Access to health services in Western Newfoundland, Canada: Issues, barriers and recommendations emerging from a community-engaged research project
Bibliographic record
Abstract
Research indicates that people living in rural and remote areas of Canada face challenges to accessing health services. This article reports on a community-engaged research project conducted by investigators at Memorial University of Newfoundland in collaboration with the Rural Secretariat Regional Councils and Regional Partnership Planners for the Corner Brook–Rocky Harbour and Stephenville–Port aux Basques Rural Secretariat Regions of Newfoundland and Labrador. The aim of this research was to gather information on barriers to accessing health services, to identify solutions to health services’ access issues and to inform policy advice to government on enhancing access to health services. Data was collected through: (1) targeted distribution of a survey to communities throughout the region, and (2) informal ‘kitchen table’ discussions to discuss health services’ access issues. A total of 1049 surveys were collected and 10 kitchen table discussions were held. Overall, the main barriers to care listed in the survey included long wait times, services not available in the area and services not available at time required. Other barriers noted by survey respondents included transportation problems, financial concerns, no medical insurance coverage, distance to travel and weather conditions. Some respondents reported poorer access to maternal/child health and breast and cervical screening services and a lack of access to general practitioners, pharmacy services, dentists and nurse practitioners. Recommendations that emerged from this research included improving the recruitment of rural physicians, exploring the use of nurse practitioners, assisting individuals with travel costs, developing specialist outreach services, increasing use of telehealth services and initiating additional rural and remote health research.Keywords: rural, remote, healthcare, health services, social determinants of health
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 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 | 0.093 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.021 |
| 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".