Dynamic patterns of personality states, affects and goal pursuit before and during an exercise intervention: a series of N-of-1 trials combined with ecological momentary assessments
Bibliographic record
Abstract
Prior studies have failed to identify the dynamics between the momentary manifestation of personality traits (namely personality states) and cognitive-affective mechanisms in relation to physical activity. The current study modelized the temporal associations between daily personality states, affect (valence) and pursuit of personal goals before and during a physical exercise intervention. Single cases using an A (10 days) -B (42 days) design paired with ecological momentary assessments was used in 10 inactive adults. Idiographic network analyses and generalized additive model were performed. The magnitude of the association between personality states, affect and pursuit of personal goals were modified during the intervention. Their respective weight of the variables in the networks during the exercise intervention followed an individual pattern. The intervention was associated with a systematic change in levels of pursuit of personal goals, with seven participants showing a non-linear association. The complexity of individual networks before and during the intervention stresses the importance of an idiographic level of analysis, especially in the context of an exercise intervention.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".