Development and validation of the Cultural Responsiveness Assessment Measure (CRAM): A self-reflection tool for mental health practitioners when working with First Nations people
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to develop and to validate a measure of cultural responsiveness that would assist mental health practitioners across a range of disciplines, in Australia, to work with Indigenous clients. AIM: The Cultural Responsiveness Assessment Measure (CRAM) was developed to provide a tool for practitioners and students to evaluate their own culturally responsive practice and professional development. METHOD: Following expert review for face validity the psychometric properties of the measure were assessed quantitatively, from the responses of 400 mental health practitioners. RESULTS: Confirmatory Factor Analysis yielded a nine factor, 36 item instrument that demonstrated strong convergent and discriminant validity as well as test-retest reliability. CONCLUSIONS: It is anticipated that the CRAM will have utility as both a learning tool and an assessment measure, for mental health practitioners to ensure that services are culturally responsive for Aboriginal and Torres Strait Islander people.
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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 | 0.029 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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 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".