Advances are still needed to help inactive individuals determine how, when, where, and with whom they can increase their physical activity. One strategy that may be especially important for this group is action planning, or prompting the user to make detailed plans about when and where they will increase their activity (28, 31). Action planning includes “if, then” plans, also known as implementation intentions (62). Such implementation intentions encourage individuals to make detailed plans about how, when, and where they will achieve their goals, which increases the likelihood that they will actually meet these goals (62). This strategy could be included in fitness technology by encouraging the user to examine their schedule for the day and determine times in which they can increase their exercise. For instance, one could identify the need to go to the grocery store in the afternoon and plan to park further away from the store to get more steps.

5. Study Quality

Placebo effects can induce clinically significant changes in various conditions, including pain, allergies, hypertension, and Parkinson disease. They do so via specific neurobiological mechanisms, including the activation of the neuronal, cardiovascular, and endocrine systems. In addition, subjective pain was underpinned by activity in pain-regulating brain regions [45].

Can Wearable Technology Shape AAMs?

The quality of the included studies in terms of high risk of bias in selection, performance, detection, or attrition, and the quality of reporting of the interventions in some of the articles also calls for more rigorous study design and reporting. In addition to NCDs, health-related apps have the added potential to aid a wide range of target audiences in a whole range of health issues [8]. For example, they can improve contraceptive knowledge of women [9] or help users to prevent nonspecific low back pain [10].

Table 2.

First, by exclusively focusing on standalone DBCIs, highlighting their potential as a scalable and cost-effective intervention strategy. Second, by incorporating both adults with healthy and unhealthy conditions, the findings offer a more comprehensive understanding of DBCIs impact across diverse groups. Third, extensive subgroup analyses help identify the optimal conditions for intervention efficacy.

Digital Public Health

• This review provided evidence that mobile health intervention improved physical activity and reduced sedentary behavior among inactive individuals.
• The new media represented by the Internet and mobile phones have become an important factor affecting the daily lifestyle of the public.
• It reduces the sense of self-efficacy and causes low self-control users to choose to “lie down” to avoid this threat source, which reduces their wellbeing.
• Many of these risk factors, such as tobacco use, unhealthy diet, physical inactivity, stress, depression, harmful use of alcohol, overweight, and obesity, can be modified by behavioral change interventions [6].
• In addition, it explored the effects of AAMs on health and well-being and several affective and behavioral determinants of health.
• This may be explained by the fact that habits of individuals are formed best when they are exposed to education-related cues when using an app (eg, how and when to exercise best) [73].

Demographic information was gathered and respondents were asked to report their age, race, ethnicity, sex, highest level of education obtained, and annual household income (Table 1). This included the number of physical activity apps respondents had used in the past 6 months, how often each app was used, which apps they used most frequently, and the average price of the apps that they used. Physical activity apps are commonly used to increase levels of activity and health status. To date, the focus of research has been to determine the potential of apps to influence behavior, to ascertain the efficacy of a limited number of apps to change behavior, and to identify the characteristics of apps that users prefer. The most targeted behaviors were physical activity, observed in 56% (5/9) of the included studies, and dietary behavior, observed in 78% (7/9) of the studies. Furthermore, QOL was measured in 67% (6/9) of the studies, followed by app use and satisfaction in 56% (5/9) of the studies.

Literature Review

Fitness trackers offer the prospect for physical activity interventions that are cost-effective and easily accessed by a wide population. Finally, future research could examine the role of mindsets in predicting wearable tracker adoption, abandonment, and user engagement, which are major obstacles to trackers’ effectiveness as well as their systematic evaluation [11,64]. To date, wearable devices are not widely used by individuals who stand to benefit the most from monitoring and improvement (including older individuals and those with poor health or chronic conditions) [64]. It may be that these individuals have inadequate activity mindsets and are afraid of being constantly reminded of their perceived unhealthy lifestyle or that they quickly become discouraged by feedback that their activity levels are inadequate. Mindset interventions may help buffer individuals from these negative effects and promote adoption and sustained engagement in diverse populations. The results showed that simply receiving accurate step count feedback led to improvements in participants’ AAMs, helping them realize that they were engaging in more health-promoting physical activity than they had previously believed.

A low-impact exercise such as walking has been shown to reduce fear of falling, and even decrease actual incidence of falling, one of the most cited concerns among inactive older adults (113, 115–117). Another potential psychological barrier for older adults could be an apprehensiveness toward technology. Research has shown that although older adults may be initially wary of fitness technology, after consistent use they report they find the technology useful and acceptable (46). This age group may, however, need help setting up the device and learning how to interpret the data. Given that many older adults have low expectations about their ability to exercise (118), strategies that increase self-efficacy for exercise may be especially beneficial for this group.

In summary, AAMs may influence health and well-being through known affective, behavioral, and physiological pathways. However, we need more research to fully understand psychophysiological links; is madmuscles legit reconcile mixed results from past studies; and examine factors shaping AAMs, such as the increasingly ubiquitous modern personal health technologies. One way fitness professionals can support behavior change efforts with clients is by using various behavior change apps.

They tested a gain incentive, where participants were given money each time they met their goal, a loss incentive, where people lost money for not meeting their goals, and a lottery incentive, where they were placed in a lottery after meeting their goals (48). Results suggested that the loss incentive was most effective in changing behaviors, motivating more people to meet their goals than the other two conditions. Overall, rewards seem to be an effective strategy for increasing physical activity, while there may be differential effects dependent on the reward type and framing. Incorporating monetary (such as entry into a lottery or drawing if one meets their goals) or other meaningful rewards into fitness technology may lead to greater motivation and engagement in reaching individual goals. The content and framing of recommendations and feedback is important to consider when examining the promotion of physical activity.

Moderating Effects of Individual Differences

Social presence refers to the degree to which individuals feel the presence of others during communication, reflecting the sense of intimacy or direct experience that individuals develop toward the communication medium in interpersonal interactions (40). When using fitness apps, users communicate with others, allowing them to compare their own fitness situations with other users. Through interaction, users can help bridge the social distance between them, enhancing their perception of others’ presence in fitness apps. As users experience a sense of authenticity and warmth from other users, they are more likely to engage in interpersonal interactions, perceive support and trust, thereby leading to continuous use of the fitness apps and an increased fitness intention. Existing literature has confirmed that social presence positively affects consumers’ online purchase intentions in social commerce (41).

A systematic review of intention to use fitness apps (2020–

It can be summarized that compared with low self-control users, high self-control users have a higher level of wellbeing when involved in the same upward social comparison. Third, we provide evidence for a novel meta-mindset intervention that empowers participants to deliberately adopt more positive mindsets and use them to improve health and well-being. Our findings increase the applied utility of mindset research as meta-mindset interventions are nondeceptive and ethical outside the research context. The intervention designer should consider whether AAM is the most relevant variable to target or whether other barriers to physical activity should be addressed first or in addition.

Identifying Behavior Change Techniques in an Artificial Intelligence-Based Fitness App: A Content Analysis

In fitness apps, social support is realized through interactions with the app interface and other users. For instance, users continuously receive informational support regarding exercises through fitness apps. Fitness apps also provide companionship and emotional support by displaying friends’ physical activities. Users’ fitness updates receive likes and comments from others, thereby fostering a sense of support. Research has found that users of fitness apps engage in exercise to receive praise from others (14), indicating that social support is an effective motivational function that fitness apps possess for users. Recent reports have suggested that over 20% of Americans own a wearable fitness tracker (101, 102).

Mindsets and Their Effects on Health and Well-being

In experimental research, a study examined a sample of hotel room attendants who objectively met physical activity guidelines through their work but still perceived themselves as inactive as they were unaware that their work counted as exercise. An intervention informing room attendants that their work constituted adequate exercise resulted in reduced weight, body fat, and blood pressure 1 month later compared with a control group [28]. Another study [24] investigated the effects on AAM of viewing the official US physical activity guidelines (prescribing a relatively high amount of activity) compared with guidelines that prescribed a lower amount of activity.