Predictors of family‐based treatment for adolescent eating disorders: Do family or diagnostic factors matter?
Bibliographic record
Abstract
OBJECTIVE: Misconceptions around which patients will and will not benefit from family-based treatment (FBT) for adolescent eating disorders (EDs) limit referrals and access to this treatment modality. The present study explored whether common demographic and clinical factors that may prevent referral to FBT predict treatment outcomes in adolescent anorexia nervosa (AN) and bulimia nervosa (BN). METHOD: The following predictors of treatment outcomes were assessed: baseline family and diagnostic factors (socioeconomic status, comorbidity, illness duration, parent feelings of self-efficacy, family status, prior treatment, sex and prior hospitalizations) in a combined sample of adolescents receiving FBT compared to those randomized to other treatment conditions, across six clinical trials in the United States and Canada (total n = 724, ages 12-18, 90% female across both diagnoses). AN and BN samples were examined separately. RESULTS: Any prior ED treatment emerged as the only predictor of outcome in AN and BN, such that having no prior treatment predicted better outcomes in FBT for AN, and in both FBT and other treatment modalities for BN. No other sociodemographic or clinical variables predicted outcomes for AN or BN in FBT or in other evidence-based treatment modalities. CONCLUSIONS: The findings of this exploratory analysis suggest that commonly assumed factors do not predict outcome in FBT. Specifically socioeconomic and demographic factors or clinical variability in families seeking treatment do not predict treatment outcomes in FBT, or other evidence-based treatment modalities, with the exception of prior treatment. Providers should consider referring to FBT even when these factors are present. PUBLIC SIGNIFICANCE: This manuscript reports that commonly assumed family, sociodemographic and diagnostic factors do not predict outcome in FBT or other evidence-based treatment modalities, with the exception of prior treatment. This data may be helpful for providers when considering referrals to FBT in the context of variability in these variables.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".