Accelerometry-Based Physical Activity and Affective Responses to Daily Stressors: An Analysis of the AAPECS Study
Bibliographic record
Abstract
Abstract Evidence suggests that physical activity on a daily basis dampens the extent to which one experiences elevations in negative affect in response to daily stressors. Yet, these studies primarily relied solely on end-of-day recall of stressors and negative affect, and self-reported physical activity. More intensive assessments throughout the day and accelerometry-based physical activity measurements are required to answer whether any type of body movement (e.g. light, moderate, vigorous) reconfigures the end-of-day recall of the intensity of the affective experience of a stressor or, rather, mitigates the actual experience of a stressor in real-time. This presentation will summarize results addressing this question using data from the University of Pittsburgh’s Assessment of Personality, Ecological Context, and Stress (AAPECS) study. AAPECS includes172 participants who wore accelerometers to assess movement-based activities and completed ecological momentary assessment 6 times daily for 14 days, with additional ‘bursts’ of affective assessments following reported stressors at any time.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".