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Record W4383737179 · doi:10.1186/s40900-023-00465-y

Exploring the lived experience of patients and families who speak language other than English (LOE) for healthcare: developing a qualitative study

2023· letter· en· W4383737179 on OpenAlexaff
Victor Do, Francine Buchanan, Peter J. Gill, David Nicholas, Gita Wahi, Zia Bismilla, Maitreya Coffey, Kim Zhou, Ann Bayliss, Presanna Selliah, Karen Sappleton, Sanjay Mahant

Bibliographic record

VenueResearch Involvement and Engagement · 2023
Typeletter
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsTrillium Health CentreNorth York General HospitalMcMaster UniversityMcMaster Children's HospitalInstitute for Work & HealthUniversity of CalgaryInstitute for Clinical Evaluative SciencesWilliam Osler Health SystemPublic Health OntarioHospital for Sick ChildrenUniversity of TorontoSickKids Foundation
Fundersnot available
KeywordsHealth careHealth equityQualitative researchParticipatory action researchPremiseCitizen journalismSet (abstract data type)Medical educationMedicinePublic relationsNursingPsychologySociologyPublic healthPolitical scienceComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Patients who use Languages other than English (LOE) for healthcare communication in an English-dominant region are at increased risk for experiencing adverse events and worse health outcomes in healthcare settings, including in pediatric hospitals. Despite the knowledge that individuals who speak LOE have worse health outcomes, they are often excluded from research studies on the basis of language and there is a paucity of data on ways to address these known disparities. Our work aims to address this gap by generating knowledge to improve health outcomes for children with illness and their families with LEP. BODY: We describe an approach to developing a study with individuals marginalized due to using LOE for healthcare communication, specifically using semi-structured qualitative interviews. The premise of this study is participatory research-our overall goal with this systematic inquiry is to, in collaboration with patients and families with LOE, set an agenda for creating actionable change to address the health information disparities these patients and families experience. In this paper we describe our overarching study design principles, a collaboration framework in working with different stakeholders and note important considerations for study design and execution. CONCLUSIONS: We have a significant opportunity to improve our engagement with marginalized populations. We also need to develop approaches to including patients and families with LOE in our research given the health disparities they experience. Further, understanding lived experience is critical to advancing efforts to address these well-known health disparities. Our process to develop a qualitative study protocol can serve as an example for engaging this patient population and can serve as a starting point for other groups who wish to develop similar research in this area. Providing high-quality care that meets the needs of marginalized and vulnerable populations is important to achieving an equitable, high-quality health care system. Children and families who use a Language other than English (LOE) in English dominant regions for healthcare have worse health outcomes including a significantly increased risk of experiencing adverse events, longer lengths of stay in hospital settings, and receiving more unnecessary tests and investigations. Despite this, these individuals are often excluded from research studies and the field of participatory research has yet to meaningfully involve them. This paper aims to describe an approach to conducting research with a marginalized population of children and families due to using a LOE. We detail protocol development for a qualitative study exploring the lived experiences of patients and families who use a LOE during hospitalization. We aim to share considerations when conducting research within this population of families with LOE. We highlight learning applied from the field of patient-partner and child and family-centred research and note specific considerations for those with LOE. Developing strong partnerships and adopting a common set of research principles and collaborative framework underlies our approach and initial learnings, which we hope spark additional work in this area.

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)0.011
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.003
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 head0.670
GPT teacher head0.568
Teacher spread0.102 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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