Ecological momentary assessment of physical activity and affective responses in healthy adults: a scoping review
Bibliographic record
Abstract
Affective experiences, including emotions and moods, are central to well-being. Physical activity (PA) is linked to improved mood, but the acute relationship between objectively measured PA and affect in daily life remains underexplored. Ecological Momentary Assessment (EMA) minimizes biases of retrospective reports and captures real-time effects. This scoping review synthesizes studies using EMA and accelerometers to examine the acute (within 30 minutes) effects of PA on positive and negative affect in healthy adults, highlighting methodological diversity and future research needs. A systematic search of MEDLINE, CINAHL, PsycINFO, and SportDiscus identified studies involving healthy adults that used EMA, accelerometer-based PA measures, and assessed acute PA effects on affect. Data extraction followed the CREMAS protocol, focusing on sample characteristics, PA and affect measures, compliance rates, and moderators. From 208 identified studies, 14 met the inclusion criteria. Studies varied in sample size, accelerometer placement, affect measurement scales, prompt frequency, and compliance, complicating comparisons. PA was consistently linked to increased arousal; findings for valence and positive affect were mixed. Negative affect tended to decrease after PA, but results were inconsistent. Several studies explored moderators, such as competence, autonomy, and social context. EMA is a valuable method for studying PA and affect dynamics in everyday life. However, methodological heterogeneity calls for more standardized protocols. Future research should improve transparency in reporting, explore additional moderators, and recruit more diverse samples to enhance generalizability . • Accelerometer-based PA is linked to increased arousal in real-world settings • Mixed results are observed for PA effects on valence and positive affect • Methodological heterogeneity limits generalizability across studies • Future studies should adopt standardized EMA and PA protocols
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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 | 0.014 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.021 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".