Health-related quality of life measures in incarcerated populations: protocol for a scoping review
Bibliographic record
Abstract
INTRODUCTION: Incarcerated populations represent a vulnerable and marginalised segment of society, with increased health needs and a higher burden of communicable and non-communicable diseases. Traditional population health outcomes do not capture physical, mental, emotional and social well-being. Health-related quality of life (HRQoL) outcomes attempt to measure these important parameters. To date, there has not been a scoping review to summarise the HRQoL literature in the incarcerated population. Thus, we aim to perform such a review to inform health policy decisions in incarcerated populations and support health economic evaluations of interventions in incarcerated populations. METHODS AND ANALYSIS: We will conduct a scoping review of the literature on the HRQoL in the incarcerated population informed by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and the corresponding PRISMA Extension for Scoping Reviews. The submissions records of six electronic databases with peer-reviewed literature and three health technology assessment agencies will be searched. The search strategy was informed by recommendations for HRQoL reviews. We will include studies that report HRQoL, health state utility values or reference to quality adjusted life years or quality-adjusted life expectancies of incarcerated populations. No assessments of items' quality will be made, as the purpose of this scoping review is to synthesise and describe the coverage of the evidence. We will also identify knowledge gaps on the HRQoL in the incarcerated population. ETHICS AND DISSEMINATION: Research ethics approval is not required as primary data will not be collected. The findings of this scoping review will be used to inform health economic analyses for the incarcerated population and will be disseminated through peer-reviewed publications and conference presentations.
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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 | 0.109 | 0.100 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.014 | 0.017 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.098 | 0.019 |
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".