MétaCan
Menu
Back to cohort
Record W4409337321 · doi:10.5334/ijic.9467

Empowering and Supporting Young Caregivers Interacting with the Healthcare System: Translating Survey Findings through Co-Design

2025· article· en· W4409337321 on OpenAlexaboutno aff
Isabelle Caven, Marianne Saragosa, Shoshana Hahn‐Goldberg, Yona Lunsky, Melissa Frew, Jennifer Rosart, Jill I. Cameron, Kristine Newman, Karen Okrainec

Bibliographic record

VenueInternational Journal of Integrated Care · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careIntegrated careSurvey researchCo-designHealthcare systemPsychologyKnowledge managementNursingProcess managementMedicineComputer scienceBusinessApplied psychologyPolitical science

Abstract

fetched live from OpenAlex

In Canada and worldwide, there is a growing awareness of young carers, or youth under 25 who provide significant and ongoing unpaid care to a loved one. Previous work by our team has identified that young carers interact with healthcare systems at various points of care and experience challenges with receiving limited information or communication from care teams, lacking acknowledgment of their caring role, balancing caregiving responsibilities with school/work, and some are tasked with making critical healthcare decisions with minimal support. Little is also known about how equipped healthcare providers who may encounter young carers are at recognizing and supporting young carers at the point of care. Drawing from a survey of Swiss professionals working with young carers, our national, cross-sectional survey of healthcare providers aims to understand the level of awareness providers have regarding young carers, their ability to recognize and support youth in caring roles as clinicians, and training/resources that are needed to help providers at point of care. Using integrated knowledge translation and experience-based co-design approaches, the survey findings will inform the development and refinement of tools to support young carers as they interact with the healthcare system. Bringing together young carers, community organizations that support caring youth, and healthcare providers, we will work to identify priority areas, as informed by survey findings and lived experiences, which will drive the co-design of support tools. The project at large, including survey content, recruitment, co-design and dissemination is advised upon by key knowledge users, including young carers and community organizations, and is co-led by a young carer. Our presentation aims to review preliminary project findings on the national survey of healthcare providers and the key areas identified through co-design where resources are needed to empower and support young caregivers interacting with the healthcare system. Interactions with the healthcare system can be complex for any patient and their families; however, by engaging with young carers and healthcare providers, we hope to learn about the most critical areas they need support in to more meaningfully and efficiently improve the health and well-being of young carers and the individuals they care for.

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)0.225
metaresearch head score (Gemma)0.249
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score0.956

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2250.249
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0050.004
Science and technology studies0.0030.005
Scholarly communication0.0090.007
Open science0.0030.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.030
GPT teacher head0.366
Teacher spread0.336 · 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.

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 routes1
Has abstractyes

Explore more

Same venueInternational Journal of Integrated CareSame topicFamily Support in IllnessFrench-language works237,207