Promotion of physical activity among people who identify as women through the ParticipACTION mobile app
Bibliographic record
Abstract
Objective Health and fitness mobile applications can increase users’ physical activity (PA) levels (Lister et al., 2014). ParticipACTION is a national non-profit organization that developed a mobile app to target PA among adults (Truelove et al., 2020). The aim of this research was to examine how women’s PA is related to their use of the ParticipACTION app.Methods and Measurement Using a mixed-methods design, participants (n = 3,493) completed a survey regarding their PA levels, motivation for PA (capability, opportunity, motivation; COM-B, Keyworth et al., 2020), and motivation for using the ParticipACTION app. Nine focus groups were conducted (n = 37) to discuss the mobile app further.Results Path analyses revealed that users’ app use was positively associated with motivations for various app functions (e.g. self-monitoring, seeking exercise guidance), however, only motivation in-turn predicted PA. Descriptive results indicated that many women in Canada who used the app do not meet national guidelines for PA per week. Qualitative findings highlight women’s motivation for using the app, concerns with app functionality, and feelings of guilt for not engaging in PA.Conclusion The ParticipACTION app may have some benefit for improving women’s PA; intervention studies are needed to determine efficacy of mobile applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".