ABSTRACT YUAN, JING. Preference And

ABSTRACT

YUAN, JING. Preference and Motivation for Solitude in Adulthood: Antecedents, Consequences, and a Developmental Perspective. (Under the direction of Dr. Daniel Grühn).

Defined as the absence of physical social interaction, solitude is often equated to negative outcomes such as loneliness. However, solitude is an inevitable part in daily life and has positive consequences. Whether one can benefit from solitude may depend on the attitudes towards solitude. The attitudes towards solitude could be multidimensional with affective components such as the preference for solitude and cognitive components such as the reasons or motivations behind the inclination towards solitude. However, it is less clear how the preferences and motivations for solitude associate with each other (i.e., multidimensional), whether they develop in the same direction across adulthood phases (i.e., multidirectional), whether they result in different outcomes (i.e., multifunctional) and result from different factors (i.e., multicausal), and whether they change under a socio-historical event (i.e., contextual). The purpose of the current two studies was to investigate the potential antecedents and consequences of attitudes towards solitude from early to middle adulthood (i.e., emerging adults, established adults, and midlife adults) from a lifespan developmental perspective (i.e., the role of adulthood phases and the historical event).

In Study 1, 465 adults in emerging adulthood (aged 18-29), established adulthood (aged

30-45), and midlife adulthood (aged 46-64) from Amazon Mechanical Turk and an undergraduate class (age range: 18-64, mean = 30.3, SD = 11.6; 50.3% female, 49.2% male,

0.4% other) were recruited from Oct.-Dec. 2019. Preference and motivations for solitude were measured with the Preference for Solitude Scale and the Motivation for Solitude Scale-Short

Form. Depressive symptoms, loneliness, life satisfaction, positive affect, negative affect, contact frequency, and activity engagement were assessed as potential consequences. Demographic variables, living arrangement, functional limitation, introversion, control, attachment, and empathy were assessed as potential antecedents. In Study 2, 144 participants (age range: 21-72, mean = 41.2, SD = 12.4; 53.5% female, 45.1% male, 1.4% other) from MTurk who participated in the Study 1 were followed up after one and a half years. Measures for preference and motivations for solitude and outcome variables were the same as Study 1. Pandemic-related variables (i.e., contact frequency, losses, social support, perceived threats, and coping strategies) were assessed as predictors.

Study 1 found that the preference for solitude remained a unique predictor for socioemotional outcomes after removing the indirect effects from the motivations for solitude

(i.e., multidimensionality). For the multidirectionality, both preference for solitude and controlled motivation peaked in established adulthood, and no group differences were found in self-determined motivation (Study 1). Both Study 1 and 2 showed that preference for solitude related to down-regulation in affect, lower social engagement, and mildly compromised well- being; controlled motivation was consistently and robustly associated with worse well-being; and self-determined motivation was consistently associated with better well-being across adulthood phases (i.e., multifunctionality). In addition, changes in attitudes, especially controlled motivation, were strong predictors for changes in well-being outcomes but not changes in social outcomes (Study 2). For the antecedents, psychological factors were better predictors than sociodemographic factors, and there were different antecedences for different aspects of attitudes towards solitude in each adulthood phase (multicausality). Although the attitudes towards solitude did not change in a consistent direction in the sample level under the context of the

COVID-19 pandemic, change in contact frequency, the number of losses, and coping with solitary activities were significant predictors for changes in attitudes towards solitude. In all, the current studies provided both cross-sectional and longitudinal evidence for the potential antecedents and consequences of attitudes towards solitude in adulthood. Future interventions on well-being should focus on controlled motivation and established adults.

Improving capacity in solitude could be a future direction for interventions aimed at boosting positive motivation and alleviating negative motivation for solitude.

by Jing Yuan

A dissertation submitted to the Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy

Psychology

Raleigh, North Carolina 2021

APPROVED BY:

______Dr. Daniel Grühn Dr. Eui Kyung Kim Committee Chair

______Dr. Shevaun D. Neupert Dr. Thomas M. Hess

DEDICATION

This dissertation is dedicated to my beloved grandpa who inspired me another way of viewing and valuing solitude.

iii

BIOGRAPHY

Jing Yuan was born and raised in Ezhou, Hubei, People’s Republic of China. She is the only child of the family. Her interests with human relationship drove her to enter the Department of Psychology at Beijing Normal University in 2011. She worked as a research assistant in the

Aging lab under the mentorship of Dr. Dahua Wang and Dr. Huamao Peng and graduated from

Beijing Normal University with a B.S. in psychology in 2015. Her growing interests in socioemotional development in later adulthood led her to enter the doctoral program of Lifespan

Developmental Psychology at North Carolina State University under the direction of Dr. Daniel

Grühn in Fall 2015. Her ultimate goal is to use her research to better help adults live an emotionally and cognitively healthy life.

ACKNOWLEDGMENTS

First and foremost, I would like to express my sincere appreciation to my advisor and committee chair Dr. Daniel Grühn for his continued guidance and support in these six years. I could not have completed my dissertation without his patient teaching that helped me to be an independent and rigorous researcher. I would also like to extend my gratitude to my committee members Dr. Shevaun D. Neupert, Dr. Thomas M. Hess, and Dr. Eui Kyung Kim for their valuable suggestions and kind helps throughout the dissertation processes.

Thanks also to all the families, friends, colleagues, and professors from both US and

China, who supported me and helped me to grow as “me” today. Special thanks to Dr. Jing Feng who funded and supervised me as her research assistant starting in the summer of 2018. She introduced me to the world of interdisciplinary collaborations and helped me to establish the confidence as a researcher with kind encouragement, mentoring, and trust. I would also like to thank Dr. Amy Halberstadt for always being encouraging, inclusive, and supportive.

Many thanks to my parents for the selfless love and nurturing in these 27 years, especially my father who always reminds me to keep my original aspiration to study psychology in mind and teaches me with his action to contribute to the society. Thanks should also go to my parents-in-law who were especially supportive during the difficult time this year.

The last person I cannot say more thanks to is my dear husband Haifeng Liu. Without his relentless support, unwavering encouragement, and profound belief in me, I could not have made it to today.

Finally, I would like to acknowledge the funding from the Suniti-Anand Gupta

Endowment Award which made it possible for me to conduct the Study 2.

TABLE OF CONTENTS

LIST OF TABLES ...... vi LIST OF FIGURES ...... vii Introduction ...... 1 Multidimensionality of Attitudes towards Solitude ...... 1 Preference for Solitude ...... 2 Motivation for Solitude ...... 4 Multidirectionality of Attitudes towards Solitude ...... 5 Emerging Adulthood ...... 5 Established Adulthood ...... 6 Midlife...... 7 Multifunctionality and Multicausality of Attitudes towards Solitude ...... 8 Potential Socioemotional Consequences of Attitudes towards Solitude ...... 8 Potential Antecedents of Attitudes towards Solitude ...... 12 Preference and Motivation for Solitude Embedded in Context ...... 16 Overview of the Present Studies ...... 19 Study 1: Preference and Motivation for Solitude in Early to Middle Adulthood ...... 21 Methods...... 22 Results ...... 27 Discussion ...... 32 Study 2: Changes in Preference and Motivation for Solitude in a Historical Event ...... 41 Methods...... 42 Results ...... 45 Discussion ...... 50 General Discussion ...... 57 References ...... 61 Appendices ...... 95

LIST OF TABLES

Table 1 Descriptive Statistics of Demographical, Independent, and Dependent Variables in Emerging, Established, and Midlife Adulthood...... 75

Table 2 Partially Standardized Regression Coefficients for the Association between Adulthood Groups and Preference or Motivation for Solitude as Mediated by Various Antecedents...... 77

Table 3 Standardized Regression Coefficients of Seven Outcome Variables Regressed on Preference and Motivation for Solitude Respectively for Emerging, Established, and Midlife Adult Groups...... 78

Table 4 Standardized Regression Coefficients for the Association between Preference for Solitude and Outcomes as Mediated by Self-determined and Controlled Motivation for Solitude...... 79

Table 5 Standardized Regression Coefficients of Preference and Motivation for Solitude Regressed on Antecedents Variables Respectively for Emerging, Established, and Midlife Adult Groups...... 80

Table 6 Baseline (Time 1) Descriptive Statistics of Demographical, Independent, and Dependent Variables in Respondent, Non-respondent, and Non-active MTurk Workers...... 81

Table 7 Descriptive Statistics, Internal Consistencies, and Rank-Order Stabilities of the Attitudes Towards Solitude and Consequences Measures in T2...... 83

Table 8 Comparisons on the Regression Models between Attitudes towards Solitude and Consequences in T1 and T2...... 84

Table 9 Comparisons on the Regression Models between Antecedents and Attitudes towards Solitude in T1 and T2...... 85

Table 10 Bivariate Correlations between Attitudes towards Solitude at T1 and T2 in Study 2 Sample...... 86

Table 11 Hierarchical Regression Coefficients of Changes in Preference and Motivations for Solitude Regressed on T1 Baseline, Demographical Variables, and COVID- related Variables...... 87

Table 12 Standardized Hierarchical Regression Coefficients of Changes in Well-being and Social Variables Regressed on T1 Baselines, Demographical Variables, and COVID-related Variables...... 89

vii

LIST OF FIGURES

Figure 1 Conceptual Mediation Models (Process Model 4) with Various Antecedents Mediate the Association between Adulthood Groups and Attitudes towards Solitude...... 91

Figure 2 Conceptual Mediation Models (Process Model 4) with Self-determined and Controlled Motivation for Solitude Mediate the Association between Preference for Solitude and Outcomes...... 92

Figure 3 Illustration of the Four Analyses on the Associations between Attitudes towards Solitude and Consequences Compared Parallelly...... 93

Figure 4 Illustration of the Three Analyses on the Associations between Antecedents and Attitudes towards Solitude Compared Parallelly...... 94

INTRODUCTION

Solitude, broadly defined as the absence of physical social interaction (Altman, 1975), is an inevitable part of everyone’s daily experience and on average takes up 15-50% of the waking hours in a day (Larson, 1990). In the current sociocultural context, engaging in social interactions and being in solitude are often considered as two opposite ends of a continuum. With social interactions being encouraged by mainstream values, the importance and benefits of solitude are downplayed. Whether one can benefit from solitude may depend on one’s attitudes towards solitude. Using a lifespan developmental perspective (Baltes, 1987; Baltes et al., 2007), I argue that attitudes towards solitude are multidimensional and multidirectional (see also Grühn et al., 2010); that is, attitudes towards solitude are composed of different facets (e.g., preferences and motivations) that exhibit different developmental trajectories across the adult lifespan. In addition, the multiple facets of attitudes towards solitude should show the characteristics of multifunctionality and multicausality (Baltes, 1996); that is, the preferences and motivations towards solitude should result in different patterns in various outcomes and be caused by different factors. Last but not least, the development of attitudes towards solitude is embedded in a socio-historical context such that the motivations and preferences for solitude should be affected by cultural forces, including history-graded events such as a global pandemic.

Multidimensionality of Attitudes towards Solitude

Empirical evidence is suggestive of both positive and negative facets of solitude (see review in Coplan et al., 2017; Long & Averill, 2003). When asked about the reason for being alone, individuals named negative reasons such as feeling lonely or killing time while longing for interpersonal contact as well as positive reasons, such as self-discovery and inner peace

(inner-directed solitude), or intimacy and spirituality (outer-directed solitude; Long et al., 2003).

A systematic review suggested that social isolation and loneliness have been consistently associated with worse physical and mental health (Leigh-Hunt et al., 2017). Other evidence revealed the restorative side of solitude (Coplan et al., 2017) by showing that solitude can help to regulate affect through reducing emotion intensity. More specifically, while being in solitude people were more likely to report less high-arousal affect and more low-arousal affect (Birditt et al., 2018; Nguyen, Ryan, & Deci, 2018; Pauly et al., 2017; Toyoshima & Sato, 2019). Whether the experience of solitude is positive, negative, or both, seems to depend on one’s attitude towards solitude. According to Rosenberg and Hovland (1960), there could be three components of attitudes: affective, cognitive, and behavioral. I focused on the affective aspect – preference for solitude, which is the liking towards solitude compared with being with others – and the cognitive aspect – motivations towards solitude, which involve the reasons behind one's preference towards solitude.

Preference for Solitude

As defined by Burger (1995), preference for solitude refers to people’s inclination towards solitude when given both options of being alone and being with other people. However, a higher preference for solitude does not mean that the person spends more time being alone than being with others. Although people with high preference for solitude usually spend relatively more time being alone than people with a lower preference for solitude, given that human beings are social creatures, they still spend and enjoy more time in the day with other people rather than being alone (Burger, 1995; Ost Mor et al., 2020). Therefore, the individual differences in preference for solitude do not necessarily result in dramatic differences in the structure of one’s social life but may determine whether one benefits or has more positive experiences in solitude.

For example, Nguyen and colleagues (2018) found in an experimental study that being in

3 solitude led to more relaxation and less stress when the participants actively chose to be alone.

Similarly, Leung (2015) found that participants with a higher general preference for solitude perceived spending time alone using a computer tablet as more stress-relieving. These findings underscore the potential moderating role of preference for solitude in the benefits of solitude.

However, the effects of preference for solitude are not always positive when it comes to socioemotional outcomes. When the inclination towards solitude is due to maladaptive reasons, such as social anxiety, positive outcomes are not guaranteed (e.g., Cramer & Lake, 1998;

Toyoshima & Sato, 2019). Although Burger (1995) argued that preference for solitude represented the dimension of appreciating the benefits of solitude, which is a separate dimension from social anxiety, he admitted that among those with a higher preference for solitude, there are not only people with low social anxiety but also people with higher social anxiety. When the motivation from appreciation of the benefits of solitude and the motivation from social anxiety are mixed together, depending on the composition of these mixed motivations behind one’s preferences in each sample, the strength or the direction of the associations between preference for solitude with different outcomes may change. Therefore, the opposite effects from the mixed motivations can potentially account for the mixed findings. For example, in Burger (1995)’s studies with two college student samples, preference for solitude was found to be unrelated to social and trait anxiety in one sample (study 3) and to be positively associated with interaction anxiousness in another sample (study 5). In the same two samples, preference for solitude correlated positively with loneliness in one sample (study 3), but in another sample the association did not exist and even became negative after social anxiety was controlled (study 5).

Similarly, preference for solitude has been found to be associated with lower life satisfaction

(Toyoshima & Sato, 2019), but had no association with life satisfaction in another study

(Waskowic & Cramer, 1999). These findings highlight the multidimensionality of one’s attitudes towards solitude and the importance of investigating not just the preference, but also the motivations behind it to understand the mechanisms of how preference for solitude impacts socioemotional outcomes.

Motivations for Solitude

Preference for solitude derives from different goals or motives (Burger, 1995). According to the self-determination theory (SDT; Ryan & Deci, 2000, 2017), there are two types of motivations: self-determined (or intrinsic) motivation and controlled (or extrinsic) motivation.

SDT stated that self-determined motivation, as driven by the three basic psychological needs

(i.e., autonomy, relatedness, and competence), leads to self-determined behaviors, and it is the self-determined behaviors that are essential for one's health and well-being. Confirmed by empirical evidence, self-determined motivation for solitude correlated with more adaptive outcomes such as higher personal growth and self-acceptance (Thomas & Azmitia, 2019). This was also confirmed in an experimental study, which found that being in solitude for 15 mins led to lower stress and higher well-being for the participants with higher autonomy for solitude

(Nguyen, Ryan, & Deci, 2018). A recent qualitative study of positive solitude experience also suggested that most positive solitude experiences were self-determined (Ost Mor et al., 2020). In contrast, controlled motivation for solitude includes reasons that are not directly related to solitude but controlled by the desire to escape from the uncomfortableness or non-belongingness while being with others. These controlled reasons correlated with maladaptive outcomes, such as lower psychological well-being, higher loneliness, higher social anxiety, and more depressive symptoms (Thomas & Azmitia, 2019; Weinstein & Nguyen, 2020).

Multidirectionality of Attitudes towards Solitude

Despite the importance of preference and motivation for solitude in optimizing one’s solitude experience and socioemotional outcomes, most efforts in this area have focused on children, adolescents, or college students (Coplan et al., 2019), with fewer efforts being made from a developmental perspective to understand how one’s preference or motivation in solitude develops in adulthood. With the phase-specific life goals, challenges, contexts, and demands experienced by each phase of adulthood (Mehta et al., 2020), I expected that the preferences and motivations in solitude would show multidirectionality or vary in different directions across different adulthood phases (i.e., emerging, established, and midlife adulthood).

Emerging Adulthood

According to Arnett (2000), emerging adulthood is defined as the phase when people aged 18-29 transition from adolescence to establishing a stable life as a “true” adult. Different from adolescents, people in emerging adulthood start to gain more control over life and more freedom in making personal choices (Coplan et al., 2019). In terms of solitude experience, it means that emerging adults start to gain autonomy in choosing when and how to spend their time alone. However, accompanying greater power of autonomy are more challenges socially, cognitively, and contextually (Arnett, 2007). In order to find their new roles and positions in society after adolescence, emerging adults need to make new friends, join new groups, start to look for a long-term partner, and find new jobs, which require them to interact with people and may reduce their time to connect with oneself in solitude. Research confirmed that people at this age spent only 10-20% of their waking time alone (Burger, 1995; Larson et al., 1982) which is much lower than people in middle-to-later adulthood (Larson et al., 1985). The stress from social interactions and the adaptation process to the society may lead them towards solitude. A

6 qualitative study of positive solitude experience showed that the controlled reasons for being in solitude such as escaping from their busy life and regulating stress were more prevalent in adults with younger ages (Ost Mor et al., 2020). The controlled motivation may be one of the mechanisms for the negative associations of preference for solitude with negative outcomes such as social anxiety and loneliness in emerging adults (Burger, 1995; Cramer & Lake, 1998). Even though no age differences were found in their motivation for solitude within the emerging adulthood (Nicole, 2005), it is possible that controlled motivation in emerging adults may be higher than in later stages of adulthood.

Established Adulthood

Even after emerging adults achieve major life goals, such as finding the long-term romantic partner, deciding which career to pursue, and having a stable social network and support system, the next life stage still has its unique developmental challenges. The stage right after emerging adulthood, as defined and separated from middle adulthood by Mehta et al.

(2020), is called established adulthood (aged 30-45). Even though it is named as “established” adulthood, the pressure and challenges that people are faced with are not lighter compared to emerging adulthood. Most established adults are burdened with work-life imbalances caused by job promotion pressures and caring responsibilities from taking care of both young children and older parents (Mehta et al., 2020). Evidence from experiential sampling study revealed that established adults spent the lowest amount of time alone than all the other adulthood phases

(Larson, 1990). Similar to emerging adults, established adults may hold a high desire for solitude for controlled reasons like escapism (Ost Mor et al., 2020). The milestone of being a parent for the first time may further elevate the controlled motivation compared to emerging adulthood due to the commonly identified themes of the loss of individuality and the related stress (Lévesque et

7 al., 2020). Meanwhile, their self-determined motivations may also thrive with their improved capacity to be alone and better self-regulation compared to emerging adulthood.

Midlife

The rest of the middle adulthood, termed midlife (aged 46-64) by Mehta et al. (2020), refers to the stage when one’s career is closer to retirement than earlier stages and the youngest children start to leave home for job or university. Research showed that the average retirement age in US was around 64 for men and 62 for women (Munnell, 2015). For some occupations such as general practitioners in Australia, it could be as early as 55 years old (Brett et al., 2009).

With their youngest children leaving home, midlife adults may also experience less work and financial pressures. One large German panel study with adults older than 52 showed that 77% of the sample were in empty nest (Kristensen et al., 2021). In addition, contradict to the conventional wisdom that empty nest is always associated with lower well-being in parents, this study showed that empty-nesters did not show higher loneliness or depressive symptoms than non-empty-nesters. With the empty nest around the corner and as the preparation for retirement going on, midlife adults may have more control over their own free time and less social pressure than when they are at the younger age. Confirmed in an experiential sampling study, people in midlife on average spent 60.5% of the sampling occasions in solitude (Lay et al., 2020), which is much higher than people in earlier adulthood. The more time alone does not mean that they have to do so. In the same study, Lay et al. (2020) found that 86% of the solitude situations were desired. Confirmed by a survey study in Japan, adults in midlife reported a higher preference for solitude as measured by Burger’s Preference for Solitude scale compared to adults in younger adulthood (Toyoshima & Sato, 2019). This suggests a higher preference for solitude in midlife compared to earlier stages. It could be due to the higher autonomous motivation and/or the lower

8 controlled motivation in midlife. The indirect evidence from two different studies conducted by

Nicole (2005) found that the sample with older age (M = 52.5, SD=16.8) had a higher averaged self-determined motivation towards solitude and lower averaged controlled motivation than another younger sample (M = 19.9, SD=3.5).

Multifunctionality and Multicausality of Attitude towards Solitude

In addition to the propositions of multidimensionality and multidirectionality, different facets of attitude towards solitude may also show multifunctionality and multicausality (Baltes,

1996; Staudinger, 2001). The different aspects of attitudes towards solitude may result from different antecedents (i.e., multicausality). The multidirectionality in the development of antecedents may result in different predictive patterns of antecedents for each attitude towards solitude in different adulthood phases. In addition, if each attitude towards solitude is a unique component, each component may lead to different patterns of losses and gains in various socioemotional outcomes (i.e., multifunctionality). As the attitudes towards solitude change across adulthood phases, the links between attitudes towards solitude and socioemotional outcomes may also vary for different adulthood groups.

Potential Socioemotional Consequences of Attitudes towards Solitude

According to the theoretical framework of the developmental trajectory of preference for solitude from childhood to emerging adulthood, the negative impact of one’s preference for solitude on socioemotional functioning may increase from childhood to early adolescence and decrease or turn positive in later adolescence and emerging adulthood (Coplan et al., 2019). This suggests that emerging adults with a higher preference for solitude may not necessarily have lower well-being or even may have higher well-being than emerging adults with a lower preference for solitude. Indeed, in the US college student samples, preference for solitude was

9 found to be unrelated to life satisfaction (Waskowic & Cramer, 1999) and depression (Thomas &

Azmitia, 2018). College students with a higher preference for solitude actually tended to report solitude time as more pleasant (Burger, 1995) and recall more positive solitude experiences

(Long, 2000) than people with a lower preference for solitude. Emerging adults with a higher level of preference for solitude also tended to report lower difficulty in remembering positive solitude experiences (Long, 2000). It is possible that the preference for solitude promotes well- being in emerging adults not only by promoting more solitary behaviors (Lee, 2013) but also by enhancing the awareness of the positive information while being in solitude. The evidence for adulthood group differences in preference for solitude is scarce. The only study that provided evidence for the association between preference for solitude and well-being outcomes in other phases of adulthood was from Japan. The study found that preference for solitude was negatively related to life satisfaction in established, midlife, and older adults after controlling for demographic variables (Toyoshima & Sato, 2019). Given that there were both quantitative and qualitative cultural differences in the solitude experience between Eastern and Western cultures

(Kaya & Weber, 2003; Wang, 2006), it is not clear whether the same association would be found in a US sample.

When it comes to emotional well-being, the associations with preference for solitude were generally more negative. Higher preference for solitude has been found to be associated with higher loneliness in emerging adults, established, and midlife adults from Japan (Toyoshima

& Sato, 2017; Toyoshima & Sato, 2019) and in colleage students from US (Burger, 1995;

Cramer & Lake, 1998; Waskowic & Cramer, 1999). Preference for solitude was also found to be negatively related to positive affect but not with negative affect in emerging adults from Japan

(Toyoshima & Sato, 2017). Confirmed this pattern, an experiential sampling study from US

10 found that on the occasion reporting a higher desire for solitude, midlife adults were also more likely to report lower positive affect but not negative affect than occasions reporting a lower desire for solitude (Lay et al., 2020). However, there were also studies showing that preference for solitude may be related to more positive emotional outcomes in midlife group than earlier adulthood groups. For example, a study in Japan showed that, for people with a higher preference for solitude, frequency of being in solitude was not associated with positive affect in midlife adults but was negatively associated with positive affect in established adults

(Toyoshima & Sato, 2019). Another study with midlife and older adults from the US also found that there were negative between-person associations between the desire for solitude and loneliness, that is, people with higher solitude desire tended to report lower loneliness (Lay et al.,

2020).

The mixed results in different well-being outcomes may lie more on the mixed motivations behind one’s preference. For example, although one study showed a positive association between preference for solitude and loneliness, in another student sample, when social anxiety was controlled, the direction of the association reverted and preference for solitude was associated with lower boredom and loneliness (Burger, 1995). Similarly, in the previous

Japan study that found the negative association between preference for solitude and positive affect but not negative affect, after loneliness was controlled, preference for solitude was not related to positive affect anymore but negatively related to negative affect (Toyoshima & Sato,

2017). Given that loneliness is usually defined as one’s desired state of social relationship not being achieved (e.g., Perlman & Peplau, 1981), if the non-belongingness leads to escapism to aloneness, it counts as the controlled motivation. Therefore, these results may suggest that it is

11 the controlled motivation like social anxiety and loneliness that has led to the negative association between preference for solitude and some socioemotional outcomes.

Although the empirical evidence on motivations for solitude was limited, it seemed to consistently support the adaptive functions of self-determined motivation for solitude and the maladaptive functions of controlled motivation. For example, controlled motivation but not self- determined motivation was positively related to loneliness and depression in an emerging adult sample (Thomas & Azmitia, 2018) and in a middle-to-older adult sample (Nicole, 2005). In samples from both earlier and later adulthood, psychological well-being was found to be positively related to self-determined motivation and negatively related to controlled motivation

(Nicole, 2005).

As for the social outcomes, the empirical evidence is scarce. A dyadic study showed that a higher-than-average desire for being alone combined with a lower-than-average desire for being with the partner was associated with more maladaptive relationship functioning and lower relationship stability in young to middle-aged couples (Czikmantori et al., 2018). It seems to suggest a negative association between preference for solitude and social outcomes in adulthood.

However, there is also evidence supporting that a person with high preference for solitude may not necessarily have maladaptive social outcomes. For example, a study found that although emerging adults with a higher preference for solitude tended to rate alone time as more pleasurable than people with a lower preference for solitude, they still rated the time being with others as pleasant (Burger, 1995). Another study with older adults in Japan showed that although interacting with friends was associated with higher positive affect for people with a lower preference for solitude, the association for people with a higher preference for solitude was not negative but non-significant (Toyoshima & Sato, 2019). This study suggests that a high

12 preference for solitude may not benefit the experience of interacting with friends but may not compromise it either. The mixed results could again be due to the mixed motivations. When

Nicole (2005) tested both motivations for solitude and motivations for relationship, results showed that motivations for solitude was actually positively associated with motivations for relationship. More specifically, self-determined motivations for solitude and for relationship correlated positively with each other, and controlled motivations for solitude and for relationship correlated positively with each other. This indicates that a person prefers solitude for mixed reasons may hold mixed motivations for relationship as well. Therefore, the positive association between self-determined motivations and between controlled motivations may suggest that self- determined motivation for solitude could relate to more positive social outcomes and controlled motivations for solitude could related to more negative social outcomes.

Potential Antecedents of Attitudes towards Solitude

Sociodemographic factors that may change with adulthood stages such as marital status and living arrangement may impact the preference and motivation in solitude. It is possible that when the need for autonomy to engage in solitude was compromised by social responsibilities, the preference or motivation towards solitude may get stronger. However, the evidence seems to support the opposite side. Being married was related to lower controlled motivation for solitude in a sample with adults from earlier adulthood (Nicole, 2005). Having children and living alone were not associated with any motivation for solitude in both samples with adults from earlier and later adulthood (Nicole, 2005). Therefore, it seems that marital status is more of a protective factor for earlier adulthood and may lead to less controlled motivation. The motivations for solitude were not amplified by having children or living with more people either. Although education level may indicate a higher capacity to be alone and may lead to higher self-

13 determined motivation for solitude, no such association was found in either younger or older samples (Nicole, 2005). However, the associations were not investigated separately for each adulthood phase in these two samples. If these demographic factors were only associated with motivations for solitude in one phase such as established adulthood, the results may not be able to reflect it. Regarding gender differences, although no gender difference was found in preference for solitude in a college student sample (Burger, 1995), women did report higher self- determined motivation but lower controlled motivation towards solitude in a sample with young to middle-aged adults (Nicole, 2005).

The physical status such as functional limitations may influence individuals’ capacity to interact with the environment effectively and voluntarily. When the capacity to autonomously make actions is compromised by functional limitations, in order to fulfill the basic need of autonomy, the individual may develop a stronger motivation towards what can be controlled, such as how the alone time is spent (Ryan & Deci, 2017). One qualitative study supported that having a sense of mastery and autonomy of the alone time is still important to people who need caregivers’ assistance (Ost Mor et al., 2020). However, if the functional limitations happen at a younger age, it is usually less expected and short-term, which may associate with higher preference for solitude and controlled motivation. For adults in later phases, the functional limitations may be more expected and long-term, Therefore, it may correlate with more self- determined motivation towards solitude.

Introversion is usually equated to preference for solitude. However, disliking socializing is only part of introversion (Major et la., 2006). One study found that introversion did not correlate with how much time people spent alone (Burger, 1995). In addition, introverts do not necessarily appreciate the benefits of solitude. For example, one study found that there was no

14 association between the enjoyment of solitary activities and extraversion (Leary et al., 2003).

The empirical evidence for the association between preference for solitude and introversion was mixed. One study found that preference for solitude correlated positively and moderately with introversion in college students (Burger, 1995). Other evidence showed that preference for solitude was not correlated with extraversion/introversion in emerging adults (Lee, 2013;

Nguyen et al., 2018). It is possible that it is due to the mixed motivations behind one’s preference for solitude. Evidence in motivation for solitude showed that in college students only controlled motivation was positively related to introversion and self-determined motivation was not

(Thomas & Azmitia, 2018). Another daily diary study also confirmed that autonomous motivation for solitude was not related to introversion in college students (Nguyen et al., 2018).

In the studies from Lee (2013) and Nguyen et al. (2018), they used different measures of preference for solitude than the Burger’s Preference for Solitude scale. The major difference is that the preference for solitude measures used in these two studies measured the inclination towards solitude but not the preference of solitude over being with others. This resulted in that the measures mixed several items with controlled reasons to motivate towards solitude. Taken together the evidence with controlled motivation and introversion, the mixed results in these two studies may be explained.

Another factor that may impact one’s solitude experience is attachment. Building upon

Bowlby’s proposal of self and other models in attachment theory (Bowlby, 1973), Bartholomew and Horowitz (1991) developed a two-dimensional model of attachment based on the positive or negative representations of oneself (anxiety) and other people (avoidance). People with a more negative representation of self (i.e., high in anxious attachment) may think that one is less worthy of being loved and may be more anxious about partner availability. People with a more negative

15 representation of others may think that other people are not dependable and trustworthy and may be more reluctant to rely on others. While being given both the options of being alone or with other people, people with a high avoidant attachment style may choose to be alone given their negative representation of others, and people with a high anxious attachment style may be more likely to cling to other people to alleviate distress. Empirical evidence seems to confirm the theoretical argument and showed that avoidance attachment was positively correlated with preference for solitude in college students, but anxiety attachment was not (Nguyen et al., 2018).

Conceptually, higher insecure attachment in both dimensions are more closely related to the controlled but not self-determined motivation for solitude in that both insecure attachment dimensions suggest the uncomfortableness of the relationships no matter it is because of themselves or others. One study with emerging adults confirmed that anxious and avoidant attachment were both positively associated with controlled motivation (Nicole, 2005). However, research also found a positive association between avoidance and self-determined motivation

(Nguyen et al., 2018; Nicole, 2005). It is possible that the negative representation of others not only leads to a reluctance to rely on and interact with other people but also a long-term tendency to actively seek and enjoy solitude experience. Evidence from large cross-sectional studies suggested that people with older age tended to be lower in anxious attachment compared to younger adults (Hudson et al., 2015). It is possible that the more positive representation of self with age may contribute to lower self-determined motivations in later adulthood phases.

When people perceive low control over a situation, they may be more likely to increase motivation and engage more resources to fill in the gap between current and desired states

(Jewell & Kidwell, 2005). Therefore, people with a lower perceived control over solitude experience may want to retrieve control by developing a higher preference for solitude and

16 higher autonomous motivation for solitude. However, the only study with college students showed that preference for solitude was not correlated with perceived control in solitude (Lee,

2013). No evidence exists for other adulthood phases.

People’s empathy or tendency to react to others’ emotions may lead to patterned emotional reactions and behavioral inclinations towards the social interaction, which in turn may make a difference in one’s preference and motivation for solitude. Although empathy could be beneficial at a group level by promoting prosocial behaviors (Eisenberg & Miller, 1987), empathy, especially emotion contagion, usually poses physiological and emotional costs to oneself. When faced with negative emotions from others, people with higher emotion contagion or higher personal distress may experience higher stress (Buffone et al., 2017), higher negative mood (Righetti et al., 2016), and elevated chronic inflammation (Manczak et al., 2016). The negative emotional and physical feedback is likely to contribute to a higher preference for being alone over being with others, especially when the interactions with others usually relate to stressful situations or negative emotions. For example, one study showed that being in solitude was associated with lower negative affect when one’s social network had more conflicts (Birditt et al., 2018). This suggests that solitude can be used as a place for restorative regulation of one’s emotions, which may be especially beneficial for people with higher emotion contagion who experience personal distress in response to other's suffering. Given that these factors are mostly external and geared to avoid overwhelming social emotions, they are more likely to contribute to controlled motivation for solitude than they are to self-determined motivation.

Preference and Motivation for Solitude Embedded in Context

One’s preference and the corresponding motivations for solitude may change across the adult lifespan in concert with changes in cognitive and social development and changes in the

17 environmental contexts. According to Baltes and Nesselroade (1979), there are three types of influences on development: normative age-graded influences, normative history-graded influences, and nonnormative influences. Normative age-graded influences are biological or cultural factors affecting most people at a specific age. For example, biological maturation facilitates competencies (e.g., language production) or triggers developmental growth (e.g., puberty) at specific age phases, and cultural structures may link specific events to specific ages

(e.g., school entry). Normative history-graded influences are influences impacting a population at a specific historical time, such as war, epidemics, or economic depression. Baltes and

Nesselroade (1979) emphasized that the impact from these historical events may affect a cohort in a similar way but may vary for different age cohorts living at the same historical time.

Nonnormative influences are from the unique events that may not happen to everyone, such as divorce or temporary unemployment.

History-graded events (Baltes & Nesselroade, 1979) such as the COVID-19 pandemic, may potentially impact one’s attitudes towards solitude or solitude experiences through three main aspects: (a) the influence of the coronavirus, (b) the influence of social distancing policy, and (c) the influence of stress resulted from society-level changes in life. First, similar to creatures’ reaction patterns when faced with any contagious pathogen (Stockmaier et al., 2021), humans may have the natural tendency to avoid coronavirus and reduce the chance of getting infected. Risk perception during the pandemic was found to be a strong indicator for perceived understanding of the policy and social behaviors (Xie et al., 2020). Therefore, a higher worry level or perceived vulnerability to the coronavirus may lead to individuals’ different understanding and adaptation to the changed social structure. The coronavirus may also impact one’s solitude experience directly through one’s own or one’s families’ sickness or even death.

People infected with the virus may be subject to either autonomous or forced social distancing

(Stockmaier et al., 2021). If death of families or friends happens, bereavement may also result in social withdrawal or elevated controlled motivation towards solitude (Zisook & Shuchter, 1985).

Second, the social distancing policy led to social structure changes in the society level. Although the social distancing policy can help with public health (Fazio et al., 2021), people may suffer from decreases in social engagement such as losses in social activities and decreases in physical social contacts (De Vos, 2020). However, how one’s solitude experience and well-being is influenced may depend on how one adapts to the situation. For example, although engaging in outdoor activities could be good way to cope with social distancing (Karl et al., 2020), not everyone chooses to make the positive moves. A study in Canada found that about 1/3 of the surveyed participants became more active during the pandemic but another 1/3 of the individuals became less active under the same historical context (Lesser & Nienhuis, 2020). The pattern may be same when it comes to the solitude experience. Although the capacity of solitude was shown to be important for one’s socioemotional outcomes (Lian et al., 2021) and the pandemic provides the opportunity of engaging in more solitary activities such as cooking, reading, or gardening, not everyone may choose to take the positive moves. For the physical engagement, people who were original active were more likely to be more active and less likely to be less active (Lesser &

Nienhuis, 2020). Similarly, people who originally have higher capacity in solitude or a higher inclination towards solitude may have a higher chance to engage more in the adaptive solitary activities and in turn develop more self-determined motivation towards solitude. Last, the pandemic may change one’s life in different domains such as health, finances, and mental health.

The resulted stress may lead to increased social withdrawal (Greenberg et al., 2014). Social and instrumental support seems to be an important indicator and protective factor for psychological

19 distress (Yu et al., 2020) in that people with higher psychological distress tended to report lower social support during the earlier stages of the pandemic in China. In all, pandemic-related factors such as losses in health and social engagement, perceived threat from the virus, coping strategies, and needed support may influence one’s attitudes towards solitude.

The influence from the COVID-19 pandemic may vary with adulthood phases. The intuitive thought may be that people with older age should be more susceptible to the virus and should suffer more from the loneliness resulted from the social isolation compared to the younger population. However, evidence from the Netherlands suggested that social isolation did not lead to higher loneliness in older adults compared to the pre-pandemic period (Van Tilburg et al., 2020). Another longitudinal study from the US confirmed that the loneliness level did not differ much when comparing before and during social isolation: adults across the adulthood lifespan in general showed resilience (Luchetti et al., 2020). It is possible that the resilience in the older population may lie on their different preference and motivation for solitude. In a sample with adults older than 35 years old and living alone, older age was associated with lower preference for solitude and controlled motivation towards solitude (Weinstein & Nguyen, 2020), which may both lead to lower well-being. However, this study did not sample enough adults younger than 35, which is supposed to be the adulthood phase that may be most impacted by a historical event such as the World War 2 and the Great Depression (Rogler, 2002). In addition, this study did not measure changes in preference and motivations for solitude.

Overview of the Present Studies

The purpose of the current studies was to investigate the potential antecedents and consequences of preference and motivation for solitude from a lifespan developmental perspective. More specifically, the main objectives were (a) to investigate adulthood group

20 differences (i.e., emerging adults, established adults, and midlife adults) in the preference and motivation for solitude (Study 1), (b) to investigate the consequences of attitudes towards solitude for different adulthood phases (Study 1 and Study 2), (c) to explore the antecedences for attitudes towards solitude in different adulthood phases (Study 1 and Study 2), and (d) to investigate the changes in the preference and motivation for solitude and their associations with various consequences and antecedents under the context of the pandemic (Study 2).

STUDY 1: PREFERENCE AND MOTIVATION FOR SOLITUDE IN EARLY TO

MIDDLE ADULTHOOD

In this study, I investigated preference and motivation for solitude and their correlates in emerging adulthood, established adulthood, and midlife adulthood (Mehta et al. 2020). The first research question addressed whether there were group differences in preference and motivation for solitude among emerging, established, and midlife adults. If yes, the secondary question was what antecedents may explain the group differences. Based on each stage’s general characteristics and available evidence, I hypothesized that established adults would have a higher preference for solitude, higher self-determined motivation, and higher controlled motivation compared to emerging adults, and midlife adults would have higher preference for solitude and self-determined motivation but lower controlled motivation for solitude than emerging and established adulthood.

The second research question investigated whether there were different socioemotional correlates with each attitude towards solitude in each adulthood group. Based on the available evidence, I hypothesized that controlled motivation for solitude would be consistently related to worse well-being and lower social engagement for all adulthood phases. Self-determined motivation would be related to less maladaptive or more adaptive socioemotional outcomes in all adulthood phases. For preference for solitude, there would be mixed associations with both adaptive and maladaptive socioemotional outcomes. In midlife adult group, the associations of preference for solitude with maladaptive outcomes would be weaker and the associations with adaptive outcomes would be stronger compared to younger adult groups. A related secondary research question was whether self-determined and controlled motivation for solitude could explain (i.e., mediate) the mixed associations between preference for solitude and socioemotional

22 outcomes. Based on the theoretical arguments and evidence, I hypothesized that after removing the indirect effects from motivations for solitude, the directions of the associations between preference for solitude and socioemotional outcomes would be more consistent.

The last research question concerned the causes of preference and motivations for solitude within each adulthood phase. Due to different characteristics of the social structure and the work-life balance from early to middle adulthood, I expected that there would be phase- specific antecedents for each adulthood stage. Given the lack of empirical evidence in established and midlife adulthood, this question remained explorative.

Methods

Participants

I recruited 301 participants from Amazon’s Mechanical Turk (MTurk) and 164 from an introductory psychology class during Oct.-Dec. 2019. The age range was between 18-64 (M =

30.3, SD = 11.6). The female percentage was similar to the population (50.3% female, 49.2% male, 0.4% other). The majority of the sample identified as White or European American (70.8%

White/European American, 9.0% Black/African American, 6.9% Asian or Asian American,

5.6% multiple ethnicities, 4.3% Hispanic or Latinx), as single (61.7% Single and 24.5%

Married), and as not having children (71.8%). Half of the sample reported having a college or higher education (49.7%). Table 1 contains the descriptive statistics for the three groups respectively (i.e., emerging, established, and midlife adulthood). Participants between the age of

18-29 were assigned into the emerging adult group, participants between the age of 30-45 were assigned into the established adult group, and participants between the age of 46-64 were assigned into the midlife adult group. There were disproportionally more females in the midlife adult group than in the emerging and established adult groups. There were fewer people married

23 or in a long-term relationship, fewer people with college or higher education, and more people not having children in the emerging adult group than in the established and midlife adult groups.

Measures

Before the solitude-related questionnaires were presented, solitude was defined for the participants to be "a state without physical social interaction with others, which could include situations like but not limited to: working or studying alone in library, eating lunch alone in the park, running by yourself in the greenway, etc.”.

Preference for Solitude. Preference for solitude was assessed by the Preference for

Solitude Scale (Burger, 1995; See Appendix A). It has twelve forced-choice questions in which participants were asked to choose between being in solitude (e.g., “I enjoy being by myself”) vs. being with others (e.g., “I enjoy being around people”). The scores were summed up with a range between 0-12 (internal consistency: 훼 = .81). A higher score meant a higher preference for solitude.

Motivation for solitude. Motivation for solitude was assessed by the 14-item Motivation for Solitude Scale-Short Form (Thomas & Azmitia, 2019; See Appendix B) with a prompt of

“When I spend time alone, I do so because...”. Participants were asked to indicate the extent they agreed with the importance of the reasons they were alone on a 4-point Likert scale from 1 (Not at all important) to 4 (Very important). There are two subscales, one with self-determined reasons (e.g., “It sparks my creativity”; internal consistency: 훼self-determined = .71), and one with non-self-determined reasons (e.g., “I don't feel liked when I'm with others”; internal consistency: 훼controlled = .90).

Antecedents. Demographic variables, living arrangement, functional limitation, and psychological factors such as introversion, control, attachment, and empathy were included as

24 potential predictor variables (i.e., antecedents) due to their expected connections with attitudes towards solitude. Demographic variables such as age, sex, marital status, and education level were included. Living arrangement was assessed with the number of people living together and the number of children they have. Functional limitation was assessed with the 9-item

Instrumental Activity of Daily Living (IADL) checklist. The domains of activities were based on

The Lawton-Brody Instrumental Activities of Daily Living (IADL) Scale (Lawton & Brody,

1969; See Appendix C), including shopping, managing finances, taking medications, doing housework, and so on. The participants checked the items to indicate whether they had difficulty with them due to a physical, mental, emotional, or memory problem. The number of checked items was summed up as a total score. A higher score meant higher functional limitation.

Introversion was assessed with the 8-item Big Five extroversion-introversion subscale

(John & Srivastava, 1999; See Appendix D). Participants were asked to indicate the extent they agreed with the statements (e.g., “In general, I am a person who is talkative.”) with a 7-point

Likert scale from 1 (Strongly disagree) to 7 (Strongly agree). The scores were averaged between items and a higher score meant higher introversion (internal consistency: 훼 = .92).

Control was assessed with the 4-item Perceived Control scale (Lee, 2013; See Appendix

E). Participants were asked to indicate the extent they agreed with the statements (e.g., “I am free to control my thoughts, regardless of whether I am with a small group or by myself.”) with a 7- point Likert scale from 1 (Not at all characteristic of me) to 7 (Very characteristic of me). The scores were averaged between items and a higher score meant higher perceived control (internal consistency: 훼 = .83).

Attachment was assessed with the 12-item Experience in Close Relationships (ECR-12) scale (Lafontaine et al., 2015). Participants were asked to think about their general experiences

25 with close relationships (e.g., family members, romantic partners, and close friends) and indicate the extent they agreed with the statements with a 5-point Likert scale from 1 (Not at all characteristic of me) to 5 (Very characteristic of me). There are two subscales: anxiety (e.g., “I worry that other people won’t care about me as much as I care about them”; internal consistency: 훼anxiety = .91) and avoidance (e.g., “I feel comfortable depending on others”; internal consistency: 훼avoidance = .87). The scores were averaged between items and higher scores meant higher anxiety or avoidance in attachment.

Empathy was assessed with the 28-item Interpersonal Reactivity Index (IRI; Davis,

1980). Participants were asked to indicate the extent to which they agreed with the statements with a 7-point Likert scale from 1 (Does not describe me well) to 7 (Describes me well). There are four subscales: perspective taking (PT; e.g., “I sometimes find it difficult to see things from the ‘other guy's’ point of view”; internal consistency: 훼PT = .82), fantasy (FS; e.g., “I really get involved with the feelings of the characters in a novel”; internal consistency: 훼FS = .79), empathic concern (EC; e.g., “I often have tender, concerned feelings for people less fortunate than me”; internal consistency: 훼EC = .85), personal distress (PD; e.g., “I sometimes feel helpless when I am in the middle of a very emotional situation”; internal consistency: 훼PD = .85). The scores were averaged between items and higher scores meant higher trait empathy.

Consequences. Depressive symptoms, loneliness, life satisfaction, negative and positive affect were measured as well-being outcomes. Activity engagement and non-physical contact frequency were measured as social engagement outcomes.

Depressive symptoms were measured with the 20-item Center for Epidemiologic Studies

Depression Scale (Radloff, 1977). Participants were asked about the frequency of feelings and behaviors in the past week ranging from Rarely or never (0-1 days) to most or all of the time (6-7

26 days). The item scores were summed up and higher scores meant more depressive symptoms

(internal consistency: 훼 = .94).

Positive and negative affect were measured with the 20-item Positive and Negative

Affect Schedule (PANAS; Watson et al., 1988). Participants were asked to indicate the frequency they experienced with 10 positive affect (internal consistency: 훼positive affect = .91) and

10 negative affect (internal consistency: 훼negative affect = .93) items with a 7-point Likert scale from

1 (Not at all) to 7 (Very frequently). The scores were averaged between items and higher scores meant higher positive or negative affect.

Life satisfaction was measured with one question: “Overall, how satisfied are you with your life?” with a 7-point Likert scale from 1 (Extremely dissatisfied) to 7 (Extremely satisfied).

The convergent validity with the Satisfaction with Life Scale (Diener et al. 1985) was .70

(Jovanovic & Lazic, 2018) and the test-retest reliability as calculated with bivariate models was over .70 in three longitudinal studies (Lucas & Donnellan, 2012).

Loneliness was measured with the 20-item UCLA Loneliness scale version 3 (Russell et al., 1978; Russell, 1996). Participants were asked to indicate their subjective feelings of loneliness as well as social isolation with a 4-point Likert scale from 1 (Never) to 4 (Often). The item scores were summed up and higher scores meant more higher loneliness (internal consistency: 훼 = .95).

Activity engagement was measured with an 8-item checklist (Banks et al., 2019; See

Appendix F). The participants checked the items to indicate whether they regularly gave any unpaid help to any person, group, club, or organization. The domains of activities included leadership, providing care, educating, counselling, and so on. The number of checked items was summed up as a total score. A higher score meant higher activity engagement.

Non-physical contact frequency was measured with four questions (See Appendix G) about the frequency people contact others in the past week through non-physical methods such as talking/facetiming through the phone, messaging, writing letters, or other online interactive communication (e.g., emails) ranging from Rarely (0-1/week) to Most of the time (Several times/day). The item scores were summed up and a higher score meant more frequent non- physical contact.

Results

Adulthood Group Differences in Preference and Motivation for Solitude

To test whether attitudes towards solitude differed between the groups (i.e., emerging, established, and midlife adulthood), three one-way ANOVAs were conducted for preference for solitude and controlled motivation for solitude with adulthood group as the independent variable.

Results showed that self-determined motivation did not differ between the groups, F(2, 462) =

0.80, p = .45, η2 = .003, whereas preference for solitude, F(2, 462) = 20.66, p < .001, η2 = .082, and controlled motivation for solitude, F(2, 462) = 6.09, p = .002, η2 = .026, differed significantly between groups. Scheffé post hoc tests revealed that people in established (M =

9.02, SD = 2.93) and midlife adult (M = 8.72, SD = 3.01) groups had significantly higher preference for solitude than people in the emerging adult group (M = 7.12, SD = 3.16). In contrast, people in emerging (M = 1.89, SD = 0.83) and established adult (M = 1.86, SD = 0.81) groups had significantly higher controlled motivation for solitude than people in the midlife adult group (M = 1.47, SD = 0.59).

Mediating Role of Antecedents in Explaining Group Differences in Preference and Motivation for Solitude

In order to investigate whether the potential antecedents could explain the group differences in the preference for solitude and controlled motivation for solitude, Process Model 4

(as illustrated in Figure 1) in SPSS was used to analyze mediation models for preference for solitude and controlled motivation separately. Adult group, as a multicategorical variable, was entered as the independent variable. Potential antecedents (i.e., age, number of people living together, number of children, introversion, attachment, and empathic concern) were entered as mediators at the same model. Because living arrangement, functional limitation, perceived control, and other three aspects of empathy were not correlated with the adult group, they were not included as mediators but as covariates. Categorical variables such as sex, race, marital status, and education were also entered as covariates.

Table 2 presents the results of mediation models with adulthood group pairs showing significant group differences. In general, group differences in preference for solitude between established and emerging adult groups were mediated by introversion and both attachments. The group differences between midlife and emerging adult groups were only mediated by anxiety attachment. For both mediation models, the total effects dropped from significant to non- significant, which suggests a full mediation.

When looking at the group differences in the controlled motivation between the midlife with emerging and established adult groups separately, both group differences were mediated by age, anxious attachment, and empathic concern. Group differences between midlife and established adult groups were additionally mediated by introversion and avoidance. Worth noting that the indirect effects from age were positive, which suggests that higher age in midlife adult

29 group was associated with higher controlled motivation compared to younger adult groups. This indicates that after removing the indirect effects, the group difference in controlled motivation between midlife with emerging and established adult groups may be stronger.

Consequences of Preference and Motivation for Solitude in Each Adulthood Group

Multiple regressions were conducted for each outcome with three attitudes towards solitude accounting for each other (see Table 3). Results showed that controlled motivation for solitude was positively associated with all the negative aspects of well-being outcomes: depressive symptoms (ps < .001), loneliness (ps < .01), and negative affect (ps < .001) for all three groups. Regarding the positive aspects of well-being outcomes, higher controlled motivation was only significantly associated with lower positive affect in emerging adult group

(p < .001) and associated with lower life satisfaction in emerging (p < .001) and established (p <

.01) adult groups. As for the social outcomes, controlled motivation was only positively associated with higher non-physical contact frequency in established adult group (p < .01). The other associations were not significant.

For well-being outcomes, higher self-determined motivation was consistently associated with higher positive affect (ps < .01), higher life satisfaction (ps < .05), and lower loneliness (ps

< .05) in all three groups. Self-determined motivation was negatively related to depressive symptoms only in the midlife adult group (p = .008) and was not associated with negative affect for all adulthood groups (ps > .05). For the social outcomes, higher controlled motivation was only significantly associated with higher activity engagement in emerging adult group (p < .01) and associated with higher non-physical contact frequency in established (p < .05) and midlife (p

< .05) adult groups. Other associations were not significant.

Higher preference for solitude was associated with some lower well-being outcomes: lower life satisfaction for all three groups (ps < .05) and higher loneliness in emerging (p < .001) and established (p < .01) adult groups. However, preference for solitude was not associated with depressive symptoms in all three groups (ps > .05). As for affective and social outcomes, high preference for solitude was associated down-regulation in affect – lower positive affect in emerging (p < .001) and established (p < .001) adult groups and lower negative affect in emerging adult group (p < .001) – and down-regulation in social outcomes – lower activity engagement in emerging adult (p < .01) and lower non-physical contact frequency in established

(p < .05) and midlife (p < .05) adult groups.

Mediating Role of Motivation for Solitude between Preference for Solitude and Consequences

In order to investigate whether two types of motivation for solitude mediate the associations between preference for solitude and different socioemotional outcomes, Process

Model 4, which refers to simple mediation models as illustrated in Figure 2, in SPSS was used.

In the mediation model for each of the seven outcomes (i.e., depressive symptoms, loneliness, positive affect, negative affect, life satisfaction, activity engagement, and non-physical contact frequency), preference for solitude was entered as the independent variable, self-determined motivation and controlled motivation for solitude were entered as the mediators, age was entered as a covariate.

As shown in Table 4, the associations between preference for solitude and most well- being outcomes (i.e., depressive symptoms, loneliness, positive affect, and life satisfaction) were significantly mediated by both self-determined and controlled motivation for solitude. Because the indirect effects from two types of motivation for solitude contradicted each other, the direct effect did not change much and remained the original directions.

The association between preference for solitude and negative affect was only mediated by controlled motivation for solitude. Surprisingly, because the indirect effect from controlled motivation was positive, the negative association between preference for solitude and negative affect got stronger after the indirect effect was removed.

The association between preference for solitude and social outcomes (i.e., activity engagement and non-physical contact frequency) was only mediated by self-determined motivation for solitude. Because the indirect effects from self-determined motivation were positive, the negative direct effects from preference for solitude got slightly stronger after the indirect effects were removed.

Antecedents of Preference and Motivation for Solitude in Each Adulthood Group

Multiple regressions were conducted for each attitude towards solitude (see Table 5).

Results showed that people higher in either introversion, perceived control, or avoidance attachment had higher preference for solitude in the emerging (ps < .001) and established adult groups (ps < .001). Uniquely, females (p < .05) and people with older age within the emerging adult group (p < .05) tended to have higher preference for solitude. For the midlife adult group, only higher introversion (p < .01) was associated with higher preference for solitude.

For self-determined motivation, higher perceived control significantly predicted higher self-determined motivation in both emerging and established adult groups (ps < .001) but not the midlife adult group (p > .05). Living with fewer people (p < .05) was a unique predictor for higher self-determined motivation for emerging adult group. Established adults with lower introversion (p < .05) and higher fantasy tendency (p < .05) tended to have lower self-determined motivation for solitude. There were no significant unique predictors for midlife adult group (ps >

.05).

For controlled motivation, higher anxiety attachment consistently predicted higher controlled motivation in all three groups (ps < .01). More functional limitations significantly predicted higher controlled motivation in the emerging (p < .001) and established (p < .05) adult group but not in midlife adult group (p > .05). For emerging adults specifically, females (p <

.05), people with older age within the emerging adult group (p < .05), higher introversion (p <

.001), higher avoidance attachment (p < .01), higher fantasy capacity (p < .05), and lower empathic concern (p < .01) were related to higher controlled motivation for solitude. Higher personal distress (p < .01) tendency were uniquely related to higher controlled motivation in the established adult group. Midlife adults living with fewer people and having more children (ps <

.05) tended to have higher controlled motivation after other factors were accounted.

Discussion

In Study 1, I investigated the group differences in and the predictors for the three attitudes towards solitude and whether these attitudes towards solitude predicted one’s well- being and social outcomes in different adulthood groups. There are three major take-away messages. First, both maladaptive attitudes towards solitude (i.e., preference for solitude and controlled motivation) peaked in established adulthood, but self-determined motivation remained stable with age. Second, higher controlled motivation was associated with high possibility to have worse well-being, which should be targeted in the intervention. Last, the patterns of predictors for each attitude towards solitude showed distinctiveness in all three adulthood phases, indicating the necessity to separate established adulthood and midlife adulthood.

Adulthood Phases Differences and Potential Mechanisms

This is the first study that explicitly investigated the adulthood phases differences (i.e., emerging, established, and midlife adulthood) in three attitudes towards solitude under the

Western culture. Similar to the results reported in the Japan study (Toyoshima & Sato, 2019), midlife adults reported a higher preference for solitude than emerging adults. This suggests that although research suggested that there were both quantitative and qualitative cultural differences in the solitude experience (Kaya & Weber, 2003; Wang, 2006), the overall developmental trend of preference for solitude may remain the same direction across cultures. However, midlife adults did not differ from established adults in preference for solitude as expected. This may suggest that the transition of preference for solitude across different adulthood phases may have completed in the established adulthood. According to the mediation analysis, one consistent reason to explain the groups differences in preference for solitude could be anxious attachment, with lower anxious attachment in older adulthood groups relating to higher preference for solitude. Introversion and avoidant attachment could be potential mechanisms as well but only for the differences from emerging to established adulthood, with higher introversion and higher avoidant attachment in established adult group relating to higher preference for solitude. In general, the group differences in attachment and introversion align with previous studies showing that introversion tended to be higher in established adulthood and may remain stable or even decline in midlife adulthood (Allen et al., 2021; Specht, 2017) and that people’s general anxious attachment tended to be lower with age and avoidant attachment tended to be higher with age and became stable in middle adulthood (Fraley, 2019; Hudson et al., 2015). The positive associations between introversion and avoidant attachment with preference for solitude align with the evidence within adulthood phases from previous studies (Burger, 1995; Nguyen et al., 2018) and current studies. However, no association was found between anxious attachment and preference for solitude in previous study using college students (Nguyen et al., 2018) and within any of the adulthood phase in Study 1. This seems to suggest that differences in anxious

34 attachment within an adulthood phase may be minimal and could only explain differences in preference for solitude in a longer term or across adulthood phases but not in a shorter term or within an adulthood phase.

The group differences in controlled motivation showed a different pattern. Although the controlled motivation was lower in midlife adults than adults in earlier adulthood phases, which aligns with the preliminary evidence from Nicole’s (2005) studies, the controlled motivation in established adults remained as high as emerging adults and was higher but not lower than midlife adults as I expected. This may suggest that the transition of controlled motivation across different adulthood phases may just start in the established adulthood and would not finish until midlife adulthood. The results also provided preliminary evidence to suggest the necessity of separating established and midlife adulthood. Given that this is the first study that separated established adulthood from midlife adulthood while investigating attitudes towards solitude, more evidence in different samples may be needed to draw firm conclusion. Regarding the potential mechanisms for the group differences, similar to preference for solitude, the mediation results from Study 1 suggested that attachment and introversion might be potential mechanisms in that the lower introversion and attachment in midlife adult group compared to established adult group relating to higher controlled motivation. The directions align with previous studies

(Nicole, 2005; Thomas & Azmitia, 2018) and also with the within-group associations found in current studies. One interesting and consistent mediator was empathic concern with higher empathic concern in midlife adult group compared to emerging and established adulthood relating to lower controlled motivation. It is possible that the higher empathic concern may serve as a buffer for the negative emotions during social interactions, which then may lead to lower controlled motivation. Improving empathic skills could be a potential future direction to

35 investigate in interventions for controlled motivation. Given that the effect size was rather small, future studies could verify the causal association with experimental studies.

Surprisingly, no age difference was found in self-determined motivation which did not align with the indirect evidence from Nicole’s (2005) studies. It could be due to that (a) the popularization of technologies in these 15 years among the midlife adults evened out the group differences, (b) the established and midlife samples from MTurk had a lower self-determined motivation towards solitude in general, (c) that the older adults but not midlife adults in Nicole’s study biased the results. To rule out different possibilities, future studies should further compare the differences between later with earlier adulthood phases and replicate the results in community samples.

Potential Consequences for Attitudes towards Solitude

The three attitudes towards solitude explained a moderate size of variances in well-being outcomes and rather small variances in social outcomes, in which the controlled motivation contributed most. This suggests that these three attitudes towards solitude are better predictors of subjective measures such as well-being but not behaviors such as social contact and engagement.

In general, most patterns of predictive effects of the three attitudes toward solitude confirmed our hypothesis and aligned with most previous studies (Burger, 1995; Cramer & Lake, 1998; Nguyen et al., 2017; Nicole, 2005; Thomas & Azmitia, 2018; Toyoshima & Sato, 2017; Toyoshima &

Sato, 2019; Waskowic & Cramer, 1999). Most specifically, self-determined motivation for solitude was associated with most positive psychological and social outcomes, controlled motivation for solitude was consistently associated with all the negative outcomes, and preference for solitude was associated with affective and social down-regulation and had mild negative side effects on well-being.

However, there were some incongruencies. First, studies with emerging adults (Thomas

& Azmitia, 2018) and midlife to older adults (Nicole, 2005) found no associations between self- determined motivation and loneliness. However, my study found the associations to be negative for all three adulthood groups. Similarly, Nicole’s (2005) study found no association between self-determined motivation and depressive symptoms, this study found the association to be negative for midlife adults. The main difference could be that the results from Study 1 were not based on bivariate correlations as used in previous two articles, but rather on the unique variances explained by self-determined motivation after accounting for preference and controlled motivation for solitude. Additional simple correlations without controlling other two attitudes showed that there were indeed no associations between self-determined motivation and loneliness for emerging adults, r (250) = -.03, p = .60, and midlife adults, r (57) = -.22, p = .09,

(it was significant for established adults, r (160) = -.18, p = .03). Similarly, no association was found between self-determined motivation and depressive symptoms for midlife adults, r (57) = -

.15, p = .25. In addition, the effect sizes were moderate (between 0.2-0.4) for all the three adulthood groups. Therefore, this result is still consistent with previous studies but provides reliable new information that higher self-determined motivation was not only associated with positive aspects of well-being (i.e., positive affect and life satisfaction) as indicated by previous study (Nguyen et al., 2017) but also uniquely associated with lower loneliness and depressive symptoms (for midlife adults only) after the maladaptive motivation was accounted. The exact same situation happens with preference for solitude and life satisfaction: no association in a US college student sample (Waskowic & Cramer, 1999) but negative in this study. Again, simple correlation showed no association between self-determined motivation and depressive symptoms for emerging adults as previous study, r (252) = .08, p = .20. This helped to reconcile the mixed

37 results in previous studies that the association between preference for solitude and life satisfaction was negative not only in established, midlife, and older adults but also in emerging adults.

Second, the patterns for negative affect are completely different between what was found in the Japan studies (Toyoshima & Sato, 2017; Toyoshima & Sato, 2019) and in the current study with a US sample. More specifically, the associations between negative affect and preference for solitude were nonsignificant for emerging adults and positive for established and midlife adults in Japan sample but negative for emerging adults and nonsignificant for established and midlife in this study. However, when looking at the patterns of correlations between preference for solitude with other well-being outcomes such as life satisfaction, positive affect, and loneliness, the patterns are the same between the Japan studies and this study. Simple correlations were also calculated using this sample for negative affect, but the pattern remained the same with the multiple regression results where two other attitudes were controlled. This suggests that there are culture differences in the association between preference for solitude and negative affect, and the association seems to be more beneficial for western culture. It could be due to that Western culture (Americans) values privacy more than Eastern culture (Kaya &

Weber, 2003), and choosing to be in solitude may help to disengage one from some negative affect. But preference for solitude was less socially expected in Japan, which may lead to additional negative affect such as guilty and self-loathing while actively choosing to be in solitude in Japan. Future studies could further investigate the specific negative affect that are associated with preference for solitude in Eastern culture.

Last, an experiential sampling study found midlife adults with higher solitude desire on average tended to report lower loneliness (Lay et al., 2020), but no association between

38 preference for solitude and loneliness was found in this study. It is possible that this is due to the trait and state differences in the construct. Even though the found association was between- person but not within-person, the way that desire for solitude is measured is by asking in the current moment whether the person would like to be alone or be with others. In comparison, preference for solitude is asking people to choose between being alone and being with others in pre-set scenarios such as during working. At least from this comparison between these two studies, state preference for solitude seems to be more adaptive than trait one. Future studies could further investigate the association between the state and trait level preference for solitude and the impact of state preference for solitude.

This study also provided first evidence for several associations that have not been investigated before. The non-significant association between preference for solitude and depressive symptoms in established and midlife adults aligns with the non-significant association found in emerging adults in previous study (Thomas & Azmitia, 2018). The new associations between motivations for solitude and well-being for each adulthood group revealed that the patterns of correlates between three attitudes towards solitude with various well-being variables showed more commonality between established adulthood with both emerging adulthood and midlife adulthood. More specifically, the patterns in positive and negative affect were similar between established and midlife adult groups, but for depressive symptoms, loneliness, and life satisfaction, results showed more commonality between established adulthood with emerging adulthood. This seems to suggest how people may transition during established adulthood: the emotional reactivity to attitude towards solitude starts to transition before the other higher-order well-being components. However, due to the cross-sectional nature of this study, this trend needs to be confirmed with long-term longitudinal studies or after controlling for cohort differences.

Confirming my hypothesis, both self-determined and controlled motivation for solitude explained part of the associations between preference for solitude and most well-being outcomes, with self-determined and controlled motivations having opposite effects on each well-being outcome. However, most of the effects of preference for solitude were not reduced much after the mediation effects from motivations for solitude were removed. Together with the rather small mediation effects, this seems to suggest that although the cognition component of attitudes towards solitude may have shared variances with affective components, they are not the main reasons behind the mixed impact of affective attitude on well-being and social outcomes.

Therefore, it can be concluded that preference for solitude is still a unique predictor for socioemotional outcomes. From the direct effects (as shown in Table 4) of preference for solitude, preference for solitude was consistently associated with affective and social downregulation. Although it correlated with negatively with life satisfaction and positively with loneliness, it did not correlate with the severe psychological risk indicator (i.e., depressive symptoms).

Potential Antecedents for Attitudes toward Solitude

For correlates with potential antecedents, demographical variables were in general not good predictors for attitudes towards solitude with rather small effect sizes. Some evidence showed that relationship quality buffers the negative impact of solitude (Pauly et al., 2017).

Future studies could focus on the qualitative impact of demographic variables such as relationship quality with spouse and children but not marital status and children number. The demographic predictors with moderate effect size were the lower number of people living together and the higher number of children which predicted higher controlled motivation for solitude in midlife adults but not in other adulthood groups. However, a previous study using

40 community sample did not find any significant association between having children and living alone with motivation for solitude across adult lifespan (Nicole, 2005). It could be that this is specific to midlife adults who start to experience empty nest. Future studies could further investigate the association between empty nest and controlled motivation.

In general, the patterns of correlates with various antecedences showed distinctiveness in all three adulthood phases, which again confirmed the necessity of separating established adulthood from emerging and midlife adulthood. The associations between attitudes towards solitude with introversion and attachment aligned mostly with previous results (Burger, 1995,

Nicole, 2005; Thomas & Azmitia, 2018). The slight difference was that introversion was associated negatively with self-determined motivation in established adulthood, which may support the previous argument that introverts do not necessarily appreciate the benefits of solitude (Major et al., 2006). From the risk factor perspective, anxiety attachment was a strong and consistent risk factor for maladaptive motivation for solitude across adulthood groups.

Introversion was another strong and consistent risk factor for less toxic preference for solitude across adulthood groups. Based on the toxic nature of controlled motivation towards solitude, I suggest future interventions prioritize emerging adults with high introversion, high insecure attachment, high functional limitations, and low empathic concern, and established adults with high anxiety attachment and high personal distress.

STUDY 2: CHANGES IN PREFERENCE AND MOTIVATION FOR SOLITUDE IN A

HISTORICAL EVENT

Currently, there is no research investigating the change or stability of preference and motivation in solitude over time or after historical events. In this study, I investigated the changes of preference and motivation for solitude in adulthood during a historical event with a follow-up study of Study 1 after one and a half years. The first research question motivating this study was whether preference and motivation for solitude changed due to the COVID-19 pandemic and whether adulthood phases were impacted differently. Taken the social structure changes brought by the pandemic and the perpetuating influence into account, I expected that there would be changes in attitudes towards solitude after people have established a new

“normal” (e.g., new social structure, newly developed solitary skills, and changed lifestyles) after one-and-a-half years from the onset of the COVID-19 pandemic. Specifically, I expected that there would be a higher preference for solitude due to the natural tendency to avoid the pathogen

(Stockmaier et al., 2021), a higher self-determined motivation for solitude and a lower controlled motivation for solitude with a better capacity of being in solitude as established through the social structure changes during the COVID-19 pandemic. Given that historical events were argued to impact earlier adulthood more than other adulthood groups (Baltes & Nesselroade,

1979; Rogler, 2002), I expected that there would be more changes in the preference and motivation for solitude in emerging adults.

The next research question would be whether the changes were due to the pandemic- related factors such as losses in health and social engagement, perceived threat from the pathogen, coping strategies, and social support. As discussed in the introduction, a higher risk or vulnerability perception (Xie et al., 2020) and losses in health, family, or social engagement may

42 result in a higher preference for solitude. Challenges and stress brought by the pandemic to one’s finances, accessibility to health facilities, maintenance of daily living, and mental health may contribute to the changes in controlled motivation. Individuals received enough social support may be less likely to have increases in controlled motivation. The ways people cope with the social isolation resulted from the social distancing policy or self-isolation tendency may determine the change in motivations for solitude, especially the self-determined motivation.

Specifically, people who developed more solitary skills may have a higher self-determined motivation and a lower controlled motivation.

The last research question concerned whether the changes in preference or motivation in solitude would predict the changes in one’s socioemotional outcomes. Previous research found that preference and motivation for solitude itself did not predict changes in well-being during the

COVID pandemic in a one- and two-week period (Weinstein & Nguyen, 2020), but changes in preference and motivation for solitude were not examined., which may contribute to the changes in the outcomes if there was any.

Methods

Participants

The 302 participants who answered the survey from Study 1 in MTurk (collected from

Oct.-Dec. 2019) received an invitation email through MTurk to participate in this follow-up study with a compensation of US $3.50. Data collection lasted from May 6th -14th 2021. Email reminders were sent out to non-respondents every two days. There were 41 non-active MTurk accounts and 117 additional MTurk workers who did not respond. Of the 302 participants in

Study 1, 144 completed Study 2 (age range: 21-72, mean = 41.2, SD = 12.4; 53.5% female,

45.1% male, 1.4% other): 33 were from emerging adulthood, 71 from established adulthood, 34

43 from midlife, and 6 from later adulthood based on their age in Time 1. The total attrition rate was

52%. When comparing respondents’ baseline with non-respondents’, MTurk workers who were invited but did not respond tended to be slightly younger but did not differ in other demographic, independent, or dependent variables (see Table 6). MTurk workers whose account became non- active tended to be younger, more likely to be married or in a relationship, with an education of college or higher, more likely to have children. Other differences in independent and dependent variables were shown in Table 6. Given that the focus on Study 2 was on changes in attitudes towards solitude but not the group differences, I excluded the six participants in older adult group for the analysis related to group differences but did not exclude them for the rest of the analyses that were not related to group differences in Study 2.

Measures

All the measures for preference for solitude, motivation for solitude, and consequences were the same as Study 1. Table 7 presents the descriptive statistics, internal consistencies, and rank-order stabilities of the attitudes towards solitude and consequences measures. The potential psychological antecedents such as introversion, attachment, and empathy were not included in

Study 2 because I believe that these traits are rather stable over a one-year period.

Perceived change in preference for solitude. I added one item about participants’ subjective report on their perceived change in preference for solitude compared to one and half year ago (i.e., before COVID-19) ranging from 1 (Much stronger) to 5 (Much weaker). A higher score means a perceived decrease in preference for solitude. The intention of adding this measure was to see whether the perceived changes matched with the actual changes in preference for solitude. On average, people reported that they perceived little change in the preference for solitude (M =2.93, SD = 0.94), which confirmed the results from the calculated changes in

44 preference for solitude as showed in result section. However, because the analyses revealed that perceived change in preference for solitude was not associated with the calculated changes in attitudes towards solitude and any of the socioemotional outcomes, it was not included in the following analysis and discussion.

COVID-19-related measures. Contact frequency, personal losses, social support, general perceived threats, and coping strategies for social isolation or loneliness were measured to operationalize the related impact of the pandemic (Van Tilburg et al., 2020).

For contact frequency, the participants were first asked about whether they have relationships with people who do not live in their house, such as parents, siblings, etc. (See

Appendix H). For each applicable relationship, participants were further asked to indicate (a) their recent contact frequency ranging from Less often or never (1), Approximately monthly (2),

At least weekly (3), to (almost) every day (4) and (b) their perceived change in the contact frequency compared to the time before the pandemic with options of More now, Not changed, and Less now. “More now” was coded as 1, “Not changed” was coded as 2, and “Less now” was coded as 3. The scores for the contact frequency for each individual’s available relationships were averaged with a range from 1-4. A higher score meant higher contact frequency. The scores for the perceived changes in contact frequency for each individual’s available relationships were averaged with a range from 1-3. A higher score meant contact frequency became lower.

Losses that impacted the person personally in domains such as social contact, social lives, health, work, and finances were measured using 11 items with options of No, More or less, and

Yes (See Appendix I). “No” was coded as 0, “More of less” was coded as 0.5, and “Yes” was coded as 1. The scores were summed up and a higher score meant a higher number of losses.

Support that was needed in the past two weeks were measured using 7 items. Participants were asked “Have you received help or support with the following activities in the past two weeks?” for different life domains with four options to choose from: Yes, it is enough, Yes, but not enough, No, but I do need support, and No, support in not necessary (See Appendix J). “Yes, it is enough” and “No, support is not necessary” were coded as 0 suggesting that the support was not needed. “Yes, but not enough” and “No, but I do need support” were coded as 1 suggesting that the support was still needed.

General threats (See Appendix K) were measured by one item for perceived threat and one item for perceived worries. The perceived threat question asked about the perceived chance of getting sick due to the coronavirus compared to other people. The five options ranged from A much smaller chance to A much bigger chance. The score ranged from 1-5 and a higher score meant higher perceived threat. The perceived worries question asked about the extent people have been worried about the pandemic recently with a 10-point Liker scale ranging from 1 (I don’t worry) to 10 (I am extremely worried). A higher score meant higher perceived worries.

Coping strategies specifically related to social isolation or loneliness were measured with an 11-item checklist of actions such as contacting using technology or engaging in indoor or outdoor activities (See Appendix L). The checked items were coded as 1 and summed up. A higher score meant a higher number of coping strategies.

Results

Comparisons of Consequences and Antecedents in Cross-sectional and Longitudinal Analysis

In order to compare the predictive effects of attitudes towards solitude on consequences in cross-sectional and longitudinal data, as illustrated in Figure 3, I compared four different models with (a) attitudes towards solitude in T1 predicting consequences in T1 (model 1 in Table

7), (b) attitudes towards solitude in T2 predicting consequences in T2 (model 2 in Table 7), (c) attitudes towards solitude in T1 predicting consequences in T2 (model 3 in Table 7), and (d) attitudes towards solitude in T1 predicting changes in consequences (step 1 in Table 11). Change scores were using T2 scores minus T1 scores. Confirmed results in Study 1, higher controlled motivation was consistently associated with lower well-being (ps < .001) but not social outcomes

(ps > .05) in both cross-sectional and longitudinal analysis (See Table 7). Higher self-determined motivation was consistently associated with higher positive affect (ps < .001), higher life satisfaction (ps < .01), and lower loneliness (ps < .05) in both cross-sectional and longitudinal analysis. Higher reference for solitude was consistently associated with lower positive affect (ps

< .05) and lower life satisfaction (ps < .05) in in both cross-sectional and longitudinal analysis.

However, when predicting changes (see step 1 in Table 11), attitudes towards solitude in T1 in general did not predict changes in consequences except that higher preference for solitude one year ago was associated with decrease in positive affect and non-physical contact frequency; higher self-determined motivation one year ago was associated with increase in positive affect; higher controlled motivation one year ago was associated with decrease in life satisfaction.

In order to compare the predictive effects of antecedents on attitudes towards solitude in cross-sectional and longitudinal data, as illustrated in Figure 4, I compared three different models with (a) antecedents in T1 predicting attitudes towards solitude in T1 (model 1 in Table 8), (b) antecedents in T1 predicting attitudes towards solitude in T2 (model 2 in Table 8), (c)

Antecedents in T1 predicting attitudes towards solitude in T2 while controlling for attitudes towards solitude in T1 (i.e., predicting changes in attitudes towards solitude; model 3 in Table 8).

As showed in Table 8, higher introversion (ps < .001) and higher avoidant attachment (ps < .05) were consistently associated with higher preference for solitude in both cross-sectional and

47 longitudinal analysis. The only consistent predictor for higher self-determined motivation was lower introversion (ps < .05). However, none of these three associations remained significant when predicting changes. For controlled motivation, higher functional limitations (ps < .05) and higher anxious attachment (ps < .01) not only consistently predicted higher controlled motivation but also predicted increases in controlled motivation.

Changes in Attitudes towards Solitude

Dependent t-tests were used to test whether there were group trends in preference and motivations for solitude before the pandemic (T1) and during the pandemic (T2). The comparisons of time 1 (preferences for solitude: M = 9.28, SD = 2.92; self-determined motivation: M = 2.63, SD = 0.65; controlled motivation: M = 1.75, SD = 0.80) with time 2

(preferences for solitude: M = 9.34, SD = 2.88; self-determined motivation: M = 2.63, SD = 0.65; controlled motivation: M = 1.76, SD = 0.82) indicated that there were no consistent trends over time in preference for solitude, t(143) = -0.42, p = .67, self-determined motivation, t(143) =

0.001, p = .99, and controlled motivation, t(143) = -0.09, p = .93. Table 9 shows the bivariate correlations between attitudes towards solitude at T1 and T2.

To test whether the changes of preference and motivations for solitude differed between the groups (i.e., emerging, established, and midlife adult groups), three one-way ANOVAs were conducted for each attitude towards solitude with change scores calculated using Time 2 variable minus Time 1 variable as dependent variable and group membership at Time 1 as the independent variable (the six older adults were excluded for this analysis). Results showed that none of the attitudes towards solitude differed significantly between the emerging (preferences for solitude: M = -0.24, SD = 2.08; self-determined motivation: M = -0.03, SD = 0.50; controlled motivation: M = -0.12, SD = 0.62), established (preferences for solitude: M = 0.38, SD = 1.78;

48 self-determined motivation: M = 0.02, SD = 0.57; controlled motivation: M = -0.04, SD = 0.65), and midlife adult (preferences for solitude: M = 0.00, SD = 1.35; self-determined motivation:

M = -0.01, SD = 0.49; controlled motivation: M = 0.20, SD = 0.59) groups (ps >.05).

In order to verify that there were significant within-person variances in three attitudes towards solitude so that the following analysis could proceed, an absolute change score was calculated for each of the attitude towards solitude and was used for one-sample t-test. Results showed that the absolute changes in preference for solitude (M = 1.20, SD = 1.31). t(143) =

11.01, p < .001, self-determined motivation (M = 0.40, SD = 0.35), t(143) = 13.69, p < .001, and controlled motivation (M = 0.41, SD = 0.47), t(143) = 10.47, p < .001, were larger than 0, which suggested that in spite of the non-significant general time effect, there were significant intra- individual variances in attitudes towards solitude over one and half year.

Pandemic-related Predictors for Changes in Attitudes towards Solitude

Descriptive statistics showed that this sample showed perceived worry (Range: 1-10; M =

4.13, SD = 2.51) and threats (Range: 1-5; M = 2.36, SD = 0.91) lightly lower than the middle point. On average, people contacted their friends and families between monthly to weekly

(Range: 1-4; M = 2.61, SD = 0.66) and perceived that their contact to be less compared to pre- pandemic time (Range: 1-3; M = 2.16, SD = 0.46). People on average reported around 3 losses

(M = 2.97, SD = 1.93), had around 1 domain that still needs support (M = 1.11, SD = 1.78), and adopted 4 coping strategies (M = 3.74, SD = 1.91).

To examine whether changes in attitudes towards solitude were associated with the above pandemic-related factors, hierarchical regressions were used with the change scores (T2-T1) of preference and motivations for solitude as the dependent variable. T1 baselines were controlled in step 1. Demographic variables including age were entered in step 2. COVID-related factors

49 were entered in step 3. As shown in Table 10, there were no age differences in the changes in attitudes towards solitude. Females were more likely than males or people with other sex to have less decrease or more increase in self-determined (p = .01) and controlled motivations (p = .02) towards solitude. Covid-related factors contributed significantly to explaining the variances in changes in self-determined motivation for solitude ( R2 =.10, p =.026), but not in changes in preference for solitude ( R2 =.06, p =.23) and self-determined motivation for solitude ( R2 =.06, p =.18). After baseline and demographic variables were controlled, people who perceived their contact frequency with friends and families as being less frequent compared to pre-pandemic time (p = .025) were more likely to have less decrease or more increase in preference for solitude. People who developed more activities to cope with loneliness and social isolation were more likely to show less decrease or more increase in self-determined motivation (p = .035) and more decrease or less increase in controlled motivation for solitude (p = .018) compared to pre- pandemic time. People who experienced more losses or impacts due to the pandemic were more likely to have less decrease or more increase in controlled motivation (p = .031) compared to pre-pandemic time.

Changes in Attitudes towards Solitude as Predictors for Changes in Socioemotional Outcomes

To examine whether individual changes in preference or motivations for solitude predicted changes in well-being and social variables, hierarchical regressions were used with the change score (T2-T1) of each outcome variable in Study 1 as the dependent variable, T1 baseline of respective outcome variable and preference for solitude controlled in step 1, changes in preference and motivations for solitude entered in step 2, demographic variables entered in step

3 to test whether the results in step 2 remained significant. As shown in Table 11, changes in preference and motivations for solitude contributed significantly to predicting changes in well-

50 being outcomes (ps < .001) but not changes in social outcomes (ps > .05). More specifically, one unit higher in change in preference for solitude was associated with 0.72 lower in change in depressive symptoms on average, B = -0.72, SE = 0.36, p = .04. Change in self-determined motivation was positively associated with changes in positive affect, B = 0.39, SE = 0.14, p =

.006, and life satisfaction, B = 0.56, SE = 0.15, p < 0.001. Change in controlled motivation was positively associated with changes in depressive symptoms, B = 8.48, SE = 1.12, p < 0.001, loneliness, B = 8.01, SE = 1.05, p < 0.001, negative affect, B = 0.60, SE = .14, p < 0.001, and negatively associated with changes in positive affect, B = -0.29, SE = .11, p = .007, and life satisfaction, B = -0.62, SE = .13, p < 0.001. All the results remained significant after demographical variables were accounted (see Table 11).

Discussion

In Study 2, I investigated whether attitudes towards solitude changed compared to pre- pandemic time and whether these changes correlated with socioemotional outcomes and pandemic-related factors. There are three major findings. First, attitudes towards solitude showed little consistent change over time, that is, I did not observe a general trend that preferences and motivations for solitude in the whole sample shifted due to the pandemic. In addition, contrary to my hypothesis, changes in attitudes towards solitude did not vary across groups. Second, there were some psychological factors and individual characteristics related the pandemic predicting individual variances in attitudes towards solitude. Finally, attitudes towards solitude were consistent predictors for well-being but not social outcomes. In addition, changes in well-being outcomes were sensitive to changes in attitudes towards solitude.

Changes in Attitudes towards Solitude

Surprisingly, I found little general trend in attitudes toward solitude or differential change patterns by adulthood phases. Despite the highly relevant changes brought by the socio-historical context of the pandemic to the social structure and subjective norms of solitude experience, attitudes toward solitude did not show consistent shifts in one direction, that is, the sample showed relatively equal amount of decrease and increase in attitudes toward solitude. The non- significant phase differences did not align with my prediction that emerging adults should be impacted most by this type of historical event (Baltes & Nesselroade, 1979; Rogler, 2002). It could be due to the facts that (a) the group-level impacts from the pandemic on the solitude experience and attitudes towards solitude have diminished as the society resumed its original social and work structure, or (b) my sample was not representative of the population due to the biased attrition or the special characteristics of the MTurk sample.

The first possible reason is highly likely. The finding that the perceived threat and worries did not relate to changes in attitudes seems to suggest that people may have adapted to the affective impact from the pandemic, which also aligns with the adaptation-level theory

(Helson, 1964) suggesting that the emotional reactions usually calm down over time if the stimulus remain constant. Although results from Study 2 also showed that the influences from the qualitative changes through permanent losses or developed skills due to the pandemic can be perpetuated through the “new normal”, these changes are high in interindividual variability and may only occur in some people. For example, the unemployment rate in the highest point after the pandemic started was around 10% higher than usual (Falk et al., 2021). The unemployment rate in Study 2 sample was 11.8%, which may include people who were in the unemployed state

52 before the pandemic. This suggests that the majority of the people did not experience the loss from being employed to unemployment.

The second possible reason is less likely. Although our attrition rate is relatively high, the respondents did not differ much with the non-respondents from their demographics to all the independent and dependent variables except that they were slightly older. Given that age was not a predictor for changes in the attitudes towards solitude, I would not expect any differences in the results if these non-respondents responded. However, there were indeed more differences between the respondents and MTurk workers whose accounts were not active anymore.

According to the results, the change levels of attitudes towards solitude might be related to the baseline levels of attitudes towards solitude. The non-active MTurk workers had lower preference for solitude and higher motivations for solitude than respondents and non-respondents with active accounts. Because there were negative associations between baseline levels of attitudes towards solitude and the changes, non-active MTurk workers may have higher changes in preference for solitude and lower changes in motivations than respondents. Therefore, the finding that the pandemic did not induce consistent changes in attitudes towards solitude in the whole sample may not apply to people who have greater functional limitations, an education of college or higher, a younger age, and married at the same time. Regarding whether the results can be generalized to the general population, given that the only significant demographic predictor for changes in attitudes was sex and the percentage of female in our sample (53.5%) did not differ much from the US census data in 2020 (50.8%; U.S. Census Bureau, 2020), I believe the results will not change much for the emerging to midlife adults in the community.

Therefore, I recommend that future studies could investigate whether the attitudes towards

53 solitude may be as stable over time in population with special characteristics such as patients with high functional limitation in a younger age.

Antecedents and Changes in Attitudes toward Solitude

The significant associations between introversion and avoidant attachment with preference for solitude but not with its changes suggest that although high introversion and high avoidance attachment may serve as the psychological context for the trait preference for solitude to form over time, they may not necessarily result in changes in the shorter-term period.

Confirmed Study 1, introversion showed consistent negative association with self-determined motivation but did not predict changes. This seems slightly contradictory but may support the notion that introverts not necessarily like solitude for the benefits of solitude. Because they already have dispositional reason to be in solitude which may prevent them from exploring the other benefits of solitude. Aligned with Study 1 results, People with higher functional limitations and anxious attachment style tended to have higher controlled motivation. In addition, both predictors associated with less decrease or more increase in the maladaptive motivation. This provides the first evidence to support that people with a negative representation of oneself in the relationship and people who had more functional limitations may have not only developed the trait controlled motivation over time, these two characteristics may keep serving as the psychological environment to make the maladaptive motivation towards solitude worse in the short-term (i.e., one and a half years).

Study 2 also found some pandemic-related individual characteristics that predicted the shifts in one’s attitudes towards solitude over time. Although the effect itself is relatively small, the significant positive association between losses and the maladaptive motivation seems to suggest that the essence of part of the perpetuating impact of the pandemic is the impact from the

54 losses on job, families’ lives or health, finances, and/or social contact. The impact of these losses on one’s solitude experience is not unique to the pandemic. Previous research in non-pandemic time showed that job loss (Brand, 2015), bereavement (Zisook & Shuchter, 1985), and the stress

(Greenberg et al., 2014) which may be caused by the losses may lead to social withdrawal. This provides a hint to the researchers and stakeholders who are looking for ways to intervene the impact of the pandemic on people’s life that they can borrow previous intervention method used for job losses, bereavement, and stress. In addition, given that the pandemic does make it possible for these nonnormative life events to break out in a short amount of time, people with multiple losses resulting from the pandemic should be prioritized and targeted for specific interventions focused on maladaptive motivations towards solitude.

Another pandemic-related factor that related to both motivations towards solitude is the number of ways people used to cope with loneliness and social isolation. Results suggested that having learned to engage oneself with more activities that could be enjoyed while alone was associated with more positive changes self-determined motivation for solitude and more negative changes in the controlled motivation for solitude. This is consistent with previous research showing that people with higher capacity of solitude were less likely to be susceptible to the psychological stress resulted from phone addiction (Lian et al., 2021). Due to the correlational nature of the data, causal inference cannot be drawn. Although it is still possible that people whose self-determined motivation increases and controlled motivation decreases due to other reasons are more likely to choose to engage themselves in more solitary activities, this finding still brings a possibility of intervening on one’s solitude skills (Thomas, 2017) to facilitate the adaptive motivation and reduce the maladaptive motivation towards solitude. Given that

55 engaging in solitary activities to cope may also help to relieve stress (Polizzi et al., 2020), it is worth future attempts at intervention.

Attitudes toward Solitude and Changes in Consequences

Confirmed results in Study 1, the maladaptive associations in controlled motivation were robust and consistent. When using controlled motivation baseline to predict changes in the outcomes, most the results were not significant except for life satisfaction. This aligns with the previous study during the earlier stage of the pandemic which found that the preference and motivations did not predict changes in ill-being a few weeks later (Weinstein & Nguyen, 2020).

However, they only measured depression, anxiety, and loneliness but not positive aspects of well-being as I measured in the current studies. I found that people with higher controlled motivation may show further decrease in life satisfaction one and a half years later. This suggests that if the controlled motivation is not intervened, people’s life satisfaction may continue to decline over time in addition to the already low well-being level. All the well-being indicators were sensitive to the changes in maladaptive motivation towards solitude, especially the negative ones (i.e., depressive symptoms, loneliness, and negative affect). Adding to the cross-sectional data from Study 1, this suggests that the controlled motivation for solitude has high potential to be an efficient factor to be intervened for higher well-being.

For self-determined motivation, results showed the consistently adaptive associations of self-determined motivation with well-being outcomes, which confirmed results in Study 1.

Taken together with the only significant association between self-determined motivation and changes in positive affect, it may suggest that high self-determined motivation not only associates with people’s high subjective well-being and loneliness in general but may also relate to further increase in positive affect over one and a half years. The positive associations between

56 positive changes in self-determined motivation and positive changes in positive affect and life satisfaction suggest that if self-determined motivation is intervened, one’s positive aspects of well-being are likely to be boosted further.

For preference for solitude, if taking a more conservative significance level of .01, the mild maladaptive associations with well-being are not so robust. In general, if people’s high preference for solitude level is not intervened, they may experience continued down-regulation in affect and social engagement (i.e., more decrease in positive affect and in non-physical contact frequency) over time. In addition, the changes in preference for solitude were not associated with worse well-being and were even negatively associated with changes in depressive symptoms.

This further validates the conclusion as discussed in Study 1 that preference for solitude may not help to boost well-being but may not lead to severe psychology risks as controlled motivation does either.

GENERAL DISCUSSION

Using a developmental perspective, two studies were conducted to investigate the potential antecedents and consequences of three attitudes towards solitude (i.e., preference for solitude, self-determined motivation, and controlled motivation for solitude across the earlier adulthood (i.e., emerging adults, established adults, and midlife adults) and the role of historical event. In general, the results confirmed that attitudes towards solitude were multidimensional, multidirectional, multifunctional, multicausal, and embedded in a sociohistorical context. Further limitations and future directions are highlighted in this section.

Multidimensionality of Attitudes towards Solitude

The findings from Study 1 support the notion that the affective aspect (i.e., preference for solitude) and cognitive aspect (i.e., motivation for solitude) of attitudes towards solitude are distinct from each other and work together in predicting socioemotional outcomes. To my knowledge, there is no previous study that considers and compares both affective and cognitive aspects of attitudes towards solitude while investigating the impact on other outcomes. Usually, attitude towards solitude is operationalized with only the affective aspect, such as interest or liking (Teppers et al., 2014), or preference or inclinations (Lee, 2013) using an attitude questionnaire. However, I did not investigate the third behavioral aspect of attitudes in current studies. There has been a long-standing debate regarding whether behaviors should be considered as attitude compositions or the outcome of attitudes (Fishbein & Ajzen, 1975). When considered as the composition, behaviors are usually investigated together with other components in one scale (Svenningsson et al., 2021). When considered as the outcome, both behaviors or intentions are usually included as proximal consequences and measured using separate measures (e.g., Lee, 2013). To investigate a complete picture of attitudes towards

58 solitude, future studies could consider either developing a new scale that integrates all three components of attitudes towards solitude or investigating the behavioral aspect by adding solitude intentions and behaviors into outcomes. In addition, how the affective and cognitive aspects of attitudes towards solitude work together in predicting solitude behavior and other outcomes may be way more complex than the mediation effects I investigated in Study 1. Similar to the health domain (Kiviniemi et al., 2018), affect and cognition could not only mediate and moderate each other’s effects, but the interplay could also change with context. It is worth conducting future studies to investigate all the possibilities to get a full picture. Finally, there may be different ways of operationalizing the different aspects of attitudes. For example, I mentioned earlier in the Study 1 discussion that state and trait preference for solitude were both affective aspects of solitude but may have different influence on the outcomes. Future studies could investigate the state level of affective, cognitive, and behavioral aspects of solitude using daily diary studies or experiments to see if the influences differ with trait ones.

Multidirectionality of Attitudes towards Solitude

My findings confirmed multidirectionality by showing that different aspects of attitudes displayed different trends across adulthood phases. What worth noting is that age did not explain the adulthood group differences in attitudes towards solitude. For controlled motivation, age even predicted the opposite direction as the adulthood group membership. This suggests that it is not age itself or the solitude experience accumulated with age that determine the differences in attitudes towards solitude. This may imply that categorizing the adulthood phases based only on age may not be accurate or reflect the essence of the group differences. Future studies could consider further investigate the specific context or characteristics that are related to each phase.

For example, although in our sample there were indeed more people married and having children

59 in older adulthood groups, it is not clear how many children are still living with the individuals, which could be a more direct predictor for one’s preference or motivation for solitude in midlife than the number of children. Quantifying empty nest and retirement in midlife with the number of children living at home and the specific retirement age could be the next step. Moreover, given the cross-sectional nature of this study, we cannot rule out the possibility that group differences were due to cohort differences. Future studies can consider conducting longitudinal cohort study or operationalize the differences in the cohorts that may impact the attitudes towards solitude such as familiarity and preference for communication technology.

Multifunctionality and Multicausality of Attitudes towards Solitude

Multifunctionality and multicausality were confirmed with the unique predictive directions of each attitude towards solitude for each outcome along with the distinctiveness of risk factor patterns for each attitude towards solitude. Although both Study 1 and 2 showed a weak association between activity engagement and attitudes towards solitude, I cannot draw the conclusion that attitudes towards solitude do not relate to social engagement outcomes. In this study, I only measured general non-physical frequency and public activity engagement. Given that there was evidence showing that one’s attitude towards solitude may associate with relationship functioning (Czikmantori et al., 2018), future studies could include social contacts, quality in specific relationships such as the communication quality, relationship satisfaction, or conflict frequency. In addition, these two studies only investigated the distal outcomes and distal predictive factors. In order to understand the mechanisms, proximal outcomes such as solitary intentions and behaviors and proximal predictors such as previous solitude experiences could be considered in future studies. Finally, I would like to empathize the correlational nature of these two studies. Although the Study 2 was a follow-up study, the essence of the association of the

60 change scores was correlation. To make causal inferences between the attitudes towards solitude and potential antecedents and consequences, experimental study is needed.

Attitudes towards Solitude Embedded in Context

Study 2 provided partial support that attitudes towards solitude changed in a socio- historical context. The pandemic provided the opportunity with qualitative discontinuity in the social structure and forced people to reframe their ways of being alone. The non-significant model changes in two out of the three attitudes towards solitude seem to suggest that the pandemic did not influence people’s solitary attitudes that much now and people in general have adapted well with respect to the impact on attitudes towards solitude. Given that there were only two time points in this longitudinal study, measurement errors may also be confounded with the change scores. More data points may be helpful to partial them out. Another follow-up study may also be beneficial in knowing how long this benefit effect from engaging in solitary activities can last in the post-covid period. With the online interactions increase and technology advances, spending time along in a healthy and productive way will be the long-term social need even after the pandemic ends. Finally, I would like to acknowledge that although it was assumed in this study that the context is the global pandemic, there are also other major contextual influences during this one year such as the election or the societal-level racial event. How these influences interplay with each other in terms of their impact on solitude attitude is hard to predict. It is possible that for the activist, the emotional events will make people forget the need to social distance and have an increased need to be with others but not alone; for the non- protestors, the turmoil outside may drive them to stay home more to avoid getting involved

(Dave et a., 2020). These effects may have confounded with the impact of the pandemic.

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Table 1

Descriptive Statistics of Demographical, Independent, and Dependent Variables in Emerging, Established, and Midlife Adulthood. Emerging Established Midlife Group differences adults adults adults (N=465) (n=252) (n=160) (n=53) Demographics Age, M (SD) 21.5 (3.6) 36.3 (4.0) 53.8 (5.3) / Sex, % of female 47.2% 46.3% 77.4% χ2 (2) = 17.53*** Race, % of white 70.2% 68.1% 81.1% χ2 (2) = 3.33 Marital status, % of people who were 11.9% 54.4% 54.7% χ2 (2) = 97.05*** married or living in a long-term relationship Education, % of people with college or 30.6% 74.4% 66.0% χ2 (2) = 91.57*** higher education Living arrangement Children, % of people 91.7% 53.1% 34.0% χ2 (2) = 114.23*** not having children People living together, % of people 23.0% 31.3% 34.0% χ2 (2) = 4.79 living alone Physical status IADLs, M (SD) 0.75 (1.43) 0.66 (1.46) 0.51 (1.10) F(2,461)=0.66 Psychological factors Introversion, M (SD) 4.00 (1.52) 4.49 (1.44) 3.73 (1.52) F(2,461)=7.74*** Control, M (SD) 4.98 (1.26) 5.20 (1.20) 5.33 (1.10) F(2,461)=2.47 Anxiety, M (SD) 2.77 (1.08) 2.28 (1.11) 1.97 (0.93) F(2,461)=17.55*** Avoidance, M (SD) 3.03 (0.99) 3.19 (1.05) 2.84 (1.03) F(2,461)=2.66 Empathy Perspective-taking, M 4.84(1.01) 4.98(1.11) 5.00(1.16) F(2,461)=1.09 (SD) Fantasy, M (SD) 4.59(1.20) 4.54(1.23) 4.72(1.16) F(2,461)=0.41 Empathic concern, M 5.05(1.06) 4.95(1.35) 5.50(1.08) F(2,461)=4.58* (SD) Personal distress, M 3.56(1.04) 3.36(1.43) 3.45(1.44) F(2,461)=1.38 (SD) Attitudes towards

Solitude Preference for 7.12(3.16) 9.02(2.93) 8.72(3.01) F(2,461)=21.13*** solitude, M (SD)

Table 1 (continued)

Self-determined 2.64(0.64) 2.63(0.65) 2.75(0.57) F(2,461)=0.82 motivation, M (SD) Controlled motivation, 1.89(0.83) 1.86(0.81) 1.47(0.59) F(2,461)=5.99** M (SD) Well-being outcomes Depressive symptoms, 17.46(12.02) 15.73(13.10) 12.42(10.94) F(2,461)=3.81* M (SD) Loneliness, M (SD) 42.30(13.73) 43.48(14.62) 38.00(12.69) F(2,461)=3.12* Negative affect, M 2.83(1.25) 2.29(1.33) 2.03(1.12) F(2,461)=14.09*** (SD) Positive affect, M 4.71(1.13) 4.29(1.28) 5.01(1.17) F(2,461)=9.59*** (SD) Life satisfaction, M 5.08(1.38) 4.67(1.71) 4.98(1.45) F(2,461)=3.82* (SD) Social outcomes 1.46(1.39) 1.09(1.26) 1.21(1.18) F(2,461)=4.16* Activity engagement, 10.13(2.64) 9.19(2.56) 9.08(2.20) F(2,461)=9.27*** M (SD) Contact frequency, M 17.46(12.02) 15.73(13.10) 12.42(10.94) F(2,461)=3.81* (SD) *p < .05. **p < .01. ***p < .001.

Table 2

Partially Standardized Regression Coefficients for the Association between Adulthood Groups and Preference or Motivation for Solitude as Mediated by Various Antecedents. Preference for solitude Controlled motivation for solitude Established vs. Midlife vs. Midlife vs. Midlife vs. a a a b Emerging Emerging Emerging Established Relative total .57*** .42** -.35* -.45** effect (Path c) Relative direct .07 .05 -.65* -.47* effect (Path c') Relative indirect effects Age .12 [-.13, .38] .27 [-.30, .83] .60 [.05, 1.15] .33 [.02, .64] # of people living .004 [-.01, .02] .01 [-.03, .04] .004 [-.02, .03] .002 [-.02, .02] together # of Children -.01 [-.05, .03] -.01 [-.06, .04] -.02 [-.08, .03] -.004 [-.03, .02] Introversion .28 [.15, .41] .02 [-.15, .19] .01 [-.05, .08] -.10 [-.17, -.03] Anxiety .03 [.003, .06] .06 [.01, .12] -.25 [-.38, -.13] -.14 [-.26, -.03] Avoidance .08 [.03, .14] .02 [-.15, .19] .01 [-.04, .06] -.04 [-.10, -.001] Empathic -.0001 [-.01, .01] .01 [-.02, .04] -.04 [-.09, -.004] -.04 [-.09, -.005] concern Note. Indirect effects were computed for each of 5,000 bootstrapped samples. Significant indirect effects were bold. Confidence interval was 95%. aEmerging adult group was the reference group. bEstablished adult group was the reference group. *p < .05. **p < .01. ***p < .001.

Table 3

Standardized Regression Coefficients of Seven Outcome Variables Regressed on Preference and Motivation for Solitude Respectively for Emerging, Established, and Midlife Adult Groups. Depressive symptoms Loneliness Negative affect Positive affect Em Es Mi Em Es Mi Em Es Mi Em Es Mi PS -.02 -.01 -.07 .17*** .20** .07 -.28*** -.09 .03 -.29*** -.26*** -.21 SDM -.10 -.11 -.28** -.20*** -.33*** -.33* -.01 -.01 -.13 .31*** .47*** .42** CM .60*** .64*** .71*** .68*** .62*** .40** .52*** .60*** .83*** -.23*** -.01 -.13 R2 .35 .39 .51 .53 .42 .22 .27 .37 .67 .18 .26 .21 Life satisfaction Activity engagement Contact Em Es Mi Em Es Mi Em Es Mi PS -.21*** -.23** -.28* -.20** -.13 -.11 -.26*** -.19* -.27* SDM .23*** .41*** .34* .20** .06 .27 .13 .20* .31* CM -.40*** -.25** -.12 .01 .11 -.02 -.08 .21** .02 R2 .23 .21 .18 .05 .03 .08 .07 .13 .15 Note. Em = Emerging adult group, Es = Established adult group, Mi = Midlife adult group. PS = Preference for solitude, SDM = Self- determined motivation for solitude, CM = Controlled motivation for solitude. *p < .05. **p < .01. ***p < .001.

Table 4

Standardized Regression Coefficients for the Association between Preference for Solitude and Outcomes as Mediated by Self- determined and Controlled Motivation for Solitude. Self-determined motivation for solitude Controlled motivation for solitude Total effect Direct effect Indirect effect Indirect effect (Path c) (Path c') Path a1 Path b1 [95% CI] Path a2 Path b2 [95% CI] Depressive .05 -.03 .25*** -.11** -.03 [-.05, -.01] .18*** .62*** .11 [.06, .16] symptoms Loneliness .23*** .18*** .25*** -.26*** -.07 [-.10, -.04] .18*** .64*** .11 [.06, .17] Negative affect -.10* -.19*** .25*** -.02 -.005 [-.02, .01] .18*** .54*** .09 [.04, .15] Positive affect -.24*** -.32*** .25*** .39*** .10 [.06, .15] .18*** -.15*** -.03 [-.05, -.01] Life .25*** -.21*** -.24*** .32*** .08 [.05, .12] .18*** -.31*** -.05 [-.09, -.02] satisfaction Activity .25*** -.13** -.17*** .16*** .04 [.01, .07] .18*** .03 .004 [-.01, .02] engagement Contact -.20*** -.25*** .25*** .17*** .04 [.02, .08] .18*** .02 .003 [-.01, .02] Note. Indirect effects were computed for each of 5,000 bootstrapped samples. Significant indirect effects were bold. CI = confidence interval. *p < .05. **p < .01. ***p < .001.

Table 5

Standardized Regression Coefficients of Preference and Motivation for Solitude Regressed on Antecedents Variables Respectively for Emerging, Established, and Midlife Adult Groups. Preference for solitude Self-determined motivation Controlled motivation Em Es Mi Em Es Mi Em Es Mi Demographics Age .17* -.03 -.10 .09 -.06 .16 .16* .01 .002 Sex .12* .09 .06 .09 .01 .05 .11* -.12 -.01 Marital status .04 .08 .09 .07 .06 -.32 -.02 -.04 -.13 Education .01 .01 -.06 -.02 .05 -.07 .01 -.06 .01 Living arrangement # of Children .00 -.15 .01 -.003 .10 .25 -.07 -.11 .38* # of people living together -.05 .14 -.06 -.13* -.02 .17 -.001 .06 -.40* Physical status IADLs .00 -.14 -.04 .07 .03 .23 .17*** .14* .19 Psychological factors Introversion .51*** .53*** .47** -.06 -.19* -.09 .24*** .01 .22 Control .22*** .24*** -.05 .37*** .31*** .07 -.01 .08 -.07 Anxiety -.07 -.04 -.24 .01 .03 -.13 .34*** .51*** .38** Avoidance .20*** .26*** .21 .11 .14 .26 .18** .10 .18 Empathy

Perspective-taking -.02 -.01 -.09 .08 -.03 .21 .05 -.01 -.26 Fantasy .06 .11 .25 .06 .23* .26 .14* .03 .13 Empathic concern .01 .06 .08 -.02 .01 -.01 -.21** -.04 .09 Personal distress -.10 -.10 -.21 .07 .10 .28 .06 .21** .17 R2 .49 .48 .51 .17 .25 .36 .48 .52 .66 Note. Em = Emerging adult group, Es = Established adult group, Mi = Midlife adult group. For sex variable, female was coded as 1 and male or other sex were coded as 0. For marital status, being married or living in a long-term relationship were coded as 1 and being single, divorced, or widowed were coded as 0. *p < .05. **p < .01. ***p < .001.

Table 6

Baseline (Time 1) Descriptive Statistics of Demographical, Independent, and Dependent Variables in Respondent, Non-respondent, and Non-active MTurk Workers. Non-active MTurk Respondent Non-respondent workers Group differences (N=302) (n=144) (n=117) (n=41) Demographics Age, M (SD) 39.63 (12.43) 34.01 (8.36) 34.34 (8.03) F(2, 122.78)a = 10.11*** Sex, % of female 53.5% 48.7% 36.6% χ2 (2) = 3.67 Race, % of white 75.0% 67.5% 75.6% χ2 (2) = 2.08 Marital status, % of people who were married or living 39.6% 47.0% 69.3% χ2 (2) = 10.61** in a long-term relationship Education, % of people with 62.5% 68.4% 95.1% χ2 (2) = 16.00*** college or higher education Living arrangement Children, % of people not 59.0% 63.2% 24.4% χ2 (2) = 19.65*** having children People living together, % of 30.6% 30.8% 43.9% χ2 (2) = 2.84 people living alone Physical status IADLs, M (SD) 0.50 (1.23) 0.38 (0.92) 2.29 (1.93) F(2, 104.25)a = 31.48*** Psychological factors Introversion, M (SD) 4.53 (1.68) 4.59 (1.46) 3.49 (0.61) F(2, 178.72)a = 30.81*** Control, M (SD) 5.12 (1.36) 5.17 (1.21) 5.41 (0.78) F(2, 141.13)a = 1.73 Anxiety, M (SD) 2.04 (1.02) 2.15 (0.98) 3.26 (0.95) F(2, 229) = 17.83*** Avoidance, M (SD) 3.22 (1.17) 3.14 (1.04) 2.57 (0.55) F(2, 157.54) = 15.16*** Empathy Perspective-taking, M (SD) 5.12 (1.22) 5.07 (1.03) 4.59 (0.62) F(2, 148.88)a = 8.96***

Table 6 (continued)

Fantasy, M (SD) 4.80 (1.32) 4.54 (1.19) 4.51 (0.74) F(2, 143.74)a = 2.10 Empathic concern, M (SD) 5.32 (1.40) 5.12 (1.27) 4.48 (0.75) F(2, 147.99)a = 14.13*** Personal distress, M (SD) 3.38 (1.54) 3.26 (1.21) 4.30 (0.79) F(2, 145.94)a = 21.84*** Attitudes towards Solitude Preference for solitude, M 9.28 (2.92) 9.28 (2.66) 6.66 (2.49) F(2, 299) = 15.90*** (SD) Self-determined motivation, 2.63 (0.65) 2.64 (0.63) 2.98 (0.50) F(2, 299) = 5.34** M (SD) Controlled motivation, M 1.75 (0.80) 1.72 (0.74) 2.48 (0.79) F(2, 299) = 16.20*** (SD) Well-being outcomes Depressive symptoms, M 14.02 (12.41) 15.19 (12.41) 24.68 (11.58) F(2, 299) = 12.33*** (SD) Loneliness, M (SD) 42.33 (15.66) 43.18 (14.78) 44.49 (9.27) F(2, 140.87)a = 0.62 Negative affect, M (SD) 2.13 (1.23) 1.97 (0.91) 3.39 (1.58) F(2, 101.59)a = 14.85*** Positive affect, M (SD) 4.40 (1.36) 4.15 (1.24) 5.47 (0.90) F(2, 131.65)a = 28.20*** Life satisfaction, M (SD) 4.53 (1.69) 4.43 (1.59) 5.61 (1.24) F(2, 125.86)a = 13.35*** Social outcomes Activity engagement, M 1.04 (1.18) 0.97 (1.10) 1.88 (1.31) F(2, 122.97)a = 16.75*** (SD) Contact frequency, M (SD) 8.66 (2.50) 8.70 (2.53) 10.85 (2.60) F(2, 299) = 13.16*** aWelch’s ANOVA was used due to non-homogeneous variances between groups. *p < .05. **p < .01. ***p < .001.

Table 7

Descriptive Statistics, Internal Consistencies, and Rank-Order Stabilities of the Attitudes Towards Solitude and Consequences Measures in T2. Internal consistency Rank-order M (SD) () stability

Motivation in Solitude Preference for solitude 9.34 (2.88) .83 .81*** Self-determined motivation 2.63 (0.65) .81 .67*** Controlled motivation 1.76 (0.82) .91 .70*** Well-being outcomes Depression 14.89 (14.35) .96 .82*** Loneliness 40.77 (16.30) .97 .87*** Negative affect 2.20 (1.41) .95 .80*** Positive affect 4.23 (1.41) .93 .82*** Life satisfaction 4.42 (1.74) / .83*** Social outcomes Civic engagement 0.79 (1.04) / .46*** Contact frequency 9.08 (2.24) / .40*** Note. N = 144. Rank-order stability was calculated with test-retest correlations between T1 and T2 measures. T1 = Time 1 which was before the pandemic (Oct.-Dec. 2019). T2 = Time 2 which was one year after the pandemic started (May 2021). ***p < .001.

Table 8

Comparisons on the Regression Models between Attitudes towards Solitude and Consequences in T1 and T2. Depressive symptoms Loneliness Negative affect Positive affect Model Model Model Model Model Model Model Model Model Model Model Model 1 2 3 1 2 3 1 2 3 1 2 3 PSS .03 -.01 .08 .16* .07 .14 .02 -.05 .04 -.19* -.24*** -.28*** SDM -.14* -.07 -.11 -.23*** -.13* -.31* -.04 -.03 -.09 .46*** .54*** .46*** CM .70*** .79*** .57*** .63*** .73*** .39*** .66*** .72*** .51*** -.30*** -.34*** -.31*** R2 .51 .63 .36 .49 .59 .39 .44 .51 .27 .31 .27 .35 Life satisfaction Social engagement Contact Model Model Model Model Model Model Model Model Model 1 2 3 1 2 3 1 2 3 PSS -.16* -.15* -.16* -.06 -.10 -.09 -.06 -.13 -.21* SDM .29*** .23*** .22** .06 .06 .06 .12 .14 .15 CM -.43*** -.58*** -.49*** -.05 .09 .05 -.03 .00 .05 R2 .29 .47 .32 .01 .02 .01 .02 .03 .05 Note. N = 144. All the coefficients were standardized regression coefficients. PS = Preference for solitude, SDM = Self-determined motivation for solitude, CM = Controlled motivation for solitude. T1 = Time 1 which was before the pandemic (Oct.-Dec. 2019). T2 = Time 2 which was one year after the pandemic started (May 2021). Model 1 = Attitudes towards solitude in T1 predicting consequences in T1. Model 2 = Attitudes towards solitude in T2 predicting consequences in T2. Model 3 = Attitudes towards solitude in T1 predicting consequences in T2. *p < .05. **p < .01. ***p < .001.

Table 9

Comparisons on the Regression Models between Antecedents and Attitudes towards Solitude in T1 and T2. Preference for solitude Self-determined motivation Controlled motivation Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 Demographics Age .06 -.002 -.05 .04 -.02 -.04 -.13 .02 .07 Sex .16 .17* .06 .14 .23* .15* .01 .15* .15* Marital status -.02 .02 .03 -.12 -.18* -.11 -.08 -.02 .01 Education .08 .12 .07 -.01 -.10 -.09 -.02 .01 .02 Living arrangement # of Children -.01 -.02 -.01 .12 .08 .01 -.04 -.09 -.08 # of people living together -.03 -.05 -.03 -.19 -.03 .07 -.04 -.08 -.06 Physical status IADLs -.05 -.05 -.02 .03 .10 .09 .14* .23*** .18** Psychological factors Introversion .58*** .48*** .08 -.30* -.33** -.16 .12 -.004 -.05 Control .15 .05 -.05 .09 .10 .04 -.15* -.11 -.05 Anxiety -.10 -.16 -.09 -.05 -.16 -.13 .30*** .33*** .21** Avoidance .20* .25** .11 .20 .14 .03 .14 .29*** .24** Empathy Perspective-taking .04 .04 .02 .16 .25* .15 .04 .03 .01 Fantasy .11 .13 .06 .10 .08 .02 .06 .001 -.02 Empathic concern -.09 -.17 -.11 -.05 -.02 .01 -.08 -.07 -.04 Personal distress -.04 -.05 .08 .17 .20 .10 .10 .20* .17* T1 baseline .70*** .58*** .38*** R2 .41 .41 .70 .19 .27 .54 .52 .58 .65 Note. N = 144. All the regression coefficients were standardized. T1 = Time 1 which was before the pandemic (Oct.-Dec. 2019). T2 = Time 2 which was one year after the pandemic started (May 2021). Model 1 = Antecedents in T1 predicting attitudes towards solitude in T1. Model 2 = Antecedents in T1 predicting attitudes towards solitude in T2. Model 3 = Antecedents in T1 predicting attitudes towards solitude in T2 while controlling for attitudes towards solitude in T1 (i.e., changes in attitudes towards solitude). *p < .05. **p < .01. ***p < .001.

Table 10

Bivariate Correlations between Attitudes towards Solitude at T1 and T2 in Study 2 Sample. 1 2 3 4 5 6 1. Preference for solitude T1

2. Self-determined motivation T1 .23**

3. Controlled motivation T1 .20* .03

4. Preference for solitude T2 .81** .16 .24**

5. Self-determined motivation T2 .08 .67** -.0001 .09

6. Controlled motivation T2 .23** -.005 .70** .26** -.07 Age T1 -.05 .16* -.40** -.13 .14 -.24** Note. N= 144. T1 = Time 1 which was before the pandemic (Oct.-Dec. 2019). T2 = Time 2 which was one year after the pandemic started (May 2021).

Table 11

Hierarchical Regression Coefficients of Changes in Preference and Motivations for Solitude Regressed on T1 Baseline, Demographical Variables, and COVID-related Variables. Change in PS Change in SDM Change in CM B SE B  B SE B  B SE B  Step 1 Dependent variable T1 -.19 .05 -.31*** -.32 .06 -.39*** -.27 .06 -.35*** baseline R2 .10 .15 .12 F 14.68*** 24.45*** 18.89*** Step 2 Dependent variable T1 -.19 .05 -.30*** -.35 .07 -.43*** -.26 .07 -.33*** baseline Age T2 -.02 .01 -.15 .00 .00 .01 .00 .00 -.03 Race .21 .34 .05 -.03 .10 -.02 .08 .12 .06 Sex .02 .31 .01 .23 .09 .22* .25 .10 .20* Education T2 .01 .31 .00 -.07 .09 -.06 -.02 .10 -.02 Work T2 .38 .38 .09 .10 .10 .08 -.02 .13 -.01 Marital status T2 .01 .30 .00 -.05 .09 -.04 -.07 .10 -.06 R2 .13 .20 .17 R2 .04 .05 .05 F 0.91 1.40 1.18 Step 3 Dependent variable T1 -.20 .06 -.32*** -.38 .07 -.46*** -.29 .07 -.37*** baseline Age T2 -.02 .01 -.14 .00 .00 .01 .00 .00 .00 Race .27 .35 .07 -.05 .10 -.04 .14 .11 .10 Sex .13 .33 .04 .15 .09 .15 .36 .11 .30*** Education T2 .05 .31 .01 -.04 .09 -.03 -.06 .10 -.05 Work T2 .26 .39 .06 .07 .11 .05 .01 .12 .01 Marital status T2 -.02 .31 -.01 -.07 .09 -.07 -.04 .10 -.03

Table 11 (continued)

Worry -.05 .07 -.07 .03 .02 .12 -.03 .02 -.12 Threat .04 .17 .02 .01 .05 .02 -.05 .06 -.08 Contact frequency -.32 .23 -.12 -.08 .07 -.09 -.08 .08 -.08 Change in contact .74 .32 .19* .12 .09 .10 -.06 .11 -.04 frequency Number of losses -.04 .09 -.05 -.04 .02 -.13 .06 .03 .19* Support needed .03 .09 .03 .01 .02 .04 .04 .03 .13 Number of coping -.08 .09 -.08 .05 .02 .19* -.07 .03 -.21* strategies R2 .20 .27 .27 R2 .06 .06 .10 F 1.36 1.49 2.36* Note. PS = Preference for solitude, SDM = Self-determined motivation for solitude, CM = Controlled motivation for solitude. T1 = Time 1 which was before the pandemic (Oct.-Dec. 2019). T2 = Time 2 which was one year after the pandemic started (May 2021). For race variable, white or European American were coded as 1 and other races were coded as 0. Sex variable, female was coded as 1 and male or other sex were coded as 0. For education variable, college or higher educations were coded as 1 and lower than college educations were coded as 0. For work status, full-time or part-time professional activities were coded as 1, and in training/education, retired, unemployed, and homemaker were coded as 0. For marital status, being married or living in a long-term relationship were coded as 1, and being single, divorced, or widowed were coded as 0. For support variable, “Yes, it is enough” and “No, support is not necessary” were coded as 0, and “Yes, but not enough” and “No, but I do need support” were coded as 1. *p < .05. ***p < .001.

Table 12

Standardized Hierarchical Regression Coefficients of Changes in Well-being and Social Variables Regressed on T1 Baselines, Demographical Variables, and COVID-related Variables. Depressive Negative Positive Life Activity Loneliness Contact symptoms affect affect satisfaction engagement

Step 1 Dependent variable T1 -.11 -.21 -.11 -.42*** -.39*** -.60*** -.63*** baseline PS T1 baseline .09 -.05 .05 -.25** -.07 -.05 -.16* SDM T1 baseline .00 .08 -.09 .22* .02 .03 .09 CM T1 baseline .03 .09 -.05 -.17 -.29** .06 .05 R2 .02 .04 .03 .15 .13 .36 .41 F .57 1.61 .99 6.30*** 5.39*** 19.97*** 23.93*** Step 2 Dependent variable T1 -.43*** -.49*** -.36** -.51*** -.51*** -.59*** -.62*** baseline PS T1 baseline -.05 -.09 -.05 -.15 -.03 -.05 -.13 SDM T1 baseline -.03 .03 -.11 .35*** .14 .01 .08 CM T1 baseline .51*** .49*** .30* -.29*** -.47*** .07 .02 Change in PS -.15* .05 -.07 .14 -.09 .04 .07 Change in SDM -.06 -.06 -.09 .25** .29*** -.06 -.02 Change in CM .64*** .61*** .45*** -.22** -.38*** .03 -.05 R2 .34 .34 .18 .27 .34 .37 .41 R2 .32 .29 .15 .12 .21 .01 .01 F 21.75*** 20.18*** 8.50*** 7.24*** 14.19*** .38 .47 Step 3 Dependent variable T1 -.44*** -.53*** -.36** -.53*** -.43*** -.62*** -.64*** baseline PS T1 baseline -.06 -.06 -.09 -.13 -.01 -.01 -.12 SDM T1 baseline -.02 .05 -.12 .31** .12 .00 .08 CM T1 baseline .48*** .50*** .26 -.23* -.45*** .13 .01 Change in PS -.17* .03 -.08 .14 -.07 .01 .05 Change in SDM -.06 -.03 -.10 .22* .28*** -.04 -.02 Change in CM .63*** .63*** .43*** -.26** -.37*** .03 -.06 Age T2 -.15 -.07 -.15 .21* .01 .07 -.07 Race .12 .12 .14 .00 -.06 .07 .08 Sex .03 -.10 .09 .04 .01 -.05 .02 Education T2 -.02 -.05 .09 -.13 -.18* .03 .00 Work T2 .02 .11 -.10 .14 .02 .14 .07 Marital status T2 .02 -.05 .01 -.04 -.06 .12 .04

Table 12 (continued)

R2 .36 .38 .23 .33 .37 .40 .43 R2 .03 .04 .05 .06 .03 .03 .02 F .97 1.52 1.32 1.77 1.08 1.20 .60 Note. PS = Preference for solitude, SDM = Self-determined motivation for solitude, CM = Controlled motivation for solitude. T1 = Time 1 which was before the pandemic (Oct.-Dec. 2019). T2 = Time 2 which was one year after the pandemic started (May 2021). Change scores were using T2 scores minus T1 scores. *p < .05. ***p < .001.

Figure 1

Conceptual Mediation Models (Process Model 4) with Various Antecedents Mediate the Association between Adulthood Groups and Attitudes towards Solitude.

Figure 2

Conceptual Mediation Models (Process Model 4) with Self-determined and Controlled Motivation for Solitude Mediate the Association between Preference for Solitude and Outcomes.

Figure 3

Illustration of the Four Analyses on the Associations between Attitudes towards Solitude and Consequences Compared Parallelly.

Figure 4

Illustration of the Three Analyses on the Associations between Antecedents and Attitudes towards Solitude Compared Parallelly.

APPENDICES

Appendix A: Preference for Solitude Scale

For each of the following pairs of statements, select the one that best describes you. In some cases neither statement may describe you well or both may describe you somewhat. In those cases, please select the statement that best describes you or that describes you more often.

I enjoy being around I enjoy being by people. o o myself. I try to structure my I try to structure my day so that I always o o day so that I always have some time to am doing something myself. with someone One feature I look for One feature I look for in a job is the o o in a job is the opportunity to opportunity to spend interact with time by myself. interesting people. After spending a few After spending a few hours surrounded by a o o hours surrounded by a lot of people, I lot of people, I am usually find myself usually eager to get stimulated and away by myself. energetic. Time spent alone is Time spent alone is often productive for o o often time wasted for me. me. I often have a strong I rarely have a strong desire to get away by o o desire to get away by myself. myself. I like to vacation in I like to vacation in places where there are o o places where there are a lot of people around few people around and a lot of activities and a lot of serenity going on. and quiet. When I have to spend When I have to spend several hours alone, I o o several hours alone, I find the time boring find the time and unpleasant. productive and pleasant. If I were to take a If I were to take a several-hour plane o o several-hour plane trip, I would like to trip, I would like to sit next to someone spend the time who was pleasant to quietly. talk with.

Time spent with other Time spent alone is people is often boring o o often boring and and uninteresting. uninteresting. I have a strong need I do not have a strong to be around other o o need to be around people. other people. There are many times There are rarely times when I just have to o o when I just have to get away and be by get away and be by myself. myself.

Appendix B: Motivation for Solitude Scale-Short Form Please take a moment to think about the time you spend alone. This could include the things you tend to do when you're alone, what you think about, and how you feel. Rate the importance of each of the following statements as a reason that you spend time alone.

For example, one item is “I enjoy the quiet.” Remember, we are not asking you to rate the extent to which you enjoy the quiet when you are alone, but the IMPORTANCE of that as a reason that you spend time alone. If enjoying the quiet is a very important reason that you spend time alone, you should check “Very important.” If it is not at all important as a reason you spend time alone, you should check “Not at all important.”

“When I spend time alone, I do so because …” Not at all Somewhat Moderately Very important important important important It sparks my creativity o o o o I enjoy the quiet o o o o I feel anxious when I'm with o o o o others Being alone helps me get in o o o o touch with my spirituality I don't feel liked when I'm with o o o o others I can't be myself around others o o o o It helps me stay in touch with my o o o o feelings I regret things I say or do when o o o o I'm with others I feel uncomfortable o o o o when I'm with others I value the privacy o o o o I can engage in activities that o o o o really interest me

I feel like I don't belong when I'm o o o o with others It helps me gain insight into why o o o o I do the things I do I feel energized when I spend o o o o time with myself

100

Appendix C: Instrumental Activity of Daily Living (IADL) checklist Here are a few more everyday activities. Please tell me if you have any difficulty with these because of a physical, mental, emotional or memory problem. Again exclude any difficulties you expect to last less than three months.

▢ Using a map to figure out how to get around in a strange place

▢ Recognising when you are in physical danger

▢ Preparing a hot meal

▢ Shopping for groceries

▢ Making telephone calls

▢ Communication (speech, hearing or eyesight)

▢ Taking medications

▢ Doing work around the house or garden

▢ Managing money, such as paying bills and keeping track of expenses

▢ None of the above

101

Appendix D: Big Five extroversion-introversion subscale In general, I am a person who... strongly strongly disagree 2 3 4 5 6 agree 1 7

is talkative. o o o o o o o

is reserved. o o o o o o o is full of energy. o o o o o o o generates a lot of enthusiasm. o o o o o o o tends to be quiet. o o o o o o o has an assertive personality. o o o o o o o is sometimes shy, o o o o o o o inhibited. is outgoing, sociable. o o o o o o o

102

Appendix E: Perceived Control scale In the following statements, please rate the extent to which the statements are characteristic of you. 1 2 3 4 5 6 7 I am free to control my thoughts, regardless of o o o o o o o whether I am with a small group or by myself.

I am free to choose when and to what extent I have o o o o o o o to speak and interact with others

I feel free to act and use my time as I see fit. o o o o o o o

I have control over the pressures and tensions of o o o o o o o everyday life.

103

Appendix F: Activity engagement checklist Do you regularly give any unpaid help to any person, group, club or organization in any of the following ways?

▢ Leading the group/member of a committee

▢ Organising or helping to run an activity or event

▢ Befriending or mentoring people

▢ Educating/teaching/coaching

▢ Providing information/counselling

▢ Keeping in touch with someone who has difficulty getting out and about (visiting in person)

▢ Babysitting or caring for children

▢ Sitting with or providing personal care (washing, dressing) for someone who is sick or frail

▢ Other ______

104

Appendix G: Non-physical contact frequency How often during the last week did you use the following method for communication? 1 2 3 4 talking/facetiming through the phone/computer/tablet o o o o

messaging o o o o

writing letters o o o o online interactive communication (e.g., email, social media, o o o o forum, or blog)

105

Appendix H: Contact frequency Do you have people in any of the following relationships who do not live in your house? (Multiple answers are possible)

▢ Parents and/or patents-in-law

▢ Children and/or grandchildren

▢ Siblings

▢ Grandparents

▢ Other family

▢ Friends

▢ Coworkers or classmates

▢ Neighbors

▢ Other acquaintances ( e.g., Shop assistants, social worker, care taker)

Carry Forward Selected Choices from "Do you have people in any of the following relationships who do not live in your house? (Multiple answers are possible)"

We would like to ask you a few questions about contact with people who do not live in your house. By contact we mean going on a visit (they come to visit you or you go to visit them), making a phone call, writing to them, emailing them, WhatsApp, contact via computer or video calls, having a chat with them. Is the contact now, in How often have you been in contact with these COVID-19 time, different people in recent weeks? from before? less (almost) approximately at least more not less often or every monthly weekly now changed now never day

106

Parents and/or patents-in- o o o o o o o law Children and/or grandchildren o o o o o o o

Siblings o o o o o o o

Grandparents o o o o o o o

Other family o o o o o o o

Friends o o o o o o o Coworkers or classmates o o o o o o o

Neighbors o o o o o o o Other acquaintances ( e.g., Shop assistants, social o o o o o o o worker, care taker)

107

Appendix I: Personal losses In this COVID-19 era, everyday life may have changed a lot. Through this crisis, are there situations and events that affect you personally? No More or less Yes I have been sick o o o The death or serious illness of your partner o o o or a housemate The death or serious illness of a family o o o member, friend, or close acquaintance No, less or other contact with o o o grandchildren and children No, less or other contact with other o o o family, friends, and acquaintances Discontinuation of normal leisure o o o activities, such as club activities Can no longer visit cafes, restaurants, and o o o many shops Loss of your job, business and financial o o o problems of your own Loss of work, business and financial o o o problems of your partner, family member, friend, or close acquaintance Fewer opportunities to exercise outdoors, o o o such as walking, cycling, and sports Necessary groceries (such as food, o o o medication) are harder to get

108

Appendix J: Social support Have you received help or support with the following activities in the past two weeks? Yes, but not No, but I do No, support is Yes, it is enough enough need support not necessary Maintaining social contacts (e.g. via computer or o o o o tablet/iPad)

Daily activities o o o o Financial situation (debts, administration, making o o o o payments) Mental health (e.g. meaning, coping with anxiety, o o o o gloominess) Physical health and dealing with medication o o o o Personal care (e.g. washing, dressing, support o o o o stockings) Housekeeping (e.g. cooking, shopping, o o o o cleaning)

109

Appendix K: General perceived threats If you compare yourself to other people, how much chance do you have of getting sick from the Corona virus?

o A much smaller chance

o A smaller chance

o An equal chance

o A bigger chance

o A much bigger chance

How worried have you been about the COVID-19 crisis in recent weeks?

o I don’t worry 1

o 2

o 3

o 4

o 5

o 6

o 7

o 8

o 9

o I am extremely worried 10

110

Appendix L: Coping strategies for social isolation or loneliness What are you doing, or have you done, to break through your social isolation or loneliness in the Corona era or to deal with the situation? In some activities we give examples.

▢ Contact with others through technology (e.g., emailing, (video) calling, texting, talking via social media, sharing videos and photos)

▢ Contact at 1.5 meters distance (e.g., talking to neighbors, walking, or visiting at a distance)

▢ Joint activities with housemates (e.g., baking, games, gardening)

▢ Participation in playful neighborhood actions (e.g., balcony music, street bingo, window concert)

▢ Participation in actions for others (e.g., clapping, burning candles)

▢ Group meetings via technology (e.g., virtual neighborhood walk, online group meeting, or TV daytime activities)

▢ Seeking spirituality (e.g., praying, meditating, reading spiritual texts)

▢ Volunteering or helping acquaintances

▢ Relativizing (e.g., humor, think that I am well off compared to some others, think that we can handle this problem in the US)

▢ Finding distractions in and around the house (e.g., gardening, hobbies, TV, computer games)

▢ Outdoor distraction (e.g., hiking, biking, sports, driving a car, going to shops)