They then provided informed consent and received a handout explaining the benefits of walking for health and well-being, anchoring them on the idea that every additional step is valuable even at low physical activity levels. Participants were also instructed to use only the AccuSteps app for physical activity information and to wear the Apple Watch every day (except when sleeping, showering, or swimming). They then completed web-based psychological assessments, and the experimenter performed physiological assessments.
How sports application functions promote college students’ exercise behavior: a mixed-methods study
Large sample, high-quality, adequately powered, randomized controlled trials are required. In light of the bias evident in the included studies, better reporting of health-related app interventions is also required. Health interventions based on the behavior analysis present the potentials to increase daily physical activity levels [8,9]. Therefore, it is critical to explore preventive interventions that the general population could easily follow. However, traditional face-to-face interventions in public health may not achieve such a purpose [10,11,12,13,14].
4. Study Quality Assessment
And then there’s a category of general habit trackers, Habitica, Streaks, Strides, that are essentially blank canvases onto which users project whatever behavior they’re trying to change. The figure displays the overall risk of bias assessments across all included studies using the Cochrane Risk of Bias tool. Among the 18 studies, six were classified as high risk of bias, while the remaining 12 studies were either at low risk or raised some concerns (Fig. 4). Sensitivity analyses were performed by excluding high-risk-of-bias studies from the main analysis that yielded significant results. After their removal, all significant findings remained robust, except for the DBCIs’ effect on body metrics in clinical groups, where the effect size shifted from 0.217 (0.005–0.429) to 0.281 (−0.255–0.818), rendering it non-significant (Table 2).
3.1. Direct Effects Analysis
Fitness apps can provide users with feedback information on diet, exercise, and body condition, improving physical fitness levels, which can significantly affect wellbeing (14). Long-term use will improve people’s physical, emotional, social, and cognitive status and promote their wellbeing (3). Mobile health (mHealth) app positively influences users’ perceived wellbeing, users rate higher levels of wellbeing regarding the mHealth app before use than after use (15). Using fitness apps allow users to engage in constant self-tracking and are described as a way to practice body awareness, it was found that fitness app use and wellbeing has causal relationship (1).
Behavior change apps promise to rewire your habits, but most people abandon them within two weeks, and the apps themselves may share the blame. The most effective ones aren’t just reminder machines; they’re built on decades of behavioral science, translating theories about motivation, habit loops, and self-determination into something that fits in your pocket. Here’s what the science actually says about which tools work, why, and what to watch out for.
Meta-analysis of the effect of mobile health applications among the inactive population on (A) physical activity, (B) physical activity follow-up, and (C) sedentary behavior. A massive two-year study reveals fitness apps can help people take more steps, but the improvements are modest and uneven—raising big questions about who benefits most and how to make digital health tools sustainable. After the final selection of the studies, one reviewer will assess the risk of bias of all the papers included in the final selection. A quarter of the studies will be randomly selected for validation by a second reviewer. If there is disagreement in judgment, the reviewers will discuss before consulting a third reviewer. The Cochrane Collaboration Risk of Bias tool will be used to assess the randomized controlled trials included in the review and assign low, unclear, or high risk to the studies for each of the potential biases [21].
Those wishing to develop physical activity apps may consider ways to integrate these mechanisms of change. Additionally, practitioners in search of apps for recommendation to improve physical activity behaviors should consider apps with an emphasis on these theory-informed mechanisms with more confidence, as they may be more likely to result in behavior change. All the DM studies reviewed (13/13, 100%) used knowledge and education, followed by self-monitoring in 77% (10/13) of the studies. Both social support or encouragement and autonomous personalized feedback were used in 54% (7/13) of the studies. Prompts or cues were used in 31% (4/13) of the studies, followed by graded tasks and gamification in 15% (2/13) of the studies.
Table 1.
- Calculations reveal that the composite reliability (CR) for each factor is greater than 0.8, indicating strong reliability for each factor (61).
- It was shown that interventions targeting ease of SB present a mean reduction of 90.94 min in SB time.
- Goal setting was used in 56% (10/18) of the studies, feedback and encouragement were used in 56% (10/18) of the studies, and prompts or cues and intention formation were used in 50% (9/18) of the studies.
- However, it is unknown how to leverage these mindsets using wearable technology and other interventions.
- The app will be considered to have some evidence of effectiveness if there is a significant difference over time but not between groups or a significant improvement in only a subgroup of the population.
- Indeed, recent reports have suggested that activity trackers are used only for short periods of time (17, 18).
While fitness trackers typically include multiple established behavior change strategies such as goal setting, self-monitoring, social support, and rewards, other missing strategies may be home training routines particularly relevant for sedentary adults (27). Identifying barriers that prevent individuals from regular physical activity, and helping them to plan where, when, and with whom they can increase their activity may be especially important (31). These features are among the biggest opportunities for improvement in fitness technology and will increase the usefulness and relevance for inactive populations.
Firstly, the existing literature rarely focuses on female fitness app users, even though they account for 60% of total fitness app users. These results help identify factors that may promote the continuous use of fitness apps for physical activity by female users. Secondly, previous research emphasized the relationship between perceived value, satisfaction, and continuance intention. This study further finds that different dimensions of perceived value have varying impacts on continuance intention. The health and utilitarian values perceived by female users have a significant impact on continuance intention, but the hedonic value does not.
Article information and data extracted.
From the perspective of female fitness app users, this study further verifies that different dimensions of perceived value have varying impacts on satisfaction and continuance intention. This may be related to the values that female fitness app users prioritize; compared to the hedonic value gained from using fitness apps, female users value health and utilitarian value more. One potential way to utilize technology in an environmental intervention comes from the MapMyFitness App3.
4 Stimulus-organism-response model
We included articles if they were published in English, in a peer-reviewed journal, after 2010, targeted at an adult population, and presented results from the analysis of primary or secondary outcomes. We only included randomized controlled trials (RCTs), case-control studies, and cohort studies that were designed for app-based interventions to improve any health-related behaviors. Conference abstracts, protocol papers, reviews, editorials, and commentary were also excluded. In general, previous research on the acceptance of new technologies in the sports industry has found that PEOU (Mohammadi and Isanejad, 2018), or PU are the primary influences on the ‘intention to use’ (Kim et al., 2017).
Presence of Other Behavior Change Technique to Increase Physical Activity
When individuals engage in upward and downward comparisons with other users, social comparison features of fitness apps help users perceive the “real presence” of other users more vividly, facilitating a precise assessment of their own fitness levels. Simultaneously, the heightened sense of competition enhances the enjoyment of fitness, increasing users’ interest in participating in fitness activities, thereby strengthening their continuous use intention of fitness apps (31). Consequently, this study employs the SOR model to explore how the two external stimuli of social support and social comparison within the fitness environment influence individuals’ organism, subsequently affecting their continuous use intention. The demand for health and exercise among individuals is steadily increasing, and the number of users of fitness apps is also growing annually.
Summary of reported intervention outcomes
It is unclear whether steps are the best activity indicator or motivator, and whether this metric is meaningful to those without a fitness tracker or app that measures steps. Research suggests that most who own a fitness tracker are primarily concerned with monitoring their steps (39). Steps alone, however, do not provide information about exercise intensity, which may be more important than number of steps taken.
5. Strategy for Data Synthesis and Analysis
If significant asymmetry was detected, the Trim-and-Fill technique was applied to adjust for potential publication bias35. Inter-rater reliability, measured using Cohen’s Kappa, demonstrated near-perfect agreement for both title/abstract screening stage (0.92) and full-text review (0.90). Throughout the process, reviewers remained blinded to each other’s decisions to maintain objectivity. This article does not contain any studies with human participants performed by any of the authors.
Fitness apps offer fitness training classes, store users’ exercise and fitness data, and provide recommendations for healthy lifestyles (1). Fitness apps can improve the regularity of users’ physical activities, the frequency of fitness exercises and walking behavior (2). Long-term use of fitness app will improve people’ s physical, emotional, social, and cognitive status and promote their wellbeing (3).