Access to ultrasound imaging: A qualitative study in two northern, remote, Indigenous communities in Canada
Bibliographic record
Abstract
Ultrasound imaging is an essential component of healthcare services. This study sought to explore perceptions of access, and factors which shape access, to ultrasound imaging in two northern, remote, Indigenous communities in Canada. Using interpretive description as a methodological approach and a multi-dimensional conceptualisation of access to care as a theoretical framework, 15 semi-structured interviews were conducted in the northern Canadian communities of Stony Rapids and Black Lake, Saskatchewan. All participants had an obstetrical or non-obstetrical ultrasound exam performed in the past 10 years. Interviews were audio recorded and interview transcripts were analysed using constant comparative analysis. Geographic isolation from imaging facilities was a central barrier to participants accessing ultrasound imaging. Other barriers became apparent when participants had to travel for ultrasound, including fear of air travel, isolation from family, financial means, and unfamiliarity with larger cities. Barriers such as family and work responsibilities were exacerbated by the barrier of geography. Participants overcame these barriers as they were motivated by potential diagnostic benefits of ultrasound imaging. This study highlights disparities in access to ultrasound for northern, remote, Indigenous populations. Future efforts to improve access to imaging should consider barriers of distance to imaging facilities and strategies to bridge these barriers.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.031 | 0.010 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".