The interaction of relatedness and social climate on exercise and weight-loss satisfaction in an 8-week weight-loss program
Bibliographic record
Abstract
Self-determination theory research asserts a direct relationship between fulfillment of basic needs and well-being. In the sport and exercise domain, the need for relatedness has been largely ignored in favour of the concepts of autonomy and competence (Kowal & Fortier, 2000). The primary purpose of this study was to examine the influence of both relatedness and social climate in relation to health behaviours and weight-loss and exercise satisfaction in an 8-week weight-loss program. METHOD: Participants (n = 84) registered in a weight-loss program targeting both diet and exercise components were recruited from 14 health centers in the Montreal region. Each client was matched with a trainer that worked with them closely during the program's duration. Health Behaviours were measured at Time 1. Health Behaviours (HB), Relatedness to Trainer (RT), Social Climate at the Gym (SC) and Weight-loss Program Self-Determined Motivation (WSM) were measured at Time 2, 4 weeks into the program. Upon completion of the 8-week program, Exercise Satisfaction (ES) and Weight-loss Satisfaction (WS) were measured at Time 3. Objective measures of weight lost (Lbs.) were also measured at all time points. RESULTS: RT and SC interacted to predict ES and WS. Further, evidence was found for mediated-moderation with the interaction of RT X SC acting on WS indirectly through Time 2 HB after controlling for WSM and Time 1 HB. DISCUSSION: The results indicate that both RT and SC at the gym are important predictors of exercise-related satisfaction and act indirectly through HB. Implications and future directions are discussed.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".