the statistical significance of the slopes of the predictor variable self-transcendent wisdom for people belonging to each coping profile. Paired-sample t -tests and one-way ANOVA analyses were conducted to explore possible group differences by nation, gender, educational level, marital status, religious affiliation, and annual household income in 2019 (See Appendix B for details). All models controlled for the main effects of nation, gender, educational level, marital status, religious affiliation, and household income prior to physical distancing (i.e., 2019).

Personal Projects Analysis

To elaborate on possible reasons for any changes in experience, we used personal projects analysis ( Little, 1983 ) to examine how participants spent their time both before and after physical distancing measures went into effect. With the results of the regression analysis suggesting an important role of self-transcendent wisdom, we conducted an extreme cases analysis of the personal projects of the participants with the highest ( n = 76) and lowest ( n = 76) self-transcendent wisdom scores, ~25% of the total sample. Logistic regressions were employed to explore the effects of demographic characteristics on high-low self-transcendence group membership. The first and fourth authors, coding independently, content-coded participants' personal projects. The first author is a researcher in humanistic psychology with previous experience using the Personal Projects Analysis Workbook ( Kim et al., 2020 ), while the fourth author has previous experience coding life narrative research. Personal projects were sorted into categories established by previous research in personal projects analysis ( Little and Gee, 2007 ). Discrepancies were resolved via discussion between the authors.

After comparing fit indices and entropy levels across all four models (see Table 5 ), a four-profile model was chosen to best classify coping strategies of participants who were physically distancing (see Figure 1 and Table 6 ). Each profile has been named after its most prominent form of coping, or, in the case of Profile 4, a core feature.

Table 5 . Fit statistics for LPA (Model 3: equal variances and equal covariances).

Figure 1 . The four latent profiles of coping mechanisms among individuals who are physically distancing. Profile 1: religious coping ( n = 144), Profile 2: substance use ( n = 46), Profile 3: average ( n = 373), Profile 4: disengagement ( n = 51).

Table 6 . Mean differences between profiles by coping mechanisms.

Profile 1: Religious (23.5%) consisted of individuals who engaged in greater religious coping, z = 1.42, greater adaptive coping strategies (e.g., active coping, z = 0.43), and less maladaptive strategies (e.g., substance use, z = −0.32).

Profile 2: Substance Use (7.49%) consisted of individuals who engaged in greater maladaptive strategies (e.g., substance use, z = 2.42 and self-blame, z = 0.29) and less adaptive coping strategies (e.g., active coping, z = −0.26) and religious coping, z = −0.45.

Profile 3: Average (60.75%) consisted of participants who engaged in both adaptive and maladaptive strategies; they also engaged in very low levels of religious coping (z = −0.59).

Profile 4: Disengagement (8.31%) engaged in more behavioral disengagement, z = 1.46, substance use, z = 1.23, denial, z = 2.67, self-blame, z = 1.08, some adaptive strategies at higher levels (e.g., instrumental support, z = 0.45), and religious coping at higher levels, z = 0.69, but with less acceptance (z = −0.36).

These results suggest individuals engaged in both adaptive and maladaptive coping strategies. However, they also show that a small group of individuals were coping relatively well with the pandemic (23.5%). These profile memberships were used for subsequent analysis as the entropy level was high (0.95).

Nested robust multiple linear regressions were used to predict both retrospectively reported pre-physical distancing well-being and current well-being not accounted for by pre-physical distancing levels. Regression models are presented in Table 7 . Studentized residuals from models 2, 3, 4, 6, and 7 were normally distributed. While the removal of responses with outstanding studentized residual, leverage, or Cook's d slightly increased the amount of variance explained by the predictor variables, the models largely remained the same. Therefore, these responses have been kept in the regression analyses table.

Table 7 . Predictive models of participants' reported levels of well-being (variables were mean-centered).

Models 1 and 5 were baseline models examining the main effects of nation, gender, household income in 2019, religious affiliation, educational level, and marital status on participants' pre-physical distancing well-being as well as the amount of variance in current well-being not explained by its pre-physical distancing level. Both models were significant, F m 1 (6,597) = 17.79, p < 0.001, F m 5 (6,597) = 2.50, p = 0.0 2, but only about 15 and 2% of the variance in pre-physical distancing well-being and the unstandardized residuals of current well-being respectively were accounted for.

Models 2 and 3 aimed to predict pre-physical distancing well-being using slightly different approaches. In Model 2, we predicted pre-physical distancing well-being using pre-physical distancing levels of negative emotion, loneliness, health, presence of and search for meaning in life, as well as constructs hypothesized to be largely stable over time (i.e., coping profiles, wisdom, social support, religiosity, and spirituality). However, since our pre-physical distancing well-being was a retrospective measure that might be significantly affected by current levels of performance, Model 3 examined the effects of current levels of negative emotion, loneliness, health, presence of and search for meaning in life, represented by unstandardized residuals, as well as difference measures of self-transcendence and alienation measured by ASTI.

As shown in Table 7 , both Model 2 and 3 significantly predicted pre-physical distancing well-being, F m 2 (18,585) = 106.73, p < 0.001, F m 3 (26,577) = 85.98, p < 0.001. Model 2 explained significantly more variance than the baseline model, F change (2−1) (12,585) = 134.92, p < 0.001, and Model 3 explained significantly more variance than Model 2, F change (3−2) (8,577) = 10.89, p < 0.001, but only for an additional 3.16% of the variance. Furthermore, among the additional predictors added in Model 3, only ASTI and the residualized current well-being turned out to be significant. The significance main effect of ASTI may be explained by the fact that it was a change score, thus had the pre-physical distancing level of self-transcendent wisdom already embedded within it. The unstandardized residuals of current well-being were negatively associated with retrospective pre-physical distancing well-being. Overall, after controlling for the other variables in Models 2 and 3, pre-physical distancing well-being was positively associated with personal wisdom, social support, and retrospective pre-physical distancing levels of presence of meaning in life and health, and was negatively associated with pre-physical distancing negative emotions and loneliness.

Before entering the interaction terms between coping profiles and ASTI, controlling for all other variables in the models, belonging to coping Profile 4 “Disengagement” was associated with higher pre-physical distancing well-being. Model 4 explored the interaction terms, F m 4 (29,574) = 78.20, p < 0.001. While the additional explanation power of Model 4 over Model 3 was only 0.34%, this change was significant, F change (4−3) (3,574) = 2.93, p = 0.03. Model 4 revealed a significant interaction effect between ASTI and Disengagement membership (see Figure 2A ). F -tests were conducted to see (1) whether the slopes of the regression lines in Figure 2A were significantly different from zero, and (2) whether the slopes of these lines were significantly different from one another. Results are presented in Table 8 . The slopes of ASTI for all coping profiles were significant, and significantly different from one another as demonstrated by the significant R 2 change between Model 3 and 4. The slope of the regression line for people with a Disengagement profile was significantly steeper than those with a Religious coping profile or used an average level of all coping strategies (Profile 3).

Figure 2 . The effects of self-transcendent wisdom on self-reported levels of well-being for people belonging to different coping profiles (variables were mean-centered). For illustrative purposes, (A,B) were created for an individual that fell into the median categories for all demographic variables (Canadian, male, Christian, married, or living with a partner, had a Bachelor's degree or equivalent, and lived in a household the annual income of which was between C$40–60k in 2019) and scored the mean values for all continuous predictors except for ASTI (i.e., unstandardized residuals = 0).

Table 8 . F-tests for significant non-zero slopes and significant differences between the slopes of pre-physical distancing well-being on ASTI by each coping profile.

Model 6 aimed to improve on the baseline Model 5 (discussed above) by adding pre-physical distancing and residualized current levels of negative emotion, loneliness, presence of and search for meaning in life, and health, as well as coping profiles, wisdom, social support, religiosity, spirituality, self-transcendent wisdom, alienation, and pre-physical distancing well-being, in the prediction of residualized current well-being. Model 6 explained 61.47% of the variance in the unstandardized residuals of current well-being, F m 6 (26,577) = 25.01, p < 0.001, representing a significant R 2 change compared to Model 5, F change (6−5) (20,577) = 30.47, p < 0.001. Model 7 further added the interaction terms between coping profiles and ASTI and explained 62.47% of the variance in the dependent variable, F m 7 (29,574) = 23.36, p < 0.001. While quite small, this R 2 change was also significant, F change (7−6) (3,574) = 2.91, p = 0.03.

Predicting variance in current well-being not accounted for by pre-physical distancing levels, after controlling for other variables, we observed significant positive main effects of social support, pre-physical distancing and residualized current presence of meaning in life, residualized current health, and ASTI, as well as significant negative main effects from residualized current negative emotion and loneliness, alienation, and retrospective pre-physical distancing well-being. The effects of the interaction terms are illustrated in Figure 2B , and the results of F -tests are shown in Table 8 . The slopes for ASTI were significant for all coping profiles, and significantly different from one another as demonstrated by the significant R 2 change between Model 6 and 7. The slope of the regression line for people with a Disengagement profile was significantly steeper than those with a Religious coping profile or an average level of all coping strategies (Profile 3). The slope of the regression line for people with a Substance Use profile was significantly steeper than with a Religious coping profile.

Extreme Case Analysis of High and Low Transcenders

Since self-transcendent wisdom plays such an important role in maintaining and improving well-being, we decided to further examine the individuals with particularly high and low self-reported transcendence. Using logistic regressions, we explored the effects of demographic characteristics (i.e., country, age, gender, annual household income in 2019, religious affiliation, marital status, and highest level of education) on whether one fell into the top and bottom 10% based on their scores on ASTI ( n = 76 participants, per group).

As shown in Table 9 , ASTI extreme group membership is significantly associated with religious affiliation. In particular, whether or not one adjusts for the effects of other demographic characteristics, the odds of being in the high-ASTI group for Christians were 2.94, those for Atheists were 0.30, those for Agnostics were 0.36, and were 1.30 for all others. Due to the more restricted sample size ( n = 152), we were not able to compare the relative odds of being a Muslim, Buddhist, or Hindu.

Table 9 . Predicting memberships in the high and low ASTI groups by demographics.

Qualitative Results

Each personal project reported was categorized as one of nine possible types: Academic, Work, Health, Recreational, Interpersonal, Intrapersonal, Maintenance, Creative, and Other. All categories come from the established work on personal projects analysis ( Little and Gee, 2007 ), except for “Creative” projects, added to classify projects that were neither academic, work, or recreational. “Other” projects did not fit cleanly within any existing category, nor align with other idiosyncratic items to suggest a new category, and were excluded from the present analysis. To highlight the prevalence the particular types of projects among participants before and during physical distancing, Figure 3 and Tables 10 , 11 report the number of participants with high or low self-transcendent wisdom who reported at least one project of the listed type. In what follows, we present only those categories that differ substantially between groups.

Figure 3. (A) Personal projects reported by participants low in self-transcendent wisdom and (B) high in self-transcendent wisdom.

Table 10 . Examples of pre and current project for the low self-transcendence group.

Table 11 . Examples of pre and current project for the high self-transcendence group.

Recreational Projects

Both the high and low self-transcendent wisdom group participants placed greater emphasis on recreational projects at the time of data collection than they did reflecting on their projects prior to physical distancing, as seen in Figure 3 . The low-transcendence group emphasized recreational pursuits that appeared more escapist in nature (e.g., playing video games, “binge” watching television series), whereas the high self-transcendent wisdom group emphasized reading books—often phrased as “catching up” on a pre-existing reading list. Where the high self-transcendent wisdom group also reported watching shows or playing games, it was often in the context of watching with family, or playing online games with friends. With such an emphasis, such projects were instead counted as interpersonal projects, reported below. Absent any mention of friends or family being involved in electronic entertainment, we theorize that playing video games and watching television series allowed participants to mimic missing social relationships through immersion in narratives, as well as being an accessible and understandable form of escapism ( Hilgard et al., 2013 ; Blasi et al., 2019 ). While there is likely also an escapist element in reading projects, reading suggests exercising the mind and the imagination, rather than turning to more sensory distractions for fun. The emphasis on more sensory, concrete, or immediate projects is a recurring theme amongst projects of participants with the lowest levels of self-transcendent wisdom.

Interpersonal Projects

Participants with high self-transcendent wisdom placed greater emphasis on projects involving deepening interactions with other people, especially family. Prior projects involving family are maintained, or participants mention transitioning toward making their current projects more focused on spending time with their family, friends, or significant others. Participants with low self-transcendent wisdom had difficulty maintaining their interpersonal projects across pre-physical distancing and current lists: For example, dating and spending time with friends dropped off their current list. We can particularly see this with projects involving electronic media. For participants with high self-transcendent wisdom, projects involving watching television or playing videos games emphasize sharing an experience, and are therefore coded as “Interpersonal” projects. Those with higher levels of self-transcendent wisdom appeared to prioritize deepening the connections they have, while those with lower reported levels of self-transcendent wisdom appear to retreat from others, engaging with projects that are accomplished alone, or are immediately salient.

Intrapersonal Projects

Intrapersonal projects cover activities that attempt to change or develop oneself (e.g., active self-care, personal growth, and spirituality). While participants with high self-transcendent wisdom reported more intrapersonal projects prior to physical distancing than participants with low self-transcendent wisdom, we see a spike in these projects among latter group during physical distancing that focus on managing negative emotions, particularly anger. Given the association between self-transcendent wisdom and feelings of interconnectedness and personal growth, it makes sense that the projects of those with higher levels of self-transcendent involve identifying ways to feel more content, happy and well, through e.g., meditation and self-care, during a global pandemic that generates an unprecedent level of anxiety and stress about the future. The projects of those low in self-transcendent wisdom, on the other hand, again, emphasize something immediate and visceral; in this case, anger management.

Maintenance

Across both groups of participants, a qualitatively noticeable difference was noted for participants with low, as compared to high, self-transcendent wisdom, toward very basic forms of survival projects during physical distancing. Projects such as grocery shopping, cooking , and cleaning were far more central for participants with low self-transcendent wisdom, particularly in comparison with the projects they listed having prior to physical distancing. As was the case with “Recreational” projects, participants with high self-transcendent wisdom emphasized interpersonal interactions even in their maintenance projects. The most common example of this was cooking with family . Rather than just mentioning the project of cooking, they specifically noted that were doing the task with family. This emphasis on spending time with others during what would otherwise be routine task moved such projects to the “Interpersonal” projects section.

Creative Projects

We created the category of “Creative” projects as distinct from “Academic,” “Work,” and “Recreational” projects in order to capture artistic projects, musical projects, or in some cases, learning languages, that lacked an emphasis on formal schooling, earning money, or hedonic fun. Creative projects instead emphasized making things or mastering skills. Prior to physical distancing, participants in both groups reported similar projects. The most common of these projects were what one would traditionally categorize as creative pursuits, such as painting, writing, or playing an instrument. During physical distancing, however, projects began to diverge. For low transcendence participants, even creative projects retain some element of a utilitarian goal: preparing food with a new recipe, for instance, or redecorating personal spaces. Creative projects among high-transcendence participants, on the other hand, tended to emphasize creation for creation's sake, with more emphasis on languages, fine arts, crafts, or even puzzles. Once again, participants with lower self-transcendent wisdom focused on concrete, tangible projects that often have a clear goal or result, while participants with higher self-transcendent wisdom focused on projects that appear more open-ended, abstract, and typically involve others.

Overall, by examining the participants with the lowest and highest self-transcendent wisdom we see a pattern of change in pre-pandemic to current personal project lists. Examples of personal project responses that display a pattern of transformation are displayed in Table 12 . The first and third example are participants with high self-transcendent wisdom, whereas the second example is a participant with low self-transcendent wisdom. Participants with high self-transcendent wisdom appeared to be more successful in staying connected with other people and larger causes. They often found new ways to spend their energy, either by connecting at a more local level or, in the case of one memorable participant displayed in Table 12 , radically scaling up their circle of concerns to new heights of political activism. Participants with low self-transcendent wisdom, by contrast, appeared to withdraw rather than venture outwards. While some managed to adjust to a world in which connections must be either immediately local or radically global, overall the projects of the lowest scoring participants seem to have been, for lack of a better word, crushed.

Table 12 . Exemplar participants pre-current personal project lists.

The analyses described above focused on determining predictors of two main variables: (1) retrospective perceptions of well-being before the beginning of physical distancing, and (2) the residuals between participants' retrospective well-being and participants' perceived well-being since the enactment of physical distancing measures, which we used to provide an estimate of change in perceived well-being since physical distancing began. Before we move to a general discussion, it is worth noting our overall approach to the interpretation of these data. Due to the retrospective nature of the data collection, we interpret these data used as representing idiographic participant self-understanding of change over time, as it seems to them at the time of data collection, rather than “objective” differences between present and past states of being. While psychology has historically emphasized nomothetic analyses of experience ( Munsterberg, 1899 ), idiographic approaches to data championed by Allport (1942) or more recently Lundh (2015) are particularly applicable to the study of events which are, incontestably, historical in nature, like the present pandemic. Indeed, computer-assisted textual analysis has revealed narrative patterns consistent with the quantitative and qualitative findings from our study, namely, that one is either experiencing the current pandemic as a time for vital re-evaluation of priorities, or as a fight for survival ( Venuleo et al., 2020 ).

In terms of quantitative findings, controlling for all other variables in the model, we observed a greater association between nationality, gender, personal wisdom, disengagement coping profile, retrospective health, loneliness, negative emotions, and meaning in life and participants' retrospective well-being than for other factors. Residualized current perceived health, negative emotions, loneliness, and alienation demonstrated the greatest association with residualized current well-being, again controlling for all other variables. The interaction between Disengaged coping and self-transcendent wisdom, as well as self-transcendent wisdom on its own, was strongly associated with both retrospective and residual well-being, as was retrospective meaning in life and social support. Controlling for all other variables, residualized current well-being is negatively associated retrospective pre-physical distanced well-being.

Many of these results are in line with past findings, both during and prior to the pandemic. For instance, personal wisdom ( Grossmann et al., 2013 ; Ardelt, 2019 ), health ( Aneshensel et al., 1984 ; Hayes and Ross, 1986 ; Hsieh and Waite, 2019 ; Park and Adler, 2003 ), and social support ( Turner, 1981 ; Thoits, 1985 ; Portero and Oliva, 2007 ; Hyde et al., 2011 ) are known to be predictive of well-being. Personal wisdom in particular has been previously found to be a protective factor for psychological well-being during the COVID-19 pandemic ( Pellerin and Raufaste, 2020 ), though it does not appear to impact residualized current well-being in the present sample. The coping responses from our participants also align with those who have experienced similar outbreaks ( Chew et al., 2020 ; Rajkumar, 2020 ). Although some strategies (e.g., distraction) may be deemed maladaptive, evidence suggests their short-term efficacy in dealing with uncontrollable situations ( Janson and Rohleder, 2017 ), explaining the existence of the Disengaged coping profile. While recent research by Park et al. (2020) also found evidence that demographic factors (e.g., age and socio-economic status) may predict differential coping responses with the pandemic, only nationality and gender appear to play a role in the models presented here. Of the two, Canada has had significantly fewer cases of COVID-19 relative to its population than the United States, as well as more centralized support from the federal government, while the pandemic is well-known to have had a disproportionate impact on women relative to men ( Alon et al., 2020 ). In summary, there do not appear to be any surprises in predictors of current well-being.

In line with previous findings that strong interpersonal relationships predict more positive experiences of solitude ( Pauly et al., 2018 ), our qualitative analyses found that participants with high self-transcendent wisdom strongly emphasized how their projects during times of physical distancing helped connect them to friends, family, and community. Previous research examining the presence of meaning in life have consistently found that meaning relates to connectedness , whether through existential mattering ( Costin and Vignoles, 2020 ), relationships of mutual care and trust ( Wong, 2020 ), or an overall sense of coherence ( Park, 2010 ). Good relationships with others are also consistently placed among the most important aspects of what it means to live a good life the world over ( Tafarodi et al., 2012 ; Bonn and Tafarodi, 2013 ). As such, the finding that the participants who are relatively thriving during periods of physical distancing have managed to center and maintain these relationships is consistent with several models of a good, meaningful life. The finding that participants with low self-transcendent wisdom have found it apparently difficult to maintain such relationships and seem to be slipping into escapism and self-distraction is consonant with the narratives of “global crisis” and “surviving a war” identified by Venuleo et al. (2020) as most frequent amongst people experiencing greater instability during lockdown measures in Italy. Combined with our quantitative findings that loneliness and alienation demonstrated negative associations with perceived well-being, such findings further evidence for the importance of strong, resilient relationships to weathering misfortune, particularly on misfortune on such a magnified scale.

That participants with the highest self-transcendent wisdom were more likely to be religious is an interesting finding, and one for which the framework of existential positive psychology provides some context. While it might be too strong a claim that religion itself is necessary, Wong's (2020) model of existential meaning emphasizes the importance of faith and concern for greater things in cultivating meaning, which religious participants could be reasonably expected to experience more strongly than non-religious participants. Religion is also known to have strong anxiolytic effects ( Kay et al., 2010 ; Newton and McIntosh, 2010 ). Interestingly, self-transcendent wisdom, otherwise an important factor in predicting change in well-being, was had a reduced impact for participants with a Religious coping profile.

Self-transcendence is defined as decreased egoic self-salience and increased feelings of connectedness to something larger than oneself ( Kitson et al., 2020 ). A sense of connectedness can provide an anchor point for coping ( Frydenberg and Lewis, 2009 ), and strengthening that sense of connectedness underlies both self-transcendence ( Kitson et al., 2020 ) and cultivation of meaning in life ( George and Park, 2016 ; Costin and Vignoles, 2020 ). In developmental research, self-transcendence is related to—and perhaps a precondition for— developing wisdom ( Aldwin et al., 2019 ), with the Adult Self-Transcendence Inventory being designed to evaluate such self-transcendent wisdom. Based on our findings, it appears that self-transcendent wisdom contributes to current well-being over and above coping style and predicts change in well-being for people using all coping styles, except for those using mainly Religious coping.

That self-transcendent wisdom seemed to have a stronger contribution to variance in well-being over coping for Profiles 2 (Substance Use) and 4 (Disengagement) than for Profiles 1 (Religious) and 3 (Average) is somewhat surprising. Perhaps wiser people have a deeper understanding of negative emotions as not necessarily bad or maladaptive; used appropriately, they can help signal the need to engage adaptive strategies for psychological safety or strategies that can generate psychological growth ( Webster, in press ). Likewise, even avoidance coping may be adaptive in certain clinical contexts [see Hofmann and Hay (2018) ].

A decreased acceptance of ongoing negative events might also have played a role. Previous research in mindfulness has found that the “non-judgmental acceptance” component of mindfulness is negatively associated with both intuition ( Remmers et al., 2014 ) and wise reasoning ( Kim et al., 2020 ), suggesting that acceptance may circumvent the exploratory processing needed to achieve greater well-being ( Weststrate, 2019 ). Pellerin and Raufaste (2020) similarly find that in the current pandemic climate, peaceful disengagement actually predicts a decline in well-being over time. Wiser individuals are particularly good at managing the sense of uncertainty and uncontrollability that necessarily comes with adverse experiences ( Glück et al., 2018 ; Glück, in press ). According to Glück et al.'s (2018 ) MORE model, wise individuals can sustain a higher level of negative emotions when trying to understand the complexity of a situation. Therefore, their use of different types of coping strategies can help maximize their well-being ( Glück, in press ).

However, for participants who already had adaptive coping mechanisms, their existing strategies probably accounted for most of the added benefit of self-transcendent wisdom, although self-transcendent wisdom still played a role in predicting their well-being. Coping strategies appear to be important for well-being in daily life ( Ben-Zur, 2009 ), as well as for helping to maintain a baseline functioning during stressful events ( Park and Adler, 2003 ). However, self-transcendent wisdom is the more robust indicator, when comparing coping and self-transcendence as indicators of well-being ( McCarthy et al., 2013 ). Additionally, the use of Religious coping may overlap sufficiently with self-transcendent wisdom in motivating attention to concerns beyond the self so as to reduce any apparent impact.

Interestingly, self-transcendence was not a significant predictor of well-being in a previous study of protective factors during the COVID-19 pandemic. Pellerin and Raufaste (2020) found that self-transcendence was only related to well-being when all other potential psychological resources (i.e., personal wisdom, self-efficacy, optimism, hope, and gratitude) were not controlled for; thus, they consider self-transcendence a meta-resource that affords the development of other resources, or perhaps this reflects a floor effect: an individual may need higher self-transcendence in order to see a benefit. Our findings suggest that it is not greater self-transcendence, but rather a more holistic approach to it that is needed to see results. While Pellerin and Raufaste (2020) used only the self-transcendence ASTI subscale in their research, to specifically target self-transcendence as an independent variable, our study used all five subscales to measure self-transcendent wisdom in its full spectrum. Our findings also suggest that self-transcendent wisdom may make the biggest contribution when an individual lacks healthy, adaptive coping strategies. Participants with adaptive coping skills could simply apply what they already know to the present situation. Without such skills, however, self-transcendent wisdom may make the difference between a traumatic experience and a transformative one.

In the philosophical literature on self-transformation, a distinction is made between self-transformation and self-cultivation ( Callard, 2018 ). Unlike self-transformation, self-cultivation involves no radical shift in values, but instead refines their ability to apply existing values. After self-cultivation, one is simply a more effective version of the same person they were before. Self-transformation, on the other hand, involves a radical shift in values ( Paul, 2014 ). Sometimes, transformation is a consequence of unexpected situations, like unplanned parenthood. At other times, self-transformation is an active pursuit, as for spiritual aspirants, or in the best traditions of liberal education ( Callard, 2017 ). In both cases, a person may be unrecognizable to their past self after self-transformation; their priorities, values, and approach to life may come to be entirely different than those they held before. In our current sample, participants with an adaptive coping profile seem to be engaged in self-cultivation —using and refining what they already know to be good for them—while participants with other coping profiles seek self-transformation.

Although the pandemic has severely affected every area of public life, it has also deepened some individuals' connections to others and complexified their worldview, which could potentially allow post-traumatic growth (PTG), defined as positive psychological change following trauma that results in a greater appreciation for life, increased personal strength, spiritual growth, more meaningful relationships, and the recognition of new possibilities ( Tedeschi and Calhoun, 1996 ). Traumatic events that trigger PTG are often described as “seismic” ( Blevins and Tedeschi, in press ), disrupting someone's entire way of life and potentially their existing coping strategies. For many people, the COVID-19 pandemic qualifies as a seismic event, given that it not only provokes a health scare, but interrupts the familiar rhythms and patterns of daily life, is impossible to escape, and has made common means of self-distraction like travel or simply going to a pub life-threatening. It has therefore, forced many people to begin to examine alternative ways of life.

Among the participants high in self-transcendent wisdom, we see evidence of such a shift in priorities. Projects oriented around family or immediate communities of friends become more prevalent during physical distancing than they were before. Intrapersonal projects, aimed at some sort of personal change, also become more focal: meditation, yoga, and contemplation on a good life become projects among participants with high self-transcendent wisdom. Memorably, one person showed a newfound commitment to political activism, possibly spurred by the surge in racial justice protests that began during the time of data collection. These projects closely match the pattern of activities that Calhoun et al. (2010) argue best facilitate PTG: reassessing one's goals, strengths, and priorities, sociocultural influences (such as social support and role models), and strategies to manage ongoing stress. They also closely match the conditions that Callard (2018) argues are ideal for supporting intentional self-transformation: ideals, a supportive community, and a sense that such transformation will be meaningful. Previous evidence following the SARS epidemic found that some individuals reported experiencing positive life transformations, similar to PTG ( Lau et al., 2006 ). Blevins and Tedeschi (in press) suggest that PTG reflects an ability for people to respond well to adversity and experience positive changes following the attempt to make sense of a disrupted world. Similar themes to PTG and the conditions for self-transformation have been identified by existential positive psychology in positioning confrontation with periods of suffering as opportunities for cultivating a greater sense of meaning ( Wong, 2020 ). The COVID-19 pandemic has severely disrupted our own worldviews and requires this sense of reconstruction to cope with our new reality.

To use an analogy, the relationship between adaptive coping and self-transcendent wisdom may be compared to boiling water. As one heats a pot of water, at some point, when the liquid water has no more capacity to disperse energy, it turns to steam. People with existing adaptive coping strategies are analogous to a larger pot of water, which takes more heat and longer exposure to boil. Those without such strategies, however, are analogous to smaller pots; the heat represented by the current disruption to daily life is enough to require them not just to cope, but to change.

Limitations

Like all studies, our study has limitations. The most salient of these is that it captures a single moment in time, representing the experience of North Americans in the early summer of 2020. It is possible that some of our findings might differ were the same questions to be asked of a different sample, or even of the same sample now, in the second winter wave of the pandemic. Another limitation of the present study is that our “baseline” measures from before the pandemic are retrospective, not pre-recorded. While this might open our study up to recency and saliency biases, we feel that this concern is balanced out by the strengths of this retrospective method: a high self-rating of well-being now may be far more meaningful than such a rating a year ago. Importantly, our interest in the present study was predominately idiographic, rather than nomothetic. Our findings should be interpreted as presenting participants' self-understanding of their life and experiences of change during a period of physical distancing and how that has changed, rather than as impersonal objective measures at two points in time. While some researchers were fortunate enough to have baseline measures for their participants that pre-dated the pandemic [see Hamza et al. (2020) ], the methods of the present study relied on participant self-understanding in the moment of data collection. Relatedly, it must be remembered that our study is exploratory, not confirmatory. We began this study to investigate a broad assortment of possible influences on how North Americans were spending their time during social distancing as compared to before such measures were enacted, and how this relates to their reported sense of well-being. Our findings, however, repeat a fairly consistent theme in the positive, existential, narrative, and phenomenological psychologies of well-being: feeling connected to others is vital to experiencing a meaningful life.

Conclusions

The present study used a broad range of measures to explore contributing factors to participants' well-being during physical distancing resulting from the COVID-19 pandemic. In particular, we used retrospective comparison to examine perceived changes in well-being prior to the pandemic, and how they contributed to a change in well-being at the time of the study. We found that self-transcendent wisdom and perceived meaning in life demonstrated the strongest positive associations with change in perceived well-being when controlling for all other variables. Analysis of the personal projects of participants reporting the highest levels of self-transcendent wisdom revealed a pattern consistent with models of PTG and aspirational self-transformation. Our findings suggest that while most participants experienced a decline in well-being, for understandable reasons (e.g., loneliness, negative emotions, and alienation), higher levels of self-transcendent wisdom were associated with positive changes in well-being during physical distancing as compared to before—especially for participants with merely average coping mechanisms, or who belonged to the Substance Use coping profile. Our findings suggest ways to avoid having the COVID-19 pandemic become the traumatic event of a generation, but instead a genuine watershed moment for growth.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The studies involving human participants were reviewed and approved by University of Toronto Research Ethics Board. The participants provided their written informed consent to participate in this study.

Author Contributions

JK, MM, ZF, and SM designed the study and contributed to writing the manuscript. JK provided theoretical framing and performed qualitative analysis. MM, MA, and RA performed latent profile analysis and data visualization. ZF performed descriptive statistics, multiple regression analysis, and data visualization. SM provided the original concept for the study, performed qualitative analysis, and data visualization. MF provided funding, resources, supervision for the study, and reviewed the manuscript. All authors contributed to the article and approved the submitted version.

This project was funded by a University of Toronto Faculty Research grant to MF.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2021.648060/full#supplementary-material

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Keywords: coronavirus, physical distancing, self-transcendence, well-being, coping

Citation: Kim JJ, Munroe M, Feng Z, Morris S, Al-Refae M, Antonacci R and Ferrari M (2021) Personal Growth and Well-Being in the Time of COVID: An Exploratory Mixed-Methods Analysis. Front. Psychol. 12:648060. doi: 10.3389/fpsyg.2021.648060

Received: 31 December 2020; Accepted: 22 February 2021; Published: 24 March 2021.

Reviewed by:

Copyright © 2021 Kim, Munroe, Feng, Morris, Al-Refae, Antonacci and Ferrari. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Juensung J. Kim, juensung.kim@mail.utoronto.ca

† These authors have contributed equally to this work and share first authorship

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Research paper: growth mindset and personal growth.

Personal growth may become an important topic for each of us at any moment in time. It shows when we realize the need to live our life with purpose, authenticity, and showing concern towards others.

Personal growth can be referred also as self-improvement and self-growth.

It is a process that requires an open mind, motivation, the desire to improve, to learn, but also the willingness to get out of the current comfort zone, and even to feel sometimes uncomfortable. It also implies to strive to make changes.

Personal growth is possible if we are willing to develop a positive mindset, a growth mindset.

According to the Merriam Webster dictionary, one definition of growth is“progressive development” and mindset is defined as“a mental attitude or inclination”.

The logical conclusion is that having a growth mindset means having a mental attitude that leads to progressive development.

The growth mindset has its roots in the Mindset Theory. At the base of the theory sits the idea that our beliefs influence the way we respond to life’s situations. The theory premises start from the way we assess our capabilities, talents, and intelligence and their impact on our lives and success. (Murphy & Dweck, 2016).

Over 30 years ago, ProfessorCarol Dweck and her colleagues studied the behavior of thousands of children on learning and they defined terms as fixed mindset and growth mindset to describe the underlying beliefs about learning and intelligence. The study demonstrated that understanding the need of putting in extra effort and time in our endeavors can lead to higher achievement.

Fixed Mindset

A fixed mindset describes people who believe that intelligence, talent, or natural-born skills are enough to lead to success and these cannot be improved.

People with fixed mindsets may avoid challenges, give up easily, and ignore useful feedback.

Growth Mindset

A growth mindset describes people who believe that can get better at something or succeed by the dedication of time, effort, and energy. People with a growth mindset embrace challenges, overcome obstacles, learn from feedback, and seek out inspiration, that can contribute to their success.

The difference between the two mindsets is that one view doesn’t support change, while the other support opportunities for improvement and can lead to change.

Understanding the benefit of cultivating a growth mindset can be very powerful and willingness to put in extra time and effort can lead to achieving desired goals. This can contribute to a fuller, more meaningful life.

The dominant mindset can show on handling a task, a project, or a situation.

We can choose to tell ourselves that we cannot handle it, we do not have enough abilities, we are not trained to do that we will find excuses not to handle it. We can choose also to see it as an opportunity to learn something new, to improve our skills, to search for resources and support to handle the topic, and finally to grow.

The growth mindset can lead us in acquiring new skills, new knowledge, and step into new areas of expertise.

How can the growth mindset be cultivated?

Personal growth is a continuing process. Cultivating a growth mindset can be very empowering and can boost our confidence to try new ways, determine us to concentrate our efforts on desired outcomes, and move us one step forward towards achieving what is meaningful to us.

By knowing precisely what we want to achieve, we can think about what skills can we use, what else do we need to learn, when is the right time to start; we can estimate how much time do we need and where do we want to concentrate our efforts. We would be able to deal with problems and challenges, to spot the distractions or barriers that might stop us or lead us astray. We move on the path to growth, learning, self-esteem, and confidence.

Self-reflection:

• Define for yourself what your purpose encompasses;
• Explore the things you are passionate about;
• Cultivate your self-awareness: more aware of your strengths and weaknesses;
• Reflect on your former experiences: understand and apply the learnings;
• Replace judgment with acceptance: pay attention to your words and thoughts;
• Create a new perspective and trust your skills and abilities;
• Commit to embracing challenges: prepare yourself for success and risk;
• Estimate realistically the time and effort your goal will take;
• Cultivate your determination and perseverance: put in hard work, weight the obstacles, think about the measures in place to overcome them;
• Value the learning process over the result;
• Reflect on your learning regularly;
• Take ownership of your attitude.

Coaching Application

Coaching serves us to explore a new path or to navigate through new circumstances.

The coaching space is set for us to explore the many perspectives that we experience in life, to enhance our skills and resources, to discover the answers within ourselves. 

During the coaching journey, you can explore how you look at the world, what inspires you; you can achieve clarity and you can understand what ideas or thoughts might be blocking our progress.

You will begin to see and think through things in a clearer and more balanced way:

• Where am I now?
• Where do I want to be?
• How can I get there?

ICA Coaching Power Tools for personal growth empowerment

Reframing is an important part of the coaching process. It’s about creating a shift and seeing new perspectives. We can look at a situation, analyze it, discern, and re-frame perspectives. However, a coach is an objective observer to our situation and can help the client, to identify unhelpful perspectives, and to support him to re-frame them. (ICA Reframing perspectives)

During the coaching process, the client is supported to lighten his current perspective, he will be able to step back, take some distance, and gain greater clarity on the situation. The clients present in the moment, free of judgments that can bind him to old ways of thinking. Discussing the worst-case scenario enables shifting the view from significance to lightness. (ICA Lightness vs Significance)

We can create a powerful platform for sustainable personal and professional growth if we start from a self-trust perspective. Often, we give space to doubt, as we let the judgments about ourselves prevail and hold us back. To trust ourselves we need to know what our beliefs are, our values, and our purpose. The coach is partnering with the client to explore and find ways in which they can create a perspective of trust. (ICA Trust vs Doubt)

Blame keeps us from fully enjoying and engaging in our lives. When we view responsibility as a privilege, instead of as a burden, we awaken many possibilities for change and growth. Using a powerful question, the coach can support the client to consider his role in the situation, and thus taking a big step towards becoming responsible. (ICA Responsibility vs Blame)

Action is the foundation needed to push us forward to achieve our goals. It is the path to growth, learning, self-esteem, and confidence. Negative judgments about ourselves can pull us back and keeps us stuck, choosing to delay instead to act. The coach can support the client to explore a different point of view and thus creating a new way of looking at the situation. By using powerful questioning, the coach can support the client to move from a dis-empowering to an empowering perspective. The client can decide to turn concerns into action. (ICA Action vs Delay)

Exploring our underlying beliefs and what we are truly committed to, we can realize that we have choices. Following through on commitments and act upon, instead of only trying gives us the desire to change. When we are determined to commit to our values, our vision, we are more likely to view these as learning opportunities and keep moving forward. In the process, we will build confidence and self-trust. Working with the client, the coach will need to support him in understanding what he wants to commit to. The coach’s role is to support the client to see the importance of aligning his own beliefs with the desired pathway forward. (ICA Commitment vs Trying)

Some thought-provoking questions to support the client in moving forward:

• What is it that you're deeply passionate about?
• Which are the areas that interest you?
• What do others see in you?
• What is your reaction when faced with a demand or a challenge?
• If you would consider your goal without worrying, what would you do?
• What might keep you from getting where you want to go?
• If all the obstacles would be removed how would that change your view?
• What can you do about the part you can/ cannot change?
• Let’s just assume for a moment that the worst thing that could happen has already happened what will you do now?
• Which option do you want to pursue?
• What can help you to feel confident that this course of action is the right one?
• If you need to translate that into action steps, what exactly will you do?
• What resources do you have access to?
• How’s your experience today getting you closer to what you want for yourself?

Having a growth mindset cannot be considered the solution to every problem; however, choosing to make the extra effort to build a growth mindset will likely make it easier and more enjoyable to work hard, it will give you the confidence you need to act towards your goals.

A growth mindset means to embraces challenges, to persists in the face of setbacks, take responsibility for actions, and acknowledge the required effort and time.

By taking the value of coaching into your life, you will be able to extend permanently your growth zone. You will eventually set new goals.

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https://www.merriam-webster.com/dictionary/growth

https://www.mindsetworks.com/science/

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The Journey of Personal Growth: A Qualitative Exploration of Personal Growth Processes in Young Adulthood

• Research in Progress
• Published: 14 November 2013
• Volume 58 , pages 456–463, ( 2013 )

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• Anindita Bhattacharya 1 &
• Seema Mehrotra 1  

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The present study aimed at qualitative exploration of personal growth processes among young adults. It also explored the linkages of personal growth processes with implicit beliefs and possible selves. An extreme case sampling approach was used and it involved two groups of individuals, those high and low on action orientation. A semi structured interview was utilized to elicit subjective accounts of these individuals about their personal growth goals and related processes. A thematic analysis of the interview protocols that individuals actively striving towards personal growth often endorsed incremental theory beliefs (considered their current self as mutable) in comparison to people not working actively on their personal growth goals. As the study focused on malleable variables such as beliefs, strategies and manner of approach to life goals, it has implications in designing promotive intervention programs to help young adults discover ways of strengthening and sustaining their motivation and efforts in intentional pursuit of their personal growth goals.

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Bhattacharya, A., Mehrotra, S. The Journey of Personal Growth: A Qualitative Exploration of Personal Growth Processes in Young Adulthood. Psychol Stud 58 , 456–463 (2013). https://doi.org/10.1007/s12646-013-0222-x

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• Open access
• Published: 17 October 2023

The impact of founder personalities on startup success

• Paul X. McCarthy 1 , 2 ,
• Xian Gong 3 ,
• Fabian Braesemann 4 , 5 ,
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• Marian-Andrei Rizoiu 3 &
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Startup companies solve many of today’s most challenging problems, such as the decarbonisation of the economy or the development of novel life-saving vaccines. Startups are a vital source of innovation, yet the most innovative are also the least likely to survive. The probability of success of startups has been shown to relate to several firm-level factors such as industry, location and the economy of the day. Still, attention has increasingly considered internal factors relating to the firm’s founding team, including their previous experiences and failures, their centrality in a global network of other founders and investors, as well as the team’s size. The effects of founders’ personalities on the success of new ventures are, however, mainly unknown. Here, we show that founder personality traits are a significant feature of a firm’s ultimate success. We draw upon detailed data about the success of a large-scale global sample of startups (n = 21,187). We find that the Big Five personality traits of startup founders across 30 dimensions significantly differ from that of the population at large. Key personality facets that distinguish successful entrepreneurs include a preference for variety, novelty and starting new things (openness to adventure), like being the centre of attention (lower levels of modesty) and being exuberant (higher activity levels). We do not find one ’Founder-type’ personality; instead, six different personality types appear. Our results also demonstrate the benefits of larger, personality-diverse teams in startups, which show an increased likelihood of success. The findings emphasise the role of the diversity of personality types as a novel dimension of team diversity that influences performance and success.

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The success of startups is vital to economic growth and renewal, with a small number of young, high-growth firms creating a disproportionately large share of all new jobs 1 , 2 . Startups create jobs and drive economic growth, and they are also an essential vehicle for solving some of society’s most pressing challenges.

As a poignant example, six centuries ago, the German city of Mainz was abuzz as the birthplace of the world’s first moveable-type press created by Johannes Gutenberg. However, in the early part of this century, it faced several economic challenges, including rising unemployment and a significant and growing municipal debt. Then in 2008, two Turkish immigrants formed the company BioNTech in Mainz with another university research colleague. Together they pioneered new mRNA-based technologies. In 2020, BioNTech partnered with US pharmaceutical giant Pfizer to create one of only a handful of vaccines worldwide for Covid-19, saving an estimated six million lives 3 . The economic benefit to Europe and, in particular, the German city where the vaccine was developed has been significant, with windfall tax receipts to the government clearing Mainz’s €1.3bn debt and enabling tax rates to be reduced, attracting other businesses to the region as well as inspiring a whole new generation of startups 4 .

While stories such as the success of BioNTech are often retold and remembered, their success is the exception rather than the rule. The overwhelming majority of startups ultimately fail. One study of 775 startups in Canada that successfully attracted external investment found only 35% were still operating seven years later 5 .

But what determines the success of these ‘lucky few’? When assessing the success factors of startups, especially in the early-stage unproven phase, venture capitalists and other investors offer valuable insights. Three different schools of thought characterise their perspectives: first, supply-side or product investors : those who prioritise investing in firms they consider to have novel and superior products and services, investing in companies with intellectual property such as patents and trademarks. Secondly, demand-side or market-based investors : those who prioritise investing in areas of highest market interest, such as in hot areas of technology like quantum computing or recurrent or emerging large-scale social and economic challenges such as the decarbonisation of the economy. Thirdly, talent investors : those who prioritise the foundation team above the startup’s initial products or what industry or problem it is looking to address.

Investors who adopt the third perspective and prioritise talent often recognise that a good team can overcome many challenges in the lead-up to product-market fit. And while the initial products of a startup may or may not work a successful and well-functioning team has the potential to pivot to new markets and new products, even if the initial ones prove untenable. Not surprisingly, an industry ‘autopsy’ into 101 tech startup failures found 23% were due to not having the right team—the number three cause of failure ahead of running out of cash or not having a product that meets the market need 6 .

Accordingly, early entrepreneurship research was focused on the personality of founders, but the focus shifted away in the mid-1980s onwards towards more environmental factors such as venture capital financing 7 , 8 , 9 , networks 10 , location 11 and due to a range of issues and challenges identified with the early entrepreneurship personality research 12 , 13 . At the turn of the 21st century, some scholars began exploring ways to combine context and personality and reconcile entrepreneurs’ individual traits with features of their environment. In her influential work ’The Sociology of Entrepreneurship’, Patricia H. Thornton 14 discusses two perspectives on entrepreneurship: the supply-side perspective (personality theory) and the demand-side perspective (environmental approach). The supply-side perspective focuses on the individual traits of entrepreneurs. In contrast, the demand-side perspective focuses on the context in which entrepreneurship occurs, with factors such as finance, industry and geography each playing their part. In the past two decades, there has been a revival of interest and research that explores how entrepreneurs’ personality relates to the success of their ventures. This new and growing body of research includes several reviews and meta-studies, which show that personality traits play an important role in both career success and entrepreneurship 15 , 16 , 17 , 18 , 19 , that there is heterogeneity in definitions and samples used in research on entrepreneurship 16 , 18 , and that founder personality plays an important role in overall startup outcomes 17 , 19 .

Motivated by the pivotal role of the personality of founders on startup success outlined in these recent contributions, we investigate two main research questions:

Which personality features characterise founders?

Do their personalities, particularly the diversity of personality types in founder teams, play a role in startup success?

We aim to understand whether certain founder personalities and their combinations relate to startup success, defined as whether their company has been acquired, acquired another company or listed on a public stock exchange. For the quantitative analysis, we draw on a previously published methodology 20 , which matches people to their ‘ideal’ jobs based on social media-inferred personality traits.

We find that personality traits matter for startup success. In addition to firm-level factors of location, industry and company age, we show that founders’ specific Big Five personality traits, such as adventurousness and openness, are significantly more widespread among successful startups. As we find that companies with multi-founder teams are more likely to succeed, we cluster founders in six different and distinct personality groups to underline the relevance of the complementarity in personality traits among founder teams. Startups with diverse and specific combinations of founder types (e. g., an adventurous ‘Leader’, a conscientious ‘Accomplisher’, and an extroverted ‘Developer’) have significantly higher odds of success.

We organise the rest of this paper as follows. In the Section " Results ", we introduce the data used and the methods applied to relate founders’ psychological traits with their startups’ success. We introduce the natural language processing method to derive individual and team personality characteristics and the clustering technique to identify personality groups. Then, we present the result for multi-variate regression analysis that allows us to relate firm success with external and personality features. Subsequently, the Section " Discussion " mentions limitations and opportunities for future research in this domain. In the Section " Methods ", we describe the data, the variables in use, and the clustering in greater detail. Robustness checks and additional analyses can be found in the Supplementary Information.

Our analysis relies on two datasets. We infer individual personality facets via a previously published methodology 20 from Twitter user profiles. Here, we restrict our analysis to founders with a Crunchbase profile. Crunchbase is the world’s largest directory on startups. It provides information about more than one million companies, primarily focused on funding and investors. A company’s public Crunchbase profile can be considered a digital business card of an early-stage venture. As such, the founding teams tend to provide information about themselves, including their educational background or a link to their Twitter account.

We infer the personality profiles of the founding teams of early-stage ventures from their publicly available Twitter profiles, using the methodology described by Kern et al. 20 . Then, we correlate this information to data from Crunchbase to determine whether particular combinations of personality traits correspond to the success of early-stage ventures. The final dataset used in the success prediction model contains n = 21,187 startup companies (for more details on the data see the Methods section and SI section  A.5 ).

Revisions of Crunchbase as a data source for investigations on a firm and industry level confirm the platform to be a useful and valuable source of data for startups research, as comparisons with other sources at micro-level, e.g., VentureXpert or PwC, also suggest that the platform’s coverage is very comprehensive, especially for start-ups located in the United States 21 . Moreover, aggregate statistics on funding rounds by country and year are quite similar to those produced with other established sources, going to validate the use of Crunchbase as a reliable source in terms of coverage of funded ventures. For instance, Crunchbase covers about the same number of investment rounds in the analogous sectors as collected by the National Venture Capital Association 22 . However, we acknowledge that the data source might suffer from registration latency (a certain delay between the foundation of the company and its actual registration on Crunchbase) and success bias in company status (the likeliness that failed companies decide to delete their profile from the database).

The definition of startup success

The success of startups is uncertain, dependent on many factors and can be measured in various ways. Due to the likelihood of failure in startups, some large-scale studies have looked at which features predict startup survival rates 23 , and others focus on fundraising from external investors at various stages 24 . Success for startups can be measured in multiple ways, such as the amount of external investment attracted, the number of new products shipped or the annual growth in revenue. But sometimes external investments are misguided, revenue growth can be short-lived, and new products may fail to find traction.

Success in a startup is typically staged and can appear in different forms and times. For example, a startup may be seen to be successful when it finds a clear solution to a widely recognised problem, such as developing a successful vaccine. On the other hand, it could be achieving some measure of commercial success, such as rapidly accelerating sales or becoming profitable or at least cash positive. Or it could be reaching an exit for foundation investors via a trade sale, acquisition or listing of its shares for sale on a public stock exchange via an Initial Public Offering (IPO).

For our study, we focused on the startup’s extrinsic success rather than the founders’ intrinsic success per se, as its more visible, objective and measurable. A frequently considered measure of success is the attraction of external investment by venture capitalists 25 . However, this is not in and of itself a good measure of clear, incontrovertible success, particularly for early-stage ventures. This is because it reflects investors’ expectations of a startup’s success potential rather than actual business success. Similarly, we considered other measures like revenue growth 26 , liquidity events 27 , 28 , 29 , profitability 30 and social impact 31 , all of which have benefits as they capture incremental success, but each also comes with operational measurement challenges.

Therefore, we apply the success definition initially introduced by Bonaventura et al. 32 , namely that a startup is acquired, acquires another company or has an initial public offering (IPO). We consider any of these major capital liquidation events as a clear threshold signal that the company has matured from an early-stage venture to becoming or is on its way to becoming a mature company with clear and often significant business growth prospects. Together these three major liquidity events capture the primary forms of exit for external investors (an acquisition or trade sale and an IPO). For companies with a longer autonomous growth runway, acquiring another company marks a similar milestone of scale, maturity and capability.

Using multifactor analysis and a binary classification prediction model of startup success, we looked at many variables together and their relative influence on the probability of the success of startups. We looked at seven categories of factors through three lenses of firm-level factors: (1) location, (2) industry, (3) age of the startup; founder-level factors: (4) number of founders, (5) gender of founders, (6) personality characteristics of founders and; lastly team-level factors: (7) founder-team personality combinations. The model performance and relative impacts on the probability of startup success of each of these categories of founders are illustrated in more detail in section  A.6 of the Supplementary Information (in particular Extended Data Fig.  19 and Extended Data Fig.  20 ). In total, we considered over three hundred variables (n = 323) and their relative significant associations with success.

The personality of founders

Besides product-market, industry, and firm-level factors (see SI section  A.1 ), research suggests that the personalities of founders play a crucial role in startup success 19 . Therefore, we examine the personality characteristics of individual startup founders and teams of founders in relationship to their firm’s success by applying the success definition used by Bonaventura et al. 32 .

Employing established methods 33 , 34 , 35 , we inferred the personality traits across 30 dimensions (Big Five facets) of a large global sample of startup founders. The startup founders cohort was created from a subset of founders from the global startup industry directory Crunchbase, who are also active on the social media platform Twitter.

To measure the personality of the founders, we used the Big Five, a popular model of personality which includes five core traits: Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Emotional stability. Each of these traits can be further broken down into thirty distinct facets. Studies have found that the Big Five predict meaningful life outcomes, such as physical and mental health, longevity, social relationships, health-related behaviours, antisocial behaviour, and social contribution, at levels on par with intelligence and socioeconomic status 36 Using machine learning to infer personality traits by analysing the use of language and activity on social media has been shown to be more accurate than predictions of coworkers, friends and family and similar in accuracy to the judgement of spouses 37 . Further, as other research has shown, we assume that personality traits remain stable in adulthood even through significant life events 38 , 39 , 40 . Personality traits have been shown to emerge continuously from those already evident in adolescence 41 and are not significantly influenced by external life events such as becoming divorced or unemployed 42 . This suggests that the direction of any measurable effect goes from founder personalities to startup success and not vice versa.

As a first investigation to what extent personality traits might relate to entrepreneurship, we use the personality characteristics of individuals to predict whether they were an entrepreneur or an employee. We trained and tested a machine-learning random forest classifier to distinguish and classify entrepreneurs from employees and vice-versa using inferred personality vectors alone. As a result, we found we could correctly predict entrepreneurs with 77% accuracy and employees with 88% accuracy (Fig.  1 A). Thus, based on personality information alone, we correctly predict all unseen new samples with 82.5% accuracy (See SI section  A.2 for more details on this analysis, the classification modelling and prediction accuracy).

We explored in greater detail which personality features are most prominent among entrepreneurs. We found that the subdomain or facet of Adventurousness within the Big Five Domain of Openness was significant and had the largest effect size. The facet of Modesty within the Big Five Domain of Agreeableness and Activity Level within the Big Five Domain of Extraversion was the subsequent most considerable effect (Fig.  1 B). Adventurousness in the Big Five framework is defined as the preference for variety, novelty and starting new things—which are consistent with the role of a startup founder whose role, especially in the early life of the company, is to explore things that do not scale easily 43 and is about developing and testing new products, services and business models with the market.

Once we derived and tested the Big Five personality features for each entrepreneur in our data set, we examined whether there is evidence indicating that startup founders naturally cluster according to their personality features using a Hopkins test (see Extended Data Figure  6 ). We discovered clear clustering tendencies in the data compared with other renowned reference data sets known to have clusters. Then, once we established the founder data clusters, we used agglomerative hierarchical clustering. This ‘bottom-up’ clustering technique initially treats each observation as an individual cluster. Then it merges them to create a hierarchy of possible cluster schemes with differing numbers of groups (See Extended Data Fig.  7 ). And lastly, we identified the optimum number of clusters based on the outcome of four different clustering performance measurements: Davies-Bouldin Index, Silhouette coefficients, Calinski-Harabas Index and Dunn Index (see Extended Data Figure  8 ). We find that the optimum number of clusters of startup founders based on their personality features is six (labelled #0 through to #5), as shown in Fig.  1 C.

To better understand the context of different founder types, we positioned each of the six types of founders within an occupation-personality matrix established from previous research 44 . This research showed that ‘each job has its own personality’ using a substantial sample of employees across various jobs. Utilising the methodology employed in this study, we assigned labels to the cluster names #0 to #5, which correspond to the identified occupation tribes that best describe the personality facets represented by the clusters (see Extended Data Fig.  9 for an overview of these tribes, as identified by McCarthy et al. 44 ).

Utilising this approach, we identify three ’purebred’ clusters: #0, #2 and #5, whose members are dominated by a single tribe (larger than 60% of all individuals in each cluster are characterised by one tribe). Thus, these clusters represent and share personality attributes of these previously identified occupation-personality tribes 44 , which have the following known distinctive personality attributes (see also Table  1 ):

Accomplishers (#0) —Organised & outgoing. confident, down-to-earth, content, accommodating, mild-tempered & self-assured.

Leaders (#2) —Adventurous, persistent, dispassionate, assertive, self-controlled, calm under pressure, philosophical, excitement-seeking & confident.

Fighters (#5) —Spontaneous and impulsive, tough, sceptical, and uncompromising.

We labelled these clusters with the tribe names, acknowledging that labels are somewhat arbitrary, based on our best interpretation of the data (See SI section  A.3 for more details).

For the remaining three clusters #1, #3 and #4, we can see they are ‘hybrids’, meaning that the founders within them come from a mix of different tribes, with no one tribe representing more than 50% of the members of that cluster. However, the tribes with the largest share were noted as #1 Experts/Engineers, #3 Fighters, and #4 Operators.

To label these three hybrid clusters, we examined the closest occupations to the median personality features of each cluster. We selected a name that reflected the common themes of these occupations, namely:

Experts/Engineers (#1) as the closest roles included Materials Engineers and Chemical Engineers. This is consistent with this cluster’s personality footprint, which is highest in openness in the facets of imagination and intellect.

Developers (#3) as the closest roles include Application Developers and related technology roles such as Business Systems Analysts and Product Managers.

Operators (#4) as the closest roles include service, maintenance and operations functions, including Bicycle Mechanic, Mechanic and Service Manager. This is also consistent with one of the key personality traits of high conscientiousness in the facet of orderliness and high agreeableness in the facet of humility for founders in this cluster.

Founder-Level Factors of Startup Success. ( A ), Successful entrepreneurs differ from successful employees. They can be accurately distinguished using a classifier with personality information alone. ( B ), Successful entrepreneurs have different Big Five facet distributions, especially on adventurousness, modesty and activity level. ( C ), Founders come in six different types: Fighters, Operators, Accomplishers, Leaders, Engineers and Developers (FOALED) ( D ), Each founder Personality-Type has its distinct facet.

Together, these six different types of startup founders (Fig.  1 C) represent a framework we call the FOALED model of founder types—an acronym of Fighters, Operators, Accomplishers, Leaders, Engineers and D evelopers.

Each founder’s personality type has its distinct facet footprint (for more details, see Extended Data Figure  10 in SI section  A.3 ). Also, we observe a central core of correlated features that are high for all types of entrepreneurs, including intellect, adventurousness and activity level (Fig.  1 D).To test the robustness of the clustering of the personality facets, we compare the mean scores of the individual facets per cluster with a 20-fold resampling of the data and find that the clusters are, overall, largely robust against resampling (see Extended Data Figure  11 in SI section  A.3 for more details).

We also find that the clusters accord with the distribution of founders’ roles in their startups. For example, Accomplishers are often Chief Executive Officers, Chief Financial Officers, or Chief Operating Officers, while Fighters tend to be Chief Technical Officers, Chief Product Officers, or Chief Commercial Officers (see Extended Data Fig.  12 in SI section  A.4 for more details).

The ensemble theory of success

While founders’ individual personality traits, such as Adventurousness or Openness, show to be related to their firms’ success, we also hypothesise that the combination, or ensemble, of personality characteristics of a founding team impacts the chances of success. The logic behind this reasoning is complementarity, which is proposed by contemporary research on the functional roles of founder teams. Examples of these clear functional roles have evolved in established industries such as film and television, construction, and advertising 45 . When we subsequently explored the combinations of personality types among founders and their relationship to the probability of startup success, adjusted for a range of other factors in a multi-factorial analysis, we found significantly increased chances of success for mixed foundation teams:

Initially, we find that firms with multiple founders are more likely to succeed, as illustrated in Fig.  2 A, which shows firms with three or more founders are more than twice as likely to succeed than solo-founded startups. This finding is consistent with investors’ advice to founders and previous studies 46 . We also noted that some personality types of founders increase the probability of success more than others, as shown in SI section  A.6 (Extended Data Figures  16 and 17 ). Also, we note that gender differences play out in the distribution of personality facets: successful female founders and successful male founders show facet scores that are more similar to each other than are non-successful female founders to non-successful male founders (see Extended Data Figure  18 ).

The Ensemble Theory of Team-Level Factors of Startup Success. ( A ) Having a larger founder team elevates the chances of success. This can be due to multiple reasons, e.g., a more extensive network or knowledge base but also personality diversity. ( B ) We show that joint personality combinations of founders are significantly related to higher chances of success. This is because it takes more than one founder to cover all beneficial personality traits that ‘breed’ success. ( C ) In our multifactor model, we show that firms with diverse and specific combinations of types of founders have significantly higher odds of success.

Access to more extensive networks and capital could explain the benefits of having more founders. Still, as we find here, it also offers a greater diversity of combined personalities, naturally providing a broader range of maximum traits. So, for example, one founder may be more open and adventurous, and another could be highly agreeable and trustworthy, thus, potentially complementing each other’s particular strengths associated with startup success.

The benefits of larger and more personality-diverse foundation teams can be seen in the apparent differences between successful and unsuccessful firms based on their combined Big Five personality team footprints, as illustrated in Fig.  2 B. Here, maximum values for each Big Five trait of a startup’s co-founders are mapped; stratified by successful and non-successful companies. Founder teams of successful startups tend to score higher on Openness, Conscientiousness, Extraversion, and Agreeableness.

When examining the combinations of founders with different personality types, we find that some ensembles of personalities were significantly correlated with greater chances of startup success—while controlling for other variables in the model—as shown in Fig.  2 C (for more details on the modelling, the predictive performance and the coefficient estimates of the final model, see Extended Data Figures  19 , 20 , and 21 in SI section  A.6 ).

Three combinations of trio-founder companies were more than twice as likely to succeed than other combinations, namely teams with (1) a Leader and two Developers , (2) an Operator and two Developers , and (3) an Expert/Engineer , Leader and Developer . To illustrate the potential mechanisms on how personality traits might influence the success of startups, we provide some examples of well-known, successful startup founders and their characteristic personality traits in Extended Data Figure  22 .

Startups are one of the key mechanisms for brilliant ideas to become solutions to some of the world’s most challenging economic and social problems. Examples include the Google search algorithm, disability technology startup Fingerwork’s touchscreen technology that became the basis of the Apple iPhone, or the Biontech mRNA technology that powered Pfizer’s COVID-19 vaccine.

We have shown that founders’ personalities and the combination of personalities in the founding team of a startup have a material and significant impact on its likelihood of success. We have also shown that successful startup founders’ personality traits are significantly different from those of successful employees—so much so that a simple predictor can be trained to distinguish between employees and entrepreneurs with more than 80% accuracy using personality trait data alone.

Just as occupation-personality maps derived from data can provide career guidance tools, so too can data on successful entrepreneurs’ personality traits help people decide whether becoming a founder may be a good choice for them.

We have learnt through this research that there is not one type of ideal ’entrepreneurial’ personality but six different types. Many successful startups have multiple co-founders with a combination of these different personality types.

To a large extent, founding a startup is a team sport; therefore, diversity and complementarity of personalities matter in the foundation team. It has an outsized impact on the company’s likelihood of success. While all startups are high risk, the risk becomes lower with more founders, particularly if they have distinct personality traits.

Our work demonstrates the benefits of personality diversity among the founding team of startups. Greater awareness of this novel form of diversity may help create more resilient startups capable of more significant innovation and impact.

The data-driven research approach presented here comes with certain methodological limitations. The principal data sources of this study—Crunchbase and Twitter—are extensive and comprehensive, but there are characterised by some known and likely sample biases.

Crunchbase is the principal public chronicle of venture capital funding. So, there is some likely sample bias toward: (1) Startup companies that are funded externally: self-funded or bootstrapped companies are less likely to be represented in Crunchbase; (2) technology companies, as that is Crunchbase’s roots; (3) multi-founder companies; (4) male founders: while the representation of female founders is now double that of the mid-2000s, women still represent less than 25% of the sample; (5) companies that succeed: companies that fail, especially those that fail early, are likely to be less represented in the data.

Samples were also limited to those founders who are active on Twitter, which adds additional selection biases. For example, Twitter users typically are younger, more educated and have a higher median income 47 . Another limitation of our approach is the potentially biased presentation of a person’s digital identity on social media, which is the basis for identifying personality traits. For example, recent research suggests that the language and emotional tone used by entrepreneurs in social media can be affected by events such as business failure 48 , which might complicate the personality trait inference.

In addition to sampling biases within the data, there are also significant historical biases in startup culture. For many aspects of the entrepreneurship ecosystem, women, for example, are at a disadvantage 49 . Male-founded companies have historically dominated most startup ecosystems worldwide, representing the majority of founders and the overwhelming majority of venture capital investors. As a result, startups with women have historically attracted significantly fewer funds 50 , in part due to the male bias among venture investors, although this is now changing, albeit slowly 51 .

The research presented here provides quantitative evidence for the relevance of personality types and the diversity of personalities in startups. At the same time, it brings up other questions on how personality traits are related to other factors associated with success, such as:

Will the recent growing focus on promoting and investing in female founders change the nature, composition and dynamics of startups and their personalities leading to a more diverse personality landscape in startups?

Will the growth of startups outside of the United States change what success looks like to investors and hence the role of different personality traits and their association to diverse success metrics?

Many of today’s most renowned entrepreneurs are either Baby Boomers (such as Gates, Branson, Bloomberg) or Generation Xers (such as Benioff, Cannon-Brookes, Musk). However, as we can see, personality is both a predictor and driver of success in entrepreneurship. Will generation-wide differences in personality and outlook affect startups and their success?

Moreover, the findings shown here have natural extensions and applications beyond startups, such as for new projects within large established companies. While not technically startups, many large enterprises and industries such as construction, engineering and the film industry rely on forming new project-based, cross-functional teams that are often new ventures and share many characteristics of startups.

There is also potential for extending this research in other settings in government, NGOs, and within the research community. In scientific research, for example, team diversity in terms of age, ethnicity and gender has been shown to be predictive of impact, and personality diversity may be another critical dimension 52 .

Another extension of the study could investigate the development of the language used by startup founders on social media over time. Such an extension could investigate whether the language (and inferred psychological characteristics) change as the entrepreneurs’ ventures go through major business events such as foundation, funding, or exit.

Overall, this study demonstrates, first, that startup founders have significantly different personalities than employees. Secondly, besides firm-level factors, which are known to influence firm success, we show that a range of founder-level factors, notably the character traits of its founders, significantly impact a startup’s likelihood of success. Lastly, we looked at team-level factors. We discovered in a multifactor analysis that personality-diverse teams have the most considerable impact on the probability of a startup’s success, underlining the importance of personality diversity as a relevant factor of team performance and success.

Data sources

Entrepreneurs dataset.

Data about the founders of startups were collected from Crunchbase (Table  2 ), an open reference platform for business information about private and public companies, primarily early-stage startups. It is one of the largest and most comprehensive data sets of its kind and has been used in over 100 peer-reviewed research articles about economic and managerial research.

Crunchbase contains data on over two million companies - mainly startup companies and the companies who partner with them, acquire them and invest in them, as well as profiles on well over one million individuals active in the entrepreneurial ecosystem worldwide from over 200 countries and spans. Crunchbase started in the technology startup space, and it now covers all sectors, specifically focusing on entrepreneurship, investment and high-growth companies.

While Crunchbase contains data on over one million individuals in the entrepreneurial ecosystem, some are not entrepreneurs or startup founders but play other roles, such as investors, lawyers or executives at companies that acquire startups. To create a subset of only entrepreneurs, we selected a subset of 32,732 who self-identify as founders and co-founders (by job title) and who are also publicly active on the social media platform Twitter. We also removed those who also are venture capitalists to distinguish between investors and founders.

We selected founders active on Twitter to be able to use natural language processing to infer their Big Five personality features using an open-vocabulary approach shown to be accurate in the previous research by analysing users’ unstructured text, such as Twitter posts in our case. For this project, as with previous research 20 , we employed a commercial service, IBM Watson Personality Insight, to infer personality facets. This service provides raw scores and percentile scores of Big Five Domains (Openness, Conscientiousness, Extraversion, Agreeableness and Emotional Stability) and the corresponding 30 subdomains or facets. In addition, the public content of Twitter posts was collected, and there are 32,732 profiles that each had enough Twitter posts (more than 150 words) to get relatively accurate personality scores (less than 12.7% Average Mean Absolute Error).

The entrepreneurs’ dataset is analysed in combination with other data about the companies they founded to explore questions about the nature and patterns of personality traits of entrepreneurs and the relationships between these patterns and company success.

For the multifactor analysis, we further filtered the data in several preparatory steps for the success prediction modelling (for more details, see SI section  A.5 ). In particular, we removed data points with missing values (Extended Data Fig.  13 ) and kept only companies in the data that were founded from 1990 onward to ensure consistency with previous research 32 (see Extended Data Fig.  14 ). After cleaning, filtering and pre-processing the data, we ended up with data from 25,214 founders who founded 21,187 startup companies to be used in the multifactor analysis. Of those, 3442 startups in the data were successful, 2362 in the first seven years after they were founded (see Extended Data Figure  15 for more details).

Entrepreneurs and employees dataset

To investigate whether startup founders show personality traits that are similar or different from the population at large (i. e. the entrepreneurs vs employees sub-analysis shown in Fig.  1 A and B), we filtered the entrepreneurs’ data further: we reduced the sample to those founders of companies, which attracted more than US$100k in investment to create a reference set of successful entrepreneurs (n \(=\) 4400).

To create a control group of employees who are not also entrepreneurs or very unlikely to be of have been entrepreneurs, we leveraged the fact that while some occupational titles like CEO, CTO and Public Speaker are commonly shared by founders and co-founders, some others such as Cashier , Zoologist and Detective very rarely co-occur seem to be founders or co-founders. To illustrate, many company founders also adopt regular occupation titles such as CEO or CTO. Many founders will be Founder and CEO or Co-founder and CTO. While founders are often CEOs or CTOs, the reverse is not necessarily true, as many CEOs are professional executives that were not involved in the establishment or ownership of the firm.

Using data from LinkedIn, we created an Entrepreneurial Occupation Index (EOI) based on the ratio of entrepreneurs for each of the 624 occupations used in a previous study of occupation-personality fit 44 . It was calculated based on the percentage of all people working in the occupation from LinkedIn compared to those who shared the title Founder or Co-founder (See SI section  A.2 for more details). A reference set of employees (n=6685) was then selected across the 112 different occupations with the lowest propensity for entrepreneurship (less than 0.5% EOI) from a large corpus of Twitter users with known occupations, which is also drawn from the previous occupational-personality fit study 44 .

These two data sets were used to test whether it may be possible to distinguish successful entrepreneurs from successful employees based on the different patterns of personality traits alone.

Hierarchical clustering

We applied several clustering techniques and tests to the personality vectors of the entrepreneurs’ data set to determine if there are natural clusters and, if so, how many are the optimum number.

Firstly, to determine if there is a natural typology to founder personalities, we applied the Hopkins statistic—a statistical test we used to answer whether the entrepreneurs’ dataset contains inherent clusters. It measures the clustering tendency based on the ratio of the sum of distances of real points within a sample of the entrepreneurs’ dataset to their nearest neighbours and the sum of distances of randomly selected artificial points from a simulated uniform distribution to their nearest neighbours in the real entrepreneurs’ dataset. The ratio measures the difference between the entrepreneurs’ data distribution and the simulated uniform distribution, which tests the randomness of the data. The range of Hopkins statistics is from 0 to 1. The scores are close to 0, 0.5 and 1, respectively, indicating whether the dataset is uniformly distributed, randomly distributed or highly clustered.

To cluster the founders by personality facets, we used Agglomerative Hierarchical Clustering (AHC)—a bottom-up approach that treats an individual data point as a singleton cluster and then iteratively merges pairs of clusters until all data points are included in the single big collection. Ward’s linkage method is used to choose the pair of groups for minimising the increase in the within-cluster variance after combining. AHC was widely applied to clustering analysis since a tree hierarchy output is more informative and interpretable than K-means. Dendrograms were used to visualise the hierarchy to provide the perspective of the optimal number of clusters. The heights of the dendrogram represent the distance between groups, with lower heights representing more similar groups of observations. A horizontal line through the dendrogram was drawn to distinguish the number of significantly different clusters with higher heights. However, as it is not possible to determine the optimum number of clusters from the dendrogram, we applied other clustering performance metrics to analyse the optimal number of groups.

A range of Clustering performance metrics were used to help determine the optimal number of clusters in the dataset after an apparent clustering tendency was confirmed. The following metrics were implemented to evaluate the differences between within-cluster and between-cluster distances comprehensively: Dunn Index, Calinski-Harabasz Index, Davies-Bouldin Index and Silhouette Index. The Dunn Index measures the ratio of the minimum inter-cluster separation and the maximum intra-cluster diameter. At the same time, the Calinski-Harabasz Index improves the measurement of the Dunn Index by calculating the ratio of the average sum of squared dispersion of inter-cluster and intra-cluster. The Davies-Bouldin Index simplifies the process by treating each cluster individually. It compares the sum of the average distance among intra-cluster data points to the cluster centre of two separate groups with the distance between their centre points. Finally, the Silhouette Index is the overall average of the silhouette coefficients for each sample. The coefficient measures the similarity of the data point to its cluster compared with the other groups. Higher scores of the Dunn, Calinski-Harabasz and Silhouette Index and a lower score of the Davies-Bouldin Index indicate better clustering configuration.

Classification modelling

Classification algorithms.

To obtain a comprehensive and robust conclusion in the analysis predicting whether a given set of personality traits corresponds to an entrepreneur or an employee, we explored the following classifiers: Naïve Bayes, Elastic Net regularisation, Support Vector Machine, Random Forest, Gradient Boosting and Stacked Ensemble. The Naïve Bayes classifier is a probabilistic algorithm based on Bayes’ theorem with assumptions of independent features and equiprobable classes. Compared with other more complex classifiers, it saves computing time for large datasets and performs better if the assumptions hold. However, in the real world, those assumptions are generally violated. Elastic Net regularisation combines the penalties of Lasso and Ridge to regularise the Logistic classifier. It eliminates the limitation of multicollinearity in the Lasso method and improves the limitation of feature selection in the Ridge method. Even though Elastic Net is as simple as the Naïve Bayes classifier, it is more time-consuming. The Support Vector Machine (SVM) aims to find the ideal line or hyperplane to separate successful entrepreneurs and employees in this study. The dividing line can be non-linear based on a non-linear kernel, such as the Radial Basis Function Kernel. Therefore, it performs well on high-dimensional data while the ’right’ kernel selection needs to be tuned. Random Forest (RF) and Gradient Boosting Trees (GBT) are ensembles of decision trees. All trees are trained independently and simultaneously in RF, while a new tree is trained each time and corrected by previously trained trees in GBT. RF is a more robust and straightforward model since it does not have many hyperparameters to tune. GBT optimises the objective function and learns a more accurate model since there is a successive learning and correction process. Stacked Ensemble combines all existing classifiers through a Logistic Regression. Better than bagging with only variance reduction and boosting with only bias reduction, the ensemble leverages the benefit of model diversity with both lower variance and bias. All the above classification algorithms distinguish successful entrepreneurs and employees based on the personality matrix.

Evaluation metrics

A range of evaluation metrics comprehensively explains the performance of a classification prediction. The most straightforward metric is accuracy, which measures the overall portion of correct predictions. It will mislead the performance of an imbalanced dataset. The F1 score is better than accuracy by combining precision and recall and considering the False Negatives and False Positives. Specificity measures the proportion of detecting the true negative rate that correctly identifies employees, while Positive Predictive Value (PPV) calculates the probability of accurately predicting successful entrepreneurs. Area Under the Receiver Operating Characteristic Curve (AUROC) determines the capability of the algorithm to distinguish between successful entrepreneurs and employees. A higher value means the classifier performs better on separating the classes.

Feature importance

To further understand and interpret the classifier, it is critical to identify variables with significant predictive power on the target. Feature importance of tree-based models measures Gini importance scores for all predictors, which evaluate the overall impact of the model after cutting off the specific feature. The measurements consider all interactions among features. However, it does not provide insights into the directions of impacts since the importance only indicates the ability to distinguish different classes.

Statistical analysis

T-test, Cohen’s D and two-sample Kolmogorov-Smirnov test are introduced to explore how the mean values and distributions of personality facets between entrepreneurs and employees differ. The T-test is applied to determine whether the mean of personality facets of two group samples are significantly different from one another or not. The facets with significant differences detected by the hypothesis testing are critical to separate the two groups. Cohen’s d is to measure the effect size of the results of the previous t-test, which is the ratio of the mean difference to the pooled standard deviation. A larger Cohen’s d score indicates that the mean difference is greater than the variability of the whole sample. Moreover, it is interesting to check whether the two groups’ personality facets’ probability distributions are from the same distribution through the two-sample Kolmogorov-Smirnov test. There is no assumption about the distributions, but the test is sensitive to deviations near the centre rather than the tail.

Privacy and ethics

The focus of this research is to provide high-level insights about groups of startups, founders and types of founder teams rather than on specific individuals or companies. While we used unit record data from the publicly available data of company profiles from Crunchbase , we removed all identifiers from the underlying data on individual companies and founders and generated aggregate results, which formed the basis for our analysis and conclusions.

Data availability

A dataset which includes only aggregated statistics about the success of startups and the factors that influence is released as part of this research. Underlying data for all figures and the code to reproduce them are available on GitHub: https://github.com/Braesemann/FounderPersonalities . Please contact Fabian Braesemann ( [email protected] ) in case you have any further questions.

Change history

07 may 2024.

A Correction to this paper has been published: https://doi.org/10.1038/s41598-024-61082-7

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Acknowledgements

We thank Gary Brewer from BuiltWith ; Leni Mayo from Influx , Rachel Slattery from TeamSlatts and Daniel Petre from AirTree Ventures for their ongoing generosity and insights about startups, founders and venture investments. We also thank Tim Li from Crunchbase for advice and liaison regarding data on startups and Richard Slatter for advice and referrals in Twitter .

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Paul X. McCarthy

School of Computer Science and Engineering, UNSW Sydney, Sydney, NSW, Australia

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Xian Gong & Marian-Andrei Rizoiu

Oxford Internet Institute, University of Oxford, Oxford, UK

Fabian Braesemann & Fabian Stephany

DWG Datenwissenschaftliche Gesellschaft Berlin, Berlin, Germany

Melbourne Graduate School of Education, The University of Melbourne, Parkville, VIC, Australia

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All authors designed research; All authors analysed data and undertook investigation; F.B. and F.S. led multi-factor analysis; P.M., X.G. and M.A.R. led the founder/employee prediction; M.L.K. led personality insights; X.G. collected and tabulated the data; X.G., F.B., and F.S. created figures; X.G. created final art, and all authors wrote the paper.

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Correspondence to Fabian Braesemann .

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McCarthy, P.X., Gong, X., Braesemann, F. et al. The impact of founder personalities on startup success. Sci Rep 13 , 17200 (2023). https://doi.org/10.1038/s41598-023-41980-y

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DOI : https://doi.org/10.1038/s41598-023-41980-y

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Which social media platforms are most common, who uses each social media platform, find out more, social media fact sheet.

Many Americans use social media to connect with one another, engage with news content, share information and entertain themselves. Explore the patterns and trends shaping the social media landscape.

To better understand Americans’ social media use, Pew Research Center surveyed 5,733 U.S. adults from May 19 to Sept. 5, 2023. Ipsos conducted this National Public Opinion Reference Survey (NPORS) for the Center using address-based sampling and a multimode protocol that included both web and mail. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race and ethnicity, education and other categories.

Polls from 2000 to 2021 were conducted via phone. For more on this mode shift, read our Q&A.

Here are the questions used for this analysis , along with responses, and  its methodology ­­­.

A note on terminology: Our May-September 2023 survey was already in the field when Twitter changed its name to “X.” The terms  Twitter  and  X  are both used in this report to refer to the same platform.

YouTube and Facebook are the most-widely used online platforms. About half of U.S. adults say they use Instagram, and smaller shares use sites or apps such as TikTok, LinkedIn, Twitter (X) and BeReal.

Note: The vertical line indicates a change in mode. Polls from 2012-2021 were conducted via phone. In 2023, the poll was conducted via web and mail. For more details on this shift, please read our Q&A . Refer to the topline for more information on how question wording varied over the years. Pre-2018 data is not available for YouTube, Snapchat or WhatsApp; pre-2019 data is not available for Reddit; pre-2021 data is not available for TikTok; pre-2023 data is not available for BeReal. Respondents who did not give an answer are not shown.

Source: Surveys of U.S. adults conducted 2012-2023.

Usage of the major online platforms varies by factors such as age, gender and level of formal education.

% of U.S. adults who say they ever use __ by …

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This fact sheet was compiled by Research Assistant  Olivia Sidoti , with help from Research Analyst  Risa Gelles-Watnick , Research Analyst  Michelle Faverio , Digital Producer  Sara Atske , Associate Information Graphics Designer Kaitlyn Radde and Temporary Researcher  Eugenie Park .

Follow these links for more in-depth analysis of the impact of social media on American life.

• Americans’ Social Media Use  Jan. 31, 2024
• Americans’ Use of Mobile Technology and Home Broadband  Jan. 31 2024
• Q&A: How and why we’re changing the way we study tech adoption  Jan. 31, 2024

Find more reports and blog posts related to  internet and technology .

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