Effect of free medicine distribution on ability to make ends meet: post hoc quantitative subgroup analysis and qualitative thematic analysis
Bibliographic record
Abstract
OBJECTIVES: Out-of-pocket medication costs can contribute to financial insecurity and many Canadians have trouble affording medicines. This study aimed to determine if the effect of eliminating out-of-pocket medication costs on individual's financial security varied by gender, racialisation, income and location. DESIGN: In this post hoc subgroup analysis of the CLEAN Meds trial, a binary logistic regression model was fitted and a qualitative inductive thematic analysis of comments related to participant's ability to make ends meet was carried out. SETTING: Primary care patients in Ontario, Canada. PARTICIPANTS: Adult patients (786) who reported not being able to afford medicines during the previous 12 months. INTERVENTION: Free access to a comprehensive list of essential medicines for 24 months. PRIMARY OUTCOME MEASURE: Ability to make ends meet or afford basic necessities. RESULTS: There were no significant differences in the effect of free medicine distribution by gender (OR for male 0.82; 95% CI 0.51 to 1.33, p=0.76), age (older than 65 years OR 1.28; 95 % CI 0.62 to 2.64, p=0.73), racialisation (OR 0.85; 95 % CI 0.51 to 1.45, p=0.66), household income level (above US$30 000 per year OR 1.08; 95 % CI 0.64 to 1.80, p=0.99) or location (urban OR 0.47; 95 % CI 0.23 to 0.96, p=0.10). The main theme in the qualitative analysis was insufficient income, and there were three related themes: out-of-pocket medication expenses, cost-related non-adherence and the importance of medication coverage. In the intervention group, additional themes identified included improved health, functioning and access to basic needs. CONCLUSIONS: Providing free essential medications improved financial security across subgroups in a trial population who all had trouble affording medicines. Free access to medicines could improve health directly by improving medicine adherence and indirectly by making other necessities more accessible to people who have an insufficient income. TRIAL REGISTRATION NUMBER: NCT02744963.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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) | 0.003 | 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 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".