A Knowledge Synthesis of Cross-Cultural Psychotherapy Research: A Critical Review
Bibliographic record
Abstract
This article presents a current knowledge synthesis of empirical studies on cross-cultural psychotherapy since 1980. Guided by a critical review framework, our search in seven relevant databases generated 80 studies published in English. Main themes are organized into (1) therapists’ cultural competence ( n = 46); (2) therapy process in cross-cultural dyads ( n = 22); and (3) cross-cultural differences in gender, sexual orientation, or social class ( n = 12). Compared to previous reviews on cross-cultural psychotherapy, the findings of this review highlight a broad range of methodological rigor in both quantitative and qualitative studies. Most studies examined actual therapy participants rather than participants in analog studies, thus emulating more therapy-near experiences in cross-cultural psychotherapy research. Also, several studies explored cross-cultural compositions beyond racial and ethnic majority therapist-minority client dyads, and included therapists of color as the participants, exploring reverse power dynamics in therapy and giving voices to foreign-born therapists. The therapy process research provides rich and full descriptions around the dynamic and interactional therapy process in cross-cultural dyads, which can be used to foster cultural sensitivities among therapists in their practice and training. We discuss the limitations of the studies included in the review and its implications for psychotherapy practice, training, and future research.
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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 | 0.032 | 0.118 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.032 | 0.021 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".