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Record W4414856173 · doi:10.1177/23743735251383246

The Need for Health Systems to Engage With and Support Youth who are Caregivers—A Lived Experience Perspective From Young Carers

2025· article· en· W4414856173 on OpenAlexafffundabout
Alexandre Grant, Nicholas Goberdhan, Kristie Mar, Amanda Ramkishun, Samiha Rahman, Tyler Redublo, Isabelle Caven, Karen Okrainec

Bibliographic record

VenueJournal of Patient Experience · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsTed Rogers Centre for Heart ResearchCentre for Excellence in Mining InnovationConcordia UniversityUniversity of AlbertaUniversity of British ColumbiaUniversity of TorontoToronto General HospitalUniversity Health Network
FundersPhysicians' Services Incorporated Foundation
KeywordsPerspective (graphical)Health careLived experienceHealthcare systemPrimary careHealth professionalsValue (mathematics)Young adult

Abstract

fetched live from OpenAlex

Caregivers under the age of 25, or young carers, lack significant recognition and support across sectors of education, employment, and healthcare. As young carer advisors on a prior research project exploring Canadian healthcare providers' awareness of young carers in their clinical practice, we were a part of an experience-based co-design process to create a toolkit for healthcare providers to better recognize, engage with, and support young carers in clinical practice. In the following Patient Perspective, we highlight our individual experiences of interacting with the healthcare system as young carers and propose three key recommendations for healthcare systems to better value and integrate young carers. These include the need to recognize that young people can be carers, the importance of support and resources for carers and care recipients alike, and the importance of accessible and reliable primary care.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.331
Teacher spread0.300 · 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 teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes3
Has abstractyes

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