Psychotherapies at a Glance: Consensus Guideline–Recommended Psychotherapies for Adults With Psychiatric Disorders
Bibliographic record
Abstract
Clinical decision making by psychiatrists and informed consent by patients require knowledge of evidence-based psychotherapies (EBPs) and their indications. However, many mental health professionals are not versed in the empirical literature on EBPs or the consensus guideline recommendations derived from this literature. The authors compared rigorous national consensus guidelines for EBP treatment of DSM-defined adult psychiatric disorders—derived from well-conducted randomized controlled trials and meta-analyses and from expert opinions from the United States, United Kingdom, and Canada—to create the Psychotherapies-at-a-Glance tool. Recommended EBPs are cognitive-behavioral therapy, family therapy, contingency management, dialectical behavior therapy, eye movement desensitization reprocessing, interpersonal psychotherapy, mentalization-based treatment, motivational interviewing, peer support, problem-solving therapy, psychoeducation, short-term psychodynamic psychotherapy, and 12-step facilitation. The Psychotherapies-at-a-Glance tool summarizes the indications, rationales, and therapeutic tasks that characterize these differing psychotherapies and psychosocial treatments. The tool is intended for use in clinical teaching, treatment planning, and patient communications.
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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 | 0.015 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".