Next Article in Journal
Correlations of Salivary and Blood Glucose Levels among Six Saliva Collection Methods
Previous Article in Journal
Changes in the Mental Health of Children and Adolescents during the COVID-19 Lockdown: Associated Factors and Life Conditions
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 19
Issue 7
10.3390/ijerph19074121
ijerph-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Associations between Leisure Preferences, Mindfulness, Psychological Capital, and Life Satisfaction

by
Aiste Dirzyte
1,2,*,
Aleksandras Patapas
3 and
Aidas Perminas
4
1
Institute of Psychology, Mykolas Romeris University, 08303 Vilnius, Lithuania
2
Faculty of Creative Industries, Vilnius Gediminas Technical University, 10223 Vilnius, Lithuania
3
Institute of Public Administration, Mykolas Romeris University, 08303 Vilnius, Lithuania
4
Department of Psychology, Vytautas Magnus University, 44248 Kaunas, Lithuania
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2022, 19(7), 4121; https://doi.org/10.3390/ijerph19074121
Submission received: 31 January 2022 / Revised: 23 March 2022 / Accepted: 29 March 2022 / Published: 30 March 2022
Browse Figures
Versions Notes

Abstract

:
This study intended to explore which leisure preferences contribute to mindfulness, psychological capital, and life satisfaction and assess whether mindfulness, psychological capital, and life satisfaction are associated with different leisure preferences. This study applied the Satisfaction with Life Scale (SWLS), the Psychological Capital Questionnaire (PCQ-12), the Mindful Attention Awareness Scale (MAAS), and the instrument to evaluate the prevalence of leisure preferences. A sample consisted of 586 participants, 104 males and 478 females. The mean age of participants was 42.06, SD = 13.29. The results show that respondents who did not spend free time watching television scored higher on life satisfaction, mindfulness, and psychological capital. Participants who preferred attending events scored higher on life satisfaction and psychological capital. Participants who preferred spending time with family as a leisure preference scored significantly higher on life satisfaction, mindfulness, and psychological capital, including PsyCap overall, PsyCap work, PsyCap relationship, and PsyCap health. The findings also reveal that time spent with family is significantly associated with life satisfaction. Besides, males’ life satisfaction was significantly associated with time spent in nature, while females’ satisfaction was associated with spending time with family and participating in events. Males’ mindfulness was significantly associated with book reading, and females’ mindfulness was associated with not watching television. Males’ psychological capital was significantly associated with spending time with family and book reading, and females’ psychological capital was associated with not watching television but spending time with family, participating in events, and spending time in nature. The findings also showed that mindfulness mediated the link between watching television and life satisfaction, and psychological capital mediated links between spending time with family, participating in events, and life satisfaction. The findings demonstrate that life satisfaction is also significantly associated with spending time with family as a leisure preference. This study also revealed a significant negative association between age and spending time with friends or family, evidencing the possible loneliness of elderly respondents. Due to limitations of this study, including sample size and characteristics, cultural context, and research design, the research findings would preferably be regarded thoughtfully.

1. Introduction

Due to the COVID-19 pandemic, people worldwide faced tense life challenges, including restrictions in leisure activities. The global lockdown has affected leisure choices, resulting in reconsidering “how, where, and when leisure takes place” [1]. Leisure, which by its Latin origin “licere” means “to be permitted” or “to be free”, gained a new perspective of somewhat limited time spending possibilities linked to leisure nostalgia [2].
The importance of daily leisure on quality of life could be based on research evidencing that psychological wellbeing increases immediately during vacation, peaks on the eighth vacation day, and rapidly returns to baseline level within the first week of work resumption [3]. As the pandemic has restricted vacation possibilities, new knowledge on the effects of daily leisure preferences on life satisfaction is needed.

1.1. Leisure Preferences

Various research has documented that leisure is one of the essential life quality domains and core ingredients of wellbeing [4]. Leisure activities reflect particular profiles corresponding to numerous variables, including age [5,6,7], health [8,9,10], goals and personality traits [11], gender [12,13], cultural contexts [14,15,16,17,18], emotions [19,20,21], intrinsic motivational orientation [22], among others.
Newman et al. proposed that the multidimensional construct of leisure encompasses structural (amount of time spent outside of work, the number of activities viewed as leisure) and subjective (sense of leisure involvement, positive feelings) aspects [4]. Subjective leisure is not necessarily tied to a particular activity but might be linked to a particular flow [23] or relaxation [24] in environments where one can feel absorbed by the present moment, free from obligations.
Research indicates that leisure preferences, allowing pleasant absorption in the present moment, might have beneficial or detrimental effects. Such leisure preferences as “recreational marihuana” [25] consumed in the user’s leisure time to relax or enhance positive affect, might temporally disengage from stress, but the long–term consequences might be rather far from the desired. On the other hand, some leisure preferences are beneficial for the user’s health and wellbeing, including meditation [9] or physical activity [26,27,28], or spending time in nature [14,29]. However, excessive engagement in some types of “user-friendly” leisure preferences might also result in wellbeing and health-related challenges [30].
Based on previous research linking various leisure activities to psychological wellbeing, we targeted several types of leisure preferences, namely, (1) time spent with family, (2) time spent with friends, (3) time spent in nature, (4) participating in events, (5) watching TV, and (6) book reading. Research suggests that these leisure preferences might signify certain qualities of a user.
(1)
Time spent with family. As a leisure preference, time spent with family indicates several user attributes. Firstly, for the user, family is a value. Research indicates that family and leisure values are positively linked to life satisfaction in all five regions: the West, Latin America, the Asian-Confucian region, ex-Communist Eastern Europe, and the Communist countries of China and Vietnam [19]. However, not every user prefers family for leisure purposes [31,32,33,34,35,36]. If the time spent with family is preferred as a leisure choice, it suggests that being with family can satisfy the user’s basic psychological needs of autonomy, competence, and relatedness [11,37]. From a Hsiao Yao (逍遙) perspective, which stems from Taoism’s Chuang Tzu’s philosophy, leisure is a carefree state of being or happiness [38]. It means that for some people, spending time with family can satisfy needs for relaxation, safety [39,40], or affiliation [4]. Next, research suggests that family leisure satisfaction is the strongest predictor of family functioning and satisfaction with family life [32,41]. Consequently, family as a leisure preference might significantly predict overall life satisfaction.
(2)
Time spent with friends. If a user enjoys leisure with friends, it can be assumed that one also scores high on extraversion and can establish and maintain strong social bonds based on mutual trust, compassion, and understanding. In conceptual research on “The social nature of leisure involvement”, Kyle and Chick proposed that leisure is a group phenomenon, and social circles, including friends, highly influence participation in recreation [42]. Next, they noted that the social organization of leisure is characterized by people interacting with others due to mutual tastes and a sense of belonging: “building memories of past experiences shared with family and friends were littered throughout all interviews. The central characters in these stories were always family and friends. Perhaps embellished over the years, these stories were retold during gatherings” [42], p. 438. Furthermore, several studies suggested that friends share unique meanings, and leisure time with friends strengthens interpersonal relationships [42,43]. Based on this perspective, it can be presumed that time spent with friends strengthens satisfaction with interpersonal relationships and, consequently, life satisfaction.
(3)
Time spent in nature. Outdoor leisure activities are preferred by users of different ages [28,39,44], genders [13], and cultural backgrounds [29,45,46]. Time spent in nature might encompass a wide range of leisure preferences, from leisure gardening, which evidenced contributing to life satisfaction of older adults [24], to outdoor activities, including enjoyment in walking or outdoor sports [34,35,47], or fishing and hunting [45,48,49]. Outdoor leisure preferences might reflect users’ connectedness to nature and environmental intelligence [49,50,51]. Based on previous research linking nature-based recreational activities and psychological wellbeing, it can be presumed that time spent in nature as a leisure preference significantly contributes to life satisfaction.
(4)
Participation in events. Recreational activities such as participating in festivals or visiting museums, theaters, cinemas, or other events, are attracting the increased attention of researchers [12,18,52,53,54,55]. Research suggests that women are more likely than men to participate in highbrow leisure activities, but there is little evidence that highbrow leisure participation is related to family background or socioeconomic status [12]. Furthermore, research indicates that cultural participation is associated with personality trait openness to experience, as open users favor visiting art and historical museums and attending classical and pop concerts [54]. Participation in events, bringing recreational enjoyment and excitement, as a leisure preference, implies users’ openness and novelty-seeking, indicating possible links to life satisfaction.
(5)
Watching television. There is a decades-long debate over the links between watching television (TV) and wellbeing. Some researchers established the benefits of TV watching, as, after a loss in the interpersonal sphere, television viewing can play a valuable role in adaptation processes [56]. Despite recognized temporal enjoyments in viewing, several studies pointed to its potential harms, including links to the “bedroom culture” phenomenon, lower physical activity, and self-control [6,25,44,57,58,59,60]. However, some research indicates that television as a leisure preference, especially for shared viewing with the family, can be a good tool for socializing and relaxation [7]. Consequently, it can also be linked to life satisfaction.
(6)
Book reading. Book reading as a leisure activity plays a vital role in school-age years for lexical development [5], resulting in better verbal fluency, nonverbal problem-solving ability, and general knowledge [61]. There is also evidence on links between book reading and life quality in adulthood, as reading preferences expand a reader’s knowledge and reflect social differentiation [62]. Furthermore, research indicates that frequent readers achieve more and demonstrate higher IQ [63], and personality trait openness to experiences is a relevant indicator of reading preferences [54]. Based on previous research linking book reading with openness and numerous advantageous outcomes, it can be presumed that leisure book reading could also be linked to life satisfaction.
Even though many studies demonstrated links between leisure activities and life satisfaction, the question of which leisure preferences are most beneficial for psychological variables is still under-researched. Similarly, even though the links between personality traits, needs, and leisure preferences have been established, it is still under-researched which other psychological variables predict different leisure preferences. As a recent wave of positive psychology delineates the importance of mindfulness and psychological capital for life satisfaction, we considered it essential to analyze which leisure preferences contribute to mindfulness, psychological capital, and life satisfaction. In addition, we regarded it as important to analyze whether mindfulness, psychological capital, and life satisfaction predict different leisure preferences.

1.2. Mindfulness

The construct of mindfulness originated in Buddhism and Brahmanic traditions but is frequently used to refer to both a state or quality of mind and a form of meditation [64]. Kabat-Zinn defined mindfulness as the awareness that arises through paying purposeful attention to the present moment, which allows the nonjudgmental unfolding of experience moment by moment to “the way things are”, as in the Chinese notion of Tao [65].
Mindfulness has recently been extensively researched in various contexts, including its impact on improving academic performance [66], reducing anxiety symptoms [67] or stress [68], boosting immunity [9], improving heart rate variability or decreasing burnout [69], links to structural brain networks [70]. Mindfulness was also linked to social sustainability [71], work engagement [72], inhibiting malicious envy [73], or higher psychological capital [74]. Moreover, numerous studies reported links between mindfulness and psychological wellbeing [75,76]. However, the links between mindfulness and leisure preferences are under-researched. On the one hand, there is a question of which leisure activities can contribute to mindfulness as a state of mind. On the other hand, based on mindfulness research, it can be implied that mindfulness can contribute to satisfaction with various leisure activities, but the question of mindful leisure preferences and their links to life satisfaction needs a deeper analysis.

1.3. Psychological Capital

A concept of psychological capital (PsyCap) emerged along with the movement of positive psychology nearly two decades ago and received considerable attention from researchers [77,78,79,80,81,82,83,84,85,86,87,88]. Luthans et al. defined psychological capital as a multidimensional construct, reflecting four dimensions: self-efficacy, hope, resilience, and optimism [83]. Self–efficacy is considered as having the confidence to take on and put in the necessary effort to succeed at challenging tasks. Optimism is regarded as making positive attributions about succeeding now and in the future. Hope is considered as persevering toward goals and, when necessary, redirecting paths to goals to succeed. Resilience is defined as sustaining and bouncing back and beyond to attain success when beset by problems and adversity [83].
Numerous studies have documented associations between psychological capital (PsyCap) and life satisfaction [89,90] or psychological capital and quality of life [91]. Research indicated that persons who score higher on PsyCap are more likely to engage in opportunities to sustain and improve wellbeing and persist in achieving their goals [92].
Even though the concept of psychological capital was developed in an organizational context, based on research linking psychological capital to outcomes of general importance, researchers designed and validated a universal measure for the PsyCap construct, with applications for all domains of life [93]. It was established that psychological capital in different domains (relationship, health, work, and overall) is associated with positive affect, perceived social support, and life satisfaction. Furthermore, several studies revealed links between psychological capital and mindfulness [72,74].
However, the links between psychological capital and leisure preferences are still under-researched, even though leisure is one of the essential life domains.

1.4. Life Satisfaction

The construct of life satisfaction indicates a cognitive evaluation of one’s life and is a component of subjective wellbeing or happiness [4,94,95]. Numerous studies have demonstrated links between leisure and happiness [21], leisure and fulfillment [32], and leisure and life satisfaction [96,97,98,99].
Newman et al. proposed five core psychological mechanisms that leisure potentially triggers to promote leisure subjective wellbeing: detachment-recovery, autonomy, mastery, meaning, and affiliation [4]. They argued that global subjective wellbeing is based on an evaluation of crucial life domains as leisure, work, and health, and leisure preferences might contribute to the various dimensions of subjective wellbeing in the leisure domain, which subsequently promotes global subjective wellbeing. A conceptual model proposed by Newman et al. on leisure and subjective wellbeing and psychological mechanisms as mediating factors delineate the importance of research on variables linked to leisure preferences and life satisfaction [4].
Furthermore, Sirgy et al., proposed a benefits theory of leisure wellbeing [11], which expanded Newman’s et al. model. In Sirgy et al.’s theory, twelve sets of mechanisms, reflecting basic and growth needs, impact satisfaction with leisure life and subjective wellbeing: leisure benefits related to safety, health, economic, hedonic, escape, sensation-seeking, symbolic, aesthetics, morality, mastery, relatedness, and distinctiveness. Sirgy et al. argued that the more a leisure activity delivers benefits related to basic and growth needs, the greater the likelihood that such an activity would contribute significantly to life satisfaction. On the other hand, it can be presumed that the more leisure activity contributes to life satisfaction, the greater is likelihood that particular leisure preference ensures the satisfaction of basic and growth needs.
This study did not focus on satisfaction or frustration of psychological needs in different leisure preferences, even though we admit the importance of such research. We considered it essential to explore links between leisure preferences and life satisfaction, mediated by earlier discussed mindfulness and psychological capital constructs, and to identify whether mindfulness, psychological capital, and life satisfaction predict different leisure preferences. Thus, this study aimed to identify associations between leisure preferences, mindfulness, psychological capital, and life satisfaction. Based on the previous research, we hypothesized that:
Hypothesis 1 (H1).
Respondents preferring different leisure types differ in life satisfaction, mindfulness, and psychological capital.
Hypothesis 2 (H2).
Life satisfaction, mindfulness, and psychological capital are associated with different types of leisure.
Hypothesis 3 (H3).
Associations between different leisure types and life satisfaction, mindfulness, and psychological capital differ between genders.
Hypothesis 4 (H4).
Mindfulness and life satisfaction mediate links between leisure preferences and life satisfaction.
Hypothesis 5 (H5).
Mindfulness, psychological capital, and life satisfaction are linked to different leisure preferences.

2. Materials and Methods

2.1. Sample

This study was conducted in Lithuania and applied a cluster random sampling method. We have randomly selected two samples of private and public sector organizations from the Lithuanian organizations’ database. From within those samples, we have randomly selected a sample of respondents. Out of 1000 selected respondents, 601 respondents consented to participate in the study. However, the data of 15 participants were excluded from the further analysis due to not meeting the inclusion criteria.
The inclusion criteria for this research were: (1) 18 years old and older; (2) not unemployed or retired, but working, at least partially; (3) permanent residents of Lithuania. The exclusion criteria were the following: (1) younger than 18 years old; (2) just studying in educational institutions and not formally working (e.g., volunteers were excluded); (3) unemployed (candidates for a position were excluded); (4) fully retired; (5) not permanent residents of Lithuania.
In order to assess whether the data are not biased, the analysis of missing data has been performed. The data had no more than 20% of missing data of the variables. An omnibus statistical test for inspecting missing data confirmed that the data are missing completely at random. A test-by-test deletion was chosen for the analysis carried out with the SPSS. For the analysis carried out with the JASP, exclusion of cases pairwise/listwise and the full information maximum likelihood (FIML) methods were applied.
The study sample consisted of 586 participants, 104 males, 478 females, and four respondents indicated their gender as “other.” The sample of females was overrepresented in this study, but the sample sizes of two genders were sufficient to test the statistical hypothesis H3. The age of respondents ranged from 18 to 76 years (mean age was 42.06, SD = 13.29). In total, 47.5 percent of respondents were married, 34 percent were unmarried, 9 percent were divorced, and 4.2 percent were widowed. Fifty-five percent of respondents held Master’s degrees, 12 percent held Bachelor’s degrees, 24.2 percent finished Higher education, and 15 percent finished Secondary education. The possible respondents were asked to participate in the study online or during group meetings organized in several organizations and were informed that personal data (names, organization) are omitted in the questionnaire to ensure data confidentiality and anonymity. The research team received anonymous data of the sample. The procedure followed the General Data Protection Regulation (GDPR) guidelines and the Declaration of Helsinki and was approved by the Research Ethics Council at the Institute of Management and Psychology, Lithuania.

2.2. Instruments

2.2.1. The SWLS

The authors measured respondents’ life satisfaction with the Satisfaction with Life Scale (SWLS), developed by E. Diener et al., a short 5-item instrument designed to assess global cognitive judgments of satisfaction with one’s life [100]. The response pattern followed a 7-point Likert scale ranging from totally disagree to agree strongly. Validation studies confirmed the one-dimensional structure of the SWLS, evidencing the instrument’s favorable psychometric properties [100,101,102,103].

2.2.2. The PCQ-12

Psychological Capital or PsyCap was measured using the 12-item Psychological Capital Questionnaire (PCQ-12), applied to health, personal relationships, work, and overall life [92]. The PCQ-12 contains three items to measure efficacy, four items to measure hope, three to measure resilience, and two to measure optimism. The response pattern followed a 6-point Likert scale ranging from strongly disagree to agree strongly. Numerous studies demonstrated the reliability and validity of the PCQ-12 in various cultural contexts [104,105,106,107].

2.2.3. The MAAS

Mindfulness was measured using the single-factor structure 15-item Mindful Attention Awareness Scale, developed by Brown and Ryan [108]. The items are rated on a 6-point Likert scale ranging from almost always to rarely. Respondents were given the following instruction: “below is a collection of statements about your everyday experience. Please answer according to what reflects your experience rather than what you think your experience should be”. The MAAS has been validated across multiple samples, evidencing good psychometric properties [75,109,110,111,112,113,114].
To ensure that the Lithuanian items corresponded as closely as possible to the English items, the original items of all instruments were translated into Lithuanian and back-translated. The McDonald’s ω and Cronbach’s α of the SWLS, the PCQ-12, and the MAAS in this study are displayed in Table 1.

2.2.4. Leisure Preferences

Leisure preferences were evaluated, asking respondents a question: “How do you spend your free time?” and providing with the following list: “watching television”, “book reading”, “spending time in nature”, “spending time with family”, “spending time with friends”, “participating in events”, “going to meditation/yoga classes”, and “other”. The items were rated on a 4-point Likert scale ranging from not at all to very much. The option “meditation/yoga classes” was somewhat chosen by 3.8 percent of participants, and due to statistical insufficiency, we eliminated this variable from further analysis. The option “other” was somewhat chosen by 35 percent of participants, who indicated mostly activities like “gaming” or “social media” and somewhat “fitness” or “using SPA services.” However, this “other” option was also eliminated from further investigation, as the data were not sufficiently transparent and appropriate for statistical analyses.

2.3. Statistical Analyses

Statistical analyses were performed using SPSS v.26.0 (IBM Corp., Armonk, NY, USA) and JASP v. 0.16. (University of Amsterdam, Amsterdam, The Netherlands). Cronbach’s alphas and McDonald’s’ omegas were calculated to evaluate instruments’ reliability [115]. Confirmatory factor analysis (CFA) evaluated instruments’ validity [116]. A model fit evaluation was based on the GFI (Goodness of Fit Index), the CFI (Comparative Fit Index), the Normed Fit Index (NFI), the Tucker–Lewis coefficient (TLI), RMSEA (Root Mean Square Error of Approximation), and SRMR (Standardized Root Mean Square Residual), whereas the χ2 was used for descriptive purposes only [117]. The values higher than 0.90 for CFI, NFI, and TLI, and values lower than 0.08 for RMSEA and SRMR were considered indicative of a good fit, and p-values less than 0.05 were considered to be indicative of a good fit be statistically significant [118,119,120]. For descriptive purposes, bivariate nonparametric correlations between the study variables were analyzed using the Spearman correlation test [121]. Differences between groups were analyzed using Welch’s t-test [122]. Associations between the study variables were analyzed using multiple regression (forward method) and mediation analyses [123,124]. Data distribution was evaluated using the Shapiro-Wilk test, which showed the departure from normality. However, the distribution was moderately negatively skewed (Table 2).

3. Results

Based on responses regarding leisure preferences ranging from “not at all” to “very much,” we created conditional groups: if respondents checked answer “not at all” (0), they were considered to fall into the group of non-users of a particular leisure preference, and if respondents checked “somewhat” to “very much” (1–3), they fall into the group of particular leisure preference users. Frequencies of leisure preferences are displayed in Table 3.
In preliminary analyses, bivariate Spearman’s correlations between the types of leisure preferences and age were calculated (Table 4). Even though several significant correlations were identified, it is worth noting that this study revealed a significant negative correlation between age and spending time with friends (rho = −0.306, p < 0.001) or family (rho = −0.092, p < 0.001), evidencing the possible loneliness of elderly respondents.
The results of the confirmatory factor analysis are presented in Table 5. Model fit for all the instruments was good regarding GFI, CFI, TLI, NFI, and SRMR. However, the RMSEA for the PCQ-12 was higher the expected. One of the CFA’s main premises is that the residuals should not be correlated; thus, we present RMSEA of the PCQ-12 with uncorrelated residuals, even though RMSEA was considerably lower and demonstrated a good fit with correlated residuals.
The descriptives and correlations between the PCQ-12, the MAAS, and the SWLS in this study are displayed in Table 6.
Table 7 displays Spearman’s correlations between types of leisure preferences and the PCQ-12, the MAAS, and the SWLS.
In the main analysis, we conducted several independent samples t-tests to test H1, which presumed that respondents preferring different leisure types differ in life satisfaction, mindfulness, and psychological capital. Firstly, we compared respondents who prefer watching television with those who reported not spending free time on TV. The results show (Table 8) that respondents who did not spend free time on TV demonstrated significantly higher scores on life satisfaction, mindfulness, and psychological capital, including PsyCap overall, PsyCap work, PsyCap relationship, and PsyCap health.
The comparison of respondents who prefer and do not prefer attending events (Table 9) showed that those who prefer attending events reported significantly higher scores on life satisfaction, PsyCap overall, and PsyCap work.
The comparative analysis of those who prefer and do not prefer spending leisure time in nature (Table 10) indicated that respondents who prefer nature also score significantly higher on psychological capital, including PsyCap overall, PsyCap relationship, and PsyCap health.
Most importantly, the comparison of respondents who prefer and do not prefer spending time with family (Table 11) showed that those who chose the family as a leisure preference also demonstrated significantly higher scores on life satisfaction, mindfulness, and psychological capital, including PsyCap overall, PsyCap work, PsyCap relationship, and PsyCap health.
Surprisingly, no significant differences were found in any of the study variables in groups of respondents who prefer or do not prefer book reading or spending time with friends.
To sum up, Welch’s t-test analysis partially confirmed H1, evidencing some differences in life satisfaction, mindfulness, and psychological capital, including PsyCap overall, PsyCap work, PsyCap relationship, and PsyCap health in groups of participants with different leisure preferences.
Furthermore, to test H2, assuming that different types of leisure associate with life satisfaction, mindfulness, and psychological capital, we conducted multiple linear regression (forward method) analyses in the total sample. The results of multiple regression models, when the dependent variables are life satisfaction, mindfulness, and psychological capital, and the predictors are leisure preferences, are displayed in Table 12.
Multiple regression analyses showed several significant regression equations concerning the dependent variable of life satisfaction. In model 1, life satisfaction was significantly predicted by time spent with family. In model 2, significant predictors of life satisfaction were time spent with family and participating in events. Model 3 indicated that life satisfaction was significantly predicted by time spent with family, participating in events, and the absence of watching television. Next, regression analysis showed a significant regression equation concerning the dependent variable of mindfulness. Predicted mindfulness equalled 4.294–0.045 (watching television) points. In other words, mindfulness was predicted by not watching television in this model. Next, several significant regression equations were found regarding the dependent variable of psychological capital. Model 1 indicated that the absence of watching television significantly predicted psychological capital. In model 2, psychological capital was predicted by time spent with family and not watching television. In model 3, significant predictors of psychological capital were spending time with family, participating in events, and not watching television. Model 4 indicated that not watching television but spending time with family, participating in events, and spending time in nature significantly predicts psychological capital.
Thus, multiple regression analyses partially confirmed H2, evidencing how different types of leisure are associated with life satisfaction, mindfulness, and psychological capital.
Furthermore, to test H3, presuming that associations between different leisure types and life satisfaction, mindfulness, and psychological capital differ between genders, we conducted multiple linear regression (forward method) analyses in two gender groups separately. The results of multiple regression models in groups of females and males, when the dependent variables are life satisfaction, mindfulness, and psychological capital, and the predictors are leisure preferences, are displayed in Table 13.
Multiple regression analyses in both genders showed several significant regression equations concerning the dependent variable of life satisfaction. In a group of males, life satisfaction was significantly predicted by time spent in nature. In a group of females, model 1, a significant predictor of life satisfaction was time spent with family, and model 2 indicated that significant predictors of females’ life satisfaction were spending time with family and participating in events. Next, regression analysis showed several significant regression equations concerning the dependent variable of mindfulness. In a group of males, mindfulness was significantly predicted by book reading. In a group of females, mindfulness was predicted by not watching television. Next, several significant regression equations were found regarding the dependent variable of psychological capital. In a group of males, model 1, overall psychological capital was significantly predicted by spending time with family. Model 2 indicated that spending time with family and book reading significantly predicted the psychological capital of males. In a group of females, model 1, overall psychological capital was predicted by not watching television. In model 2, significant predictors of females’ psychological capital were participating in events and not watching television. In model 3, females’ psychological capital was significantly predicted by participating in events, not watching television, and spending time with family. Model 4 indicated that females’ psychological capital was significantly predicted by not watching television but spending time with family, participating in events, and spending time in nature.
Therefore, multiple regression analyses partially confirmed H3, evidencing that associations between different leisure types and life satisfaction, mindfulness, and psychological capital differ between genders.
Furthermore, to test H4, assuming that mindfulness and psychological capital mediate links between leisure preferences and life satisfaction, we initially performed multiple mediation analyses based on the conceptual model of links between leisure preferences, psychological capital, mindfulness, and life satisfaction. However, most of the links were statistically insignificant. For clarity, we present separately two significant models demonstrating the role of mindfulness and the role of psychological capital as mediators.
In a model shown in Figure 1, the outcome variable for the mediation analysis was life satisfaction. Based on previous analyses, the predictor variables were spending time with family and participation in events, and the mediator variables were the PsyCap overall and PsyCap relationship.
The mediation analysis results indicating the role of psychological capital are presented in Table 14. The indirect effects of spending time with family and participating in events on life satisfaction were statistically significant. Spending time with family significantly predicted psychological capital overall and psychological capital relationship, which significantly predicted life satisfaction. Participating in events significantly predicted overall psychological capital, subsequently predicting life satisfaction. However, R² for life satisfaction in the total sample was 0.254, PsyCap overall R2 was 0.049, and PsyCap relationship R2 was 0.055.
In a model shown in Figure 2, the outcome variable for the mediation analysis was life satisfaction, the predictor variable was watching television, and the mediator variable was mindfulness.
The mediation analysis results indicating the role of mindfulness are presented in Table 15. The indirect effect of watching television on life satisfaction was statistically significant, even though R² for life satisfaction was 0.043, and R² for mindfulness was 0.028.
Thus, mediation analyses partially confirmed H4, evidencing that mindfulness and psychological capital mediate links between leisure preferences and life satisfaction. Mindfulness mediated the link between watching television and life satisfaction, and psychological capital mediated links between spending time with family, participating in events, and life satisfaction.
Next, to test H5, assuming that mindfulness, psychological capital, and life satisfaction are linked to different leisure preferences, multiple regression analyses (forward method) were conducted (Table 16).
Regression analysis showed a significant regression equation concerning the dependent variable of spending time with family. Life satisfaction was a significant predictor of spending time with family as a leisure preference F (1, 259) = 16.510, p < 0.001, with R2 = 0.060. Predicted spending time with family was equal to 2.193 + 0.469 (life satisfaction) points. Spending time with family increased + 0.469 for each life satisfaction point (p < 0.001). Thus, life satisfaction contributed significantly to the model and was a significant predictor of spending time with family as a leisure preference. Next, predicted watching television was equal to 5.095–0.622 (PsyCap relationship) points, F (1, 258) = 8.428, p = 0.004, with R2 = 0.032. Watching television decreased—0.622 points for each PsyCap relationship point. Thus, the PsyCap relationship was a significant predictor of watching television. Then, predicted participation in events increased +0.480 points for each PsyCap overall point, F (1, 259) = 5.066, p = 0.025, with R2 = 0.019. However, mindfulness was not a significant predictor of any leisure preferences.
Thus, regression analyses partially confirmed H5, evidencing links between leisure preferences and life satisfaction and psychological capital. Life satisfaction was associated with spending time with family, PsyCap relationship was associated with spending less time on TV, and PsyCap was overall associated with participation in events. However, these findings need further investigation.

4. Discussion

This study was a preliminary attempt to explore links between leisure preferences and mindfulness, psychological capital, and life satisfaction. It explored which leisure preferences contribute to mindfulness, psychological capital, and life satisfaction. In addition, it aimed to assess whether mindfulness, psychological capital, and life satisfaction are linked to different leisure preferences. Many previous studies established links between leisure preferences and life satisfaction [23,31], links between life satisfaction and psychological capital [89,90,125,126,127,128], life satisfaction and mindfulness [129,130], or mindfulness and psychological capital [72,74,76,131]. Previous studies also examined links between several types of leisure activities and psychological capital [99,132] or links between some activities (meditation, physical activity) and mindfulness [9,133,134,135]. However, the links between leisure preferences, mindfulness, psychological capital, and life satisfaction have not previously been investigated in the same study.
The context of restrictions due to COVID-19 makes the findings of this study important as this research draws attention to possible psychological benefits of different daily leisure preferences. In addition, it proposes some insights on psychological antecedents of leisure choices, as established by previous research [2].
The research was focused on three psychological constructs: mindfulness, proposed by Kabat-Zinn [65]; life satisfaction, proposed by Diener et al. [94]; and psychological capital, proposed by Luthans et al. [136].
In this study, we hypothesized (H1) that respondents preferring different leisure types differ in life satisfaction, mindfulness, and psychological capital. The findings partially confirmed H1, evidencing some differences in life satisfaction, mindfulness, and psychological capital, including PsyCap overall, PsyCap work, PsyCap relationship, and PsyCap health in groups of participants with different leisure preferences. The results show that respondents who did not spend free time watching television demonstrated significantly higher scores on life satisfaction, mindfulness, and psychological capital, including PsyCap overall, PsyCap work, PsyCap relationship, and PsyCap health. Next, the findings indicat that those who prefer attending events score higher on life satisfaction, PsyCap overall, and PsyCap work. Most importantly, the results show that those who spend time with family as a leisure preference demonstrated significantly higher scores on life satisfaction, mindfulness, and psychological capital, including PsyCap overall, PsyCap work, PsyCap relationship, and PsyCap health. Surprisingly, no significant differences were found in any of the study variables in groups of respondents who prefer or do not prefer book reading or spending time with friends. These results might be partially linked to previous research suggesting associations between life satisfaction and leisure preferences, namely, family [12,39,40,55,137,138], watching television [5,7,10,56,60,139,140,141,142], or participation in events [54,58,143]. However, it is unclear why the differences concerning book reading or spending time with friends were not significant in this study and why those who prefer spending leisure time with a family score higher on mindfulness and psychological capital.
Furthermore, in this study, we hypothesized (H2) that different types of leisure preferences link to life satisfaction, mindfulness, and psychological capital. The findings reveal that time spent with family significantly predicts life satisfaction. In another model, life satisfaction was also significantly predicted by time spent with family, participating in events, and the absence of watching television. Moreover, mindfulness was also predicted by not watching television. Next, the results demonstrate that not watching television but spending time with family, participating in events, and spending time in nature significantly predicts psychological capital. Thus, the findings partially confirmed H2, evidencing how different types of leisure predict life satisfaction, mindfulness, and psychological capital. These findings align with some prior research on links between life satisfaction and spending time with family [41], watching television [54], and participation in events [14,44,143,144]. However, the question of why watching television decreases mindfulness and psychological capital and why spending time in nature or with friends or book reading is not significant for life satisfaction needs further investigation and warns that these results should be regarded with caution.
This study also hypothesized (H3) that associations between different leisure types and life satisfaction, mindfulness, and psychological capital differ between genders, as previous research indicated possible effects [12,13]. The findings revealed that males’ life satisfaction was significantly predicted by time spent in nature, while females’ satisfaction was predicted by spending time with family and participating in events. Next, males’ mindfulness was significantly predicted by book reading, and females’ mindfulness was predicted by not watching television. Then, the psychological capital of males was significantly predicted by spending time with family and book reading, and females’ psychological capital was predicted by not watching television but spending time with family, participating in events, and spending time in nature. Therefore, the findings partially confirmed H3, showing that associations between leisure types and life satisfaction, mindfulness, and psychological capital differ between genders. These results are consistent with some previous studies suggesting the possible effect of gender on leisure preferences and the related variables [96,144,145]. However, the mechanism underlying the links’ specifics in different genders is still unclear and needs further investigation.
Furthermore, this research assumed (H4) that mindfulness and psychological capital mediate links between leisure preferences and life satisfaction. The findings show that mindfulness mediated the link between watching television and life satisfaction, and psychological capital mediated links between spending time with family, participating in events, and life satisfaction. Mediation analyses revealed that the indirect effects of spending time with family and participating in events on life satisfaction were statistically significant: spending time with family significantly predicted psychological capital overall and psychological capital relationship, which significantly predicted life satisfaction. Participating in events significantly predicted overall psychological capital, subsequently predicting life satisfaction. Moreover, the indirect effect of watching television on life satisfaction was also statistically significant. Thus, H4 was partially confirmed, evidencing that mindfulness and psychological capital mediate links between leisure preferences and life satisfaction. These results signify that leisure preferences and life satisfaction are interrelated constructs mediated by psychological variables, as indicated by previous studies [17,21,28,45,132,137,141,143,146,147,148,149,150]. However, these associations’ details concerning particular leisure preferences require a more grounded approach, preferably including personality traits as predictors [96] and psychological needs satisfaction [134] as covariates in further research.
This study also hypothesized (H5) that mindfulness, psychological capital, and life satisfaction could be linked to different leisure preferences. The findings demonstrate that life satisfaction was a significant predictor of spending time with family as a leisure preference. Next, the PsyCap relationship was a significant predictor of (not) watching television, and PsyCap overall was a significant predictor of participation in events. However, contrary to the expected, mindfulness was not a significant predictor of any leisure preferences in this study. Even though the results partially confirm H5, as life satisfaction is associated with spending time with family, the PsyCap relationship is associated with spending less time watching television, and PsyCap overall is associated with participation in events, which might be partially explained by previous research [11,19,23,31,96] these findings need further investigation.
However, we acknowledge that the associations found in the current study may change depending on the contextual factors in which the leisure activities are chosen. Recent studies indicated that the associations between leisure activities and well-being could be moderated by the timing, duration, types of content, and social factors of the leisure activities. E.g., Hartanto et al. (2021) indicated the moderating role of contextual factors in the associations between video gaming and well-being [151]; Tooth et al. (2021) delineated the effect of family context related to screen time, child behavior, and health-related quality of life [152]. These findings impose the need for detailed exploration of contextual factors in future research.

5. Limitations

This study is a preliminary attempt to explore links between leisure preferences and psychological variables of mindfulness, psychological capital, and life satisfaction, and it has many limitations. The first limitation is the sample size and sample characteristics. The research sample was not representative; females were overrepresented, and the samples were statistically insufficient for structural equation modeling (SEM) regarding comparing SEMs in different groups. Thus, the results should be cautioned due to the sample characteristics. The second limitation is cultural context. The study was conducted in Lithuania, which since 2004 has belonged to the European Union but is a post-soviet country. Possibly, the same research in other world regions would generate different results. Comparison of previous studies suggests that leisure research is sensitive to cultural factors [150,151,152,153]. Thus, the findings should be taken with concern. Next, the measurement of leisure preferences was based on the authors’ created instrument, which intended to assess the prevalence of certain leisure preferences but did not measure leisure satisfaction. Besides, this instrument did not include leisure options like “social media”, “gaming”, “SPA services”, or many others, which are “the must” to be included in future research. Besides, recent studies have suggested analyzing “screen-based” recreational activities [147,154,155,156]. Next, in future research, it will be important to adjust for demographic variables such as age to ensure that the results were not confounded. Finally, the results indicate a necessity for longitudinal or experimental research design because it is possible only to identify significant relationships among the examined variables based on the data obtained. This research can be used to describe characteristics that exist in the selected sample, but not to determine cause-and-effect relationships between different variables.

6. Conclusions

This study provided some evidence that (H1) respondents preferring different leisure types differ in life satisfaction, mindfulness, and psychological capital; (H2) life satisfaction, mindfulness, and psychological capital are associated with different types of leisure; (H3) associations between different leisure types and life satisfaction, mindfulness, and psychological capital partially differ between genders. The findings also reveal that (H4) mindfulness and life satisfaction mediate links between leisure preferences and life satisfaction, and (H5) mindfulness, psychological capital, and life satisfaction are linked to different leisure preferences. The results show that respondents who did not spend free time watching television scored higher on life satisfaction, mindfulness, and psychological capital. Participants who preferred attending events scored higher on life satisfaction and psychological capital. Participants who preferred spending time with family as a leisure preference scored significantly higher on life satisfaction, mindfulness, and psychological capital, including PsyCap overall, PsyCap work, PsyCap relationship, and PsyCap health. The findings also reveal that time spent with family is significantly associated with life satisfaction. Besides, males’ life satisfaction was significantly associated with time spent in nature, while females’ satisfaction was associated with spending time with family and participating in events. Males’ mindfulness was significantly associated with book reading, and females’ mindfulness was associated with not watching television. Males’ psychological capital was significantly associated with spending time with family and book reading, and females’ psychological capital was associated with not watching television but spending time with family, participating in events, and spending time in nature. The findings also show that mindfulness mediated the link between watching television and life satisfaction, and psychological capital mediated links between spending time with family, participating in events, and life satisfaction. The findings demonstrated that life satisfaction is also significantly associated with spending time with family as a leisure preference. This study also evidenced a significant negative association between age and spending time with friends or family, evidencing the possible loneliness of elderly respondents. However, due to limitations of this study, including sample size and characteristics, cultural context, and research design, the research findings would preferably be regarded thoughtfully.

Author Contributions

Conceptualization: A.D., A.P. (Aleksandras Patapas) and A.P. (Aidas Perminas); methodology: A.D. and A.P. (Aidas Perminas); data collection: A.D. and A.P. (Aleksandras Patapas); data curation: A.D. and A.P. (Aidas Perminas); formal analysis and investigation: A.D.; writing—original draft preparation: A.D.; writing—review and editing: A.D. and A.P. (Aleksandras Patapas); funding acquisition: A.D.; supervision: A.D. and A.P. (Aidas Perminas). All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by LVPA, project number Nr. 01.2.1-LVPA-K-856-01-0250, based on the agreement Nr. IP-VIPI-1.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Research Ethics Council at the Institute of Management and Psychology, Lithuania, Nr. VIPI-IP-2020-K-856-01-0250.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Gammon, S.; Ramshaw, G. Distancing from the Present: Nostalgia and Leisure in Lockdown. Leis. Sci. 2021, 43, 131–137. [Google Scholar] [CrossRef]
  2. Cho, H. The Impacts of Leisure Nostalgia on Well-Being and Turnover Intention: The Mediating Roles of Leisure Satisfaction and Work Commitment. Leis. Sci. 2021, 1–21. [Google Scholar] [CrossRef]
  3. De Bloom, J.; Geurts, S.A.E.; Kompier, M.A.J. Vacation (after-) effects on employee health and well-being, and the role of vacation activities, experiences and sleep. J. Happiness Stud. 2013, 14, 613–633. [Google Scholar] [CrossRef] [Green Version]
  4. Newman, D.B.; Tay, L.; Diener, E. Leisure and Subjective Well-Being: A Model of Psychological Mechanisms as Mediating Factors. J. Happiness Stud. 2014, 15, 555–578. [Google Scholar] [CrossRef]
  5. Nippold, M.A.; Duthie, J.K.; Larsen, J. Literacy as a leisure activity: Free-time preferences of older children and young adolescents. Lang. Speech Heart Serv. Sch. 2005, 36, 93–102. [Google Scholar] [CrossRef]
  6. Kleiber, D.; McGuire, F.A.; Aybar-Damali, B.; Norman, W. Having more by doing less: The paradox of leisure constraints in later life. J. Leis. Res. 2008, 40, 343–359. [Google Scholar] [CrossRef]
  7. Fedele, M.; García-Muñoz, N.; Prado, E. Catalan adolescents’ media uses and leisure preferences related to new media and television. Catalan J. Commun. Cult. Stud. 2015, 7, 51–70. [Google Scholar] [CrossRef] [Green Version]
  8. Conine, D.E.; Vollmer, T.R. Relative preferences for edible and leisure stimuli in children with autism. J. Appl. Behav. Anal. 2019, 52, 557–573. [Google Scholar] [CrossRef]
  9. Jiang, T.; Hou, J.; Sun, R.; Dai, L.; Wang, W.; Wu, H.; Zhang, T.; Su, B. Immunological and Psychological Efficacy of Meditation/Yoga Intervention among People Living with HIV (PLWH): A Systematic Review and Meta-analyses of 19 Randomized Controlled Trials. Ann. Behav. Med. 2021, 55, 505–519. [Google Scholar] [CrossRef]
  10. Lancioni, G.E.; Singh, N.N.; O’Reilly, M.F.; Sigafoos, J.; Chiapparino, C.; Stasolla, F.; Bosco, A.; De Pace, C.; Oliva, D. Enabling a young man with minimal motor behavior to manage independently his leisure television engagement. Percept. Mot. Skills 2007, 105, 47–54. [Google Scholar] [CrossRef] [PubMed]
  11. Sirgy, M.J.; Uysal, M.; Kruger, S. Towards a Benefits Theory of Leisure Well-Being. Appl. Res. Qual. Life 2017, 12, 205–228. [Google Scholar] [CrossRef]
  12. Katz-Gerro, T.; Meier Jæger, M. Does Women’s Preference for Highbrow Leisure Begin in the Family? Comparing Leisure Participation among Brothers and Sisters. Leis. Sci. 2015, 37, 415–430. [Google Scholar] [CrossRef]
  13. Rosa, C.D.; Larson, L.R.; Collado, S.; Cloutier, S.; Profice, C.C. Gender Differences in Connection to Nature, Outdoor Preferences, and Nature-Based Recreation Among College Students in Brazil and the United States. Leis. Sci. 2020, 1–21. [Google Scholar] [CrossRef]
  14. Xiao, X.; Lee, K.J.J.; Larson, L.R. Who visits U.S. national parks (and who doesn’t)? A national study of perceived constraints and vacation preferences across diverse populations. J. Leis. Res. 2021, 53, 1–22. [Google Scholar] [CrossRef]
  15. Wright Wendel, H.E.; Zarger, R.K.; Mihelcic, J.R. Accessibility and usability: Green space preferences, perceptions, and barriers in a rapidly urbanizing city in Latin America. Landsc. Urban Plan. 2012, 107, 272–282. [Google Scholar] [CrossRef]
  16. Shinew, K.J.; Floyd, M.F.; McGuire, F.A.; Noe, F.P. Class polarization and leisure activity preferences of African Americans: Intragroup comparisons. J. Leis. Res. 1996, 28, 219–232. [Google Scholar] [CrossRef]
  17. Mitchell, B.A.; Wister, A.V.; Fyffe, I.A. Leisure Time Satisfaction and Activity Preferences Among Ethnically Diverse Aging Parents in Metro Vancouver. J. Cross-Cult. Gerontol. 2021, 36, 387–406. [Google Scholar] [CrossRef]
  18. Floyd, M.F.; Shinew, K.J.; McGuire, F.A.; Noe, F.P. Race, Class, and Leisure Activity Preferences: Marginality and Ethnicity Revisited. J. Leis. Res. 1994, 26, 158–173. [Google Scholar] [CrossRef]
  19. Headey, B.; Trommsdorff, G.; Wagner, G.G. Alternative Recipes for Life Satisfaction: Evidence from Five World Regions. Appl. Res. Qual. Life 2021. [Google Scholar] [CrossRef]
  20. Kim, J.; Lee, S.; Chun, S.; Han, A.; Heo, J. The effects of leisure-time physical activity for optimism, life satisfaction, psychological well-being, and positive affect among older adults with loneliness. Ann. Leis. Res. 2017, 20, 406–415. [Google Scholar] [CrossRef]
  21. Lepp, A. Correlating leisure and happiness: The relationship between the leisure experience battery and the Satisfaction With Life Scale. Ann. Leis. Res. 2018, 21, 246–252. [Google Scholar] [CrossRef]
  22. Barnett, L.A. Accounting for leisure preferences from within: The relative contributions of gender, race or ethnicity, personality, affective style, and motivational orientation. J. Leis. Res. 2006, 38, 445–474. [Google Scholar] [CrossRef]
  23. An, B.; Sato, M.; Harada, M. Grit, Leisure Involvement, and Life Satisfaction: A Case of Amateur Triathletes in Japan. Leis. Sci. 2021, 1–17. [Google Scholar] [CrossRef]
  24. Cheng, E.H.P.; Patterson, I.; Packer, J.; Pegg, S. Identifying the satisfactions derived from leisure gardening by older adults. Ann. Leis. Res. 2010, 13, 395–419. [Google Scholar] [CrossRef]
  25. Gould, J.; Donnelly, R.; Innacchione, B. Turning over a new leaf in Colorado: An exploration of legalized recreational marijuana preferences, leisure interests, and leisure motivations in a sample of young adults. World Leis. J. 2019, 61, 113–130. [Google Scholar] [CrossRef]
  26. Izquierdo Sanchez, S.; Elliott, C.; Simmons, R. Substitution between leisure activities: A quasi-natural experiment using sports viewing and cinema attendance. Appl. Econ. 2016, 48, 3848–3860. [Google Scholar] [CrossRef] [Green Version]
  27. Zhou, J.; Wang, H.; Rajaram, S.S.; Britigan, D.H.; Su, D. Changes in leisure time physical activity preferences and hypertension risk. Am. J. Health Behav. 2019, 43, 145–157. [Google Scholar] [CrossRef] [PubMed]
  28. Houge Mackenzie, S.; Brymer, E. Conceptualizing adventurous nature sport: A positive psychology perspective. Ann. Leis. Res. 2020, 23, 79–91. [Google Scholar] [CrossRef] [Green Version]
  29. Marques, C.; Reis, E.; Menezes, J.; de Fátima Salgueiro, M. Modelling preferences for nature-based recreation activities. Leis. Stud. 2017, 36, 89–107. [Google Scholar] [CrossRef]
  30. Bo Andersen, L.; Schnohr, P.; Schroll, M.; Ole Hein, H. All-cause mortality associated with physical activity during leisure time, work, sports, and cycling to work. Arch. Intern. Med. 2000, 160, 1621–1628. [Google Scholar] [CrossRef]
  31. Schmiedeberg, C.; Schröder, J. Leisure Activities and Life Satisfaction: An Analysis with German Panel Data. Appl. Res. Qual. Life 2017, 12, 137–151. [Google Scholar] [CrossRef]
  32. Pinquart, M.; Silbereisen, R.K. Patterns of fulfilment in the domains of work, intimate relationship, and leisure. Appl. Res. Qual. Life 2010, 5, 147–164. [Google Scholar] [CrossRef]
  33. Kekäläinen, T.; Freund, A.M.; Sipilä, S.; Kokko, K. Cross-Sectional and Longitudinal Associations between Leisure Time Physical Activity, Mental Well-Being and Subjective Health in Middle Adulthood. Appl. Res. Qual. Life 2020, 15, 1099–1116. [Google Scholar] [CrossRef] [Green Version]
  34. Hakoköngäs, E.; Puhakka, R. Happiness from Nature? Adolescents’ Conceptions of the Relation between Happiness and Nature in Finland. Leis. Sci. 2021, 1–20. [Google Scholar] [CrossRef]
  35. Kim, J.; Heo, J.; Dvorak, R.; Ryu, J.; Han, A. Benefits of leisure activities for health and life satisfaction among Western migrants. Ann. Leis. Res. 2018, 21, 47–57. [Google Scholar] [CrossRef]
  36. Chick, G.; Hsu, Y.C.; Yeh, C.K.; Hsieh, C.M.; Bae, S.Y.; Iarmolenko, S. Cultural Consonance in Leisure, Leisure Satisfaction, Life Satisfaction, and Self-Rated Health in Urban Taiwan. Leis. Sci. 2016, 38, 402–423. [Google Scholar] [CrossRef]
  37. Pagán, R. How Do Leisure Activities Impact on Life Satisfaction? Evidence for German People with Disabilities. Appl. Res. Qual. Life 2015, 10, 557–572. [Google Scholar] [CrossRef]
  38. Yeh, C.K.; Chick, G. Hsiao Yao: A Chinese Analog of the Classical Western Idea of Leisure. Leis. Sci. 2021, 1–15. [Google Scholar] [CrossRef]
  39. Izenstark, D.; Middaugh, E. Patterns of family-based nature activities across the early life course and their association with adulthood outdoor participation and preference. J. Leis. Res. 2021, 1–23. [Google Scholar] [CrossRef]
  40. Crawford, D.W.; Houts, R.M.; Huston, T.L.; George, L.J. Compatibility, leisure, and satisfaction in marital relationships. J. Marriage Fam. 2002, 64, 433–449. [Google Scholar] [CrossRef]
  41. Williamson, M.; Zabriskie, R.; Townsend, J.; Ward, P.; Fellingham, G.; Kuznetsova, I. The contribution of family leisure to family functioning and family satisfaction among urban Russian families. Ann. Leis. Res. 2019, 22, 607–628. [Google Scholar] [CrossRef]
  42. Kyle, G.; Chick, G. The social nature of leisure involvement. J. Leis. Res. 2002, 34, 426–448. [Google Scholar] [CrossRef]
  43. Harmon, J.; Kyle, G.T. Positive emotions and passionate leisure involvement. Ann. Leis. Res. 2016, 19, 62–79. [Google Scholar] [CrossRef] [Green Version]
  44. Baranov, V.V.; Savinov, A.M.; Ashrafullina, G.S.; Makarov, A.L.; Korzhanova, A.A.; Dzhamalova, B.B.; Magomedrasulov, M.N. Youth Leisure in Cultural Space of Modern City: State and Prospects of Development. Propósitos Represent. 2020, 8. [Google Scholar] [CrossRef]
  45. Schroeder, S.A.; Cornicelli, L.; Fulton, D.C.; Merchant, S.S. The influence of motivation versus experience on recreation satisfaction: How appreciative- versus achievement-oriented recreation experience preferences relate to hunter satisfaction. J. Leis. Res. 2019, 50, 107–131. [Google Scholar] [CrossRef]
  46. Sari, D. A study on the qualities that affect preference of rural recreation areas. Appl. Ecol. Environ. Res. 2019, 17, 11509–11523. [Google Scholar] [CrossRef]
  47. Bailey, A.W.; Anderson, M.; Cox, G. The Cortex in Context: Investigating the Influence of Activity and Space on Psychological Well-Being. Leis. Sci. 2021, 1–18. [Google Scholar] [CrossRef]
  48. Finucane, M.L.; Fox, J.; Saksena, S.; Spencer, J.H. Understanding Society and Natural Resources; Springer: Dordrecht, The Netherlands, 2014; ISBN 978-94-017-8958-5. [Google Scholar]
  49. Rosa, C.D.; Profice, C.C.; Collado, S. Nature experiences and adults’ self-reported pro-environmental behaviors: The role of connectedness to nature and childhood nature experiences. Front. Psychol. 2018, 9, 1–10. [Google Scholar] [CrossRef]
  50. Brügger, A.; Kaiser, F.G.; Roczen, N. One for all?: Connectedness to nature, inclusion of nature, environmental identity, and implicit association with nature. Eur. Psychol. 2011, 16, 324–333. [Google Scholar] [CrossRef]
  51. Van Doorn, J.R.; Hortman, J.W. Environmental Intelligence and Relationships with Conservation, Nature Sensitivity and Exercise. Ph.D. Thesis, Troy University, Triy, AL, USA, 2012. [Google Scholar]
  52. O’Brien, E.; Roney, E. Worth the Wait? Leisure Can Be Just as Enjoyable With Work Left Undone. Psychol. Sci. 2017, 28, 1000–1015. [Google Scholar] [CrossRef] [PubMed]
  53. Karlis, G.; Stratas, A.; Webb, E. Canada-based peer-reviewed leisure studies research: From the 1970s to today. Loisir Soc. 2018, 41, 9–26. [Google Scholar] [CrossRef]
  54. Kraaykamp, G.; van Eijck, K. Personality, media preferences, and cultural participation. Pers. Individ. Dif. 2005, 38, 1675–1688. [Google Scholar] [CrossRef] [Green Version]
  55. Chidambaram, B.; Scheiner, J. Leisure quality among german parents—exploring urbanity, mobility, and partner interaction as determinants. Sustainability 2021, 13, 5883. [Google Scholar] [CrossRef]
  56. Van Der Goot, M.; Beentjes, J.W.J.; Van Selm, M. Meanings of television in older adults’ lives: An analysis of change and continuity in television viewing. Ageing Soc. 2012, 32, 147–168. [Google Scholar] [CrossRef]
  57. Pritchard, A.; Kharouf, H. Leisure consumption in cricket: Devising a model to contrast forms and time preferences. Leis. Stud. 2016, 35, 438–453. [Google Scholar] [CrossRef]
  58. Voigt, C.; Howat, G.; Brown, G. Hedonic and eudaimonic experiences among wellness tourists: An exploratory enquiry. Ann. Leis. Res. 2010, 13, 541–562. [Google Scholar] [CrossRef]
  59. Hanley, G.P.; Iwata, B.A.; Roscoe, E.M.; Thompson, R.H.; Lindberg, J.S. Response-Restriction Analysis: Ii. Alteration of Activity Preferences. J. Appl. Behav. Anal. 2003, 36, 59–76. [Google Scholar] [CrossRef] [Green Version]
  60. Teychenne, M.; Ball, K.; Salmon, J. Correlates of socio-economic inequalities in women’s television viewing: A study of intrapersonal, social and environmental mediators. Int. J. Behav. Nutr. Phys. Act. 2012, 9, 3–9. [Google Scholar] [CrossRef] [Green Version]
  61. Torppa, M.; Niemi, P.; Vasalampi, K.; Lerkkanen, M.K.; Tolvanen, A.; Poikkeus, A.M. Leisure Reading (But Not Any Kind) and Reading Comprehension Support Each Other—A Longitudinal Study Across Grades 1 and 9. Child Dev. 2020, 91, 876–900. [Google Scholar] [CrossRef]
  62. Kraaykamp, G.; Dijkstra, K. Preferences in leisure time book reading: A study on the social differentiation in book reading for the Netherlands. Poetics 1999, 26, 203–234. [Google Scholar] [CrossRef]
  63. Mol, S.E.; Bus, A.G. To Read or Not to Read: A Meta-Analysis of Print Exposure From Infancy to Early Adulthood. Psychol. Bull. 2011, 137, 267–296. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  64. Brown, K.W.; Ryan, R.M. The Benefits of Being Present: Mindfulness and Its Role in Psychological Well-Being. J. Personal. Soc. Psychol. 2003, 84, 822–848. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Kabat-Zinn, J. Mindfulness-based interventions in context: Past, present, and future. Clin. Psychol. Sci. Pract. 2003, 10, 144–156. [Google Scholar] [CrossRef]
  66. Méndez Prado, S.M.; Rosado Anastacio, J.A. An assessment of mindfulness intervention as a regular subject in Ecuadorian higher education. Int. J. Adolesc. Youth 2018, 23, 520–529. [Google Scholar] [CrossRef] [Green Version]
  67. Koszycki, D.; Raab, K.; Aldosary, F.; Bradwejn, J. A multifaith spiritually based intervention for generalized anxiety disorder: A pilot randomized trial. J. Clin. Psychol. 2010, 66, 430–441. [Google Scholar] [CrossRef]
  68. Trammel, R. Effectiveness of an MP3 Christian mindfulness intervention on mindfulness and perceived stress. Ment. Health Relig. Cult. 2018, 21, 500–514. [Google Scholar] [CrossRef]
  69. Trammel, R.C.; Park, G.; Karlsson, I. Religiously oriented mindfulness for social workers: Effects on mindfulness, heart rate variability, and personal burnout. J. Relig. Spiritual. Soc. Work 2021, 40, 19–38. [Google Scholar] [CrossRef]
  70. Baltruschat, S.; Cándido, A.; Maldonado, A.; Verdejo-Lucas, C.; Catena-Verdejo, E.; Catena, A. There Is More to Mindfulness Than Emotion Regulation: A Study on Brain Structural Networks. Front. Psychol. 2021, 12, 1–10. [Google Scholar] [CrossRef] [PubMed]
  71. Sajjad, A.; Shahbaz, W. Mindfulness and Social Sustainability: An Integrative Review. Soc. Indic. Res. 2020, 150, 73–94. [Google Scholar] [CrossRef]
  72. Kotzé, M. The influence of psychological capital, self-leadership, and mindfulness on work engagement. S. Afr. J. Psychol. 2018, 48, 279–292. [Google Scholar] [CrossRef] [Green Version]
  73. Dong, X.; Xiang, Y.; Zhao, J.; Li, Q.; Zhao, J.; Zhang, W. How mindfulness affects benign and malicious envy from the perspective of the mindfulness reperceiving model. Scand. J. Psychol. 2020, 61, 436–442. [Google Scholar] [CrossRef]
  74. Mu, L. Effects of mindfulness training on psychological capital, depression, and procrastination of the youth demographic. Iran J. Public Health 2020, 49, 1692–1700. [Google Scholar]
  75. De Barros, V.V.; Kozasa, E.H.; De Souza, I.C.W.; Ronzani, T.M. Validity evidence of the Brazilian version of the mindful attention awareness scale (MAAS). Psicol. Reflex. Crit. 2015, 28, 87–95. [Google Scholar] [CrossRef] [Green Version]
  76. Roche, M.; Haar, J.M.; Luthans, F. The role of mindfulness and psychological capital on the well-being of leaders. J. Occup. Health Psychol. 2014, 19, 476–489. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  77. Ahmed, S.K.; Khan, M.M.; Khan, R.A.; Mujtaba, B.G. The Relationship Between Social Capital and Psychological Well-Being: The Mediating Role of Internet Marketing. Mark. Manag. Innov. 2020, 1, 40–53. [Google Scholar] [CrossRef]
  78. Arnold, M.; Rigotti, T. Is it Getting Better or Worse? Health-Oriented Leadership and Psychological Capital as Resources for Sustained Health in Newcomers. Appl. Psychol. 2020, 70, 709–737. [Google Scholar] [CrossRef]
  79. Avey, J.B.; Luthans, F.; Youssef, C.M. The Additive Value of Positive Psychological Capital in Predicting Work Attitudes and Behaviors. J. Manag. 2010, 36, 430–452. [Google Scholar] [CrossRef] [Green Version]
  80. Avey, J.B.; Wernsing, T.S.; Luthans, F. Can Positive Employees Help Positive Organizational Change? Impact of Psychological Capital and Emotions on Relevant Attitudes and Behaviors. J. Appl. Behav. Sci. 2008, 44, 48–70. [Google Scholar] [CrossRef] [Green Version]
  81. Avey, J.B.; Luthans, F.; Jensen, S.M. Psychological Capital: A Positive resource for combating employees stress and turnover. Hum. Resour. Manag. 2009, 48, 677–693. [Google Scholar] [CrossRef]
  82. Avey, J.B.; Luthans, F.; Smith, R.M.; Palmer, N.F. Impact of positive psychological capital on employee well-being over time. J. Occup. Health Psychol. 2010, 15, 17–28. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Luthans, F.; Avolio, B.J.; Avey, J.B.; Norman, S.M. Positive Psychological Capital: Measurement and Relationship with Performance and Satisfaction Positive Psychological Capital: Measurement and Relationship with performance and satisfaction. Pers. Psychol. 2007, 60, 541–572. [Google Scholar] [CrossRef] [Green Version]
  84. Luthans, F.; Norman, S.M.; Avolio, B.J.; Avey, J.B. The mediating role of psychological capital in the supportive organizational climate—employee performance relationship. J. Organ. Behav. 2008, 29, 219–238. [Google Scholar] [CrossRef] [Green Version]
  85. Luthans, F.; Youssef, C.M.; Rawski, S.L. A Tale of Two Paradigms: The Impact of Psychological Capital and Reinforcing Feedback on Problem Solving and Innovation. J. Organ. Behav. Manag. 2011, 31, 333–350. [Google Scholar] [CrossRef] [Green Version]
  86. Luthans, F. Developing the Psychological Capital of Resiliency. Hum. Resour. Dev. Rev. 2006, 5, 25–44. [Google Scholar] [CrossRef] [Green Version]
  87. Manzano-García, G.; Ayala, J.C. Relationship between psychological capital and psychological well-being of direct support staff of specialist autism services. The mediator role of burnout. Front. Psychol. 2017, 8, 2277. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  88. Maykrantz, S.A.; Langlinais, L.A.; Houghton, J.D.; Neck, C.P. Self-Leadership and Psychological Capital as Key Cognitive Resources for Shaping Health-Protective Behaviors during the COVID-19 Pandemic. Adm. Sci. 2021, 11, 41. [Google Scholar] [CrossRef]
  89. Datu, J.A.D.; Valdez, J.P.M. Psychological capital is associated with higher levels of life satisfaction and school belongingness. Sch. Psychol. Int. 2019, 40, 331–346. [Google Scholar] [CrossRef]
  90. Pathak, D.; Joshi, G. Impact of psychological capital and life satisfaction on organizational resilience during COVID-19: Indian tourism insights. Curr. Issues Tour. 2021, 24, 2398–2415. [Google Scholar] [CrossRef]
  91. Santisi, G.; Lodi, E.; Magnano, P.; Zarbo, R.; Zammitti, A. Relationship between psychological capital and quality of life: The role of courage. Sustainability 2020, 12, 5238. [Google Scholar] [CrossRef]
  92. Luthans, F.; Youssef, C.M.; Sweetman, D.S.; Harms, P.D. Meeting the leadership challenge of employee well-being through relationship Psycap and health PsyCap. J. Leadersh. Organ. Stud. 2013, 20, 118–133. [Google Scholar] [CrossRef]
  93. Lorenz, T.; Beer, C.; Pütz, J.; Heinitz, K. Measuring Psychological Capital: Construction and Validation of the Compound PsyCap Scale (CPC-12). PLoS ONE 2016, 11, e0152892. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  94. Diener, E.; Inglehart, R.; Tay, L. Theory and Validity of Life Satisfaction Scales. Soc. Indic. Res. 2013, 112, 497–527. [Google Scholar] [CrossRef]
  95. Diener, E.; Tay, L.; Oishi, S. Rising Income and the Subjective Well-Being of Nations. J. Personal. Soc. Psychol. 2013, 104, 267–276. [Google Scholar] [CrossRef] [PubMed]
  96. Sato, M.; Jordan, J.S.; Funk, D.C.; Sachs, M.L. Running involvement and life satisfaction: The role of personality. J. Leis. Res. 2018, 49, 1–18. [Google Scholar] [CrossRef]
  97. Heo, J.; Stebbins, R.A.; Kim, J.; Lee, I. Serious Leisure, Life Satisfaction, and Health of Older Adults. Leis. Sci. 2013, 35, 16–32. [Google Scholar] [CrossRef]
  98. Kim, B.; Lee, Y.; Chun, S. An exploratory study examining the relationships between the leisure- related variables and subjective well-being of community residents. Ann. Leis. Res. 2010, 13, 613–629. [Google Scholar] [CrossRef]
  99. Kim, M.; Jasper, A.D.; Lee, J.; Won, H. Work, Leisure, and Life Satisfaction for Employees with Physical Disabilities in South Korea. Appl. Res. Qual. Life 2021. [Google Scholar] [CrossRef]
  100. Diener, E.; Emmons, R.A.; Larsem, R.J.; Griffin, S. The Satisfaction With Life Scale. J. Personal. Assess. 1985, 49, 71–75. [Google Scholar] [CrossRef] [PubMed]
  101. Dirzyte, A.; Perminas, A.; Biliuniene, E. Psychometric properties of satisfaction with life scale (Swls) and psychological capital questionnaire (pcq-24) in the lithuanian population. Int. J. Environ. Res. Public Health 2021, 18, 2608. [Google Scholar] [CrossRef]
  102. Gouveia, V.V.; Milfont, T.L.; da Fonseca, P.N.; de Miranda Coelho, J.A.P. Life satisfaction in Brazil: Testing the psychometric properties of the Satisfaction With Life Scale (SWLS) in five Brazilian samples. Soc. Indic. Res. 2009, 90, 267–277. [Google Scholar] [CrossRef]
  103. Jovanović, V.; Lazić, M.; Gavrilov-Jerković, V. Measuring life satisfaction among psychiatric patients: Measurement invariance and validity of the Satisfaction with Life Scale. Clin. Psychol. Psychother. 2020, 27, 378–383. [Google Scholar] [CrossRef] [PubMed]
  104. Kamei, H.; Ferreira, M.C.; Valentini, F.; Peres, M.F.P.; Kamei, P.T.; Damásio, B.F. Psychological capital questionnaire—short version (PCQ-12): Evidence of validity of the Brazilian version. Psico-USF 2018, 23, 203–214. [Google Scholar] [CrossRef] [Green Version]
  105. Murgić, D.; Rijavec, M.; Miljković, D. Initial validation of the shortened psychological capital uestionnaire (PCQ-12) on Croatian sample. Ekon. Pregl. 2019, 70, 3–21. [Google Scholar] [CrossRef]
  106. Santana-Cárdenas, S.; Viseu, J.; Inmaculada López Núñez, M.; Neves, S.; Jesús, D. Validity and reliability evidence of the Psychological Capital Questionnaire-12 in a sample of Mexican workers. Ann. Psychol. 2018, 34, 562–570. [Google Scholar] [CrossRef]
  107. León-Pérez, J.M.; Antino, M.; León-Rubio, J.M. Adaptation of the short version of the Psychological Capital Questionnaire (PCQ-12) into Spanish/Adaptación al español de la versión reducida del Cuestionario de Capital Psicológico (PCQ-12). Rev. Psicol. Soc. 2017, 32, 196–213. [Google Scholar] [CrossRef]
  108. Brown, K.W.; Ryan, R.M. Mindful Attention Awareness Scale. Mindful Atten. Aware. Scale 2003, 4–5. [Google Scholar] [CrossRef]
  109. Seema, R.; Quaglia, J.T.; Brown, K.W.; Sircova, A.; Konstabel, K.; Baltin, A. The Estonian Mindful Attention Awareness Scale: Assessing Mindfulness Without a Distinct Linguistic Present Tense. Mindfulness 2015, 6, 759–766. [Google Scholar] [CrossRef]
  110. Buz, J.; Gómez-Martínez, Á.M.; Crego, A.; Yela, J.R.; Sánchez-Zaballos, E. Validity Evidence of the Spanish Version of the Mindful Attention Awareness Scale Using the Rasch Measurement Model. Assessment 2021. [Google Scholar] [CrossRef] [PubMed]
  111. Deng, Y.Q.; Li, S.; Tang, Y.Y.; Zhu, L.H.; Ryan, R.; Brown, K. Psychometric properties of the Chinese translation of the mindful attention awareness scale (MAAS). Mindfulness 2012, 3, 10–14. [Google Scholar] [CrossRef]
  112. Nooripour, R.; Ghanbari, N.; Hoseinian, S.; Vakili, Y.; Dobkins, K. Psychometric Validation of the Farsi Version of the Mindful Attention Awareness Scale (MAAS) in a Sample of Iranian Students in the USA. Int. J. Ment. Health Addict. 2021. [Google Scholar] [CrossRef]
  113. Michalak, J.; Heidenreich, T.; Ströhle, G.; Nachtigall, C. Die deutsche version der Mindful Attention and Awareness Scale (MAAS) Psychometrische befunde zu einem achtsamkeitsfragebogen. Z. Klin. Psychol. Psychother. 2008, 37, 200–208. [Google Scholar] [CrossRef]
  114. Jermann, F.; Billieux, J.; Larøi, F.; d’Argembeau, A.; Bondolfi, G.; Zermatten, A.; Van der Linden, M. Mindful Attention Awareness Scale (MAAS): Psychometric Properties of the French Translation and Exploration of Its Relations With Emotion Regulation Strategies. Psychol. Assess. 2009, 21, 506–514. [Google Scholar] [CrossRef]
  115. Şimşek, G.G.; Noyan, F. McDonald’s ω t, Cronbach’s α, and Generalized θ for Composite Reliability of Common Factors Structures. Commun. Stat.—Simul. Comput. 2013, 42, 2008–2025. [Google Scholar] [CrossRef]
  116. Byrne, B.M. Structural Equation Modeling With AMOS; Routledge: New York, NY, USA, 2013; ISBN 9781138797031. [Google Scholar]
  117. Kline, R.B. Principles and Practices of Structural Equation Modelling, 4th ed.; The Guilford Press: New York, NY, USA, 2016; ISBN 9781609182304. [Google Scholar]
  118. Murtaugh, P.A. In defense of P values. Ecology 2014, 95, 811–817. [Google Scholar] [CrossRef] [Green Version]
  119. Richter, N.F.; Sinkovics, R.R.; Ringle, C.M.; Schlägel, C. A critical look at the use of SEM in international business research. Int. Mark. Rev. 2016, 33, 376–404. [Google Scholar] [CrossRef]
  120. Bagozzi, R.P.; Yi, Y. Specification, evaluation, and interpretation of structural equation models. J. Acad. Mark. Sci. 2012, 40, 8–34. [Google Scholar] [CrossRef]
  121. Tabachnick, B.G.; Fidell, L.S. Using Multivariate Statistics; Pearson Education Limited: New York, NY, USA, 2014. [Google Scholar]
  122. Delacre, M.; Lakens, D.; Leys, C. Why psychologists should by default use welch’s t-Test instead of student’s t-Test. Int. Rev. Soc. Psychol. 2017, 30, 92–101. [Google Scholar] [CrossRef] [Green Version]
  123. Sardeshmukh, S.R.; Vandenberg, R.J. Integrating Moderation and Mediation: A Structural Equation Modeling Approach. Organ. Res. Methods 2017, 20, 721–745. [Google Scholar] [CrossRef]
  124. Jose, P. Doing Stats Mediation and Moderation; The Guilford Press: New York, NY, USA; London, UK, 2013; ISBN 9781462508150. [Google Scholar]
  125. Dirzyte, A.; Patapas, A. Positive Organizational Practices, Life Satisfaction, and Psychological Capital in the Public and Private Sectors. Sustainability 2022, 14, 488. [Google Scholar] [CrossRef]
  126. Bajwa, J.; Abai, M.; Couto, S.; Kidd, S.; Dibavar, A.; McKenzie, K. Psychological capital and life satisfaction of refugees in Canada: Evidence from a community-based educational support program. J. Community Psychol. 2019, 47, 504–516. [Google Scholar] [CrossRef]
  127. Bockorny, K.; Youssef-Morgan, C.M. Entrepreneurs’ courage, psychological capital, and life satisfaction. Front. Psychol. 2019, 10, 789. [Google Scholar] [CrossRef] [Green Version]
  128. Zhang, R.; Ewalds-Kvist, B.M.; Li, D.; Jiang, J. Chinese Students’ Satisfaction with Life Relative to Psychological Capital and Mediated by Purpose in Life. Curr. Psychol. 2019, 38, 260–271. [Google Scholar] [CrossRef]
  129. Cheung, R.Y.M.; Lau, E.N.S. Is Mindfulness Linked to Life Satisfaction? Testing Savoring Positive Experiences and Gratitude as Mediators. Front. Psychol. 2021, 12, 591103. [Google Scholar] [CrossRef] [PubMed]
  130. Liang, S.; Dong, M.; Zhao, H.; Song, Y.; Yang, A. Mindfulness and life satisfaction: The moderating effect of self-control and the moderated moderating effect of resilience. Personal. Individ. Dif. 2022, 185, 111241. [Google Scholar] [CrossRef]
  131. Ali, M.; Khan, A.N.; Khan, M.M.; Butt, A.S.; Shah, S.H.H. Mindfulness and study engagement: Mediating role of psychological capital and intrinsic motivation. J. Prof. Cap. Community 2021. [Google Scholar] [CrossRef]
  132. Tu, H.M. Does active leisure participation promote psychological capital through peer support in economically disadvantaged children? PLoS ONE 2020, 15, e0234143. [Google Scholar] [CrossRef]
  133. Kim, A.C.H.; Ryu, J.; Lee, C.; Kim, K.M.; Heo, J. Sport Participation and Happiness Among Older Adults: A Mediating Role of Social Capital. J. Happiness Stud. 2021, 22, 1623–1641. [Google Scholar] [CrossRef]
  134. Chang, W.H.; Chang, J.H.; Chen, L.H. Mindfulness Enhances Change in Athletes’ Well-being: The Mediating Role of Basic Psychological Needs Fulfillment. Mindfulness 2018, 9, 815–823. [Google Scholar] [CrossRef]
  135. Chen, L.H.; Wu, C.H.; Chang, J.H. Gratitude and Athletes’ Life Satisfaction: The Moderating Role of Mindfulness. J. Happiness Stud. 2017, 18, 1147–1159. [Google Scholar] [CrossRef] [Green Version]
  136. Luthans, F.; Youssef-Morgan, C.M. Psychological Capital: An Evidence-Based Positive Approach. Annu. Rev. Organ. Psychol. Organ. Behav. 2017, 4, 339–366. [Google Scholar] [CrossRef] [Green Version]
  137. Tomczyk, S.; Altweck, L.; Schmidt, S. How is the way we spend our time related to psychological wellbeing? A cross-sectional analysis of time-use patterns in the general population and their associations with wellbeing and life satisfaction. BMC Public Health 2021, 21, 1858. [Google Scholar] [CrossRef] [PubMed]
  138. Arránz Becker, O.; Lois, D. Competing Pleasures? The Impact of Leisure Time Use on the Transition to Parenthood. J. Fam. Issues 2013, 34, 661–688. [Google Scholar] [CrossRef]
  139. Frederick, D.A.; Sandhu, G.; Morse, P.J.; Swami, V. Correlates of appearance and weight satisfaction in a U.S. National Sample: Personality, attachment style, television viewing, self-esteem, and life satisfaction. Body Image 2016, 17, 191–203. [Google Scholar] [CrossRef] [PubMed]
  140. Wiese, C.W.; Kuykendall, L.; Tay, L. Get active? A meta-analysis of leisure-time physical activity and subjective well-being. J. Posit. Psychol. 2018, 13, 57–66. [Google Scholar] [CrossRef]
  141. Yoon, H.; Lee, W.S.; Kim, K.B.; Moon, J. Effects of leisure participation on life satisfaction in older korean adults: A panel analysis. Int. J. Environ. Res. Public Health 2020, 17, 4402. [Google Scholar] [CrossRef] [PubMed]
  142. Gatersleben, B.; Jackson, T.; Meadows, J.; Soto, E.; Yan, Y.L. Leisure, materialism, well-being and the environment. Rev. Eur. Psychol. Appl. 2018, 68, 131–139. [Google Scholar] [CrossRef]
  143. Lee, H.; Heo, S. Arts and Cultural Activities and Happiness: Evidence from Korea. Appl. Res. Qual. Life 2021, 16, 1637–1651. [Google Scholar] [CrossRef]
  144. Ateca-Amestoy, V.; Ugidos, A. Gender differences in cultural and sports activities attendance: An intra-couple analysis. Appl. Econ. 2021, 53, 6426–6438. [Google Scholar] [CrossRef]
  145. Sharma, B.; Nam, E.W.; Kim, D.; Yoon, Y.M.; Kim, Y.; Kim, H.Y. Role of gender, family, lifestyle and psychological factors in self-rated health among urban adolescents in Peru: A school-based cross-sectional survey. BMJ Open 2016, 6, 1–8. [Google Scholar] [CrossRef] [Green Version]
  146. Hwang, H.; Lee, Y. Effects of Relative Leisure Deprivation between Regions on Life Satisfaction in Koreans: Focusing on Baby Boomers. Int. J. Environ. Res. Public Health 2021, 18, 12905. [Google Scholar] [CrossRef]
  147. Bum, C.H.; Hums, M.A.; Picklesimer, A.; Choi, C. Comparison of the influence of participation in screen golf on self-esteem, loneliness, depression, social isolation, and life satisfaction between people with and without disabilities in Republic of Korea. Phys. Cult. Sport. Stud. Res. 2021, 89, 11–21. [Google Scholar] [CrossRef]
  148. Van der Zwan, P.; Hessels, J.; Rietveld, C.A. Self-employment and satisfaction with life, work, and leisure. J. Econ. Psychol. 2018, 64, 73–88. [Google Scholar] [CrossRef] [Green Version]
  149. Jia, S. Leisure motivation and satisfaction: A text mining of yoga centres, yoga consumers, and their interactions. Sustainability 2018, 10, 4458. [Google Scholar] [CrossRef] [Green Version]
  150. Ahn, B.W.; Song, W.I. A study of differences in leisure satisfaction of leisure activity patterns for South Korean adults. Int. J. Environ. Res. Public Health 2021, 18, 10790. [Google Scholar] [CrossRef]
  151. Hartanto, A.; Lua, V.Y.; Quek, F.Y.; Yong, J.C.; Ng, M.H. A critical review on the moderating role of contextual factors in the associations between video gaming and well-being. Comput. Hum. Behav. Rep. 2021, 4, 100135. [Google Scholar] [CrossRef]
  152. Tooth, L.R.; Moss, K.M.; Mishra, G.D. Screen time and child behaviour and health-related quality of life: Effect of family context. Prev. Med. 2021, 153, 106795. [Google Scholar] [CrossRef]
  153. Chen, N.; Tsai, C.T.L. Rural-Urban Divide and the Social Stratification in Leisure Participation in China: Application of Multiple Hierarchy Stratification Perspective. Appl. Res. Qual. Life 2020, 15, 1535–1548. [Google Scholar] [CrossRef]
  154. Nawijn, J. Determinants of Daily Happiness on Vacation. J. Travel Res. 2011, 50, 559–566. [Google Scholar] [CrossRef]
  155. Vacchiano, M.; Bolano, D. Online and offline leisure, relatedness and psychological distress: A study of young people in Switzerland. Leis. Stud. 2021, 40, 338–351. [Google Scholar] [CrossRef]
  156. Vacchiano, M.; Valente, R. Did the screens win? An autoregressive model linking leisure, relatedness and mental health. Comput. Hum. Behav. 2021, 120, 106755. [Google Scholar] [CrossRef]
Ijerph 19 04121 g001 550
Figure 1. Mediation analysis: path plot in the total sample, the role of psychological capital as a mediator. Fml: spending time with family; Evn: participating in events; PsyCpv: PsyCap overall; PsyCpr: PsyCap relationship; LfS: life satisfaction.
Figure 1. Mediation analysis: path plot in the total sample, the role of psychological capital as a mediator. Fml: spending time with family; Evn: participating in events; PsyCpv: PsyCap overall; PsyCpr: PsyCap relationship; LfS: life satisfaction.
Ijerph 19 04121 g001
Ijerph 19 04121 g002 550
Figure 2. Mediation analysis: path plot in the total sample, the role of mindfulness as a mediator. TVc: watching television; Mnd: mindfulness; LfS: life satisfaction.
Figure 2. Mediation analysis: path plot in the total sample, the role of mindfulness as a mediator. TVc: watching television; Mnd: mindfulness; LfS: life satisfaction.
Ijerph 19 04121 g002
Table
Table 1. Cronbach alphas and McDonald’s omegas for the SWLS, the PCQ-12, and the MAAS.
Table 1. Cronbach alphas and McDonald’s omegas for the SWLS, the PCQ-12, and the MAAS.
ScalesMcDonald’s ω Cronbach’s α
Psychological Capital, overall0.8900.889
Psychological Capital, work0.8930.892
Psychological Capital, relationship0.8910.890
Psychological Capital, health0.8840.882
Mindful Attention Awareness0.8620.859
Satisfaction with Life0.8820.881
Table
Table 2. The data distribution for the SWLS, the PCQ-12, and the MAAS.
Table 2. The data distribution for the SWLS, the PCQ-12, and the MAAS.
ScalesShapiro-WilkpSkewnessSEKurtosisSE
Psychological Capital, overall0.987>0.001−0.3520.1170.3180.234
Psychological Capital, work0.9910.008−0.2540.117−0.1140.234
Psychological Capital, relationship0.986>0.001−0.3680.1180.0240.235
Psychological Capital, health0.9900.004−0.3180.1180.2340.235
Mindful Attention Awareness0.9840.001−0.4650.1340.2860.267
Satisfaction with Life0.987>0.001−0.1220.103−0.5480.206
Table
Table 3. Frequencies of leisure preferences.
Table 3. Frequencies of leisure preferences.
Types of Leisure PreferencesTotal, %Total, nFemale, nMale, n
Spending time in nature51.8730524952
Spending time with family67.5739832668
Spending time with friends40.2323718351
Reading books59.3534931135
Watching TV44.1426020551
Participating in events38.7122819727
Table
Table 4. Bivariate Spearman’s correlations between the types of leisure preferences and age.
Table 4. Bivariate Spearman’s correlations between the types of leisure preferences and age.
Types of Leisure PreferencesNatureFamilyFriendsBooksTVAge
Spending time in nature- 0.017
Spending time with family0.034- −0.092 *
Spending time with friends0.069−0.048- −0.306 **
Reading books0.018−0.129 **0.008- 0.239 **
Watching TV0.016−0.0380.083 *0.224 ***−0.216 **
Participating in events0.036−0.0590.153 ***0.240 ***0.103 *0.117 **
* p < 0.05, ** p < 0.01, *** p < 0.001.
Table
Table 5. Confirmatory factor analysis (CFA): Model fit indices for the PCQ-12, the MAAS, and the SWLS.
Table 5. Confirmatory factor analysis (CFA): Model fit indices for the PCQ-12, the MAAS, and the SWLS.
Factor Modelχ2DfGFICFITLINFIRMSEA [90% CI]SRMR
Psychological capital, overall320.848440.9850.9780.9720.9740.120 [0.108–0.133]0.067
Psychological capital, work255.238540.9890.9860.9830.9830.093 [0.082–0.105]0.056
Psychological capital, relationship124.316350.9900.9870.9840.9840.091 [0.078–0.104]0.054
Psychological capital, health506.283540.9750.9640.9560.9600.140 [0.129–0.151]0.083
Mindful Attention Awareness156.282900.9910.9930.9910.9830.047 [0.034–0.059]0.051
Satisfaction with Life6406.24650.9990.9990.9990.9990.022 [0.000–0.066]0.014
Table
Table 6. The means, standard deviations, and bivariate correlations between the PCQ-12, the MAAS, and the SWLS.
Table 6. The means, standard deviations, and bivariate correlations between the PCQ-12, the MAAS, and the SWLS.
ScalesMeanSD12345
1. Psychological Capital, overall4.4060.792-
2. Psychological Capital, work4.3980.7790.786 ***-
3. Psychological Capital, relationship4.3390.8340.802 ***0.689 ***-
4. Psychological Capital, health4.2200.8090.729 ***0.666 ***0.721 ***-
5. Mindful Attention Awareness4.1890.7660.321 ***0.270 ***0.348 ***0.323 ***-
6. Satisfaction with Life4.2761.3150.469 ***0.387 ***0.470 ***0.422 ***0.199 ***
*** p < 0.001.
Table
Table 7. Bivariate correlations between types of leisure preferences and the PCQ-12, the MAAS, and the SWLS.
Table 7. Bivariate correlations between types of leisure preferences and the PCQ-12, the MAAS, and the SWLS.
ScalesNatureFamilyFriendsBooksTVEvents
1. Psychological Capital, overall0.100 *0.182 ***0.026−0.038−0.189 ***0.107 *
2. Psychological Capital, work0.0900.173 ***−0.0570.019−0.0900.117 *
3. Psychological Capital, relationship0.106 *0.239 ***0.006−0.077−0.158 **0.063
4. Psychological Capital, health0.118 *0.133 **−0.003−0.051−0.140 **0.056
5. Mindful Attention Awareness0.0270.064−0.026−0.027−0.147 **0.013
6. Satisfaction with Life0.0140.185 ***0.059−0.007−0.0810.108 *
* p < 0.05, ** p < 0.01, *** p < 0.001.
Table
Table 8. Comparison (Welch’s t-test) of life satisfaction, mindfulness, and psychological capital in groups of respondents who prefer and do not prefer TV.
Table 8. Comparison (Welch’s t-test) of life satisfaction, mindfulness, and psychological capital in groups of respondents who prefer and do not prefer TV.
VariablesLeisure TypesMeanSDtdfpMean DifferenceSE DifferenceCohen’s d
Life satisfactionNo TV4.3931.2452.367484.5970.0180.2690.1140.204
TV4.1241.393
MindfulnessNo TV4.3030.7243.115294.6070.0020.2640.0850.348
TV4.0380.795
PsyCap overallNo TV4.5450.7514.187375.429<0.0010.3220.0770.411
TV4.2230.817
PsyCap workNo TV4.4660.7612.042379.9020.0420.1570.0770.201
TV4.3090.805
PsyCap relationshipNo TV4.4590.7863.334366.978<0.0010.2720.0820.329
TV4.1870.869
PsyCap healthNo TV4.3340.8203.430401.235<0.0010.2670.0780.335
TV4.0670.774
Table
Table 9. Comparison (Welch’s t-test) of life satisfaction, mindfulness, and psychological capital in groups of respondents who prefer and do not prefer participation in events.
Table 9. Comparison (Welch’s t-test) of life satisfaction, mindfulness, and psychological capital in groups of respondents who prefer and do not prefer participation in events.
VariablesLeisure TypesMeanSDtdfpMean DifferenceSE DifferenceCohen’s d
Life satisfactionNot Events4.1711.311−2.443443.7010.015−0.2800.114−0.213
Events4.4501.311
MindfulnessNot Events4.1760.741−0.303230.2940.762−0.0270.090−0.035
Events4.2030.810
PsyCap overallNot Events4.3370.801−2.397346.4220.017−0.1870.078−0.238
Events4.5240.773
PsyCap workNot Events4.3230.789−2.620348.5860.009−0.2010.077−0.260
Events4.5240.757
PsyCap relationshipNot Events4.2920.849−1.634356.0690.103−0.1330.082−0.162
Events4.4260.800
PsyCap healthNot Events4.1720.834−1.596360.5740.111−0.1260.079−0.158
Events4.2990.765
Table
Table 10. Comparison (Welch’s t-test) of life satisfaction, mindfulness, and psychological capital in groups of respondents who prefer and do not prefer spending leisure time in nature.
Table 10. Comparison (Welch’s t-test) of life satisfaction, mindfulness, and psychological capital in groups of respondents who prefer and do not prefer spending leisure time in nature.
VariablesLeisure TypesMeanSDtdfpMean DifferenceSE DifferenceCohen’s d
Life satisfactionNot nature4.2541.336−0.350549.2660.727−0.0390.112−0.030
Nature4.2931.299
MindfulnessNot nature4.1310.809−1.140291.3780.255−0.0980.086−0.128
Nature4.2290.732
PsyCap overallNot nature4.2970.799−2.669415.5950.008−0.2050.077−0.259
Nature4.5010.783
PsyCap workNot nature4.3270.792−1.765412.7110.078−0.1340.076−0.172
Nature4.4610.773
PsyCap relationshipNot nature4.2360.832−2.445413.6610.015−0.1970.081−0.238
Nature4.4330.826
PsyCap healthNot nature4.1010.789−2.827417.9450.005−0.2210.078−0.275
Nature4.3210.818
Table
Table 11. Comparison (Welch’s t-test) of life satisfaction, mindfulness, and psychological capital in groups of respondents who prefer and do not prefer spending leisure time with family.
Table 11. Comparison (Welch’s t-test) of life satisfaction, mindfulness, and psychological capital in groups of respondents who prefer and do not prefer spending leisure time with family.
VariablesLeisure TypesMeanSDtdfpMean DifferenceSE DifferenceCohen’s d
Life satisfactionNot family3.8511.381−5.154314.770<0.001−0.6260.121−0.477
Family4.4771.237
MindfulnessNot family4.1070.795−1.111150.4620.268−0.1080.097−0.140
Family4.2150.755
PsyCap overallNot family4.1930.846−3.647 232.232<0.001−0.3110.085−0.388
Family4.5040.753
PsyCap workNot family4.2000.783−3.518 244.616 <0.001−0.2870.082−0.371
Family4.4870.768
PsyCap relationshipNot family4.0640.843−4.632237.296<0.001−0.4030.087−0.491
Family4.4670.798
PsyCap healthNot family4.0760.908−2.311215.5920.022−0.2090.090−0.250
Family4.2850.755
Table
Table 12. Multiple regression model, the dependent variables are life satisfaction, mindfulness, and psychological capital, and the predictors are leisure preferences.
Table 12. Multiple regression model, the dependent variables are life satisfaction, mindfulness, and psychological capital, and the predictors are leisure preferences.
Dependent
Variable		Predictors/
Models		Unstandardized
Coefficients		Standardized
Coefficients		tSig.RR2Adjusted R2FSig.
BStd. ErrorBeta
Life Satisfaction1 (Constant)3.8620.096 40.3440.0000.2170.0470.04527.433
(1,555)		<0.001
Spend time with family0.1040.0200.2175.2380.000
2 (Constant)3.7190.107 34.8020.0000.2490.0620.05818.205
(2,555)		<0.001
Spend time with family0.1100.0200.2295.5370.000
Participate in events0.0620.0210.1212.9330.003
3 (Constant)3.8190.116 32.8140.0000.2630.0690.06413.728
(3,555)		<0.001
Spend time with family0.1080.0200.2255.4580.000
Participate in events0.0650.0210.1273.0710.002
Watch TV−0.0430.020−0.088−2.1310.034
Mindfulness1 (Constant)4.2940.055 77.3830.0000.1620.0260.0238.775
(1,327)		0.003
Watch TV−0.0450.015−0.162−2.9620.003
PsyCap overall1 (Constant)4.5340.049 91.7180.0000.1900.0360.03416.072
(1,428)		<0.001
Watch TV−0.0570.014−0.190−4.0090.000
2 (Constant)4.3230.073 59.2280.0000.2630.0690.06515.878
(2,428)		<0.001
Watch TV−0.0570.014−0.192−4.1020.000
Spend time with family0.0530.0140.1823.8920.000
3 (Constant)4.2360.079 53.6680.0000.2930.0860.07913.309
(3,428)		<0.001
Watch TV−0.0580.014−0.195−4.2030.000
Spend time with family0.0560.0140.1934.1410.000
Participate in events0.0410.0150.1292.7700.006
4 (Constant)4.1320.087 47.3430.0000.3180.1010.09311.932
(4,428)		<0.001
Watch TV−0.0580.014−0.195−4.2350.000
Spend time with family0.0550.0130.1894.0830.000
Participate in events0.0430.0150.1372.9550.003
Spend time in nature0.0370.0140.1242.6860.008
Table
Table 13. Multiple regression model, the dependent variables are life satisfaction, mindfulness, and psychological capital, and the predictors are leisure preferences.
Table 13. Multiple regression model, the dependent variables are life satisfaction, mindfulness, and psychological capital, and the predictors are leisure preferences.
Dependent
Variable		Predictors/
Models		Unstandardized
Coefficients		Standardized
Coefficients		tSig.RR2Adjusted R2FSig.
BStd. ErrorBeta
Life SatisfactionMales
1 (Constant)4.0610.194 20.9810.0000.2090.0440.0344.336
(1,96)		0.040
Spend time in nature0.1060.0510.2092.0820.040
Females
1 (Constant)3.8340.105 36.3890.0000.2300.0530.05125.229
(1,451)		0.000
Spend time with family0.1090.0220.2305.0230.000
2 (Constant)3.6630.118 31.0820.0000.2710.0730.06917.736
(2,451)		0.000
Spend time with family0.1150.0220.2435.3310.000
Participate in events0.0720.0230.1423.1230.002
MindfulnessMales
1 (Constant)3.8020.145 26.2030.0000.3300.1090.0936.722
(1,56)		0.012
Read books0.1070.0410.3302.5930.012
Females
1 (Constant)4.3150.058 74.3370.0000.1540.0240.0206.397
(1,265)		0.012
Watch TV−0.0420.016−0.154−2.5290.012
PsyCap overallMales
1 (Constant)4.1010.190 21.5390.0000.2650.0700.0585.902
(1,79)		0.017
Spend time with family0.0960.0390.2652.4290.017
2 (Constant)3.8700.214 18.0900.0000.3530.1240.1025.466
(2,79)		0.006
Spend time with family0.1150.0390.3192.9120.005
Read books0.0880.0400.2382.1790.032
Females
1 (Constant)4.5250.051 88.1500.0000.2120.0450.04216.099
(1,343)		0.000
Watch TV−0.0590.015−0.212−4.0120.000
2 (Constant)4.4400.059 75.5420.000
Watch TV−0.0610.015−0.217−4.1480.0000.2600.0680.06212.401
(2,343)		0.000
Participate in events0.0440.0150.1512.8910.004
3 (Constant)4.2540.083 51.2490.0000.3060.0940.08611.731
(3,343)		0.000
Watch TV−0.0600.014−0.214−4.1440.000
Participate in events0.0480.0150.1633.1390.002
Spend time with family0.0440.0140.1623.1230.002
4 (Constant)4.1610.093 44.8110.0000.3260.1060.09610.087
(4,343)		0.000
Watch TV−0.0600.014−0.213−4.1470.000
Participate in events0.0500.0150.1703.2990.001
Spend time with family0.0440.0140.1603.1090.002
Spend time in nature0.0310.0140.1122.1830.030
Table
Table 14. Mediation analysis results in the total sample of respondents: the role of psychological capital as a mediator.
Table 14. Mediation analysis results in the total sample of respondents: the role of psychological capital as a mediator.
PathsCoeff.Std. Errorz-Valuep95% CI
Lower Upper
Direct effects
Family →Life Satisfaction0.3750.1103.405<0.0010.1590.592
Events →Life Satisfaction0.1800.1041.7340.0830.0240.384
Indirect effects
Family →PsyCap overall →Life Satisfaction0.1320.0502.6460.0080.0340.230
Family →PsyCap relationship →Life Satisfaction0.1340.0532.5420.0110.0310.237
Events →PsyCap overall →Life Satisfaction0.0930.0412.2440.0250.0120.174
Events →PsyCap relationship →Life Satisfaction0.0580.0331.7360.0830.0070.123
Total effects
Family →Life Satisfaction0.6420.1165.544<0.0010.4150.869
Events →Life Satisfaction0.3310.1112.9800.0030.1130.549
Total indirect effects
Family →Life Satisfaction0.2660.0644.191<0.0010.1420.391
Events →Life Satisfaction0.1510.0582.6050.0090.0370.265
Residual covariances
PsyCap overall <-> PsyCap relationship0.5010.03813.1110.0000.4260.576
Life satisfaction R2 = 0.254; PsyCap overall R2 = 0.049; PsyCap relationship R2 = 0.055.
Note. Delta method standard errors, normal theory confidence intervals, ML estimator.
Table
Table 15. Mediation analysis results in the total sample of respondents: the role of mindfulness as a mediator.
Table 15. Mediation analysis results in the total sample of respondents: the role of mindfulness as a mediator.
PathsCoeff.Std. Errorz-Valuep95% CI
Lower Upper
Direct effects
TV →Life Satisfaction−0.1900.114−1.6710.095−0.413−0.033
Indirect effects
TV →Mindfulness →Life Satisfaction−0.0810.035−2.2990.022−0.150−0.012
Total effects
TV →Life Satisfaction−0.2710.112−2.4200.016−0.490−0.052
Life satisfaction R2 = 0.043; Mindfulness R2 = 0.028.
Note. Delta method standard errors, normal theory confidence intervals, ML estimator.
Table
Table 16. Multiple regression model, the dependent variables are leisure preferences, and the predictors are life satisfaction, mindfulness, and psychological capital.
Table 16. Multiple regression model, the dependent variables are leisure preferences, and the predictors are life satisfaction, mindfulness, and psychological capital.
Dependent
Variable		Predictors/
Models		Unstandardized
Coefficients		Standardized
Coefficients		tSig.RR2Adjusted R2FSig.
BStd. ErrorBeta
Spending time with Family1 (Constant)2.1930.527 4.1650.0000.2450.0600.05716.510 (1,259)<0.001
Life satisfaction0.4690.1160.2454.0630.000
Watching Television 1 (Constant)5.0950.958 5.3210.0000.1780.0320.0288.428 (1,258)0.004
PsyCap relationship−0.6220.214−0.178−2.9030.004
Participating in Events1 (Constant)−0.3850.961 −0.4010.6890.1390.0190.0155.066 (1,259)0.025
PsyCap overall0.4800.2130.1392.2510.025
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Dirzyte, A.; Patapas, A.; Perminas, A. Associations between Leisure Preferences, Mindfulness, Psychological Capital, and Life Satisfaction. Int. J. Environ. Res. Public Health 2022, 19, 4121. https://doi.org/10.3390/ijerph19074121

AMA Style

Dirzyte A, Patapas A, Perminas A. Associations between Leisure Preferences, Mindfulness, Psychological Capital, and Life Satisfaction. International Journal of Environmental Research and Public Health. 2022; 19(7):4121. https://doi.org/10.3390/ijerph19074121

Chicago/Turabian Style

Dirzyte, Aiste, Aleksandras Patapas, and Aidas Perminas. 2022. "Associations between Leisure Preferences, Mindfulness, Psychological Capital, and Life Satisfaction" International Journal of Environmental Research and Public Health 19, no. 7: 4121. https://doi.org/10.3390/ijerph19074121

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop