The impact of socioeconomic inequality on access to health care for patients with advanced cancer: A qualitative study
Bibliographic record
Abstract
Objective: In Canada, populations experiencing socioeconomic inequality have lower rates of access to screening and diagnosis and higher mortality rates than people from higher-income areas. Limited evidence exists concerning their experiences when living with advanced cancer. We explored how socioeconomic inequality shapes the experiences of patients with advanced cancer. Methods: We utilized a qualitative study design that combined tenets of hermeneutic phenomenological inquiry and critical theory. Four individuals with advanced cancer from low-income neighborhoods, three family members, and six cancer care providers were accrued through a tertiary cancer center in a western Canadian city. One-on-one interviews and brief notes were used for data collection. Data were analyzed through thematic analysis. Results: Three interrelated themes were identified: 'Lack of access to socioeconomic supports,' 'Gaps in access to health care resources and services,' and 'Limited access to symptom relief.' Patients experienced inadequate finances, housing, and transportation. Most patients lived alone and had limited family and social support. Patients reported lack of knowledge of available resources and health system navigation issues, including communication problems with providers and among levels of care. Cancer care providers and patients described issues achieving symptom relief as well as challenges associated with extensive disease. Conclusions: Study findings suggest that socioeconomic inequality interferes with the ability of persons with advanced cancer to access health care and contributes to less optimal cancer outcomes. Socioeconomic inequality may increase symptom severity. Findings call for the development of tailored interventions for populations with advanced cancer and socioeconomic inequality.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".