Reconsidering the experience machine: Self-reported versus objective measures of physical activity to increase positive affect

The Within-Subject Association of Physical Behavior and Affective Well-Being in Everyday Life: A Systematic Literature Review

BACKGROUND

The interplay of physical activity (PA) with affective well-being (AWB) is highly critical to both health behaviors and health outcomes. Current prominent theories presume AWB to be crucial for PA maintenance, and PA is evidenced to foster mental health. However, thus far, PA-AWB associations have mainly been researched in laboratory settings and with interventional designs, but the everyday life perspective had not been focused on, mostly due to technological limitations. In the course of digitization, the number of studies using device-based methods to research the within-subject association of physical activity and affective well-being (PA-AWB) under ecological valid conditions increased rapidly, but a recent comprehensive systematic review of evidence across populations, age groups, and distinct AWB components remained inconclusive.

OBJECTIVES

Therefore, we aimed to firstly review daily-life studies that assessed intensive longitudinal device-based (e.g., electronic smartphone diaries and accelerometry) and real-time PA-AWB data, secondly to develop and apply a quality assessment tool applicable to those studies, and thirdly to discuss findings and draw implications for research and practice.

METHODS

To this end, the literature was searched in three databases (Web of Science, PubMed, Scopus) up to November 2022. The systematic review followed the PRISMA guidelines and had been pre-registered (PROSPERO id: CRD42021277327). A modified quality assessment tool was developed to illustrate the risk of bias of included studies.

RESULTS

The review of findings showed that, in general, already short PA bouts in everyday life, which clearly differ from structured exercise sessions, are positively associated with AWB. In particular, feelings of energy relate to incidental (non-exercise and unstructured) activity, and PA-AWB associations depend on population characteristics. The quality assessment revealed overall moderate study quality; however, the methods applied were largely heterogeneous between investigations. Overall, the reviewed evidence on PA-AWB associations in everyday life is ambiguous; for example, no clear patterns of directions and strengths of PA-AWB relationships depending on PA and AWB components (such as intensity, emotions, affect, mood) emerged.

CONCLUSIONS

The reviewed evidence can fuel discussions on whether the World Health Organization's notion "every move counts" may be extended to everyday life AWB. Concurrently, the PA-AWB relationship findings endorse prominent theories highlighting the critical role of AWB in everyday PA engagement and maintenance. However, the review also clearly highlights the need to advance and harmonize methodological approaches for more fine-grained investigations on which specific PA/AWB characteristics, contextual factors, and biological determinants underly PA-AWB associations in everyday life. This will enable the field to tackle pressing challenges such as the issue of causality of PA-AWB associations, which will help to shape and refine existing theories to ultimately predict and improve health behavior, thereby feeding into precision medicine approaches.

Effects of a digital self-control intervention to increase physical activity in middle-aged adults

The goal of this study was to test the effects of a 7-week digital self-control intervention to increase physical activity using a two-arm randomized controlled trial. The self-control treatment group showed greater increases in self-reported physical activity (MET's) than the comparison group. Both groups significantly increased their daily steps and self-control. Participants with higher initial levels of conscientiousness were better able to increase their daily steps during the intervention and participants who increased more in self-control showed greater increases in MET's. These moderation effects were more pronounced in the self-control treatment group as compared to the comparison group. This study shows that the effects of physical activity interventions may depend on personality characteristics and outcomes may be improved when individual differences are considered and targeted.

Stress buffering after physical activity engagement: An experience sampling study

OBJECTIVES

While encountering daily hassles is a normative experience, it poses a threat to individuals' daily affective well-being. However, physical activity engagement may help to reduce the current stress-related impact on affective well-being (i.e. stress buffering), which we investigate in this study. Furthermore, we examined the possible moderating role of people's global stress context (i.e. exposure to major life events and chronic stress) on this within-person stress-buffering effect.

DESIGN

We approached these ideas using six-times-a-day experience sampling assessments over a period of 22 days.

METHODS

Drawing on a broad national sample of 156 middle-aged adults from the EE-SOEP-IS study, we aimed to elucidate the naturally occurring within-person dynamics of current stress, physical activity engagement, and momentary affect within individuals' everyday lives. Major life events and chronic stress were measured as between-person variables.

RESULTS

Multilevel analyses revealed significant within-person associations of current stress and physical activity engagement with momentary affect. Stress-related negative affect was lower when individuals engaged in physical activity, in accordance with the idea of a within-person stress-buffering effect of physical activity engagement. For individuals exposed to more severe major life events, the stress-buffering effect of physical activity engagement for negative affect was lower. Chronic stress did not moderate the within-person stress-buffering effect.

CONCLUSIONS

Overall, results add to the existing literature that links physical activity to increased stress resilience and emphasizes the need for taking the global between-person stress context into account.

NET-RMDs study: networks of fatigue and pain in rheumatic and musculoskeletal diseases - protocol for an international cross-sectional study

INTRODUCTION

Fatigue and pain are the main symptoms of rheumatic and musculoskeletal diseases (RMDs). Healthcare professionals have a primary role in helping patients to manage both these symptoms, which are part of a complex network of co-occurring factors including sleep problems, psychological distress, social support, body weight, diet, inactive lifestyle and disease activity. The patterns of relationships (networks) between these factors and these symptoms, fatigue and pain, are largely unknown. The current proposal aims to reveal them using network estimation techniques. We will also consider differences in networks for subgroups of people with (1) different RMDs and (2) different clusters (profiles) of biopsychosocial factors.

METHODS AND ANALYSIS

Adults with at least one RMD will be recruited to this online cross-sectional observational project. To provide a complete overview, a large sample size from different countries will be included. A brief online survey, using 0-10 numeric rating scales will measure, for the past month, levels of fatigue and pain as well as scores on seven biopsychosocial factors. These factors were derived from literature and identified by interviews with patients, health professionals and rheumatologists. Using this input, the steering committee of the project decided the factors to be measured giving priority to those that can be modified in self-management support in community health centres worldwide. Network estimation techniques are used to detect the complex patterns of relationships between these biopsychosocial factors, fatigue and pain; and how these differ for subgroups of people with different RMDs and profiles.

ETHICS AND DISSEMINATION

Ethical approval of national Institutional Review Boards was obtained. The online survey includes an information letter and informed consent form. The findings will be disseminated via conferences and publications in peer-reviewed scientific journals, while public media channels will be used to inform people with RMDs and other interested parties.

Enjoying nature, exercise, social interaction, and affect: A daily diary study

This study investigated the pathways linking daily nature enjoyment to affect by testing whether the associations would be fully explained by exercise and social interaction. Participants (N = 782; 55.6% female; age 25-74, Mage = 47.9) from the Midlife in the United States (MIDUS) refresher study completed surveys across 8 days. Multilevel models indicated that enjoying nature with others tended to predict affect at the within-person level, while enjoying nature alone did not. However, enjoying nature alone did predict affect at the between-person level. Lastly, many of these associations remained, even while controlling for exercise and social interaction.

The Impact of Wearable Technologies in Health Research: Scoping Review

Background

Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research.

Objective

In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research.

Methods

We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing.

Results

We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations—wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%).

Conclusions

Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.