Intraclass Correlation Associated with Therapists: Estimates and Applications in Planning Psychotherapy Research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
It is essential that outcome research permit clear conclusions to be drawn about the efficacy of interventions. The common practice of nesting therapists within conditions can pose important methodological challenges that affect interpretation, particularly if the study is not powered to account for the nested design. An obstacle to the optimal design of these studies is the lack of data about the intraclass correlation coefficient (ICC), which measures the statistical dependencies introduced by nesting. To begin the development of a public database of ICC estimates, the authors investigated ICCs for a variety outcomes reported in 20 psychotherapy outcome studies. The magnitude of the 495 ICC estimates varied widely across measures and studies. The authors provide recommendations regarding how to select and aggregate ICC estimates for power calculations and show how researchers can use ICC estimates to choose the number of patients and therapists that will optimize power. Attention to these recommendations will strengthen the validity of inferences drawn from psychotherapy studies that nest therapists within conditions.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it