Relationship between COVID-19 Pandemic-Related Life Behavior, Dispositional Mindfulness, and Psychological Health: Evidence from a Sample of Japanese Working Adults
Abstract
:1. Introduction
2. Methods
2.1. Participants and Procedures
2.2. Measures
2.2.1. COVID-19-Related Daily Life Behavior
2.2.2. Dispositional Mindfulness
2.2.3. Perceived Stress
2.2.4. Anxiety
2.2.5. Depression
2.3. Statistical Analyses
3. Results
3.1. COVID-19-Related Daily Life Behavior and Pre–Post Comparisons
3.2. Scores from Psychological Scales and Correlations between Scales
3.3. Correlations between Characteristics of Participants and Daily Life Behavior
3.4. Correlations between COVID-19-Related Daily Life Behavior and Psychological Scales
3.5. Moderating Effects of Mindfulness
4. Discussion
4.1. COVID-19-Related Changes in Daily Life Behavior
4.2. Altered Daily Life Behavior and Psychological Health
4.3. Protective Role of Mindfulness for Psychological Health
4.4. Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Kabat-Zinn, J. Wherever You Go, There You Are: Mindfulness Meditation in Everyday Life; Hyperion: New York, NY, USA, 1994. [Google Scholar]
- Lutz, A.; Greischar, L.L.; Rawlings, N.B.; Ricard, M.; Davidson, R.J. Long-term meditators self-induce high-amplitude gamma synchrony during mental practice. Proc. Natl. Acad. Sci. USA 2004, 101, 16369–16373. [Google Scholar] [CrossRef] [PubMed]
- Slagter, H.A.; Davidson, R.J.; Lutz, A. Mental training as a tool in the neuroscientific study of brain and cognitive plasticity. Front. Hum. Neurosci. 2011, 5, 17. [Google Scholar] [CrossRef] [PubMed]
- Kabat-Zinn, J.; Lipworth, L.; Burney, R. The clinical use of mindfulness meditation for the self-regulation of chronic pain. J. Behav. Med. 1985, 8, 163–190. [Google Scholar] [CrossRef] [PubMed]
- Segal, Z.V.; Williams, J.M.G.; Teasdale, J.D. Mindfulness-Based Cognitive Therapy for Depression: A New Approach to Preventing Relapse; Guilford: New York, NY, USA, 2002. [Google Scholar]
- Creswell, J.D. Mindfulness interventions. Annu. Rev. Psychol. 2017, 68, 491–516. [Google Scholar] [CrossRef]
- Miyata, H.; Okanoya, K.; Kawai, N. Mindfulness and psychological status of Japanese yoga practitioners: A cross-sectional study. Mindfulness 2015, 6, 560–571. [Google Scholar] [CrossRef]
- Tomlinson, E.R.; Yousaf, O.; Vittersø, A.D.; Jones, L. Dispositional mindfulness and psychological health: A systematic review. Mindfulness 2018, 9, 23–43. [Google Scholar] [CrossRef]
- Rau, H.K.; Williams, P.G. Dispositional mindfulness: A critical review of construct validation research. Personal. Individ. Differ. 2016, 93, 32–43. [Google Scholar] [CrossRef]
- Baer, R.A.; Smith, G.T.; Hopkins, J.; Krietemeyer, J.; Toney, L. Using self-report assessment methods to explore facets of mindfulness. Assessment 2006, 13, 27–45. [Google Scholar] [CrossRef]
- Sugiura, Y.; Sugiura, T. Mindfulness as a moderator in the relation between income and psychological well-being. Front. Psychol. 2018, 9, 1477. [Google Scholar] [CrossRef]
- Bentalge, E.; Ammar, A.; How, D.; Ahmed, M.; Trabelsi, K.; Chtourou, H.; Brach, M. Practical recommendations for maintaining active lifestyle during the COVID-19 pandemic: A systematic literature review. Int. J. Environ. Res. Public Health 2020, 17, 6265. [Google Scholar] [CrossRef]
- Caroppo, E.; Mazza, M.; Sannella, A.; Marano, G.; Avallone, C.; Claro, A.E.; Janiri, D.; Moccia, L.; Janiri, L.; Sani, G. Will nothing be the same again? Changes in lifestyle during COVID-19 pandemic and consequences on mental health. Int. J. Environ. Res. Public Health 2021, 18, 8433. [Google Scholar]
- Meyer, J.; McDowell, C.; Lansing, J.; Brower, C.; Smith, L.; Tully, M.; Herring, M. Changes in physical activity and sedentary behavior in response to COVID-19 and their associations with mental health in 3052 US adults. Int. J. Environ. Res. Public Health 2020, 17, 6469. [Google Scholar] [CrossRef]
- Van Zoonen, W.; Sivunen, A.E. The impact of remote work and mediated communication frequency on isolation and psychological distress. Eur. J. Work Organ. Psychol. 2022, 31, 610–621. [Google Scholar] [CrossRef]
- Blustein, D.L.; Guarino, P.A. Work and unemployment in the time of COVID-19: The existential experience of loss and fear. J. Humanist. Psychol. 2020, 60, 702–709. [Google Scholar] [CrossRef]
- Japan Ministry of Land, Infrastructure and Transport. Impacts of the COVID-19 Pandemic on Daily Life Behavior, Evaluations of Life Behavior, and Their Changes: Results of a Survey on Daily Life Behavior Associated with the COVID-19 Pandemic; Japan Ministry of Land, Infrastructure and Transport: Tokyo, Japan, 2020; pp. 1–70. (In Japanese)
- Okada, J.; Deguchi, A. Introduction of telework during the first state of emergency of COVID-19 and after its lifting based on questionnaire survey on daily life behavior in 2020. J. City Plan. Inst. Jpn. 2021, 56, 913–920. (In Japanese) [Google Scholar] [CrossRef]
- Ishikawa, H.; Kamoda, S.; Chen, J.; Yamagami, A.; Miyata, H. Psychological health in undergraduates under the COVID-19 pandemic and a protecting role of mindfulness: Focusing on lifestyles and their changes. J. Health Psychol. Res. 2022, 35, 53–61. (In Japanese) [Google Scholar] [CrossRef]
- Lakhan, R.; Agrawal, A.; Sharma, M. Prevalence of depression, anxiety, and stress during COVID-19 pandemic. J. Neurosci. Rural. Pract. 2020, 11, 519–525. [Google Scholar] [CrossRef]
- Taylor, S.; Landry, C.A.; Paluszek, M.M.; Fergus, T.A.; McKay, D.; Asmundson, G.J.G. COVID stress syndrome: Concept, structure, and correlates. Depress. Anxiety 2020, 37, 706–714. [Google Scholar] [CrossRef]
- Zhang, C.; Ye, M.; Fu, Y.; Yang, M.; Luo, F.; Yuan, J.; Tao, Q. The psychological impact of the COVID-19 pandemic on teenagers in China. J. Adolesc. Health 2020, 67, 747–755. [Google Scholar] [CrossRef]
- Alzueta, E.; Perrin, P.; Baker, F.C.; Caffarra, S.; Ramos-Usuga, D.; Yuksel, D.; Arango-Lasprilla, J.C. How the COVID-19 pandemic has changed our lives: A study of psychological correlates across 59 countries. J. Clin. Psychol. 2021, 77, 556–570. [Google Scholar] [CrossRef]
- Targa, A.D.S.; Benítez, I.D.; Moncusí-Moix, A.; Arguimbau, M.; de Batlle, J.; Dalmases, M.; Barbé, F. Decrease in sleep quality during COVID-19 outbreak. Sleep Breath. 2021, 25, 1055–1061. [Google Scholar] [CrossRef] [PubMed]
- Kecojevic, A.; Basch, C.H.; Sullivan, M.; Davi, N.K. The impact of the COVID-19 epidemic on mental health of undergraduate students in New Jersey, cross-sectional study. PLoS ONE 2020, 15, e0239696. [Google Scholar] [CrossRef] [PubMed]
- Smith, L.; Jacob, L.; Trott, M.; Yakkundi, A.; Butler, L.; Barnett, Y.; Armstrong, N.C.; McDermott, D.; Schuch, F.; Meyer, J.; et al. The association between screen time and mental health during COVID-19: A cross sectional study. Psychiatry Res. 2020, 292, 113333. [Google Scholar] [CrossRef] [PubMed]
- Yomoda, K. Concerns and stress caused by the novel coronavirus disease (COVID-19) pandemic: A quantitative text analysis of Twitter data. Jpn. J. Phys. Educ. Health Sport Sci. 2020, 65, 757–774. (In Japanese) [Google Scholar] [CrossRef]
- Marshall, G.W.; Michaels, C.E.; Mulki, J.P. Workplace isolation: Exploring the construct and its measurements. Psychol. Mark. 2007, 24, 195–223. [Google Scholar] [CrossRef]
- Racine, S.; Miller, A.; Mehak, A.; Trolio, V. Examining risk and protective factors for psychological health during the COVID-19 pandemic. Anxiety Stress Coping 2022, 35, 124–140. [Google Scholar] [CrossRef]
- Smirmaul, B.P.C.; Chamon, R.F.; de Moraes, F.M.; Rozin, G.; Moreira, A.S.B.; de Almeida, R.; Guimarães, S.T. Lifestyle medicine during (and after) the COVID-19 pandemic. Am. J. Lifestyle Med. 2020, 15, 60–67. [Google Scholar] [CrossRef]
- Widha, L.; Rahmat, H.K.; Basri, A.S.H. A review of mindfulness therapy to improve psychological well-being during the COVID-19 pandemic. Proc. Int. Conf. Sci. Eng. 2021, 4, 383–386. [Google Scholar]
- Al-Refae, M.; Al-Refae, A.; Munroe, M.; Sardella, N.A.; Ferrari, M. A self-compassion and mindfulness-based cognitive mobile intervention (Serene) for depression, anxiety, and stress: Promoting adaptive emotional regulation and wisdom. Front. Psychol. 2021, 12, 648087. [Google Scholar] [CrossRef]
- Roemer, A.; Sutton, A.; Medvedev, O.N. The role of dispositional mindfulness in employee readiness for change during the COVID-19 pandemic. J. Organ. Chang. Manag. 2021, 34, 917–928. [Google Scholar] [CrossRef]
- Sbrilli, M.D.; Haigler, K.; Laurent, H.K. The indirect effect of parental intolerance of uncertainty on perinatal mental health via mindfulness during COVID-19. Mindfulness 2021, 12, 1999–2008. [Google Scholar] [CrossRef]
- Ikeno, S. Nihon ni Okeru Mindfulness No Tenbo [Perspectives of Mindfulness in Japan]. Jpn. J. Hum. Welf. Stud. 2014, 7, 7–11. (In Japanese) [Google Scholar]
- Peters, J. The Art of Japanese Living: Bring Mindfulness, Joy and Simplicity into Your Life; Summersdale Publishers: Chichester, UK, 2019. [Google Scholar]
- Miyata, H.; Kobayashi, D.; Sonoda, A.; Motoike, H.; Akatsuka, S. Mindfulness and psychological health in practitioners of Japanese martial arts: A cross-sectional study. BMC Sports Sci. Med. Rehabil. 2020, 12, 75. [Google Scholar] [CrossRef]
- Wakashima, K.; Asai, K.; Kobayashi, D.; Koiwa, K.; Kamoshida, S.; Sakuraba, M. The Japanese version of the Fear of COVID-19 scale: Reliability, validity, and relation to coping behavior. PLoS ONE 2020, 15, e0241958. [Google Scholar] [CrossRef]
- Fujishima, Y.; Takahashi, S.; Erikawa, S.; Yamada, K. Reliability and factor validity of the Japanese version of the “Regret and Maximization Scale” in voluntary panel Web surveys. Jpn. Psychol. Res. 2018, 89, 387–395. (In Japanese) [Google Scholar] [CrossRef]
- Smyth, J.D.; Dillman, D.A.; Christian, L.M.; Stern, M.J. Comparing check-all and forced-choice question formats in Web surveys. Public Opin. Q. 2006, 70, 66–77. [Google Scholar] [CrossRef]
- Japan Ministry of Health, Labour and Welfare. Summary of Basic Survey on National Life in 2021; Japan Ministry of Health, Labour and Welfare: Tokyo, Japan, 2022. (In Japanese)
- Sugiura, Y.; Sato, A.; Ito, Y.; Murakami, H. Development and validation of the Japanese version of the Five Facet Mindfulness Questionnaire. Mindfulness 2012, 3, 85–94. [Google Scholar] [CrossRef]
- Cohen, S.; Kamarck, T.; Mermelstein, R. A global measure of perceived stress. J. Health Soc. Behav. 1983, 24, 385–396. [Google Scholar] [CrossRef]
- Sumi, K. Reliability and validity of the Japanese version of the Perceived Stress Scale. Jpn. J. Health Psychol. 2006, 19, 44–53. (In Japanese) [Google Scholar] [CrossRef]
- Spielberger, C.D.; Gorsuch, R.L.; Lushene, R.; Vagg, P.R.; Jacobs, G.A. State-Trait Anxiety Inventory for Adults; Consulting Psychologists Press: Palo Alto, CA, USA, 1983. [Google Scholar]
- Shimizu, H.; Imae, K. State-Trait Anxiety Inventory no Nihongo-Ban (Daigakusei-Yo) No Sakusei [Development of the Japanese version of the State-Trait Anxiety Inventory for University Students]. Jpn. J. Educ. Psychol. 1981, 29, 348–353. (In Japanese) [Google Scholar]
- Radloff, L.S. The CES-D Scale: A self-report depression scale for research in the general population. Appl. Psychol. Meas. 1977, 1, 385–401. [Google Scholar] [CrossRef]
- Shima, S.; Shikano, T.; Kitamura, T.; Asai, M. Atarashii Yokuutsu-Sei Jikohyoka Syakudo ni Tsuite [New Self-Rating Scales for Depression]. Seishin Igaku (Clin. Psychiatry) 1985, 27, 717–723. (In Japanese) [Google Scholar]
- Shimizu, H. An introduction to the statistical free software HAD: Suggestions to improve teaching, learning and practice data analysis. J. Media Inf. Commun. 2016, 1, 59–73. (In Japanese) [Google Scholar]
- Coughlin, S.S. Recall bias in epidemiologic studies. J. Clin. Epidemiol. 1990, 43, 87–91. [Google Scholar] [CrossRef] [PubMed]
- Cohen, J. Statistical Power Analysis for the Behavioral Sciences, 2nd ed.; Lawrence Erlbaum Associates: Hillsdale, NJ, USA, 1988. [Google Scholar]
- Liao, Y.; Shibata, A.; Ishii, K.; Koohsari, M.J.; Oka, K. Cross-sectional and prospective associations of neighbourhood environmental attributes with screen time in Japanese middle-aged and older adults. BMJ Open 2018, 8, S550. [Google Scholar] [CrossRef]
- Hong, W.; Liu, R.D.; Ding, Y.; Fu, X.; Zhen, R.; Sheng, X. Social media exposure and college students’ mental health during the outbreak of COVID-19: The mediating role of rumination and the moderating role of mindfulness. Cyberpsychol. Behav. Soc. Netw. 2021, 24, 282–287. [Google Scholar] [CrossRef]
- Himes, L.; Hubbard, N.A.; Maruthy, G.B.; Gallagher, J.; Turner, M.P.; Rypma, B. The relationship between trait mindfulness and emotional reactivity following mood manipulation. Mindfulness 2021, 12, 170–185. [Google Scholar] [CrossRef]
- Yalçın, I.; Can, N.; Çalışır, O.M.; Yalçın, S.; Çolak, B. Latent profile analysis of COVID-19 fear, depression, anxiety, stress, mindfulness, and resilience. Curr. Psychol. 2021, 41, 459–469. [Google Scholar] [CrossRef]
- Boals, A.; Banks, J.B. Stress and cognitive functioning during a pandemic: Thoughts from stress researchers. Psychol. Trauma Theory Res. Pract. Policy 2020, 12, S255–S257. [Google Scholar] [CrossRef]
- Behan, C. The benefits of meditation and mindfulness practices during times of crisis such as COVID-19. Ir. J. Psychol. Med. 2020, 37, 256–258. [Google Scholar] [CrossRef]
Characteristics of Participants | Proportion (%) |
---|---|
Sex | |
Male | 68.96% |
Female | 31.04% |
Region | |
Hokkaidō | 3.92% |
Tōhoku | 4.34% |
Kantō | 41.95% |
Chūbu | 17.16% |
Kansai (Kinki) | 18.54% |
Chūgoku | 5.72% |
Shikoku | 2.33% |
Kyūshū & Okinawa | 6.04% |
Marital status | |
Unmarried | 33.26% |
Married | 57.52% |
Bereaved | 0.21% |
Divorced | 9.00% |
Employment status | |
Self-employed/family worker | 13.67% |
Full-time worker | 68.96% |
Part-time worker | 16.00% |
Others | 1.38% |
Household income level | |
Below JPA 2,000,000 Japanese | 7.84% |
Between JPA 2,000,000 and JPA 4,990,000 | 29.56% |
Between JPA 5,000,000 and JPA 8,990,000 | 38.24% |
Above JPA 9,000,000 | 24.36% |
N people per household | |
1 (Min) | 22.78% |
2 | 21.61% |
3 | 24.58% |
4 | 22.78% |
5 | 6.04% |
6 | 1.59% |
7 (Max) | 0.64% |
Daily practice of mindfulness/meditation | |
Yes | 8.47% |
No | 91.53% |
Daily Life Behavior | Pre-Pandemic | Post-Pandemic | Pre–Post Comparison | ||
---|---|---|---|---|---|
M (SD) | M (SD) | t (p) | Cohen’s d | ||
Spent at home | 7.58 (3.84) | 8.70 (4.54) | 11.123 (<0.001 ***) | 0.27 | |
Spent indoors other than at home | 6.94 (3.91) | 6.17 (4.05) | −8.971 (<0.001 ***) | −0.19 | |
Spent outdoors | 3.30 (3.33) | 2.89 (3.16) | −8.229 (<0.001 ***) | −0.13 | |
Sleeping | 6.54 (1.12) | 6.58 (1.15) | 2.397 (0.017 *) | 0.04 | |
Time use | Using a PC | 4.02 (3.22) | 4.18 (3.28) | 3.452 (<0.001 ***) | 0.05 |
(hours per day) | Using a smartphone | 1.72 (1.49) | 1.88 (1.63) | 6.354 (<0.001 ***) | 0.11 |
Engaging with social media | 0.59 (0.73) | 0.63 (0.81) | 3.196 (0.0014 **) | 0.05 | |
Engaging in work at home | 0.52 (1.77) | 1.50 (2.89) | 11.268 (<0.001 ***) | 0.41 | |
Engaging in work at places other than at home | 5.47 (3.99) | 4.89 (4.00) | −7.319 (<0.001 ***) | −0.15 | |
Engaging in activities other than work | 1.44 (1.44) | 1.34 (1.38) | −3.621 (<0.001 ***) | −0.07 | |
Anticipation of infection | 3.35 (2.56) | 5.97 (2.48) | 24.974 (<0.001 ***) | 1.04 | |
Media exposure | 3.99 (2.63) | 6.22 (2.26) | 21.741 (<0.001 ***) | 0.91 | |
Well-regulated life | 6.07 (2.28) | 6.26 (2.24) | 3.615 (<0.001 ***) | 0.08 | |
Self-evaluation | Enough sleep | 6.02 (2.17) | 6.13 (2.22) | 2.855 (0.004 **) | 0.05 |
Smoothness of work | 6.00 (2.13) | 5.55 (2.25) | −7.881 (<0.001 ***) | −0.21 | |
Smoothness of nonwork activities | 5.52 (2.30) | 5.15 (2.32) | −5.535 (<0.001 ***) | −0.16 | |
Communication at work | 6.03 (2.06) | 5.67 (2.14) | −7.020 (<0.001 ***) | −0.17 | |
Communication with family | 6.29 (2.16) | 6.38 (2.23) | 2.057 (0.040 *) | 0.04 |
Psychological Scale | M (SD) | Correlation Coefficient (r) | |||||||
---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | ||
1. FFMQ total | 120.24 (13.07) | ― | |||||||
2. Observing | 20.60 (5.65) | 0.259 *** | ― | ||||||
3. Describing | 24.07 (5.13) | 0.792 *** | 0.237 *** | ― | |||||
4. Acting with awareness | 28.62 (5.50) | 0.549 *** | −0.451 *** | 0.263 *** | ― | ||||
5. Nonjudging | 27.43 (5.53) | 0.353 *** | −0.603 *** | 0.065 * | 0.657 *** | ― | |||
6. Nonreactivity | 19.51 (4.68) | 0.549 *** | 0.499 *** | 0.444 *** | −0.161 *** | −0.310 *** | ― | ||
7. PSS total | 27.95 (7.56) | −0.610 *** | 0.011 | −0.484 *** | −0.395 *** | −0.346 *** | −0.314 *** | ― | |
8. STAI-T total | 46.41 (10.70) | −0.589 *** | 0.096 ** | −0.447 *** | −0.463 *** | −0.407 *** | −0.246 *** | 0.780 *** | ― |
9. CES-D total | 16.03 (10.75) | −0.508 *** | 0.129 *** | −0.359 *** | −0.469 *** | −0.377 *** | −0.186 *** | 0.623 *** | 0.787 *** |
Daily Life Behavior | Age | Household Income Level | N People per Household | |
---|---|---|---|---|
Spent at home | −0.019 | −0.102 ** | −0.094 ** | |
Spent indoors other than at home | 0.041 | 0.145 *** | 0.084 * | |
Spent outdoors | 0.003 | 0.036 | <0.001 | |
Sleeping | −0.115 *** | −0.087 ** | −0.016 | |
Time use | Using a PC | 0.025 | 0.099 ** | −0.099 ** |
(hours per day) | Using a smartphone | −0.265 *** | −0.036 | 0.063 |
Engaging with social media | −0.201 *** | 0.022 | 0.054 | |
Engaging in work at home | −0.065 * | 0.129 *** | −0.062 | |
Engaging in work at places other than at home | 0.020 | 0.047 | 0.037 | |
Engaging in activities other than work | −0.092 ** | 0.070 * | −0.077 * | |
Anticipation of infection | −0.046 | 0.046 | 0.075 * | |
Media exposure | 0.039 | 0.099 ** | 0.059 | |
Well-regulated life | 0.061 | 0.105 ** | 0.078 * | |
Self-evaluation | Enough sleep | 0.002 | 0.063 | 0.040 |
Smoothness of work | −0.012 | 0.213 *** | 0.138 *** | |
Smoothness of nonwork activities | −0.087 ** | 0.173 *** | 0.030 | |
Communication at work | 0.006 | 0.113 *** | 0.091 ** | |
Communication with family | −0.002 | 0.204 *** | 0.239 *** |
Daily Life Behavior | Pre–Post Difference-Based Correlation | Post-Pandemic-Based Correlation | |||||||
---|---|---|---|---|---|---|---|---|---|
FFMQ | PSS | STAI-T | CES-D | FFMQ | PSS | STAI-T | CES-D | ||
Spent at home | 0.048 | 0.026 | 0.005 | −0.015 | 0.009 | 0.068 * | 0.039 | 0.028 | |
Spent indoors other than at home | −0.041 | −0.023 | −0.004 | −0.006 | −0.018 | −0.076 * | −0.038 | −0.023 | |
Spent outdoors | −0.025 | −0.019 | −009 | −0.047 | −0.014 | −0.047 | −0.027 | 0.008 | |
Sleeping | 0.003 | 0.009 | 0.008 | −0.003 | −0.014 | −0.031 | −0.022 | −0.037 | |
Time use | Using a PC | 0.035 | 0.011 | −0.030 | −0.041 | 0.007 | 0.008 | 0.031 | 0.021 |
(hours per day) | Using a smartphone | 0.002 | 0.053 | 0.012 | 0.005 | −0.152 *** | 0.115 *** | 0.136 *** | 0.167 *** |
Engaging with social media | −0.022 | 0.043 | 0.032 | 0.044 | −0.043 | 0.087 ** | 0.134 *** | 0.185 *** | |
Engaging in work at home | 0.013 | −0.001 | −0.013 | −0.016 | 0.011 | 0.027 | 0.030 | 0.037 | |
Engaging in work at places other than at home | −0.034 | −0.022 | −0.028 | 0.005 | −0.036 | 0.002 | −0.014 | −0.035 | |
Engaging in activities other than work | −0.010 | −0.042 | −0.046 | −0.047 | 0.069 * | −0.085 ** | −0.046 | −0.035 | |
Anticipation of infection | 0.019 | 0.056 | 0.042 | 0.002 | −0.029 | 0.131 *** | 0.133 *** | 0.115 *** | |
Media exposure | 0.029 | 0.071 * | 0.038 | −0.001 | 0.057 | 0.092 ** | 0.071 * | 0.060 | |
Well-regulated life | 0.036 | −0.090 ** | −0.039 | −0.024 | 0.224 *** | −0.244 *** | −0.252 *** | −0.234 *** | |
Self-evaluation | Enough sleep | 0.057 | −0.046 | −0.070 * | −0.094 ** | 0.158 *** | −0.218 *** | −0.252 *** | −0.224 *** |
Smoothness of work | −0.066 * | −0.098 ** | −0.061 | −0.090 ** | 0.187 *** | −0.387 *** | −0.389 *** | −0.376 *** | |
Smoothness of nonwork activities | −0.059 | −0.049 | −0.015 | −0.001 | 0.161 *** | −0.264 *** | −0.255 *** | −0.192 *** | |
Communication at work | −0.019 | −0.087 ** | −0.015 | −0.044 | 0.277 *** | −0.341 *** | −0.334 *** | −0.341 *** | |
Communication with family | 0.048 | −0.050 | −0.043 | −0.063 | 0.272 *** | −0.270 *** | −0.344 *** | −0.341 *** |
Independent Variables | PSS | STAI-T | CES-D | ||||||
---|---|---|---|---|---|---|---|---|---|
Step 1 | Step 2 | Step 3 | Step 1 | Step 2 | Step 3 | Step 1 | Step 2 | Step 3 | |
Step 1 | |||||||||
Sex | 0.077 * | 0.086 ** | 0.098 *** | 0.062 | 0.073 ** | 0.079 ** | −0.040 | −0.031 | −0.013 |
Age | −0.052 | −0.007 | −0.004 | −0.050 | 0.007 | 0.010 | −0.111 ** | −0.049 | −0.039 |
Unmarried | 0.073 | 0.048 | 0.042 | 0.190 ** | 0.172 *** | 0.169 *** | 0.148 * | 0.137 ** | 0.128 ** |
Married | 0.057 | 0.026 | 0.027 | 0.115 | 0.091 * | 0.093 * | 0.059 | 0.046 | 0.050 |
Bereaved | 0.020 | 0.018 | 0.020 | 0.018 | 0.015 | 0.015 | −0.022 | −0.024 | −0.028 |
Full-time worker | −0.032 | 0.007 | 0.010 | −0.008 | 0.022 | 0.024 | 0.006 | 0.041 | 0.040 |
Part-time worker | −0.001 | 0.009 | 0.001 | 0.016 | 0.027 | 0.022 | 0.059 | 0.073 * | 0.064 |
Household income level | −0.161 *** | −0.052 | −0.055 ** | −0.181 *** | −0.074 ** | −0.078 ** | −0.146 *** | −0.047 | −0.059 * |
N people per household | −0.010 | −0.007 | −0.013 | −0.014 | −0.015 | −0.019 | −0.029 | −0.031 | −0.033 |
Daily practice of mindfulness/meditation | −0.008 | −0.022 | −0.020 | −0.029 | −0.035 | −0.036 | −0.068 * | −0.068 ** | −0.067 ** |
Step 2 | |||||||||
Time spent at home | 0.007 | <0.001 | −0.029 | −0.032 | −0.026 | −0.032 | |||
Time spent using a smartphone | −0.025 | −0.026 | −0.006 | −0.007 | 0.022 | 0.027 | |||
Time spent engaged with social media | 0.020 | 0.022 | 0.062 * | 0.064 * | 0.103 *** | 0.111 *** | |||
Anticipation of infection | 0.028 | 0.030 | 0.061 * | 0.066 * | 0.054 | 0.065 * | |||
Media exposure | 0.142 *** | 0.143 *** | 0.101 ** | 0.098 ** | 0.088 ** | 0.077 * | |||
Smoothness of work | −0.293 *** | −0.298 *** | −0.286 *** | −0.290 *** | −0.288 *** | −0.293 *** | |||
FFMQ total | −0.554 *** | −0.530 *** | −0.520 *** | −0.511 *** | −0.431 *** | −0.422 *** | |||
Step 3 | |||||||||
FFMQ total × Time spent engaged with social media | −0.011 | −0.017 | 0.035 | ||||||
FFMQ total × Anticipation of infection | 0.048 | −0.004 | 0.019 | ||||||
FFMQ total × Media exposure | −0.097 *** | −0.021 | −0.027 | ||||||
FFMQ total × Smoothness of work | 0.085 *** | 0.050 * | 0.148 *** | ||||||
R2 | 0.052 *** | 0.492 *** | 0.504 *** | 0.076 *** | 0.484 *** | 0.487 *** | 0.078 *** | 0.408 *** | 0.428 *** |
ΔR2 | 0.440 *** | 0.012 *** | 0.408 *** | 0.004 | 0.330 *** | 0.020 *** |
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Miyata, H.; Yamasaki, K.; ChaeEun, N.; Ishikawa, H. Relationship between COVID-19 Pandemic-Related Life Behavior, Dispositional Mindfulness, and Psychological Health: Evidence from a Sample of Japanese Working Adults. Int. J. Environ. Res. Public Health 2023, 20, 5873. https://doi.org/10.3390/ijerph20105873
Miyata H, Yamasaki K, ChaeEun N, Ishikawa H. Relationship between COVID-19 Pandemic-Related Life Behavior, Dispositional Mindfulness, and Psychological Health: Evidence from a Sample of Japanese Working Adults. International Journal of Environmental Research and Public Health. 2023; 20(10):5873. https://doi.org/10.3390/ijerph20105873
Chicago/Turabian StyleMiyata, Hiromitsu, Kaho Yamasaki, Noh ChaeEun, and Haruyuki Ishikawa. 2023. "Relationship between COVID-19 Pandemic-Related Life Behavior, Dispositional Mindfulness, and Psychological Health: Evidence from a Sample of Japanese Working Adults" International Journal of Environmental Research and Public Health 20, no. 10: 5873. https://doi.org/10.3390/ijerph20105873
APA StyleMiyata, H., Yamasaki, K., ChaeEun, N., & Ishikawa, H. (2023). Relationship between COVID-19 Pandemic-Related Life Behavior, Dispositional Mindfulness, and Psychological Health: Evidence from a Sample of Japanese Working Adults. International Journal of Environmental Research and Public Health, 20(10), 5873. https://doi.org/10.3390/ijerph20105873