Investigating Microtemporal Processes Underlying Health Behavior Adoption and Maintenance: Protocol for an Intensive Longitudinal Observational Study (Preprint)

Sensor-triggered ecological momentary assessment in physical activity and sedentary behaviour research among Belgian community-dwelling elderly: lessons learnt from intensive longitudinal studies

OBJECTIVES

Regular physical activity (PA) and reduced sedentary behaviour (SB) have been associated with positive health outcomes, but many older adults do not comply with the current recommendations. Sensor-triggered ecological momentary assessment (EMA) studies allow capturing real-time data during or immediately after PA or SB, which can yield important insights into these behaviours. Despite the promising potential of sensor-triggered EMA, this methodology is still in its infancy. Addressing methodological challenges in sensor-triggered EMA studies is essential for improving protocol adherence and enhancing validity. Therefore, this study aimed to examine (1) the patterns in sensor-triggered EMA protocol adherence (eg, compliance rates), (2) the impact of specific settings (eg, event duration) on the number of prompted surveys, and (3) participants' experiences with engaging in a sensor-triggered EMA study.

DESIGN

Two longitudinal, sensor-triggered EMA studies-one focused on PA and the other on SB-were conducted using similar methodologies from February to October 2022. Participants' steps were monitored for seven days using a Fitbit activity tracker, which automatically prompted an EMA survey through the HealthReact smartphone application when specified (in)activity thresholds were reached. After the monitoring period, qualitative interviews were conducted. Data from both studies were merged.

SETTING

The studies were conducted among community-dwelling Belgian older adults.

PARTICIPANTS

The participants had a median age of 72 years, with 54.17% being females. The PA study included 88 participants (four dropped out), while the SB study included 76 participants (seven dropped out).

PRIMARY AND SECONDARY OUTCOME MEASURES

Descriptive methods and generalised logistic mixed models were employed to analyse EMA adherence patterns. Simulations were conducted to assess the impact of particular settings on the number of prompted EMA surveys. Additionally, qualitative interview data were transcribed verbatim and thematically analysed using NVivo.

RESULTS

Participants responded to 81.22% and 79.10% of the EMA surveys in the PA and SB study, respectively. The confirmation rate, defined as the percentage of EMA surveys in which participants confirmed the detected behaviour, was 94.16% for PA and 72.40% for SB. Logistic mixed models revealed that with each additional day in the study, the odds of responding to the EMA survey increased significantly by 1.59 times (OR=1.59, 95% CI: 1.36 to 1.86, p<0.01) in the SB study. This effect was not observed in the PA study. Furthermore, time in the study did not significantly impact the odds of participants confirming to be sedentary (OR=0.97, 95% CI: 0.92 to 1.02, p=0.28). However, it significantly influenced the odds of confirming PA (OR: 0.81, 95% CI: 0.68 to 0.97, p=0.02), with the likelihood of confirming decreasing by 19% with each additional day in the study. Furthermore, a one-minute increase in latency (ie, time between last syncing and starting the EMA survey) in the PA study decreased the odds of the participant confirming to be physically active by 20% (OR: 0.80, 95% CI: 0.72 to 0.89, p<0.01). Simulations of the specific EMA settings revealed that reducing the event duration and shorter minimum time intervals between prompts increased the number of EMA surveys. Overall, most participants found smartphone usage to be feasible and rated the HealthReact app as user-friendly. However, some reported issues, such as not hearing the notification, receiving prompts at an inappropriate time and encountering technical issues. While the majority reported that their behaviour remained unchanged due to study participation, some noted an increased awareness of their habits and felt more motivated to engage in PA.

CONCLUSIONS

This study demonstrates the potential of sensor-triggered EMA to capture real-time data on PA and SB among older adults, showing strong adherence potential with compliance rates of approximately 80%. The SB study had lower confirmation rates than the PA study, due to technical issues and discrepancies between self-perception and device-based measurements. Practical recommendations were provided for future studies, including improvements in survey timing, technical reliability and strategies to reduce latency.

Determinants of physical activity adoption and maintenance in older adults: A dual process approach

BACKGROUND

Dual process models represent a useful framework for explaining physical activity (PA) in that behavior is explained by reflective (i.e., conscious, effortful) and automatic (i.e., unconscious, effortless) determinants. Yet the distinct momentary reflective and automatic determinants associated with PA adoption and maintenance are unclear.

METHODS

Older adults (N = 202; ≥60 years) wore accelerometers to measure PA (i.e., moderate to vigorous intensity PA [MVPA], step counts) and completed brief mobile phone prompts assessing general reflective (i.e., demands, deliberation, self-efficacy, self-control, stress coping, emotion regulation), behavior-specific reflective (i.e., PA intentions, self-efficacy, planning), and automatic determinants (i.e., affect, physical and social context, functional stability of one's routine) as part of three, 2-week waves of data collection spaced over one year. Multilevel modeling was used to examine the within- and between-person associations between these determinants and subsequent PA.

RESULTS

There were within- or between-person differences between general reflective, behavior specific, and automatic determinants and PA by adopter and maintainer status. General reflective determinants tended to be more predictive of step counts compared to MVPA. Within-person behavior-specific reflective determinants (i.e., intentions, self-efficacy, plans) were positively associated with PA behavior but associations tended to be more positive among PA maintainers. Automatic determinants were more predictive of the amount of PA as opposed to the likelihood of PA occurring.

CONCLUSION

Reflective and automatic determinants, as well as the levels at which these determinants operate (i.e., between vs within), need to be considered when attempting to explain and predict the adoption and maintenance of PA.

Combining Ecological Momentary Assessment and Social Network Analysis to Study Youth Physical Activity and Environmental Influences: Protocol for a Mixed Methods Feasibility Study

BACKGROUND

Physical activity (PA) is crucial for youth health, but up to 74% of adolescents fail to meet recommended levels, especially during summer when structured supports associated with school are not available. The social and built environments significantly influence youth PA; yet, their complex interactions remain poorly understood. This study aims to evaluate the feasibility of combining ecological momentary assessment (EMA) and social network analysis to examine bidirectional influences among youth PA, built environments, and social networks during summer.

OBJECTIVE

The objectives are to (1) evaluate the feasibility and acceptability of the combined EMA and Social Network Analysis protocol, and (2) identify phenotypes using person-level, microtemporal, and dynamic overlap between social and built environments.

METHODS

This mixed methods feasibility study with an exploratory observational component will recruit 120 youth aged 12 years to 15 years from an urban school district in Central Texas, US. Participants will first complete a baseline survey to report their general social network patterns and environmental perceptions. Then participants will wear an ActiGraph LEAP accelerometer and respond to EMA prompts via smartphone for 7 days. EMA will assess real-time perceptions of social networks and surrounding built environments, which will be time-matched with accelerometer-assessed PA data. GPS coordinates will be collected with each EMA prompt to assess features of the built environment. Follow-up semistructured interviews will assess protocol acceptability.

RESULTS

This study has been funded by the National Heart, Lung, and Blood Institute. Data collection is expected in the summers of 2025, 2026, and 2027.

CONCLUSIONS

This innovative approach combines EMA, SNA, accelerometry, and GPS data to provide unprecedented insights into the dynamic interplay between social networks, built environments, and youth PA during summer. Findings will inform the development of more targeted, effective interventions to promote PA among youth. While limitations include potential participant burden and generalizability, the study's strengths in capturing real-time, contextualized data make it a valuable contribution to understanding youth PA determinants.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/68667.

Exploring person-centred sleep and rest-activity cycle dynamics over 6 months

Sleep and circadian characteristics are associated with health outcomes, but are often examined cross-sectionally or using variable-centred analyses. Person-centred longitudinal research is needed to identify combined effects of sleep and circadian characteristics while allowing for change over time. We aimed to classify individuals into sleep-circadian statuses (aim 1), determine whether they transitioned between statuses over time (aim 2), and explore associated covariates and health outcomes (aim 3). Young adults (N = 151) wore smartwatches continuously for 6 months. Sleep (total sleep time, wake after sleep onset) and circadian rest-activity cycle indicators (interdaily stability, intradaily variability, relative amplitude) were derived from acceleration data and aggregated into person-means for months 1, 3, and 6. These values were entered into a latent transition model for aims 1 and 2. Multinomial logistic regressions, ANOVA, and ANCOVA addressed aim 3. Four statuses were extracted (entropy = 0.88): optimal sleepers, restless sleepers, short sleepers, and nappers. 10%-13% of optimal sleepers and 21% of restless sleepers became nappers, 7%-18% of nappers transitioned to other statuses, and 94%-100% of short sleepers remained unchanged. Males were more likely than females to be short versus optimal sleepers (p < 0.001). Restless sleepers had more physical dysfunction than nappers and short sleepers (p = 0.014, 0.022), while short sleepers reported more excessive sleepiness than optimal sleepers and nappers (p = 0.006, 0.060). This study identified four sleep-circadian statuses and found evidence for change over time. Our longitudinal person-centred approach could help inform the development of tailored diagnostic guidelines for sleep and circadian-related disorders that fluctuate within-individuals.

Moving Beyond Mean Levels: Associations Between Subject-Level Variability in Psychological Determinants and Physical Activity in Older Adults

BACKGROUND

Research investigating the psychological determinants of physical activity (PA) tends to conceptualize determinants as stable, trait-like factors. Growing evidence suggests that people and the processes that regulate people's behavior fluctuate over short timescales (eg, hours and days). This study explores the extent to which subject-level variability (vs stability) in determinants of PA, as well as the interaction between subject-level mean and variability in those determinants, is associated with moderate- to vigorous-intensity PA (MVPA) in older adults.

METHODS

Older adults (N = 202) enrolled in a measurement burst design study with 3 data collection waves occurring over a 1-year period. Each data collection wave consisted of accelerometers and ecological momentary assessment to capture MVPA and psychological determinants of MVPA, respectively. Mixed-effects location scale modeling was first used to estimate subject-level means and variability in psychological determinants. These estimates were then used as predictors of daily MVPA using multilevel modeling.

RESULTS

Subject-level variability in PA intentions (β = 0.199, SE = 0.062, P = .001), self-efficacy (β = 0.133, SE = 0.064, P = .037), and planning (β = 0.154, SE = 0.062, P = .014) were positively associated with daily MVPA. Associations between subject-level variability in PA intentions and self-efficacy decreased in strength, becoming nonsignificant at higher mean levels of PA intentions (β = -0.147, SE = 0.062, P = .018) and self-efficacy (β = -0.116, SE = 0.063, P = .062).

CONCLUSIONS

Greater subject-level variability in psychological determinants may be adaptive for PA engagement, especially among older adults experiencing low levels of those determinants. Moving beyond mean levels to include subject-level variability in psychological determinants of PA may help to improve our understanding of the processes that drive PA engagement.

Ask Less, Learn More: Adapting Ecological Momentary Assessment Survey Length by Modeling Question-Answer Information Gain

Ecological momentary assessment (EMA) is an approach to collect self-reported data repeatedly on mobile devices in natural settings. EMAs allow for temporally dense, ecologically valid data collection, but frequent interruptions with lengthy surveys on mobile devices can burden users, impacting compliance and data quality. We propose a method that reduces the length of each EMA question set measuring interrelated constructs, with only modest information loss. By estimating the potential information gain of each EMA question using question-answer prediction models, this method can prioritize the presentation of the most informative question in a question-by-question sequence and skip uninformative questions. We evaluated the proposed method by simulating question omission using four real-world datasets from three different EMA studies. When compared against the random question omission approach that skips 50% of the questions, our method reduces imputation errors by 15%-52%. In surveys with five answer options for each question, our method can reduce the mean survey length by 34%-56% with a real-time prediction accuracy of 72%-95% for the skipped questions. The proposed method may either allow more constructs to be surveyed without adding user burden or reduce response burden for more sustainable longitudinal EMA data collection.

Burden and Inattentive Responding in a 12-Month Intensive Longitudinal Study: Interview Study Among Young Adults

BACKGROUND

Intensive longitudinal data (ILD) collection methods have gained popularity in social and behavioral research as a tool to better understand behavior and experiences over time with reduced recall bias. Engaging participants in these studies over multiple months and ensuring high data quality are crucial but challenging due to the potential burden of repeated measurements. It is suspected that participants may engage in inattentive responding (IR) behavior to combat burden, but the processes underlying this behavior are unclear as previous studies have focused on the barriers to compliance rather than the barriers to providing high-quality data.

OBJECTIVE

This study aims to broaden researchers' knowledge about IR during ILD studies using qualitative analysis and uncover the underlying IR processes to aid future hypothesis generation.

METHODS

We explored the process of IR by conducting semistructured qualitative exit interviews with 31 young adult participants (aged 18-29 years) who completed a 12-month ILD health behavior study with daily evening smartphone-based ecological momentary assessment (EMA) surveys and 4-day waves of hourly EMA surveys. The interviews assessed participants' motivations, the impact of time-varying contexts, changes in motivation and response patterns over time, and perceptions of attention check questions (ACQs) to understand participants' response patterns and potential factors leading to IR.

RESULTS

Thematic analysis revealed 5 overarching themes on factors that influence participant engagement: (1) friends and family also had to tolerate the frequent surveys, (2) participants tried to respond to surveys quickly, (3) the repetitive nature of surveys led to neutral responses, (4) ACQs within the surveys helped to combat overly consistent response patterns, and (5) different motivations for answering the surveys may have led to different levels of data quality.

CONCLUSIONS

This study aimed to examine participants' perceptions of the quality of data provided in an ILD study to contribute to the field's understanding of engagement. These findings provide insights into the complex process of IR and participant engagement in ILD studies with EMA. The study identified 5 factors influencing IR that could guide future research to improve EMA survey design. The identified themes offer practical implications for researchers and study designers, including the importance of considering social context, the consideration of dynamic motivations, and the potential benefit of including ACQs as a technique to reduce IR and leveraging the intrinsic motivators of participants. By incorporating these insights, researchers might maximize the scientific value of their multimonth ILD studies through better data collection protocols.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/36666.

Rationale, Design, and Baseline Characteristics of Participants in the Health@NUS mHealth Augmented Cohort Study Examining Student-to-Work Life Transition: Protocol for a Prospective Cohort Study

BACKGROUND

Integration of mobile health data collection methods into cohort studies enables the collection of intensive longitudinal information, which gives deeper insights into individuals' health and lifestyle behavioral patterns over time, as compared to traditional cohort methods with less frequent data collection. These findings can then fill the gaps that remain in understanding how various lifestyle behaviors interact as students graduate from university and seek employment (student-to-work life transition), where the inability to adapt quickly to a changing environment greatly affects the mental well-being of young adults.

OBJECTIVE

This paper aims to provide an overview of the study methodology and baseline characteristics of participants in Health@NUS, a longitudinal study leveraging mobile health to examine the trajectories of health behaviors, physical health, and well-being, and their diverse determinants, for young adults during the student-to-work life transition.

METHODS

University students were recruited between August 2020 and June 2022 in Singapore. Participants would complete biometric assessments and questionnaires at 3 time points (baseline, 12-, and 24-month follow-up visits) and use a Fitbit smartwatch and smartphone app to continuously collect physical activity, sedentary behavior, sleep, and dietary data over the 2 years. Additionally, up to 12 two-week-long bursts of app-based ecological momentary surveys capturing lifestyle behaviors and well-being would be sent out among the 3 time points.

RESULTS

Interested participants (n=1556) were screened for eligibility, and 776 participants were enrolled in the study between August 2020 and June 2022. Participants were mostly female (441/776, 56.8%), of Chinese ethnicity (741/776, 92%), undergraduate students (759/776, 97.8%), and had a mean BMI of 21.9 (SD 3.3) kg/m2, and a mean age of 22.7 (SD 1.7) years. A substantial proportion were overweight (202/776, 26.1%) or obese (42/776, 5.4%), had indicated poor mental well-being (World Health Organization-5 Well-Being Index ≤50; 291/776, 37.7%), or were at higher risk for psychological distress (Kessler Psychological Distress Scale ≥13; 109/776, 14.1%).

CONCLUSIONS

The findings from this study will provide detailed insights into the determinants and trajectories of health behaviors, health, and well-being during the student-to-work life transition experienced by young adults.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05154227; https://clinicaltrials.gov/study/NCT05154227.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/56749.

Engineering Virtuous health habits using Emotion and Neurocognition: Flexibility for Lifestyle Optimization and Weight management (EVEN FLOW)

Interventions to preserve functional independence in older adults are critically needed to optimize 'successful aging' among the large and increasing population of older adults in the United States. For most aging adults, the management of chronic diseases is the most common and impactful risk factor for loss of functional independence. Chronic disease management inherently involves the learning and adaptation of new behaviors, such as adopting or modifying physical activity habits and managing weight. Despite the importance of chronic disease management in older adults, vanishingly few individuals optimally manage their health behavior in the service of chronic disease stabilization to preserve functional independence. Contemporary conceptual models of chronic disease management and health habit theory suggest that this lack of optimal management may result from an underappreciated distinction within the health behavior literature: the behavioral domains critical for initiation of new behaviors (Initiation Phase) are largely distinct from those that facilitate their maintenance (Maintenance Phase). Psychological factors, particularly experiential acceptance and trait levels of openness are critical to engagement with new health behaviors, willingness to make difficult lifestyle changes, and the ability to tolerate aversive affective responses in the process. Cognitive factors, particularly executive function, are critical to learning new skills, using them effectively across different areas of life and contextual demands, and updating of skills to facilitate behavioral maintenance. Emerging data therefore suggests that individuals with greater executive function are better able to sustain behavior changes, which in turn protects against cognitive decline. In addition, social and structural supports of behavior change serve a critical buffering role across phases of behavior change. The present review attempts to address these gaps by proposing a novel biobehavioral intervention framework that incorporates both individual-level and social support system-level variables for the purpose of treatment tailoring. Our intervention framework triangulates on the central importance of self-regulatory functioning, proposing that both cognitive and psychological mechanisms ultimately influence an individuals' ability to engage in different aspects of self-management (individual level) in the service of maintaining independence. Importantly, the proposed linkages of cognitive and affective functioning align with emerging individual difference frameworks, suggesting that lower levels of cognitive and/or psychological flexibility represent an intermediate phenotype of risk. Individuals exhibiting self-regulatory lapses either due to the inability to regulate their emotional responses or due to the presence of executive functioning impairments are therefore the most likely to require assistance to preserve functional independence. In addition, these vulnerabilities will be more easily observable for individuals requiring greater complexity of self-management behavioral demands (e.g. complexity of medication regimen) and/or with lesser social support. Our proposed framework also intuits several distinct intervention pathways based on the profile of self-regulatory behaviors: we propose that individuals with intact affect regulation and impaired executive function will preferentially respond to 'top-down' training approaches (e.g., strategy and process work). Individuals with intact executive function and impaired affect regulation will respond to 'bottom-up' approaches (e.g., graded exposure). And individuals with impairments in both may require treatments targeting caregiving or structural supports, particularly in the context of elevated behavioral demands.

Evaluating the Effects of Rewards and Schedule Length on Response Rates to Ecological Momentary Assessment Surveys: Randomized Controlled Trials

BACKGROUND

Ecological momentary assessments (EMAs) are short, repeated surveys designed to collect information on experiences in real-time, real-life contexts. Embedding periodic bursts of EMAs within cohort studies enables the study of experiences on multiple timescales and could greatly enhance the accuracy of self-reported information. However, the burden on participants may be high and should be minimized to optimize EMA response rates.

OBJECTIVE

We aimed to evaluate the effects of study design features on EMA response rates.

METHODS

Embedded within an ongoing cohort study (Health@NUS), 3 bursts of EMAs were implemented over a 7-month period (April to October 2021). The response rate (percentage of completed EMA surveys from all sent EMA surveys; 30-42 individual EMA surveys sent/burst) for each burst was examined. Following a low response rate in burst 1, changes were made to the subsequent implementation strategy (SMS text message announcements instead of emails). In addition, 2 consecutive randomized controlled trials were conducted to evaluate the efficacy of 4 different reward structures (with fixed and bonus components) and 2 different schedule lengths (7 or 14 d) on changes to the EMA response rate. Analyses were conducted from 2021 to 2022 using ANOVA and analysis of covariance to examine group differences and mixed models to assess changes across all 3 bursts.

RESULTS

Participants (N=384) were university students (n=232, 60.4% female; mean age 23, SD 1.3 y) in Singapore. Changing the reward structure did not significantly change the response rate (F3,380=1.75; P=.16). Changing the schedule length did significantly change the response rate (F1,382=6.23; P=.01); the response rate was higher for the longer schedule (14 d; mean 48.34%, SD 33.17%) than the shorter schedule (7 d; mean 38.52%, SD 33.44%). The average response rate was higher in burst 2 and burst 3 (mean 50.56, SD 33.61 and mean 48.34, SD 33.17, respectively) than in burst 1 (mean 25.78, SD 30.12), and the difference was statistically significant (F2,766=93.83; P<.001).

CONCLUSIONS

Small changes to the implementation strategy (SMS text messages instead of emails) may have contributed to increasing the response rate over time. Changing the available rewards did not lead to a significant difference in the response rate, whereas changing the schedule length did lead to a significant difference in the response rate. Our study provides novel insights on how to implement EMA surveys in ongoing cohort studies. This knowledge is essential for conducting high-quality studies using EMA surveys.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05154227; https://clinicaltrials.gov/ct2/show/NCT05154227.