Moderators of Theory-Based Interventions to Promote Physical Activity in 77 Randomized Controlled Trials
Bibliographic record
Abstract
A meta-analysis of randomized controlled trials (RCTs) has recently showed that theory-based interventions designed to promote physical activity (PA) significantly increased PA behavior. The objective of the present study was to investigate the moderators of the efficacy of these theory-based interventions. Seventy-seven RCTs evaluating theory-based interventions were systematically identified. Sample, intervention, methodology, and theory implementation characteristics were extracted, coded by three duos of independent investigators, and tested as moderators of interventions effect in a multiple-meta-regression model. Three moderators were negatively associated with the efficacy of theory-based interventions on PA behavior: intervention length (≥14 weeks; β = -.22, p = .004), number of experimental patients (β = -.10, p = .002), and global methodological quality score (β = -.08, p = .04). Our findings suggest that the efficacy of theory-based interventions to promote PA could be overestimated consequently due to methodological weaknesses of RCTs and that interventions shorter than 14 weeks could maximize the increase of PA behavior.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.080 | 0.230 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.024 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".