Family‐based treatment for adolescent anorexia nervosa: A meta‐analysis
Bibliographic record
Abstract
Abstract Anorexia nervosa (AN) is a complex illness that typically onsets during adolescence and has severe consequences. Family‐based treatment (FBT) is currently regarded as the leading treatment option for adolescents with AN; however, there is confusion within the literature as to what exactly constitutes FBT. This meta‐analysis aimed to examine the specific efficacy of FBT in increasing weight gain and reducing eating disorder (ED) symptomology for adolescents with AN. Inclusion criteria required that studies followed the manualised FBT model, be restricted to adolescents, and have patients with diagnosed AN. Several databases were searched: MEDLINE, PsycINFO, Google Scholar, ProQuest Dissertations & Theses, and SCOPUS, and retrieval was limited to between 1984 and November 2023. Once identified, studies were screened and coded by two researchers who met to resolve any disagreements. Thirteen studies met the eligibility criteria. The impact of FBT on treatment outcomes revealed a large effect size for continuous (d = 0.955, 95% CI [0.386–1.523], p < 0.001) and remission (d = 2.32, 95% CI [1.827, 2.807], p < 0.001) outcomes. However, outcome measures varied across studies. These findings corroborate previous literature finding that FBT is an effective treatment for adolescents with AN. They also demonstrate the applicability and utility of this treatment across different cultures. FBT is a promising treatment modality to alleviate adolescents' physical and psychological suffering while also enhancing family relationships. Additionally, as an outpatient and low‐resource‐intensive treatment, it helps to reduce the healthcare burden.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.025 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".