The stage model for psychotherapy manual development: A valuable tool for promoting evidence-based practice.
Bibliographic record
Abstract
This article provides a commentary on the stage model for psychotherapy manual development proposed by Carroll and Nuro (this issue). We endorse the emphasis on the evolution of treatment manuals, dependent on their stage of development, research base, and intended audience. At the same time, we discuss some of the conceptual and practical challenges to the smooth and steady transition of treatment manuals from efficacy trials into clinical practice. These issues include incentives for researchers to conduct effectiveness trials, lack of funding for such research, skepticism in some quarters of the field about the utility of treatment manuals, issues of dissemination, and the general lack of feedback from the clinical community to the developers of treatment manuals about ways to make them flexible enough for use in clinical practice. We end with an encouragement of the template of a stage model for manual development.
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 | 0.143 | 0.251 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.007 | 0.040 |
| Scholarly communication | 0.014 | 0.022 |
| Open science | 0.007 | 0.012 |
| Research integrity | 0.022 | 0.023 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".