Prognostic value of autonomous and controlled motivation in outpatient eating‐disorder treatment
Bibliographic record
Abstract
According to Self-Determination Theory, when motivation to reach an objective is fully internal, it is said to be "autonomous"; when driven by external incentives, it is said to be "controlled". Previous research has indicated that autonomously motivated individuals show better response to treatments for eating disorders. OBJECTIVE: In individuals undergoing different intensities of outpatient treatment for an eating disorder, we sought to assess associations between autonomous and controlled motivations and response to treatment on the one hand, and likelihood of dropping out of treatment, on the other. METHOD: Seven hundred seventy adults meeting DSM-5 criteria for an eating disorder (216 with Anorexia Nervosa, 282 with Bulimia Nervosa, and 272 with Other Specified Feeding or Eating Disorder) were included in this study. Before an interval of outpatient treatment, individuals completed the Eating Disorder Examination Questionnaire and the Autonomous and Controlled Motivations for Treatment Questionnaire. Participants completed the Eating Disorder Examination Questionnaire again at one or two subsequent timepoints. RESULTS: After controlling for diagnosis, treatment intensity, and number of previous treatments, analyses showed that higher autonomous motivation was associated with better response on eating-disorder overall symptoms and lower likelihood of dropping out of treatment. In contrast, controlled motivation was not associated with response to treatment. DISCUSSION: Our results suggest that autonomous motivation has trans-diagnostic influence upon response to various intensities of treatment for an eating disorder. In support of an autonomy supportive approach to treatment, findings link autonomous motivation with more favorable outcome.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".