MétaCan
Menu
← Back to cohort
Record W4292014169 · doi:10.1186/s12913-022-08406-3

Community trial evaluating the integration of Indigenous healing practices and a harm reduction approach with principles of seeking safety in an Indigenous residential treatment program in northern Ontario

2022· article· en· W4292014169 on OpenAlexafffundabout
Kristen A. Morin, Teresa Naseba Marsh, C. Eshakakogan, Joseph K. Eibl, M. Anne Spence, Graham Gauthier, Jennifer Walker, Dean Sayers, Alan Ozawanimke, Brent Bissaillion, David C. Marsh

Bibliographic record

VenueBMC Health Services Research · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsAssembly of First NationsMcMaster UniversityNOSM UniversityHealth Sciences NorthCentre for Addiction and Mental Health
FundersCanadian Institutes of Health ResearchNorthern Ontario Academic Medicine Association
KeywordsIndigenousNursing researchHealth administrationMedicineHealth informaticsPublic healthHarm reductionHarmNursingEnvironmental healthPolitical scienceEcology

Abstract

fetched live from OpenAlex

OBJECTIVE: Our primary objective was to evaluate how the Indigenous Healing and Seeking Safety (IHSS) model impacted residential addiction treatment program completion rates. Our secondary objective was to evaluate health service use 6 months before and 6 months after residential treatment for clients who attended the program before and after implementing IHSS. METHODS: We observed clients of the Benbowopka Residential Treatment before IHSS implementation (from April 2013 to March 31, 2016) and after IHSS implementation (from January 1, 2018 - March 31, 2020). The program data were linked to health administration data, including the Ontario Health Insurance Plan (OHIP) physician billing, the Registered Persons Database (RPDB), the National Ambulatory Care Reporting System (NACRS), and the Discharge Abstract Database (DAD). Chi-square tests were used to compare patient characteristics in the no-IHSS and IHSS groups. We used logistic regression to estimate the association between IHSS and treatment completion. We used generalized estimating equation (GEE) regression model to evaluate health service use (including primary care visits, ED visits overall and for substance use, hospitalizations and mental health visits), Results: There were 266 patients in the no-IHSS group and 136 in the IHSS group. After adjusting for individual characteristics, we observed that IHSS was associated with increased program completion rates (odds ratio = 1.95, 95% CI 1.02-3.70). There was no significant association between IHSS patients' health service use at time one or time two. Primary care visits time 1: aOR 0.55, 95%CI 0.72-1.13, time 2: aOR 1.13, 95%CI 0.79-1.23; ED visits overall time 1: aOR 0.91, 95%CI 0.67-1.23, time 2: aOR 1.06, 95%CI 0.75-1.50; ED visits for substance use time 1: aOR 0.81, 95%CI 0.47-1.39, time 2: aOR 0.79, 95%CI 0.37-1.54; Hospitalizations time 1: aOR 0.78, 95%CI 0.41-1.47, time 2: aOR 0.76, 95%CI 0.32-1.80; Mental health visits time 1: aOR 0.66, 95%CI 0.46-0.96, time 2: aOR 0.92 95%CI 0.7-1.40. CONCLUSIONS: Our results indicate that IHSS positively influenced program completion but had no significant effect on health service use. TRIAL REGISTRATION: This study was registered with clinicaltrials.gov (identifier number NCT04604574). First registration 10/27/2020.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score0.792

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.215
GPT teacher head0.501
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2022
Admission routes3
Has abstractyes

Explore more

Same venueBMC Health Services Research→Same topicIndigenous Health, Education, and Rights→French-language works237,207→