Evaluating and refining a pain quality information visualization tool with patients and interpreters to facilitate pain assessment in primary care settings.

Information visualization card-sorting communication pain participatory design user-centered design

Journal

Informatics for health & social care
ISSN: 1753-8165
Titre abrégé: Inform Health Soc Care
Pays: England
ID NLM: 101475011

Informations de publication

Date de publication:
02 Oct 2023
Historique:
medline: 7 12 2023
pubmed: 21 8 2023
entrez: 21 8 2023
Statut: ppublish

Résumé

Information visualization (InfoViz) tools offer a potential solution to pain communication challenges. Incongruencies in communication styles between patients with limited English proficiency (LEP), interpreters, and providers contribute to significant disparities in pain care and outcomes. This study's purpose is to evaluate and refine a culturally appropriate InfoViz pain quality assessment tool for LEP Hmong patients. We conducted a three-part iterative user-centered study with LEP Hmong, bilingual Hmong, and Hmong interpreters with (1) participatory design sessions to evaluate and refine pain infographics for inclusion on the tool, (2) card-sorting to organize the infographics to match the mental models of LEP patients, and (3) a tool assessment to identify which tool accurately represented LEP patients' mental models and was preferred in clinical settings. Fifty-five participants provided three common themes for pain infographics refinement: culturally-relevant colors, infographics resembling human anatomy, and action-specific squiggle lines. The card-sorting sessions revealed three organizational themes: sensation (

Identifiants

pubmed: 37603830
doi: 10.1080/17538157.2023.2240411
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

353-369

Subventions

Organisme : NINR NIH HHS
ID : K23 NR019289
Pays : United States

Auteurs

Maichou Lor (M)

School of Nursing, University of Wisconsin-Madison, Madison, WI, USA.

Nancy B Yang (NB)

School of Nursing, University of Wisconsin-Madison, Madison, WI, USA.

Uba Backonja (U)

Department of Biomedical Informatics and Medical Education, University of Washington-Seattle, Seattle, WA, USA.

Suzanne Bakken (S)

School of Nursing and Biomedical Informatics, Columbia University, New York, NY, USA.

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Classifications MeSH