Unmet health care needs: factors predicting satisfaction with health care services among community-dwelling Canadians living with neurological conditions
Bibliographic record
Abstract
BACKGROUND: Neurological conditions (NCs) can lead to long-term challenges including functional impairments and limitations to activities of daily living. People with neurological conditions often report unmet health care needs and experience barriers to care. This study aimed to (1) explore the factors predicting patient satisfaction with general health care, hospital, and physician services among Canadians with NCs, (2) examine the association between unmet health care needs and satisfaction with health care services among neurological patients in Canada, and (3) contrast patient satisfaction between physician care and hospital care among Canadians with NCs. METHODS: We conducted a secondary analysis on a subsample of the 2010 Canadian Community Health Survey - Annual Component data (N = 6335) of respondents with neurological conditions, who received general health care services, hospital services, and physician services within twelve months. Multivariate logistic regression fitted the models and odds ratios and 95% confidence intervals were reported using STATA version 14. RESULTS: Excellent quality care predicts higher odds of patient satisfaction with general health care services (OR, 95%CI-237.6, 70.4-801.5), hospital services (OR, 95%CI-166.9, 67.9-410.6), and physician services (OR, 95%CI-176.5, 63.89-487.3). In contrast, self-perceived unmet health care needs negatively predict patient satisfaction across all health care services: general health care services (OR, 95%CI-0.59, 0.37-0.93), hospital services (OR, 95%CI-0.41, 0.21-0.77), and physician services (OR, 95%CI-0.29, 0.13-0.69). Other negative predictors of patient satisfaction include some post-secondary education (OR, 95%CI-0.36, 0.18-0.72) for general health services and (OR, 95%CI-0.26, 0.09-0.80) for physician services. Those with secondary (OR, 95% CI-0.32, 0.13-0.76) and post-secondary graduation (OR, 95%CI- 0.28, 0.11-0.67) negatively predicted patient satisfaction among users of physician services while being an emergency room patient most recently (OR, 95%CI- 0.39, 0.20-0.77) was also negatively associated with patients satisfaction among hospital services users. CONCLUSION: This study found self-perceived unmet health care needs as a significant negative predictor of neurological patients' satisfaction across health care services and emphasizes the importance of ensuring coordinated efforts to provide appropriate and accessible care of the highest quality for Canadians with neurological conditions.
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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 | 0.001 | 0.004 |
| 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 | 0.000 | 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".