Advancing Scientific Methods in Community and Cultural Context to Promote Health Equity: Lessons From Intervention Outcomes Research With American Indian and Alaska Native Communities
Open accessAbstract
Evidence-based interventions hold promise for reducing gaps in health equity across diverse populations, but evidence about effectiveness within these populations lags behind the mainstream, often leaving opportunities to fulfill this promise unrealized. Mismatch between standard intervention outcomes research methods and the cultural and community contexts of populations at greatest risk presents additional challenges in designing and implementing rigorous studies; these challenges too often impede efforts to generate needed evidence. We draw on experiences with American Indian and Alaska Native communities to illustrate how consideration of culture and context can constructively shape intervention research and improve the quality of evidence produced. Case examples from a partnership with one American Indian community highlight opportunities for increasing alignment in intervention development, research design, and study implementation to maximize both validity and feasibility. We suggest that responsively tailoring intervention outcomes research to cultural and community contexts is fundamental to supporting health equity.
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Grant-based funding models often fail to support long-term capacity development essential for sustainability.
“Grant-based funding models often fail to support long-term capacity development essential for sustainability (Scheirer & Dearing, 2011; Whitesell et al., 2018)”
From Bridging Traditions and Prevention: Insights into Implementing and Sustaining Substance Use Programs for Urban AI/AN Communities (2026) · cites this paper as Whitesell et al., 2018
The articulated value of partnerships with federal and state agencies echoes challenges identified in previous research regarding funding shortfalls and sustainability.
“This and the articulated value of partnerships with federal and state agencies echo the challenges identified in previous research regarding funding shortfalls and sustainability (Scheirer & Dearing, 2011; Whitesell et al., 2018).”
From Bridging Traditions and Prevention: Insights into Implementing and Sustaining Substance Use Programs for Urban AI/AN Communities (2026) · cites this paper as Whitesell et al., 2018
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Self-citation
- Authors
- Whitesell, N. R., Sarche, M., Keane, E., Mousseau, A. C., & Kaufman, C. E.
- Affiliations
- Colorado School of Public Health (US)
- Corresponding author
- Whitesell, Nancy Rumbaugh
- Venue
- American Journal of Evaluation
- Publisher
- SAGE Publications
- Published
- 2017-09-01
- Volume
- 39
- Issue
- 1
- Pages
- 42-57
- ISSN
- 1098-2140 (ISSN-L)
- 1557-0878
- PMC
- PMC6812651
- OpenAlex
- W2752979103
- Cited by
- 37
- References
- 52
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 3 · 2023: 2 · 2022: 3 · 2021: 6 · 2020: 6 · 2019: 5 · 2018: 4
- FWCI
- 4.56
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Evaluation (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Centers for Disease Control and Prevention (R01PH000027)
- National Institute of Mental Health (R01MH069086)
- National Institute on Drug Abuse (R01DA035111, R01DA027665)
- Topics
- Social Sciences › Health › Indigenous Health, Education, and Rights
- Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
- Social Sciences › Sociology and Political Science › Cultural Competency in Health Care
- Keywords
- health equity, American Indian and Alaska Native communities, culturally tailored interventions, community context, evidence-based interventions, community partnerships, health disparities
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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