Age, gender, and current living status were associated with perceived access to treatment among Canadians using a cross sectional survey
Bibliographic record
Abstract
Abstract Background Access, particularly timely access, to care is the Canadian public’s most important healthcare concern. The drivers of perceived appropriateness of access to care among patients with at least one chronic health condition (CHC) are not, however, well defined. This study evaluated whether personal characteristics, self-reported health status and care received were associated with patients’ perception of effective access in managing a chronic illness. Methods The study population (n = 619) was drawn from a representative sample of the adult Canadian population who reported having ≥1 CHC in the 2013–2014 Health Care in Canada survey. Ordinal regression, with the continuation ratio model, was used to evaluate association of perceived level of access to treatment with socio-demographic factors, perceived health status and care utilization experience. Results Factors most closely associated with patients’ satisfaction with care access were: age, sex, current cohabitation, care affordability, and availability of support and information to help manage their CHCs. Individuals, particularly females, < 35 years, currently living alone, with poor access to professional support or information and who feel affordability of care has worsened over the past five years were more likely to report a poorer level of treatment access. Conclusions Individuals living alone, who are younger, and women may be especially susceptible to lower perceived access to care of CHCs and a sense of pessimism about things not getting better. Further evaluation of the reasons behind these findings may help develop effective strategies to assist these populations to access the care they need.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".