Bidirectional week-to-week relationships between weekly psychological stress across multiple life domains and engagement with an exercise intervention: secondary analysis of data from a randomized trial
Bibliographic record
Abstract
BACKGROUND: Engaging in physical activity can reduce the risk of multiple morbidities and premature mortality. Psychological stress can hinder the development and maintenance of physical activity behaviors. There is a dearth of research on how these two processes interact. PURPOSE: The purpose of this study was to identify the week-to-week bidirectional associations between weekly psychological stress across multiple domains (e.g. social, economic) and adherence to a six-week mHealth exercise program among a previously inactive sample. METHODS: The secondary analyses reported in this study examine data derived from adults randomized to one of three mobile application(s)-based exercise arms embedded within the COPE trial (N = 251). The interventions delivered to participants in each arm involved six weeks of at-home exercise requiring no additional equipment. Relationships between psychological stress (as measured by a modified version of the Chronic Burden Scale) and engagement with the commercially available exercise apps were explored using a random intercept cross-lagged panel model (RI-CLPM). This model simultaneously assessed the longitudinal and bidirectional associations between psychological stress and exercise engagement and vice versa. RESULTS: Both psychological stress and engagement with the exercise interventions demonstrated significant positive autoregressive effects across successive weeks. However, the cross-lagged associations between stress and engagement with the exercise intervention were not significant. CONCLUSIONS: While the cross-lagged effects were non-significant, there was high variability between individuals. Future studies should use larger samples and methods that would allow an examination of an individual's relationship between psychological stress and exercise engagement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.036 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".