Content Analysis Informing the Development of Adapted Harm Reduction Talking Circles (HaRTC) with Urban American Indians and Alaska Natives Experiencing Alcohol Use Disorder
Bibliographic record
Abstract
Prior studies with Native populations have highlighted concerns about the cultural acceptability of highly directive, Eurocentric approaches, such as cognitive behavioral therapy and 12-step programs in treating alcohol use disorder (AUD). When asked in a prior qualitative study how they would redesign AUD treatment, urban American Indian and Alaska Native (AI/AN) participants reported wanting more low-barrier, harm-reduction treatment options, Native treatment providers, and culturally relevant practices. Talking Circles, which are gatherings where people share what is on their hearts, were the most requested Native cultural practice. After developing and piloting its initial iteration, researchers, community members, and traditional health professionals collaborated on the present qualitative research study to further refine an adapted Harm Reduction Talking Circle (HaRTC) protocol to address AUD with urban AI/ANs. This study features a conventional content analysis of 31 patient interviews, 6 key informant interviews with management and traditional health professionals, and 5 staff and provider focus groups to inform the development of the HaRTC. Specifically, this study describes staff, management, traditional health professionals, provider, and patient participants’ a) perspectives on HaRTC, including potential benefits, risks and mitigating factors, b) preferred traditional medicines and practices, c) preferred approaches/Circle Facilitator stance for engagement and facilitation, and d) HaRTC logistics (e.g., timing, frequency). Analyses indicated a central tendency preference for 8, weekly HaRTC sessions. Although participants expressed concerns about the potential inclusion of intoxicated people in HaRTC sessions, a large majority of staff, management and patient participants felt it was important to have HaRTC be as inclusive and accepting of community members as possible. Participants provided suggestions for how to structure facilitation of the HaRTC and mitigate risks of intoxication and patient escalation. Participants preferred an approach that is acceptance-based, respects individuals’ autonomy and culture, and creates a safe space for recovery. Most participants felt the specific traditions and medicines applied in the HaRTC should be maximally inclusive to honor the diversity of tribal affiliations and backgrounds represented among urban AI/ANs. In conclusion, participants largely supported an integration of harm-reduction principles and the North American Indigenous tradition of the Talking Circle to provide a compassionate, culturally appropriate healing practice to a larger spectrum of AI/ANs with AUD. Future research is planned to test the efficacy of this community-informed approach.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".