Inability to access primary care clinics among people who inject drugs in a Canadian health care setting
Bibliographic record
Abstract
<h3>Objective</h3> To examine the prevalence and correlation of self-reported inability to access community primary care clinics among people who inject drugs (PWID). <h3>Design</h3> Self-report questionnaire data. <h3>Setting</h3> Vancouver, BC. <h3>Participants</h3> Data were derived from 3 prospective cohort studies of PWID between 2013 and 2016. <h3>Main outcome measures</h3> Multivariable generalized estimating equations were used to determine prevalence of and reasons for self-reported inability to access primary care, as well as factors associated with inability to access care. <h3>Results</h3> Of 1396 eligible participants, including 525 (37.6%) women, 209 (15.0%) persons were unable to access a primary care clinic at some point during the study period. In the multivariable analysis, factors independently associated with inability to access clinics included ever being diagnosed with a mental health disorder (adjusted odds ratio [AOR] = 1.63, 95% CI 1.14 to 2.35), dealing drugs (AOR = 1.60, 95% CI 1.15 to 2.22), using emergency services (AOR = 1.51, 95% CI 1.13 to 2.02), being female (AOR = 1.49, 95% CI 1.08 to 2.08), and testing positive for HIV (AOR = 0.47, 95% CI 0.30 to 0.72) (for all factors, <i>P</i> < .05). <h3>Conclusion</h3> Specific exposures were linked to challenges in accessing primary care among the sample of PWID, even in a publicly funded health care setting. Notably, models designed for care of people with HIV appear to increase access to primary care among PWID. Further research is needed to determine how to effectively treat accompanying mental illness, how to provide women-centred services, and how to connect people with primary care who would likely otherwise go to the emergency department.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".