Broadening the evidentiary basis for clinical practice guidelines: Recommendations from qualitative psychotherapy researchers.
Bibliographic record
Abstract
To improve the provision of psychotherapy, many countries have now established clinical practice guidelines for the treatment of specific disorders and mental health concerns. These guidelines have typically been based on evidence from meta-analyses of randomized clinical trials with minimal consideration of findings from qualitative research designs. This said, there has been growing interest in incorporating qualitative research in guideline development processes from both stakeholders and guideline development bodies. In this international collaboration, 19 qualitative psychotherapy researchers from 10 countries articulated the benefits of including qualitative findings within the guideline development process and generated recommendations for guideline developers. The underlying question of this report was "Why and how should qualitative research be used in efforts to develop guidance for psychotherapy practice?" The advantages of reviewing qualitative findings included the ability to identify treatment patterns at the level of in-session dynamics, cultural contexts, interpersonal relationships, and internal experiences, thereby creating guidance that is responsive to clients' needs in the moment-to-moment therapy process. Recommendations are offered at the systemic level (e.g., guideline formation processes, methods of education, research funding priorities). Also, methodological advice is offered for guideline developers when selecting to incorporate qualitative research in the implementation of an expanded guideline development process. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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 | 0.512 | 0.733 |
| Meta-epidemiology (narrow) | 0.003 | 0.005 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.021 | 0.026 |
| Open science | 0.021 | 0.019 |
| Research integrity | 0.026 | 0.033 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".