Prescription charge policy acceptance among UK adults with and without long-term health conditions: a mixed-method survey
Bibliographic record
Abstract
OBJECTIVES: Since their introduction in 1952, per-prescribed item charges in England have continually risen. This study investigated the acceptability and impact of per-prescribed item charges, and awareness and use of initiatives designed to reduce prescription charge financial burden (the prescription prepayment certificate (PPC) initiative), in people living with and without long-term health conditions (LTHCs) in the UK. DESIGN: Cross-sectional mixed-method survey of people with and without an LTHC across the UK. PARTICIPANTS: 381 people, 267 people with an LTHC and 114 people without an LTHC, participated. OUTCOME MEASURES: Acceptability and impact of prescription charge policy, awareness and use of the PPC. RESULTS: Over half (53.2 %) of participants disagreed with current per-prescribed item charges. In most domains, the impact of prescription charges did not differ between people with and without LTHCs. However, people with LTHCs were more likely to report financial burden and deviate from prescribed medication regimes. 35.29% of respondents were aware of the PPC, with people with LTHCs being more likely to be aware of and use this initiative. Qualitative findings indicate perceived inequalities in current policy with themes including (1) the need for re-evaluation; (2) the burden of prescription charges; (3) inconsistencies and inequalities in current policy; and (4) positive reflections of prescription charge policy. CONCLUSIONS: Inconsistencies in current policy and a lack of public support may suggest that a re-evaluation of current policy is required. The lack of difference in the impact of prescription charge policy between people with and without LTHCs indicates that the effects of such policy are not constrained to people with LTHCs. Thus, policy amendments would benefit the wider population. Systematic efforts to increase awareness of the PPC and reduce inequalities in medical exemption criteria are suggested. TRIAL REGISTRATION NUMBER: Study protocol and analysis strategy are preregistered on Open Science Framework (https://shorturl.at/IrvnS).
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".