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Record W4294669832 · doi:10.1016/s2468-2667(22)00161-x

The mental and physical health of young carers: a systematic review

2022· review· en· W4294669832 on OpenAlexaboutno aff
Rebecca Lacey, Baowen Xue, Anne McMunn

Bibliographic record

VenueThe Lancet Public Health · 2022
Typereview
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsnot available
FundersEconomic and Social Research Council
KeywordsMental healthGerontologyMedicinePhysical healthMEDLINEPsychologyPsychiatry

Abstract

fetched live from OpenAlex

The health of those who care for someone with a health condition or advanced age is poorer, on average, than non-carers. However, the health of young carers (<18 years of age) has been under-researched, especially in quantitative studies. This systematic review aimed to summarise studies assessing the mental and physical health of young carers. 1162 unique studies were screened and 14 associations between being a young carer and health were identified (two studies were treated as a single unit of analysis as they had information from the same sample). Most of the included studies were done in the UK, with the remaining studies done in the USA, Canada, Australia, and Austria. A cross-European study of 21 countries was also included. Five of the included studies investigated both mental and physical health outcomes, seven studies investigated only mental health outcomes, and one study investigated only physical health outcomes of being a young carer. All of the included studies, except one, were cross-sectional in design. Most studies found that young carers had poorer physical and mental health, on average, than their non-caregiving peers. However, the evidence is relatively weak and more quantitative research is needed, particularly research that is longitudinal in design and assesses physical health outcomes.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.178
GPT teacher head0.438
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations99
Published2022
Admission routes1
Has abstractyes

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