Assessing the mental and physical health of young carers: a systematic review
Bibliographic record
Abstract
Background The health of people providing unpaid care to someone with a health condition or old age is known to be poorer, on average, than those who do not provide care. However, the health of young carers (<18 years of age) has been hugely under-researched, especially in quantitative studies. The aim of this study was to systematically review studies assessing the mental and physical health of young carers.Methods A systematic review was conducted in accordance with PRISMA guidelines. Original studies written in English, which examined associations between caring under 18 years of age and any measure of health, were included. Two independent reviewers carried out the article screening and quality assessment. A narrative synthesis was conducted. Findings We screened 901 unique articles and identified 14 studies examining associations between young caring and health. Most studies were from the UK (n=8), with the rest from the US (n=2), Canada (n=1), Australia (n=1), Austria (n=1), Switzerland (n=1) and a cross-European study (n=1). Six studies investigate both mental and physical health outcomes, seven studies investigated only mental health outcomes, and one study solely investigated the physical health impacts of being a young carer. Almost all studies were cross-sectional in design (n=13). Most studies found that young carers had poorer physical and mental health, on average, than their non-caregiving peers. Interpretation Young carers appear to have poorer health than their non-caregiving peers. However, the extant research base is relatively weak. More quantitative research is urgently needed, particularly that which is longitudinal in design, and which considers physical health outcomes.
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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 | 0.017 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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 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".