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Record W4403682989 · doi:10.1093/pch/pxae067.086

87 Far from home: Qualitative evaluation of the impact of geographic distance from a tertiary paediatric hospital in Canada on family experiences

2024· article· en· W4403682989 on OpenAlexaboutno aff
Asia van Buuren, Adam Sage, Adam Sernoskie, Brittney Udall, Matthew Carwana

Bibliographic record

VenuePaediatrics & Child Health · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsQualitative researchGeographyFamily medicineMedicineSociologySocial science

Abstract

fetched live from OpenAlex

Abstract Background Canada’s expansive geography has implications for children and their families seeking tertiary paediatric care. There is minimal literature describing their experiences, particularly challenges associated with receiving inpatient care. This qualitative study builds on previous work that captured out-of-pocket costs and stress levels facing families while admitted to our hospital. Objectives Gather an in-depth understanding of family experiences through exploring gaps in current approaches and supports received 2) Generate potential patient-centred solutions to challenges identified Design/Methods Ethics approval was obtained. Family partners were involved in all aspects of study design. Qualitative descriptive methodology was adopted to allow for in-depth exploration of family experiences. Semi-structured interviews explored the above objectives. Participants were families that travelled more than 50 km to receive inpatient care under General Paediatrics at a tertiary hospital in Canada within 1 year of when the interview was conducted. In addition, families were purposively recruited through collaboration with community paediatricians until theoretical saturation was reached. Interviews were transcribed verbatim, de-identified, and analyzed for common themes using descriptive analysis in NVivo software. Results Between June and October 2023, 16 caregivers participated in our study. The key themes identified were in the following categories: navigating the unknown, bridging the gaps for far away families through equitable resources, and the role of self-advocacy. Families spoke to the overwhelm they faced when being admitted to our centre. For many, it was their first time in our city and the costs associated with being in this city were significant. They identified key gaps in resources and supports, such as knowledge of medical teams, difficulties with eligibility requirements and reimbursement, and inadequate availability of resources after-hours and on weekends. Self-advocacy was important to all participants and innovative solutions were proposed, such as knowledge exchange facilitated by caregivers with lived experience and caregiver-facilitated trainings for providers. Conclusion This qualitative study highlights the unique challenges facing families traveling significant distances to receive essential healthcare at a tertiary paediatric hospital in Canada. While significant gaps in resources exist, participants suggested innovative, patient-centred, equitable strategies to bridge these gaps. We plan to partner with patient partners to translate this data into evidence-based interventions to support these families at our institution.

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)0.011
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.497

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0250.014
Scholarly communication0.0060.002
Open science0.0030.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.030
GPT teacher head0.399
Teacher spread0.369 · 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 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
Published2024
Admission routes1
Has abstractyes

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