Culturally sensitive psychotherapy for perinatal women: A mixed methods study.
Bibliographic record
Abstract
OBJECTIVE: There is a critical need to better understand psychological treatments from a culturally sensitive lens. Using a process-oriented model, we examined treatment satisfaction among perinatal patients who received behavioral activation (BA) within a large psychotherapy trial for perinatal depression and anxiety, and explored how to optimize culturally sensitive delivery through a multistakeholder perspective. METHOD: = 417) using one-way analysis of variance. We also conducted semistructured interviews with 20 ethnically diverse perinatal participants, 19 treatment providers, and five clinical leads. We employed content analysis to identify barriers, facilitators, and strategies for delivering culturally sensitive treatment. RESULTS: = .67. Most participant interviewees reported that topics of race, ethnicity, and culture were raised during treatment sessions and that providers were able to address these topics in a culturally sensitive way. Despite this, almost all providers and clinical leads reported insufficient training to deliver culturally sensitive psychotherapy. The most-endorsed challenge for participants and providers was apprehension to bring up issues of race and ethnicity during treatment. Key facilitators included provider style, previous training, ongoing training resources, and supervision. CONCLUSION: BA offers one psychotherapeutic model that uses an idiosyncratic and process-oriented approach that fosters intersectional humility and benefits from cultural humility, comfort, and opportunities. We identify key recommendations to inform culturally sensitive, evidence-based psychological treatments that include explicitly acknowledging and eliciting topics of race, ethnicity, and culture during sessions and supervision and ongoing training and supervision. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".