The Efficacy of a Health Promotion Intervention for Indigenous Women: Reclaiming Our Spirits
Bibliographic record
Abstract
Indigenous women globally are subjected to high rates of multiple forms of violence, including intimate partner violence (IPV), yet there is often a mismatch between available services and Indigenous women's needs and there are few evidence-based interventions specifically designed for this group. Building on an IPV-specific intervention (Intervention for Health Enhancement After Leaving [iHEAL]), "Reclaiming Our Spirits" (ROS) is a health promotion intervention developed to address this gap. Offered over 6 to 8 months in a partnership between nurses and Indigenous Elders, nurses worked individually with women focusing on six areas for health promotion and integrated health-related workshops within weekly Circles led by an Indigenous Elder. The efficacy of ROS in improving women's quality of life and health was examined in a community sample of 152 Indigenous women living in highly marginalizing conditions in two Canadian cities. Participants completed standard self-report measures of primary (quality of life, trauma symptoms) and secondary outcomes (depressive symptoms, social support, mastery, personal agency, interpersonal agency, chronic pain disability) at three points: preintervention (T1), postintervention (T2), and 6 months later (T3). In an intention-to-treat (ITT) analysis, Generalized Estimating Equations (GEE) were used to examine hypothesized changes in outcomes over time. As hypothesized, women's quality of life and trauma symptoms improved significantly pre- to postintervention and these changes were maintained 6 months later. Similar patterns of improvement were noted for five of six secondary outcomes, although improvements in interpersonal agency were not maintained at T3. Chronic pain disability did not change over time. Within a context of extreme poverty, structural violence, and high levels of trauma and substance use, some women enrolled but were unable to participate. Despite the challenging circumstances in the women's lives, these findings suggest that this intervention has promise and can be effectively tailored to the specific needs of Indigenous women.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".