A meta‐analysis of the relation between therapeutic alliance and treatment outcome in eating disorders
Bibliographic record
Abstract
The therapeutic alliance has demonstrated an association with favorable psychotherapeutic outcomes in the treatment of eating disorders (EDs). However, questions remain about the inter-relationships between early alliance, early symptom improvement, and treatment outcome. We conducted a meta-analysis on the relations among these constructs, and possible moderators of these relations, in psychosocial treatments for EDs. Twenty studies met inclusion criteria and supplied sufficient supplementary data. Results revealed small-to-moderate effect sizes, βs = 0.13 to 0.22 (p < .05), indicating that early symptom improvement was related to subsequent alliance quality and that alliance ratings also were related to subsequent symptom reduction. The relationship between early alliance and treatment outcome was partially accounted for by early symptom improvement. With regard to moderators, early alliance showed weaker associations with outcome in therapies with a strong behavioral component relative to nonbehavioral therapies. However, alliance showed stronger relations to outcome for younger (vs. older) patients, over and above the variance shared with early symptom improvement. In sum, early symptom reduction enhances therapeutic alliance and treatment outcome in EDs, but early alliance may require specific attention for younger patients and for those receiving nonbehaviorally oriented treatments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.015 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".