An Integrated Strategy for the Cultural Adaptation of Evidence-Based Interventions
Bibliographic record
Abstract
Background: The importance of adapting evidence-based health interventions to enhance their congruence with the beliefs of ethno-cultural communities is well recognized. Although a systematic cultural adaptation process is available, it lacks specific instructions on how to adapt interventions so that they are aligned with cultural beliefs. In this paper, we present an integrated strategy that operationalizes the adaptation process by describing specific practical instructions on how to align interventions with cultural beliefs. Methods: The strategy integrates concept and intervention mapping, and uses mixed methods for gathering data from community representatives. The data pertain to a community’s cultural beliefs and values related to a health problem, acceptability of evidence-based interventions targeting the problem, and aspects of the interventions that should be modified to enhance their fit with cultural beliefs. A step-by-step protocol is described to guide application of the integrated strategy for cultural adaptation. Conclusions: The strength of the integrated strategy relies on the use of concept and intervention mapping approaches for specifying a step-by-step protocol to actively engage community representatives in the cultural adaptation of interventions. Future research should evaluate the utility of this strategy.
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How this classification was reachedexpand
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".