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Record W4229445710 · doi:10.3390/ijerph19105826

The Young Carers’ Journey: A Systematic Review and Meta Ethnography

2022· review· en· W4229445710 on OpenAlexafffund
Marianne Saragosa, Melissa Frew, Shoshana Hahn‐Goldberg, Ani Orchanian‐Cheff, Howard Abrams, Karen Okrainec

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2022
Typereview
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersOntario Ministry of Research and Innovation
KeywordsEthnographyQualitative researchPsychologyDepictionInclusion (mineral)Social psychologySociology

Abstract

fetched live from OpenAlex

Despite growing international interest, the caregiving body of literature lacks a recent understanding of young carers' experiences and their contact with the health care system. We conducted a systematic review of qualitative studies to (1) synthesize more recent qualitative evidence on young carers' experience, and (2) to identify how these young carers interact with the health care system in their caregiving role. Using a meta-ethnographic synthesis, a total of 28 empirical studies met inclusion. Key findings helped inform an overarching framework of the experience of young carers as illustrated by a journey map. The journey map is a visual depiction of the stages these young carers go through when in a caregiving role framed by three themes: (1) encountering caregiving; (2) being a young caregiver, and (3) moving beyond caregiving. The caregiving experience is perceived by young people as challenging and complex, which could be improved with more informational navigation and emotional support. Understanding these experiences provides insight into gaps in health services and potential solutions that align with the stages outlined in the journey map.

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)0.029
metaresearch head score (Gemma)0.080
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 score0.029
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.080
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.007
Bibliometrics0.0180.016
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0020.003
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 head0.289
GPT teacher head0.488
Teacher spread0.200 · 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

Citations58
Published2022
Admission routes2
Has abstractyes

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Same venueInternational Journal of Environmental Research and Public HealthSame topicFamily Support in IllnessFrench-language works237,207