Time-Use and Mental Health in Older Adults: A Scoping Review
Abstract
:1. Introduction
2. Materials and Methods
2.1. Research Question
2.2. Search Strategy
2.3. Eligibility Criteria
- Any study from inception until 30 November 2020;
- Studies from any country;
- Studies only in English;
- Studies only published in peer-review journals;
- Quantitative study with either experimental, longitudinal, cross-sectional, or correlational designs so that the relationship between time-use and mental health could be evaluated if the study did the analysis;
- Studies that involved human time-use and mental health involving older adults. Studies that involved both older adults and non-older adults were permitted with the condition that the involvement of non-older adults was so that the findings on older adults could be compared with non-older adults;
- Studies that collected time-use on a broad range of daily activities, but not discrete activity in isolation. Studies that collected activity engagement using a frequency scale or with “yes/no” responses were excluded as they cannot provide information on activity duration.
2.4. Screening
2.5. Data Extraction
2.6. Data Analysis
3. Results
3.1. Study Characteristics
3.2. Time-Use and Its Measurement
3.3. Mental Health and Its Measurement
3.4. Thematic Summary
3.4.1. Demographic, Time-Use and Mental Health
3.4.2. Changes in Time-Use and Mental Health
3.4.3. Work Status, Types of Activities and Mental Health
3.4.4. Activity Profiles and Mental Health
4. Discussion
4.1. More Evidence on Time-Use and Mental Health in Older Adults Are Required
4.2. Considering Robust Research Design in Time-Use and Mental Health Study
4.3. Allowing Full Richness of Time-Use Data
4.4. Incorporating Demographic Issues in Time-Use and Mental Health Studies
4.5. Limitations of This Study
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variables | Target Group | |||
---|---|---|---|---|
activity pattern OR time OR diary OR time-use OR time budget OR yesterday diary OR time studies OR time utilization OR daily activities OR time allocation | AND | mental health OR psychological health OR psychological distress OR psychological OR psychosocial OR mental OR life satisfaction | AND | elderly OR aging OR geriatric OR over-65 OR older |
Domain | Inclusion Criteria | Exclusion Criteria | Rationale |
---|---|---|---|
1. Publication year | Studies from inception until 30 November 2020 | Studies published after 30 November 2020 | We did a preliminary search using the search terms at Google Scholar and found that the number of papers available was not overwhelmed |
2. Publication type | Studies published in peer-reviewed journals only | Studies, reports, or other materials not published in peer-reviewed journals | To ensure the academic rigor and quality of the studies |
3. Research design | Quantitative studies involved experimental, longitudinal, and correlational study design | Qualitative study or any study not involved quantitative research design | To evaluate the relationship between time-use and mental health if the study did examine for it |
4. Study scope/variables | Studies that involved collecting human time-use and mental health data | Studies that collected discrete activity in isolation Studies that collected activity engagement using frequency scale or with “yes/no” response | To ensure that the review question is addressed Frequency scale or “yes/no” response cannot provide information on activity duration |
5. Target group | Older adults with no specific age Studies involved both older adults, and non-older adults were permitted with the condition that the involvement of non-older adults was to so that the findings on older adults could be compared with non-older adults | Studies that did not involve older adults at all | To ensure that the review question is addressed |
6. Location | Any country | Not applicable | Analyzing studies from Western and non-Western countries could help researchers in gaining deeper insight into the cultural differences in older adults’ time-use and mental health |
Year | Number of Studies |
---|---|
1995 | 1 |
2003 | 1 |
2007 | 1 |
2011 | 1 |
2012 | 1 |
2013 | 1 |
2014 | 1 |
2018 | 3 |
2019 | 1 |
Author, Y | Country | Study Objective | Study Design | Sample Characteristics | Instrument Used to Measure Time Use | Type of Mental Health Measured | Instrument to Assess Mental Health | Main Statistical Analysis | Study Findings |
---|---|---|---|---|---|---|---|---|---|
1. (Prigerson et al. 1995) [31] | United States | To determine if high regularity in the timing of daily activities was protective against depressive symptoms among older adults soon after spousal death | Cohort study The regularity of daily activities was assessed at 3 months post-loss; depressive symptoms were measured at 3, 12, and 24 months post-loss | 47 older adults aged between 60 and above who just lost their spouse; The distribution of the sample by sex and description of sample’s age was not provided | Time use measured by using the social rhythm metric (SRM); The instrument is diary-like in form, requiring the subject to provide daily details of the time of day at which each event occurred; Data for each week were then analyzed to come out with an SRM score; The score lies on a continuum between 0 and 7, with 0 representing greatest irregularity and 7 greatest regularity | Depressive symptoms | 17-Item Hamilton rating scale for depression | Multiple regression | Baseline SRM was not associated with severity of depression at 12- or 24-month post-loss; For those with activity level index (ALI) scores of 80 or above, lifestyle regularity was negatively associated with depressive symptoms at 12-month post-loss; In subjects with ALI scores of 90 or above, baseline lifestyle regularity was associated with lower levels of depressive symptoms at 24-month post-loss |
2. (Jennings and Darwin, 2003) [32] | United States | To evaluate the relationship between daily activities and memory performance in older adults | Cross-sectional study | Group 1:29 older adults, aged from 69 to 93 y (mean age = 78.1); Group 2:30 undergraduate students, aged 18 to 20 y (mean = 18.70); Distribution of respondents by sex was not provided | Participants were asked to indicate how many hours per week and how many weeks per month they participated in a variety of physical activities, mental activities, and social activities | Memory performance | California verbal learning test | Independent sample t-test | Time-use in physical activity was positively associated with memory performance; No association was noted between time-use in social and mental activity with memory performance |
3. (Mckenna, Broome, and Liddle, 2007) [5] | Australia | To describe the time-use profile and role participation in community-dwelling older adults; to analyze if time-use and role participation changed with increasing age, and to examine the relationship between role participation and life satisfaction | Cross-sectional study Secondary data analysis of a driving cessation study | Total sample = 195 community-dwelling older adults (81 men and 114 women); Majority of them were aged from 65–74 y old (n = 94), followed by 75–84 y (n = 79), and 85+ y (n = 22) | Activity configuration was used to record time-use retrospectively; Participants were asked to recall their activities from the past week in half-hour intervals | Life satisfaction | Life satisfaction index-Z | ANOVA, chi-squared analysis, independent sample t-test, linear regression | Participants spent most of the time on sleep, followed by solitary activities and social leisure; The most common roles were friend, family member, and home maintainer; Participants aged 75 y and older spent significantly more time on solitary leisure and less time on paid work and transport compared to those aged 65–74 y; Role maintenance was significantly related to greater life satisfaction in participants aged 75–84 y; This study did not examine the relationship between time-use and life satisfaction |
4. (Hahn, Cichy, Almeida, and Haley, 2011) [33] | United States | To compare daily time-use and daily wellbeing in widowed and married women | Cross-sectional study; Secondary data analysis; Data source: second wave (2004–2006) of National study of daily experiences | 75 widowed women (mean age = 72.4 ± 6.67) and 125 married women (mean age = 70.0 ± 5.97) | Respondents were asked about the daily time spent for the following activities: interacting with children, performing household chores, doing work or school work, relaxing or doing leisure activities, watching TV, volunteering, giving or receiving unpaid assistance, giving or receiving emotional support, providing help to someone with a disability, and sleeping; Daily time use was collected for 8 consecutive days | Daily wellbeing | Respondents were asked how often during the past day they experienced 14 different negative emotions and 13 different positive emotions with a Likert scale ranging from 0 (none of the time) to 4 (all of the time) | ANCOVA, independent samples t-test | No difference in daily activity time-use for most of the activities between married and widowed women; Widowed women spent more time accompanying their children and watching television and spent less time sleeping than married women; No difference was noted in wellbeing between widowed and married older women |
5. (Liddle, Gustafsson, Bartlett, and Mckenna, 2012) [34] | Australia | To examine the impact of driving status on time use, role participation and life satisfaction in older adults | Cross-sectional study | 137 current drivers (mean age = 73.2 ± 6.1), 56 retired drivers (mean age = 78.7 ± 6.7), and 41 people who have never driven (mean age = 76.2 ± 6.2); The distribution of the study sample by sex was not reported | Time use was measured using activity configuration; Participants were asked to recall activities from the past week in half-hour intervals, including the location of the activity, presence of other people and subjective classification of the activity | Life satisfaction | Life satisfaction index Z | ANOVA, chi-squared, multiple regression, logistic regression | Those who have never driven spent more time doing charity activities than retired drivers; Current drivers spent more time in social leisure activities than retired drivers; However, retired drivers spent more time in solitary leisure than current drivers; Current drivers spent more time away from home than retired drivers; Current drivers had higher life satisfaction than retired drivers; No difference in life satisfaction between retired drivers and people who have never driven; This study did not examine the relationship between time-use and life satisfaction |
6. (Tadic, Oerlemans, Bakker, and Veenhoven, 2013) [35] | The Netherlands | To examine the role of current work status in the relationship between time-use and happiness | Longitudinal study; Data on time use and happiness were collected monthly over three y | 381 men and 198 women with mean age = 65.3 ± 7.78 | Respondents were asked to fill in “yesterday ‘s diary”, once every month throughout 2006–2008 to capture time use in activities over weekdays and weekends; “yesterday’s diary” was built based on the day reconstruction method | Happiness | A single item for happiness, with a graphical faces scale ranging from 1 (extremely unhappy) up to 10 (extremely happy) | Hierarchical linear modeling, multilevel modeling | Non-working older adults were happier than working older individuals; Paid and voluntary works were associated with higher happiness; Administrative duties were associated with lower happiness in older adults with a paid job; Regardless of work status, relaxing activities were associated with higher happiness; Older adults with paid jobs reported higher levels of happiness on weekends compared to weekdays |
7. (Morrow-Howell et al. 2014) [36] | United States | To identify activity profiles and explore the relationships between activity profiles and wellbeing outcomes | Cross-sectional study Secondary data analysis; Data source: 2008 and 2010, as well as the 2009 Health and retirement study consumption and activities mail survey | 1942 men, 2743 women with mean age = 69.5 ± 8.91 | 36 activity measures—measured continuously—hours per week, hours per month | Self-reported health; Depressive symptoms | Single-item self-reported health scale with Likert scale from 1 (excellent) to 5 (poor); Center for Epidemiologic Studies—Depression (CES-D) | Generalized linear modeling, multinomial logistic regression, multiple linear regression, general mixture model | Five activity profiles were identified: “low activity,” “moderate activity,” “high activity,” “working,” and “physically active; ” Older adults in “high activity” “physically active” and “working” groups had better self-reported health than those in the “low activity” group; Older adults in the “low activity” group reported higher depressive symptoms than all other groups |
8. (Adjei, Jonsson, and Brand, 2018) [37] | Italy, Spain, UK, France and the Netherlands | To examine the associations between work-related time use, social time use and self-rated health; To examine if stress mediated the relationship between work-related time use activities on self-reported health | Cross-sectional study; Secondary data analysis Data source: Multinational time use study (WTUS, version W53) | 11,168 men (mean age = 72.4 ± 5.01) and 14,295 women (mean age = 73.1 ± 5.13) | Time use was collected by self-administered diary; Respondents reported the total time spent on 41 activities over a 24 h period in 5-, 10- or 15-min intervals; Respondents in France, Italy and Spain reported the time use during a randomly assigned day in a week; Respondents from the UK filled in the diary for two days (weekday and weekend); In the Netherlands, respondents reported their time use activities for seven consecutive day | Self-rated health; Stress | One-item self-reported health scale with Likert scale ranging from 0 (poor) to 3 (very good); Time pressure was measured by asking respondents, “Would you say you always feel rushed even to do the things you must do, only sometimes feel rushed, or almost never feel rushed?” with Likert scale ranging from 1 (never) to 3 (always) | Pearson’s correlation, linear structural model | Housework was associated with higher stress in both older men and women; Paid work was associated with lower stress only in older men; Social activities were associated with better self-rated health, but no association was found with stress; Stress did not mediate the association between housework, paid work and self-reported health |
9. (Lee et al. 2018) [38] | United States | To examine the associations between activity diversity and psychological wellbeing in people from different age group; older adults (60–74 y), middle-aged adults (35–59 y), and younger individuals (24–34 y) | 10 y longitudinal study; Secondary data analysis; Data source: National survey of daily experiences (1996–1997 and 2006–2007) | 793 (349 men, 444 women) individuals aged from 24 to 74 y at baseline (mean age = 46.71 ± 12.5) | 8-day daily diary was administered to participants to capture their daily experiences, including daily time use; Seven activities were captured: paid work, with children, doing chores, on leisure, in physical activities, on formal volunteering, and giving informal help to people who do not live with respondents | Psychological wellbeing; Depression positive and negative affect | The psychological wellbeing scale 7 items of depressive affect and 6 items of anhedonia; Positive and negative affect scales | Multilevel models, residualized gain models, ANCOVA-type regression model | Older adults who engaged in more diverse activities reported higher psychological wellbeing than older adults who engaged in less diverse activities; Longitudinally, increased activity diversity over 10 y was associated with the increases in positive affect; Compared with younger individuals who increased activity diversity, older adults who increased activity diversity reported smaller decreases in psychological wellbeing, greater increases in positive affect, and greater decreases in negative affect |
10. (Olds et al. 2018) [39] | Australia | To determine the effects of activity changes after retirement on mental health | Longitudinal study; Data on time use, physical health, mental health and sociodemographic characteristics were gathered 6 months before and at 3-, 6- and 12-month post-retirement | 54 women and 51 men with pre-retirement mean age = 62.3 ± 4.3 y and post-retirement mean age = 63.4 ± 4.3 y | Time use in activities was collected by using multimedia activity recall for children and adults (MARCA); The MARCA was administered at each time point on two occasions, each time recalling the two previous days, one weekday and one day on the weekend | Depression, anxiety, and stress Wellbeing Life satisfaction self-esteem | Depression, anxiety, and stress scales; The short Warwick–Edinburgh mental wellbeing scale Australian unity personal wellbeing index The Rosenberg self-esteem scale | Regression analysis, compositional isotemporal substitution models | Work time flowed mainly to household chores, sleep, screen time and quiet time after retirement; Changes in overall time use were significantly associated with lower depressive symptoms and stress, as well as higher self-esteem; Replacing work time with physical activity and sleep was associated with improvements in all measures of mental health |
11. (Chen, Putnam, Lee, and Morrow-Howell, 2019) [40] | United States | To examine the relationships between activity, health, and nature of engagement in older adults | Cross-sectional study Secondary data analysis Data source: 2010 and 2012 Health and retirement study linked with 2011 consumption and activity mail survey | 3516 women and 2528 men with mean age 64.4 ± 10.37 y | 33 items that captured a wide range of activities that involved varying degrees of physical, cognitive, and social engagement; Time use for each activity was divided into three levels; low, medium, and high | Cognitive function Depressive symptoms Self-rated health | Numbers of words recalled immediately and delayed The modified version of the Center for Epidemiologic Studies-Depression scale Single item of self-rated health with Likert scale 1 = excellent to 5 = poor | Latent class analysis, linear regression | Five patterns of activity (high, medium, low, passive leisure, working) and three nature of activity engagement (full, partial, minimal) were identified; High and working groups, compared to the passive leisure group, showed better health and cognition outcomes; Older adults in the category of “low” activity with “full” engagement reported higher levels of self-rated health than older adults in the “passive leisure” group; Older adults in the category of “moderate” activity, “high” activity, and “working” group reported lower levels of depressive symptoms only when they fully engage in the activity |
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Foong, H.F.; Lim, S.Y.; Koris, R.; Haron, S.A. Time-Use and Mental Health in Older Adults: A Scoping Review. Int. J. Environ. Res. Public Health 2021, 18, 4459. https://doi.org/10.3390/ijerph18094459
Foong HF, Lim SY, Koris R, Haron SA. Time-Use and Mental Health in Older Adults: A Scoping Review. International Journal of Environmental Research and Public Health. 2021; 18(9):4459. https://doi.org/10.3390/ijerph18094459
Chicago/Turabian StyleFoong, Hui Foh, Sook Yee Lim, Roshanim Koris, and Sharifah Azizah Haron. 2021. "Time-Use and Mental Health in Older Adults: A Scoping Review" International Journal of Environmental Research and Public Health 18, no. 9: 4459. https://doi.org/10.3390/ijerph18094459