Barriers and facilitators to opioid agonist therapy in rural and remote communities in Canada: an integrative review
Bibliographic record
Abstract
BACKGROUND: People living in rural and remote communities in Canada are often disproportionately impacted by opioid use disorder. When compared to urban centres, rural and remote populations face additional barriers to treatment, including geographical distance as well as chronic shortages of health care professionals. This integrative review of the literature was conducted to explore the facilitators and barriers of OAT in rural and remote Canadian communities. METHODS: A search of the literature identified relevant studies published between 2001 and 2021. RESULTS: The search strategy yielded 26 scholarly peer-reviewed publications, which explored specific barriers and facilitators to rural and remote OAT in Canada, along with two reports and one fact sheet from the grey literature. Most of the scholarly articles were descriptive studies (n = 14) or commentaries (n = 9); there were only three intervention studies. Facilitators and barriers to OAT programs were organized into six themes: intrapersonal/patient factors, social/non-medical program factors, family/social context factors (including community factors), infrastructure/environmental factors, health care provider factors, and system/policy factors. CONCLUSIONS: Although themes in the literature resembled the social-ecological framework, most of the studies focused on the patient-provider dyad. Two of the most compelling studies focused on community factors that positively impacted OAT success and highlighted a holistic approach to care, nested in a community-based holistic model. Further research is required to foster OAT programs in rural and remote communities.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".