Reciprocal influence of alliance to the group and outcome in day treatment for eating disorders.
Bibliographic record
Abstract
The nature of the alliance-outcome relationship is still emerging. This study examined the reciprocal influence of change in alliance to the group and change in urge to restrict in eating-disordered individuals attending a group-based day treatment. Participants (N = 238) were a transdiagnostic or mixed diagnostic sample of eating-disordered individuals consecutively admitted to a day treatment program. On a weekly basis, participants completed a measure of alliance to the group of patients with whom they attended multiple group therapies each week. After each meal, they rated the intensity of their urge to restrict food intake, and the intensity ratings were averaged per week. Latent change score analysis was used to assess the reciprocal relationship between prior change in alliance to the group with subsequent change in urge to restrict, and prior change in urge to restrict with subsequent change in alliance to the group across each participant's first 9 weeks in the program. A reciprocal causal model was a good fit to the data. Prior growth in alliance to the group was significantly associated with subsequent reduction in urge to restrict, and concurrently, prior reduction in urge to restrict was significantly associated with subsequent growth in alliance to the group. Alliance to the group and individual outcomes are dynamically related and changing constructs represented by a reciprocal causal model. Clinicians may improve group treatment by assessing alliance to the group and outcomes repeatedly, being aware of their interplay, and structuring interventions based on the mutual causal effects of change in each.
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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 | 0.008 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".