The Associations Between Daily Activities and Affect: a Compositional Isotemporal Substitution Analysis

Le, Flora; Yap, Yang; Tung, Natasha Yan Chi; Bei, Bei; Wiley, Joshua F.

doi:10.1007/s12529-021-10031-z

Cited by 10 publications

(4 citation statements)

References 53 publications

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“…This study was a secondary analysis of eight datasets that assessed repeated measures of sleep across multiple days. For a summary of all studies and the demographics of each sample, see Table S1 (Dietch & Taylor, 2021; Le et al, 2021; Molzof et al, 2018; Slavish et al, 2020; Taylor et al, 2013; Taylor et al, 2017; Yap et al, 2020). To focus on healthy sleepers, participants were excluded from analyses if: (i) they had <3 days of usable sleep diary data; or (ii) they reported a mean diary‐determined sleep duration <300 or >600 min (indicating very short or very long sleep duration) or mean diary‐determined sleep efficiency <80% (indicating possible insomnia).…”

Section: Methodsmentioning

confidence: 99%

How much does sleep vary from night‐to‐night? A quantitative summary of intraindividual variability in sleep by age, gender, and racial/ethnic identity across eight‐pooled datasets

Messman

Wiley

Yap

et al. 2022

Journal of Sleep Research

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Summary Habitual sleep duration and efficiency vary widely by age, gender, and racial/ethnic identity. Despite growing research on the importance of night‐to‐night, intraindividual variability (IIV) in sleep, few studies have examined demographic differences in sleep IIV. The present study describes typical sleep IIV overall and by demographics among healthy sleepers. Eight datasets of healthy sleepers (N = 2,404; 26,121 total days of sleep data) were synthesised to examine age, gender, and racial/ethnic identity differences in sleep IIV measured via diaries, actigraphy, and electroencephalography (EEG). Sleep IIV estimates included the intraindividual standard deviation (iSD), root mean square of successive differences (RMSSD), coefficient of variation (CV), and a validated Bayesian Variability Model (BVM). There was substantial IIV in sleep across measurement types (diary, actigraphy, EEG) for both sleep duration (iSD: 85.80 [diary], 77.41 [actigraphy], 67.04 [EEG] minutes; RMSSD: 118.91, 108.89, 91.93 minutes; CV: 19.19%, 19.11%, 18.57%; BVM: 60.60, 58.20, 48.60 minutes) and sleep efficiency (iSD: 5.18% [diary], 5.22% [actigraphy], 6.46% [EEG]; RMSSD: 7.01%, 7.08%, 8.44%; CV: 5.80%, 6.27%, 8.14%; BVM: 3.40%, 3.58%, 4.16%). Younger adults had more diary and actigraphy sleep duration IIV. Gender differences were inconsistent. White and non‐Hispanic/Latinx adults had less IIV in sleep duration and efficiency compared to racial/ethnic minority groups. Even among healthy sleepers, sleep varies widely from night‐to‐night. Like mean sleep, there also may be disparities in IIV in sleep by demographic characteristics. Study results help characterise normative values of sleep IIV in healthy sleepers.

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Section: Methodsmentioning

confidence: 99%

How much does sleep vary from night‐to‐night? A quantitative summary of intraindividual variability in sleep by age, gender, and racial/ethnic identity across eight‐pooled datasets

Messman

Wiley

Yap

et al. 2022

Journal of Sleep Research

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“…In a recent study with adults, eEMA and actigraphy were used to explore the associations of affect with movement behavior compositions and reallocations within the 24-hour period. The associations between affect and 24-hour movement behavior composition varied by activity and behavior reallocation patterns, suggesting complex interrelationships among the behaviors within 24-hour compositions [ 84 ]. The development of eEMA technologies and their potential integration with accelerometry have enabled the study of movement behaviors and their correlates within a 24-hour context.…”

Section: Discussionmentioning

confidence: 99%

“…This definition was used to emphasize studies examining momentary experiences rather than allowing for larger recall durations and diary methodologies; however, this may have limited the research on sleep, as self-reported sleep is often measured using a daily morning recall. We adhered to a strict age range for the young adult life stage based on the Society for Adolescent Health Medicine’s definition of young adult [ 11 ]; therefore, studies with slightly older or younger samples were excluded [ 84 , 90 ]. The lack of standardized definitions, specific quality coding metrics, and reporting for EMA studies may have resulted in the exclusion of interesting studies and an increase in reporting bias, thereby affecting the risk of bias and confidence in this synthesis.…”

Section: Discussionmentioning

confidence: 99%

Use of Electronic Ecological Momentary Assessment Methodologies in Physical Activity, Sedentary Behavior, and Sleep Research in Young Adults: Systematic Review

Hartson¹,

Huntington‐Moskos²,

Sears³

et al. 2023

J Med Internet Res

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Background Recent technological advances allow for the repeated sampling of real-time data in natural settings using electronic ecological momentary assessment (eEMA). These advances are particularly meaningful for investigating physical activity, sedentary behavior, and sleep in young adults who are in a critical life stage for the development of healthy lifestyle behaviors. Objective This study aims to describe the use of eEMA methodologies in physical activity, sedentary behavior, and sleep research in young adults. Methods The PubMed, CINAHL, PsycINFO, Embase, and Web of Science electronic databases were searched through August 2022. Inclusion criteria were use of eEMA; sample of young adults aged 18 to 25 years; at least 1 measurement of physical activity, sedentary behavior, or sleep; English language; and a peer-reviewed report of original research. Study reports were excluded if they were abstracts, protocols, or reviews. The risk of bias assessment was conducted using the National Heart, Lung, and Blood Institute’s Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Screening, data extraction, and risk of bias assessments were conducted by independent authors, with discrepancies resolved by consensus. Descriptive statistics and narrative synthesis were used to identify overarching patterns within the following categories guided by the Checklist for Reporting Ecological Momentary Assessments Studies: study characteristics, outcomes and measures, eEMA procedures, and compliance. Results The search resulted in 1221 citations with a final sample of 37 reports describing 35 unique studies. Most reports (28/37, 76%) were published in the last 5 years (2017-2022), used observational designs (35/37, 95%), consisted of samples of college students or apprentices (28/35, 80%), and were conducted in the United States (22/37, 60%). The sample sizes ranged from 14 to 1584 young adults. Physical activity was measured more frequently (28/37, 76%) than sleep (16/37, 43%) or sedentary behavior (4/37, 11%). Of the 37 studies, 11 (30%) reports included 2 movement behaviors and no reports included 3 movement behaviors. eEMA was frequently used to measure potential correlates of movement behaviors, such as emotional states or feelings (25/37, 68%), cognitive processes (7/37, 19%), and contextual factors (9/37, 24%). There was wide variability in the implementation and reporting of eEMA procedures, measures, missing data, analysis, and compliance. Conclusions The use of eEMA methodologies in physical activity, sedentary behavior, and sleep research in young adults has greatly increased in recent years; however, reports continue to lack standardized reporting of features unique to the eEMA methodology. Additional areas in need of future research include the use of eEMA with more diverse populations and the incorporation of all 3 movement behaviors within a 24-hour period. The findings are intended to assist investigators in the design, implementation, and reporting of physical activity, sedentary behavior, and sleep research using eEMA in young adults. Trial Registration PROSPERO CRD42021279156; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021279156

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“…It suggests that male students should spend more time in vigorous PA and females more walking for optimal mental health. The relationship between PA and happiness has been widely documented ( Zhang and Chen, 2019 ; Le et al, 2021 ). In most studies, the intensity of the physical activities had not been distinguished in the relationship.…”

Section: Discussionmentioning

confidence: 99%

Gender Difference in the Relationship of Physical Activity and Subjective Happiness Among Chinese University Students

2021

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Background: Gender makes a difference in health and physical activity (PA). This research aimed to identify the gender difference in the relationship of PA and subjective happiness among Chinese university students.Methods: A cross-sectional survey was conducted in Shanghai Jiao Tong University from July 7 to 17 in 2021, using an anonymous online self-report questionnaire. The questionnaire included the Chinese version of the International Physical Activity Questionnaire-Short Form (IPAQ-SF), the Subjective Happiness Scale (SHS), the Depression Anxiety Stress Scale-21(DASS-21). The demographic and health-related factors were also reported. Linear regression was carried out to identify the relationship of PA and subjective happiness.Findings: In total, 1,512 students (1,108 males and 404 females) from three comprehensive schools completed the survey. The SHS score was 17.20 ± 3.44, and it was 17.00 ± 3.23 in males, and 17.75 ± 3.93 in females, respectively (p < 0.001). There was no gender difference in vigorous, moderate PA, or walk min/week, while female students had longer sedentary behavior hours/day than males. Male students scored higher in each subscale of DASS-21. After controlling for confounders, vigorous PA min/week (β = 0.002, p = 0.002) and sedentary behavior hours/day (β = 0.168, p = 0.005) were significantly positively associated with happiness in male students. In contrast, walk min/week (2= 0.002, p = 0.005) was significantly positively associated with happiness in female students.Interpretation: This research demonstrated a significant gender difference in the association between PA and happiness. Policymakers and college management should pay more attention to PA programs to promote students’ happiness and mental health status.

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The Associations Between Daily Activities and Affect: a Compositional Isotemporal Substitution Analysis

Cited by 10 publications

References 53 publications

How much does sleep vary from night‐to‐night? A quantitative summary of intraindividual variability in sleep by age, gender, and racial/ethnic identity across eight‐pooled datasets

How much does sleep vary from night‐to‐night? A quantitative summary of intraindividual variability in sleep by age, gender, and racial/ethnic identity across eight‐pooled datasets

Use of Electronic Ecological Momentary Assessment Methodologies in Physical Activity, Sedentary Behavior, and Sleep Research in Young Adults: Systematic Review

Gender Difference in the Relationship of Physical Activity and Subjective Happiness Among Chinese University Students

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