Self-tracking of daily physical activity using a fitness tracker and the effect of the 10,000 steps goal

Beyond Validation: Getting Wearable Activity Trackers into Cardiovascular Care - A Discussion Paper

This paper addresses the challenge of integrating wearable activity trackers into cardiovascular disease care. Despite evidence supporting the use of trackers for monitoring and promoting physical activity, implementation challenges persist in clinical settings. The paper emphasises the lack of systematic, evidence-based implementation approaches for integrating trackers. It underscores the urgent need for stakeholder collaboration between clinicians, patients, implementation scientists, researchers, health and technology partners, and the use of proven implementation science methodologies. This is crucial for bridging the gap and ensuring effective translation of wearable activity trackers into cardiovascular disease care, meeting the increasing demand from patients and clinicians.

Exercise or not? An empirical illustration of the role of behavioral alternatives in exercise motivation and resulting theoretical considerations

Objective

Individuals' decisions to engage in exercise are often the result of in-the-moment choices between exercise and a competing behavioral alternative. The purpose of this study was to investigate processes that occur in-the-moment (i.e., situated processes) when individuals are faced with the choice between exercise and a behavioral alternative during a computerized task. These were analyzed against the background of interindividual differences in individuals' automatic valuation and controlled evaluation of exercise.

Method

In a behavioral alternatives task 101 participants were asked whether they would rather choose an exercise option or a behavioral alternative in 25 trials. Participants' gaze behavior (first gaze and fixations) was recorded using eye-tracking. An exercise-specific affect misattribution procedure (AMP) was used to assess participants' automatic valuation of exercise before the task. After the task, self-reported feelings towards exercise (controlled evaluation) and usual weekly exercise volume were assessed. Mixed effects models with random effects for subjects and trials were used for data analysis.

Results

Choosing exercise was positively correlated with individuals' automatic valuation (r = 0.20, p = 0.05), controlled evaluation (r = 0.58, p < 0.001), and their weekly exercise volume (r = 0.43, p < 0.001). Participants showed no bias in their initial gaze or number of fixations towards the exercise or the non-exercise alternative. However, participants were 1.30 times more likely to fixate on the chosen alternative first and more frequently, but this gaze behavior was not related to individuals' automatic valuation, controlled evaluation, or weekly exercise volume.

Conclusion

The results suggest that situated processes arising from defined behavioral alternatives may be independent of individuals' general preferences. Despite one's best general intention to exercise more, the choice of a non-exercise alternative behavior may seem more appealing in-the-moment and eventually be chosen. New psychological theories of health behavior change should therefore better consider the role of potentially conflicting alternatives when it comes to initiating physical activity or exercise.

Self-tracking of daily physical activity using a fitness tracker and the effect of the 10,000 steps goal

Activity self-tracking technologies have become a popular tool for monitoring physical activity, used to assist individuals in increasing physical activity. Previous findings, however, are inconclusive on whether standalone activity self-tracking, alone or in combination with a step goal, is efficient in encouraging physical activity behavior. This study aimed at investigating the effects of mere activity self-tracking and activity self-tracking with a daily 10,000 steps goal on physical activity levels in a randomized-controlled parallel group trial (N = 150; mean age= 24.66, standard deviation = 4.75), using a publicly available fitness tracker and associated smartphone application. Two experimental groups, one of which without and the other with step goal, recorded daily physical activity (daily step count) via a fitness tracker wearable and associated smartphone application and via daily self-reports of activity over the course of 6 weeks. An unequipped control group recorded physical activity only via daily self-reports. Both experimental groups were compared against each other based on step count data, and against the control group based on daily self-reports of activity. Results of mixed-effect multilevel analyses suggest that activity tracking using fitness trackers and externally assigned goals do not drive greater physical activity behavior. Rather, results indicate substantial individual differences that should be targeted in future studies to better understand individual behavioral processes boosting or hindering daily activity.