Predictors of Treatment Acceptance and of Participation in a Randomized Controlled Trial Among Women with Anorexia Nervosa
Bibliographic record
Abstract
OBJECTIVE: This study aimed to identify predictors of acceptance of intensive treatment and of participation in a randomized controlled trial (RCT) among women with anorexia nervosa (AN). METHOD: Participant data were drawn from a tertiary care intensive treatment programme including a previously published RCT. Women with AN (N = 106) were offered intensive treatment, and 69 were approached to participate in an RCT of olanzapine's efficacy as an adjunctive treatment for AN. AN subtype and pretreatment psychological variables were used to predict acceptance of intensive treatment and RCT participation. RESULTS: AN binge purge subtype and higher depression and body dissatisfaction predicted intensive treatment acceptance. No variable predicted RCT participation among treatment acceptors. DISCUSSION: Clinicians may focus on enhancing motivation or use a stepped care approach to increase intensive treatment acceptance especially among women with AN-restricting type and among all those with AN who have lower levels of distress.
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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 | 0.029 | 0.076 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".