Understanding the uptake of family‐based treatment for adolescents with anorexia nervosa: Therapist perspectives
Bibliographic record
Abstract
OBJECTIVE: To explore and describe therapists' perceptions of the factors affecting their uptake of family-based treatment (FBT) for adolescents with anorexia nervosa (AN). METHOD: Fundamental qualitative description guided the sampling and data collection in this study. A purposeful sample of 40 therapists providing treatment to youth with AN, completed an in-depth interview. Conventional content analysis guided the development of initial codes and categories, whereas constant comparison analytic techniques were used to compare and contrast therapist perceptions across contexts. Summative content analysis was used to provide counts of keywords, phrases, and themes. RESULTS: Therapists face several barriers to the implementation of FBT, divided broadly into interventional, organizational, interpersonal, patient/family, systemic, and illness factors. Therapists support the implementation of evidence-based practices, including FBT for AN, but fidelity to this model is not practiced. Specific concerns about the intervention included weighing the patient, providing nutritional advice, and the family meal. Ninety-five percent of therapists requested further training in the FBT model. DISCUSSION: Further investigation into the barriers and facilitating factors to the use of FBT is warranted. Understanding effective dissemination and training strategies is critical to ensuring patients receive the best possible care.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".