Exploring the lived experience of patients and families who speak language other than English (LOE) for healthcare: developing a qualitative study
Notice bibliographique
Résumé
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.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,034 | 0,037 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,018 | 0,019 |
| Communication savante | 0,009 | 0,011 |
| Science ouverte | 0,003 | 0,012 |
| Intégrité de la recherche | 0,003 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».