Autonomy support, self-regulation, and weight loss.
Bibliographic record
Abstract
OBJECTIVE: Social support is believed to contribute to weight loss success, yet the type of support received is rarely assessed. To develop more effective weight loss interventions, examinations of the types of support that are associated with positive outcomes are needed. Self-Determination Theory suggests that support for an individual's autonomy is beneficial and facilitates internalization of autonomous self-regulation. We examined whether autonomy support and directive forms of support were associated with weight loss outcomes in a larger randomized controlled trial. METHOD: Adults (N = 201; 48.9 ± 10.5 years; 78.1% women) participating in a weight loss trial were assessed at 0, 6, and 18 months. Autonomy support (AS), directive support, and autonomous self-regulation (ASR) were measured at 0 and 6 months and examined in relation to 18-month weight loss outcomes. RESULTS: Baseline AS and ASR did not predict outcomes; however, AS and ASR at 6 months positively predicted 18-month weight losses (ps < .05), encouragement of healthy eating at 6 months was negatively related to 18-month weight losses (p < .01), and other forms of directive support were not associated with outcomes. CONCLUSIONS: Autonomy support predicted better weight loss outcomes while some forms of directive support hindered progress. Weight loss trials are needed to determine whether family members and friends can be trained to provide autonomy support and whether this is more effective than programs targeting more general or directive forms of support.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".