Learning how to rate video-recorded therapy sessions: A practical guide for trainees and advanced clinicians.
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
Watching and rating psychotherapy sessions is an important yet often overlooked component of psychotherapy training. This article provides a simple and straightforward guide for using one Website (www.ATOStrainer.com) that provides an automated training protocol for rating of psychotherapy sessions. By the end of the article, readers will be able to have the knowledge to go to the Website and begin using this training method as soon as they have a recorded session to view. This article presents, (a) an overview of the Achievement of Therapeutic Objectives Scale (ATOS; McCullough et al., 2003a), a research tool used to rate psychotherapy sessions; (b) a description of APA training tapes, available for purchase from APA Books, that have been rated and scored by ATOS trained clinicians and posted on the Website; (c) step-by-step procedures on how ratings can be done; (d) an introduction to www.ATOStrainer.com where ratings can be entered and compared with expert ratings; and (e) first-hand personal experiences of the authors using this training method and the benefits it affords both trainees and experienced therapists. This psychotherapy training Website has the potential to be a key resource tool for graduate students, researchers, and clinicians. Our long-range goal is to promote the growth of our understanding of psychotherapy and to improve the quality of psychotherapy provided for patients.
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.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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