Closing the Gap Between Physical Activity Intentions and Sustained Behavior: An Overview of Evidence
Bibliographic record
Abstract
This visual overview of evidence examines the intention–physical activity (I–PA) gap, where positive intentions often fail to translate into behavior, a central challenge in physical activity (PA) promotion. Although intentions are necessary precursors to PA, nearly half of individuals with positive intentions do not follow through, underscoring the importance of identifying predictors of successful intention enactment for theory and practice. Evidence highlights reflective processes (i.e., affective judgments and self-efficacy/perceived control), regulatory processes (i.e., planning and self-monitoring), and reflexive processes (i.e., habit and identity) as key predictors of intention translation. Interventions targeting these constructs as mechanisms of action (MoAs) show small to medium effects on PA, but progress is limited by heterogeneity in behavior-change technique (BCT) application and under-examination of some MoAs. Closing the I–PA gap requires strengthening behavioral regulation, supporting positive affect, and aligning behavior with identity. By synthesizing theory and evidence across four figures, this review illustrates the role of intention in behavioral theories, the I–PA gap, I–PA moderators, and a logic model aligning BCTs with MoAs, offering practical guidance for researchers and practitioners. Future research using sustained experimental designs, including factorial studies, which precisely link BCTs to MoAs will be essential for developing interventions to close the gap between intentions and sustained PA.
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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".