Healthcare interventions to improve health outcomes for racially minoritised people with multiple long-term conditions: A Systematic Review and Narrative synthesis
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
Racially minoritised people with multiple long-term conditions (MLTCs) face inequalities across different dimensions of health(care), yet little is known about how to improve their health(care) outcomes. This systematic review and narrative synthesis seeks to identify and describe healthcare interventions designed to improve health outcomes for racially minoritised people with MLTCs and identify areas for further exploration. Given that primary care is considered the ideal setting to manage MLTCs, we focus on interventions targeted at healthcare providers/systems. We searched 9 bibliographic databases and one website and identified 6566 studies, 15 of which met the inclusion criteria. The studies were conducted in the US (n=13), Canada (n=1) and Australia (n=1). Most studies recruited racially minoritised people mainly of African American and Hispanic/Latinx descent with comorbid depression and a physical condition (diabetes (n=3), hypertension (n=3), cancer (n=2). Depression/mental health outcomes, patient-reported outcomes, clinical outcomes, medication use, and adherence were the most frequently assessed outcomes. All interventions made socio-cultural adaptations, thereby, promoting equitable and inclusive care. Community actors/assets were considered key to improving health outcomes. Of the 15 interventions, five resulted in statistically significant improvements in all outcomes of interest and nine resulted in improvements in some outcomes. This review illustrates the feasibility of socio-culturally adapted interventions, many of which successfully integrate physical and mental health care, delivered through multidisciplinary teams working collaboratively, and leveraging community assets to improve health outcomes for racially minoritised people with MLTCs. Future research is needed to assess the impact of these interventions beyond North America and Australia.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it