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Record W3208691478 · doi:10.1093/pch/pxab061.097

120 The Experience of Housing Need Amongst Families Caring for Children with Medical Complexity: A Qualitative Study

2021· article· en· W3208691478 on OpenAlexaff
Clara Moore, Kara Grace Hounsell, Arielle Zahavi, Danielle Arje, Natalie Weiser, Kayla Esser, Kathy Netten, Joanna Soscia, Eyal Cohen, Julia Orkin

Bibliographic record

VenuePaediatrics & Child Health · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsNonprobability samplingThematic analysisStressorQualitative researchPsychologyPopulationHealth careNursingMedicineFamily medicineClinical psychologySociologyEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Primary Subject area Complex Care Background Caregivers of children with medical complexity (CMC) face many financial, social and emotional stressors related to their child’s medical condition(s). Previous research has demonstrated that financial stress among this population can have an impact on their housing situation. Families of CMC may face other unique housing challenges such as disability accommodations in the home and housing space and layout. Objectives The primary aim of this study was to explore families’ perspectives and experiences of housing need, and its relationship to their child’s health status as it pertains to CMC. Design/Methods We conducted a qualitative study using semi-structured interviews to identify themes surrounding families of CMC’s experiences of housing need. Parents of CMC were recruited through purposive sampling from the Complex Care Program at a tertiary pediatric health sciences centre. Recruitment ceased when thematic saturation was reached, as determined by consensus of the research team. Interviews were recorded, transcribed verbatim, coded, and analyzed using thematic analysis. Results Twenty parents completed the interview, of whom 89% were mothers and 42% identified a non-English language as their first language. Two major themes and five subthemes (in parentheses) were identified: 1) the impact of health on housing (housing preferences, housing possibilities, housing outcome as a trade-off) and 2) the impact of housing on health (health of the caregiver, health of the child). Some parents reported that their child’s medical needs resulted in specific preferences regarding the location and layout of their home. Parents also indicated that their caregiving role often affected their income and home ownership status, which in turn, affected their housing possibilities. Thus, the housing situation (location and layout of the home) was often the result of a trade-off between the parent’s housing preferences and possibilities. Conclusion Housing is a recognized social determinant of health. We found that among CMC, health also appears to be a significant determinant of housing as families reported that the health of their child impacted their housing preferences and the options available to them (possibilities). To support the health of CMC and their families, policies targeting improved access to subsidized housing, improved sources of funding and regulations allowing families who rent to make accessibility changes are vital. Future research should investigate the impact of household income on housing need and identify interventions to support appropriate housing for CMC.

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)0.008
metaresearch head score (Gemma)0.013
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 score0.016
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0100.006
Scholarly communication0.0030.004
Open science0.0010.004
Research integrity0.0010.002
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 head0.059
GPT teacher head0.398
Teacher spread0.340 · 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
Published2021
Admission routes1
Has abstractyes

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