Population confidence in the health system in 15 countries: results from the first round of the People's Voice Survey
Bibliographic record
Abstract
Population confidence is essential to a well functioning health system. Using data from the People's Voice Survey—a novel population survey conducted in 15 low-income, middle-income, and high-income countries—we report health system confidence among the general population and analyse its associated factors. Across the 15 countries, fewer than half of respondents were health secure and reported being somewhat or very confident that they could get and afford good-quality care if very sick. Only a quarter of respondents endorsed their current health system, deeming it to work well with no need for major reform. The lowest support was in Peru, the UK, and Greece—countries experiencing substantial health system challenges. Wealthy, more educated, young, and female respondents were less likely to endorse the health system in many countries, portending future challenges for maintaining social solidarity for publicly financed health systems. In pooled analyses, the perceived quality of the public health system and government responsiveness to public input were strongly associated with all confidence measures. These results provide a post-COVID-19 pandemic baseline of public confidence in the health system. The survey should be repeated regularly to inform policy and improve health system accountability.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".