Effect of Adding Online Social Support Tools to an Adult Walking Program: A Pilot Randomized Controlled Trial

What Effect Do Goal Setting Interventions Have on Physical Activity and Psychological Outcomes in Insufficiently Active Adults? A Systematic Review and Meta-Analysis

BACKGROUND

Goal setting is commonly used for promoting physical activity (PA) among insufficiently active individuals. Previous reviews have analyzed the effects of goal setting on PA, but the purpose of this systematic review was to examine the concurrent effects of goal setting on PA and psychological outcomes in insufficiently active individuals to support interventions aiming to produce sustained PA behavior change.

METHODS

In this review (PROSPERO: CRD42021243970), we identified 13 studies with 1208 insufficiently active adults that reported the effects of goal-setting interventions (range 3-24 wk) on both PA and psychological outcomes (eg, self-efficacy, motivation, and affect). We used meta-analysis and narrative synthesis to analyze these effects.

RESULTS

All goals used in the included studies were specific goals. Setting specific goals had a large, positive effect on PA (g [standard mean difference] = 1.11 [P < .001]; 95% confidence interval, 0.74-1.47), but only a small, positive effect on the combined psychological outcomes (g [standard mean difference] = 0.25 [P < .001]; 95% CI, 0.10-0.40). Moderator analyses revealed that interventions that did not reward participants had a significantly greater effect on PA than interventions that did provide rewards (g = 1.30 vs 0.60, respectively, P ≤ .003). No other significant moderators were found.

CONCLUSION

Our review offers initial insight into the long-term effects of specific goals on PA and psychological outcomes in insufficiently active adults. Further research that examines the PA and psychological effects of goal-setting interventions and investigates a wider range of goal types could develop a stronger evidence base to inform intervention for insufficiently active individuals.

Do physical activity interventions combining self-monitoring with other components provide an additional benefit compared with self-monitoring alone? A systematic review and meta-analysis

Objective

To determine the net effect of different physical activity intervention components on step counts in addition to self-monitoring.

Design

A systematic review with meta-analysis and meta-regression.

Data sources

Five databases (PubMed, Scopus, Web of Science, ProQuest and Discus) were searched from inception to May 2022. The database search was complemented with backward and forward citation searches and search of the references from relevant systematic reviews.

Eligibility criteria

Randomised controlled trials comparing an intervention using self-monitoring (active control arm) with an intervention comprising the same treatment PLUS any additional component (intervention arm).

Data extraction and synthesis

The effect measures were mean differences in daily step count. Meta-analyses were performed using random-effects models, and effect moderators were explored using univariate and multivariate meta-regression models.

Results

Eighty-five studies with 12 057 participants were identified, with 75 studies included in the meta-analysis at postintervention and 24 at follow-up. At postintervention, the mean difference between the intervention and active control arms was 926 steps/day (95% CI 651 to 1201). At a follow-up, the mean difference was 413 steps/day (95% CI 210 to 615). Interventions with a prescribed goal and involving human counselling, particularly via phone/video calls, were associated with a greater mean difference in the daily step count than interventions with added print materials, websites, smartphone apps or incentives.

Conclusion

Physical activity interventions that combine self-monitoring with other components provide an additional modest yet sustained increase in step count compared with self-monitoring alone. Some forms of counselling, particularly remote phone/video counselling, outperformed other intervention components, such as websites and smartphone apps.

PROSPERO registered number

CRD42020199482.

The Design and Development of a Personalized Leisure Time Physical Activity Application Based on Behavior Change Theories, End-User Perceptions, and Principles From Empirical Data Mining

Introduction: Many adults do not reach the recommended physical activity (PA) guidelines, which can lead to serious health problems. A promising method to increase PA is the use of smartphone PA applications. However, despite the development and evaluation of multiple PA apps, it remains unclear how to develop and design engaging and effective PA apps. Furthermore, little is known on ways to harness the potential of artificial intelligence for developing personalized apps. In this paper, we describe the design and development of the Playful data-driven Active Urban Living (PAUL): a personalized PA application.

Methods: The two-phased development process of the PAUL apps rests on principles from the behavior change model; the Integrate, Design, Assess, and Share (IDEAS) framework; and the behavioral intervention technology (BIT) model. During the first phase, we explored whether location-specific information on performing PA in the built environment is an enhancement to a PA app. During the second phase, the other modules of the app were developed. To this end, we first build the theoretical foundation for the PAUL intervention by performing a literature study. Next, a focus group study was performed to translate the theoretical foundations and the needs and wishes in a set of user requirements. Since the participants indicated the need for reminders at a for-them-relevant moment, we developed a self-learning module for the timing of the reminders. To initialize this module, a data-mining study was performed with historical running data to determine good situations for running.

Results: The results of these studies informed the design of a personalized mobile health (mHealth) application for running, walking, and performing strength exercises. The app is implemented as a set of modules based on the persuasive strategies “monitoring of behavior,” “feedback,” “goal setting,” “reminders,” “rewards,” and “providing instruction.” An architecture was set up consisting of a smartphone app for the user, a back-end server for storage and adaptivity, and a research portal to provide access to the research team.

Conclusions: The interdisciplinary research encompassing psychology, human movement sciences, computer science, and artificial intelligence has led to a theoretically and empirically driven leisure time PA application. In the current phase, the feasibility of the PAUL app is being assessed.

Unraveling Mobile Health Exercise Interventions for Adults: Scoping Review on the Implementations and Designs of Persuasive Strategies

Background

It is unclear why some physical activity (PA) mobile health (mHealth) interventions successfully promote PA whereas others do not. One possible explanation is the variety in PA mHealth interventions—not only do interventions differ in the selection of persuasive strategies but also the design and implementation of persuasive strategies can vary. However, limited studies have examined the different designs and technical implementations of strategies or explored if they indeed influenced the effectiveness of the intervention.

Objective

This scoping review sets out to explore the different technical implementations and design characteristics of common and likely most effective persuasive strategies, namely, goal setting, monitoring, reminders, rewards, sharing, and social comparison. Furthermore, this review aims to explore whether previous mHealth studies examined the influence of the different design characteristics and technical operationalizations of common persuasive strategies on the effectiveness of the intervention to persuade the user to engage in PA.

Methods

An unsystematic snowball and gray literature search was performed to identify the literature that evaluated the persuasive strategies in experimental trials (eg, randomized controlled trial, pre-post test). Studies were included if they targeted adults, if they were (partly) delivered by a mobile system, if they reported PA outcomes, if they used an experimental trial, and when they specifically compared the effect of different designs or implementations of persuasive strategies. The study methods, implementations, and designs of persuasive strategies, and the study results were systematically extracted from the literature by the reviewers.

Results

A total of 29 experimental trials were identified. We found a heterogeneity in how the strategies are being implemented and designed. Moreover, the findings indicated that the implementation and design of the strategy has an influence on the effectiveness of the PA intervention. For instance, the effectiveness of rewarding was shown to vary between types of rewards; rewarding goal achievement seems to be more effective than rewarding each step taken. Furthermore, studies comparing different ways of goal setting suggested that assigning a goal to users might appear to be more effective than letting the user set their own goal, similar to using adaptively tailored goals as opposed to static generic goals. This study further demonstrates that only a few studies have examined the influence of different technical implementations on PA behavior.

Conclusions

The different implementations and designs of persuasive strategies in mHealth interventions should be critically considered when developing such interventions and before drawing conclusions on the effectiveness of the strategy as a whole. Future efforts are needed to examine which implementations and designs are most effective to improve the translation of theory-based persuasive strategies into practical delivery forms.

Role of empowerment and sense of community on online social health support group

Purpose

Drawing on the taxonomy of patient empowerment and a sense of community (SoC), the purpose of this paper is to analyze the factors that impact the intention of the individual to continue using online social health support community for their chronic disease management.

Design/methodology/approach

A survey design was used to collect the data from multiple online social health support groups related to chronic disease management. The survey yielded a total of 246 usable responses.

Findings

The primary findings from this study indicate that the informational support – not the nurturant support such as emotional, network, and esteem support – are the major types of support people are seeking from an online social health support community. This research also found that patient empowerment and SoC would positively impact their intention to continue using the online health community.

Research limitations/implications

This study utilized a survey design method may limit precision and realism. Also, there is the self-selection bias as the respondents self-selected themselves to take the survey.

Practical implications

The findings can help the community managers or webmasters to design strategies for the promotion and diffusion of online social health group among patient of chronic disease. Those strategies should focus on patient’s empowerment through action facilitating and social support and through creating a SoC.

Originality/value

An innovative research model integrates patient empowerment and a SoC to study patient’s chronic disease management through online social health groups to fill the existing research gap.

Self-Efficacy, Self-Regulation, Social Support, and Outcomes Expectations for Daily Physical Activity in Adults with Chronic Stroke: A Descriptive, Exploratory Study

Interventions are needed to increase physical activity throughout the day in adults with chronic stroke, but mechanisms of action for doing so have not been identified. In this descriptive, exploratory study of 36 ambulatory, community-dwelling adults with chronic stroke, participants completed questionnaires investigating self-efficacy, self-regulation, social support, and outcomes expectations for daily physical activity. In the absence of any intervention, participants consistently reported high self-efficacy and outcomes expectations but low use of self-regulation and social support strategies. Discussion of how these results can inform the development of interventions to facilitate daily physical activity in adults with chronic stroke is provided.

"Active Team" a social and gamified app-based physical activity intervention: randomised controlled trial study protocol

Background

Physical inactivity is a leading preventable cause of chronic disease and premature death globally, yet over half of the adult Australian population is inactive. To address this, web-based physical activity interventions, which have the potential to reach large numbers of users at low costs, have received considerable attention. To fully realise the potential of such interventions, there is a need to further increase their appeal to boost engagement and retention, and sustain intervention effects over longer periods of time. This randomised controlled trial aims to evaluate the efficacy of a gamified physical activity intervention that connects users to each other via Facebook and is delivered via a mobile app.

Methods

The study is a three-group, cluster-RCT. Four hundred and forty (440) inactive Australian adults who use Facebook at least weekly will be recruited in clusters of three to eight existing Facebook friends. Participant clusters will be randomly allocated to one of three conditions: (1) waitlist control condition, (2) basic experimental condition (pedometer plus basic app with no social and gamification features), or (3) socially-enhanced experimental condition (pedometer plus app with social and gamification features). Participants will undertake assessments at baseline, three and nine months. The primary outcome is change in total daily minutes of moderate-to-vigorous physical activity at three months measured objectively using GENEActive accelerometers [Activeinsights Ltd., UK]. Secondary outcomes include self-reported physical activity, depression and anxiety, wellbeing, quality of life, social-cognitive theory constructs and app usage and engagement.

Discussion

The current study will incorporate novel social and gamification elements in order to examine whether the inclusion of these components increases the efficacy of app-based physical activity interventions. The findings will be used to guide the development and increase the effectiveness of future health behaviour interventions.

Trial registration

This trial was registered with the Australian and New Zealand Clinical Trial Registry (ACTRN12617000113358, date of registration 23 January, 2017).