Modelling multiple health behavior change with network analyses: results from a one-year study conducted among overweight and obese adults

The Digital Therapeutics Real-World Evidence Framework: An Approach for Guiding Evidence-Based Digital Therapeutics Design, Development, Testing, and Monitoring

Digital therapeutics (DTx) are a promising way to provide safe, effective, accessible, sustainable, scalable, and equitable approaches to advance individual and population health. However, developing and deploying DTx is inherently complex in that DTx includes multiple interacting components, such as tools to support activities like medication adherence, health behavior goal-setting or self-monitoring, and algorithms that adapt the provision of these according to individual needs that may change over time. While myriad frameworks exist for different phases of DTx development, no single framework exists to guide evidence production for DTx across its full life cycle, from initial DTx development to long-term use. To fill this gap, we propose the DTx real-world evidence (RWE) framework as a pragmatic, iterative, milestone-driven approach for developing DTx. The DTx RWE framework is derived from the 4-phase development model used for behavioral interventions, but it includes key adaptations that are specific to the unique characteristics of DTx. To ensure the highest level of fidelity to the needs of users, the framework also incorporates real-world data (RWD) across the entire life cycle of DTx development and use. The DTx RWE framework is intended for any group interested in developing and deploying DTx in real-world contexts, including those in industry, health care, public health, and academia. Moreover, entities that fund research that supports the development of DTx and agencies that regulate DTx might find the DTx RWE framework useful as they endeavor to improve how DTxcan advance individual and population health.

A Network Analysis of Multiple Preconception Health Behaviors in Chinese Women

BACKGROUND

A healthy preconception lifestyle, consisting of multiple health behaviors, is crucial for preventing adverse health outcomes in mothers and offspring. Although knowledge about the pattern of inter-behavior relations may provide insights for nudging multiple health behavior changes, this has not been adequately explored in the existing literature. Adopting a network perspective, the present study conceptualized multiple health behaviors as a behavior network (i.e., behaviors as nodes, inter-behavior relations as edges) and utilized network analysis to investigate the pattern of interrelations of preconception health behaviors in a large sample of Chinese women.

METHOD

We used the data of a population-based cohort study in China to estimate the behavior network. An analytic sample included 41,127 Chinese women who were surveyed about their adoptions of multiple health behaviors during the preconception period.

RESULTS

Network analysis revealed a relatively dense behavior network and visualized the network structure of multiple preconception health behaviors. Subsequent centrality analysis identified three central behaviors (i.e., avoiding second- or third-hand smoke, reducing psychosocial stress, and reducing alcohol) that had distinctively stronger connections to other behaviors.

CONCLUSIONS

Preconception health behaviors were strongly interconnected, and certain behaviors had stronger influences than others within the behavior network. Our findings highlight the strong inter-relatedness of preconception health behaviors. This study also encourages targeting the three central behaviors in preconception lifestyle promotions because this may bring more secondary improvements on other non-targeted behaviors and thereby achieve comprehensive lifestyle change.

Within-Person Temporal Associations Among Self-Reported Physical Activity, Sleep, and Well-Being in College Students

OBJECTIVE

A holistic understanding of the naturalistic dynamics among physical activity, sleep, emotions, and purpose in life as part of a system reflecting wellness is key to promoting well-being. The main aim of this study was to examine the day-to-day dynamics within this wellness system.

METHODS

Using self-reported emotions (happiness, sadness, anger, anxiousness) and physical activity periods collected twice per day, and daily reports of sleep and purpose in life via smartphone experience sampling, more than 28 days as college students ( n = 226 young adults; mean [standard deviation] = 20.2 [1.7] years) went about their daily lives, we examined day-to-day temporal and contemporaneous dynamics using multilevel vector autoregressive models that consider the network of wellness together.

RESULTS

Network analyses revealed that higher physical activity on a given day predicted an increase of happiness the next day. Higher sleep quality on a given night predicted a decrease in negative emotions the next day, and higher purpose in life predicted decreased negative emotions up to 2 days later. Nodes with the highest centrality were sadness, anxiety, and happiness in the temporal network and purpose in life, anxiety, and anger in the contemporaneous network.

CONCLUSIONS

Although the effects of sleep and physical activity on emotions and purpose in life may be shorter term, a sense of purpose in life is a critical component of wellness that can have slightly longer effects, bleeding into the next few days. High-arousal emotions and purpose in life are central to motivating people into action, which can lead to behavior change.

Exploring the longitudinal clustering of lifestyle behaviors, social determinants of health, and depression

Lifestyle behaviors such as exercise, sleep, smoking, diet, and social interaction are associated with depression. This study aimed to model the complex relationships between lifestyle behaviors and depression and among the lifestyle behaviors. Data from three waves of the Midlife in the United States study were used, involving 6898 adults. Network models revealed associations between the lifestyle behaviors and depression, with smoker status being strongly associated with depression. Depression, smoker status, age, time, and exercise were some of the most central components of the networks. Future lifestyle intervention research might prioritize specific behaviors based on these associations and centrality indices.

Thinking Health-related Behaviors in a Climate Change Context: A Narrative Review

BACKGROUND

Human activities have changed the environment so profoundly over the past two centuries that human-induced climate change is now posing serious health-related threats to current and future generations. Rapid action from all scientific fields, including behavioral medicine, is needed to contribute to both mitigation of, and adaption to, climate change.

PURPOSE

This article aims to identify potential bi-directional associations between climate change impacts and health-related behaviors, as well as a set of key actions for the behavioral medicine community.

METHODS

We synthesized the existing literature about (i) the impacts of rising temperatures, extreme weather events, air pollution, and rising sea level on individual behaviors (e.g., eating behaviors, physical activity, sleep, substance use, and preventive care) as well as the structural factors related to these behaviors (e.g., the food system); and (ii) the concurrent positive and negative roles that health-related behaviors can play in mitigation and adaptation to climate change.

RESULTS

Based on this literature review, we propose a first conceptual model of climate change and health-related behavior feedback loops. Key actions are proposed, with particular consideration for health equity implications of future behavioral interventions. Actions to bridge the fields of behavioral medicine and climate sciences are also discussed.

CONCLUSIONS

We contend that climate change is among the most urgent issues facing all scientists and should become a central priority for the behavioral medicine community.

Day-to-day associations between sleep and physical activity: a set of person-specific analyses in adults with overweight and obesity

The objective of the present study was to estimate whether physical activity on one day was associated with both sleep quality and quantity the following night and to examine to what extent sleep on one night was associated with physical activity the next day. We collected data from 33 young adults who were overweight or obese and consistently wore a Fitbit Charge 3. A total of 7094 days and nights were analyzed. Person-specific models were conducted to test the bi-directional associations for each participant separately. Results suggest an absence of association between steps and sleep efficiency in the two directions. More heterogeneous results were observed for the association between steps and total sleep time, with 19 participants (58%) showing a negative association between total sleep time and next day steps, and 9 (27%) showing a negative association between steps and next day total sleep time. Taken together, these results suggest a potential conflicting association between total sleep time and physical activity for some participants. Pre- and post-print doi: https://doi.org/10.31236/osf.io/nfjqv ; supplemental material: https://osf.io/y7nxg/ .

Association between Physical Activity, Sedentary Behaviors, Sleep, Diet, and Adiposity among Children and Adolescents in China

INTRODUCTION

Physical activity (PA), sedentary behaviors (SB), sleep, and diet are related to adiposity among children and adolescents. However, there may be interactions between PA, SB, sleep, and diet, and these lifestyle behaviors may work together to affect body weight. The purpose of this study was to explore the impact of multiple lifestyle behaviors of PA, SB, sleep, and diet on childhood adiposity (body mass index z-score and overweight/obesity), and to investigate the effect of meeting multiple guidelines on adiposity among children and adolescents in China.

METHODS

Cross-sectional results were based on 28,048 children aged 6-17 years from the China National Nutrition and Health Surveillance in 2010-2012. Information about PA, SB, and sleep was measured through interview-administered questionnaire. Dietary intake was assessed with food frequency questionnaire. The associations between multiple lifestyle behaviors and BMI z-score and overweight/obese were examined.

RESULTS

The prevalence of overweight/obesity in the participants was 19.2%. The average time of moderate-to-vigorous PA (MVPA), leisure SB, and sleep was 76.7 ± 45.5 min, 2.9 ± 1.4 h, and 8.5 ± 1.1 h per day, respectively. The China Dietary Guidelines Index for Youth (CDGI-Y) score was 62.6 ± 11.0. Sleep duration and diet score were negative associated with BMI z-score (both p < 0.001). MVPA and SB time were positive associated with BMI z-score (p = 0.041, 0.004). Meeting the SB, sleep, and diet guidelines had a lower BMI z-score (all p < 0.01) and lower odds of overweight/obesity (all p < 0.05). There were significant interactions between PA and diet. Compared with meeting no guidelines, those who met multiple guidelines had a lower risk of overweight/obesity (all p < 0.01). The more guidelines the participants met, the lower odds of overweight/obesity (p for trend <0.001).

CONCLUSIONS

PA, SB, sleep, and diet are important behaviors associated with adiposity among children and adolescents. Attaining adequate amounts of appropriate multiple behaviors provided an additional benefit. It is important for children to meet recommended behavioral guidelines or recommendations. Interventions that aim to improve awareness of and compliance with these guidelines are needed in future.

Association between Fruit and Vegetable Intake and Physical Activity among Breast Cancer Survivors: A Longitudinal Study

This study examines the association between rates of change in daily fruit and vegetable intake and in weekly levels of moderate-to-vigorous intensity physical activity (MVPA) over a 15-month period in women following primary treatment completion for breast cancer. Breast cancer survivors (N = 199) self-reported fruit and vegetable intake and wore an accelerometer for 7 consecutive days to measure levels of MVPA on five occasions every 3 months. Multivariate latent growth modeling revealed that the rate of change in fruit and vegetable intake was not associated with the rate of change in levels of MVPA. Baseline (Mean = 3.46 months post-treatment) levels of MVPA were not associated with the rate of change of daily fruit and vegetable intake; likewise, baseline fruit and vegetable intake was not associated with the rate of change in levels of MVPA. Behavioral interventions promoting fruit and vegetable intake should not be assumed to yield concomitant effects in promoting MVPA or vice versa.

Evaluation of Latent Models Assessing Physical Fitness and the Healthy Eating Index in Community Studies: Time-, Sex-, and Diabetes-Status Invariance

Accurate measurement requires assessment of measurement equivalence/invariance (ME/I) to demonstrate that the tests/measurements perform equally well and measure the same underlying constructs across groups and over time. Using structural equation modeling, the measurement properties (stability and responsiveness) of intervention measures used in a study of metabolic syndrome (MetS) treatment in primary care offices, were assessed. The primary study (N = 293; mean age = 59 years) had achieved 19% reversal of MetS overall; yet neither diet quality nor aerobic capacity were correlated with declines in cardiovascular disease risk. Factor analytic methods were used to develop measurement models and factorial invariance were tested across three time points (baseline, 3-month, 12-month), sex (male/female), and diabetes status for the Canadian Healthy Eating Index (2005 HEI-C) and several fitness measures combined (percentile VO₂ max from submaximal exercise, treadmill speed, curl-ups, push-ups). The model fit for the original HEI-C was poor and could account for the lack of associations in the primary study. A reduced HEI-C and a 4-item fitness model demonstrated excellent model fit and measurement equivalence across time, sex, and diabetes status. Increased use of factor analytic methods increases measurement precision, controls error, and improves ability to link interventions to expected clinical outcomes.

Goal setting and achievement for walking: A series of N-of-1 digital interventions

OBJECTIVE

Despite evidence that goal setting is valuable for physical activity promotion, recent studies highlighted a potential oversimplification in the application of this behavior change technique. While more difficult performance goals might trigger higher physical activity levels, higher performance goals might concurrently be more difficult to achieve, which could reduce long-term motivation. This study examined (a) the association between performance goal difficulty and physical activity and (b) the association between performance goal difficulty and goal achievement.

METHOD

This study used data from an e-Health intervention among inactive overweight adults (n = 20). The study duration included a 2-week baseline period and an intervention phase of 80 days. During the intervention, participants received a daily step goal experimentally manipulated by taking participants' baseline physical activity median (i.e., number of steps) multiplied by a pseudorandom factor ranging from 1 to 2.6. A continuous measure of goal achievement was inferred for each day by dividing the daily number of steps by the goal prescribed that day. Linear and generalized additive models were fit for each participant.

RESULTS

The results confirm that, for a majority of the participants involved in the study, performance goal difficulty was positively and significantly associated with physical activity (n = 14), but, concurrently, negatively and significantly associated with goal achievement (n = 19). These associations were mainly linear.

CONCLUSION

At the daily level, setting a higher physical activity goal leads to engaging in higher physical activity levels, but concurrently lower goal achievement. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Lifestyle behaviors, psychological distress, and well-being: A daily diary study

RATIONALE

Many lifestyle behaviors such as diet, exercise, social interaction, and substance use are related to physical and mental health. Less understood are the day-to-day associations of these behaviors with both psychological distress, well-being, and with each other.

OBJECTIVE

This study investigated how a number of common lifestyle behaviors were associated with psychological distress and well-being using a daily diary study with multilevel modeling. Associations among behaviors were analyzed with multilevel mediation and network models.

METHODS

An online participant pool consisting of seventy-six adults (age range: 19-64; mean age: 40.29; 58% female) completed daily diary surveys over 14 days and reported their engagement in lifestyle behaviors, psychological distress, hedonic well-being, and eudaimonic well-being.

RESULTS

Time spent in social interaction was the most consistent within-person correlate of psychological distress and well-being. The association between daily time in nature and well-being was mediated by social interaction and exercise. Network models found within-person associations among the lifestyle behaviors.

CONCLUSION

The results indicate that social interaction may be an especially important lifestyle behavior to consider when promoting well-being. Future research should recognize that daily fluctuations in many lifestyle behaviors cluster together.