A review of the inclusion of ethnoracial groups in empirically supported posttraumatic stress disorder treatment 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
OBJECTIVE: Empirically supported treatments (ESTs) have been criticized for lack of ethnoracial representation, which may limit the generalizability of findings for non-White patients. This study assessed ethnoracial representation in United States-based randomized controlled trials (RCTs) for three evidence-based treatments for posttraumatic stress disorder (PTSD)-Prolonged Exposure (PE), Cognitive Processing Therapy (CPT), and Eye-Movement Desensitization and Reprocessing (EMDR). METHOD: Representation was measured by explicit inclusion of people of color in published PTSD RCTs. Follow-up emails were sent to corresponding authors if full demographic information was not included in the reviewed manuscripts. Information concerning participant remuneration was collected for descriptive purposes. RESULTS: All three treatment modalities reported White participants as the majority in their sample. PE and CPT trials reported similar levels of ethnoracial diversity, while EMDR efficacy studies reported the least ethnoracial diversity. Across the reviewed studies, with few exceptions, we found low numbers of non-White participants in the majority of reviewed studies, which was compounded by poor or unclear methods of reporting ethnoracial information. CONCLUSIONS: This study demonstrates that the ESTs for PTSD are not adequately representative of the majority of non-White participants. Future RCTs should place a stronger emphasis on broad ethnoracial diversity in study participants to improve generalizability of findings. (PsycInfo Database Record (c) 2022 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.
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 | 0.027 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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