Temporal Aspects of Psychosocial Mediators of the Exercise-Weight Loss Maintenance Relationship Within Scalable Behavior-Change Treatments
Bibliographic record
Abstract
STUDY BACKGROUND: Limited knowledge of psychological correlates of weight loss is associated with continuing failures of behavioral obesity treatments beyond the short term. PURPOSE: This study aimed to inform health professionals' obesity interventions via an increased knowledge of mediators of the exercise-weight loss maintenance relationship. METHODS: = 54) means. Changes in mood, self-regulating eating, and weight over 6, 12, and 24 months were assessed. A moderated mediation model was tested using the PROCESS macro instruction. RESULTS: Improvements in mood, self-regulating eating, and weight were significantly greater in the in-person group. The relationship between a dichotomous measure of completing at least 3 sessions of exercise per week (or not) and change in weight over 6 months was no longer significant when the mediators of changes in negative mood and self-regulation of eating were sequentially entered. Paths of exercise→negative mood reduction→eating self-regulation increase→weight loss over 6, 12 and 24 months were significant. Exercise self-regulation at Month 3 significantly moderated the mood change→eating self-regulation change relationship. CONCLUSIONS: Based on the identified paths, scalable obesity-treatment content and emphases were informed. This could help guide health professionals' actions concerning the management of obesity.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".