Examining therapist effects in the alliance–outcome relationship: A multilevel meta-analysis.
Bibliographic record
Abstract
OBJECTIVE: The relationship between the therapeutic alliance and outcome has been supported consistently over time. More recently, studies have examined therapist effects in the alliance-outcome relationship and came up with somewhat mixed findings. The purpose of this study was to replicate and extend previous meta-analytic work using a much larger data set, permitting not only the verification of the overall impact of the therapists' contribution but, at the same time, controlling for several potential covariates effecting this relationship. METHOD: = 152; 827 total effect sizes) to examine the significance of several potential moderators of the alliance-outcome correlation. These moderators included (a) Patient-Therapist Ratio (PTR; Patient N divided by therapist N to test therapist effects), (b) Alliance and Outcome Rater's contribution (patient, therapist, observer, and other), (c) Alliance Measures, (d) Research Design (RCT, Other) and (e) Personality Disorder. RESULTS: The PTR, an index of the therapist's contribution to the alliance, was a significant moderator of the alliance-outcome correlation in both the two- and three-level models. When several potential confounds were simultaneously tested in a three-level multipredictor metaregression, including rater of alliance and outcome, research design, alliance measure, and personality disorder, PTR remained a significant moderator of the alliance-outcome correlation. CONCLUSION: Replicating and extending previous research, this study supported the significance of therapists' impact in the alliance-outcome relationship. These results remained significant even when, using three-level metaregressions, several potential covariates were simultaneously controlled. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.043 | 0.059 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.048 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".