Journal of the American Medical Informatics Association : JAMIA · 2020
Patient preferences for visualization of longitudinal patient-reported outcomes data.
Оценочное исследованиеСтатьяПоддержка NIH: внешняя программаНазвание и аннотация: Перевод пока не подготовлен
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Stonbraker Samantha, Porras Tiffany, Schnall Rebecca
Аннотация
OBJECTIVE: The study sought to design symptom reports of longitudinal patient-reported outcomes data that are understandable and meaningful to end users.
MATERIALS AND METHODS: We completed a 2-phase iterative design and evaluation process. In phase I, we developed symptom reports and refined them according to expert input. End users then completed a survey containing demographics, a measure of health literacy, and items to assess visualization preferences and comprehension of reports. We then collected participants' perspectives on reports through semistructured interviews and modified them accordingly. In phase II, refined reports were evaluated in a survey that included demographics, validated measures of health and graph literacy, and items to assess preferences and comprehension of reports. Surveys were administered using a think-aloud protocol.
RESULTS: Fifty-five English- and Spanish-speaking end users, 89.1% of whom had limited health literacy, participated. In phase I, experts recommended improvements and 20 end users evaluated reports. From the feedback received, we added emojis, changed date and font formats, and simplified the y-axis scale of reports. In phase II, 35 end users evaluated refined designs, of whom 94.3% preferred reports with emojis, the favorite being a bar graph combined with emojis, which also promoted comprehension. In both phases, participants literally interpreted reports and provided suggestions for future visualizations.
CONCLUSIONS: A bar graph combined with emojis was participants' preferred format and the one that promoted comprehension. Target end users must be included in visualization design to identify literal interpretations of images and ensure final products are meaningful.
MATERIALS AND METHODS: We completed a 2-phase iterative design and evaluation process. In phase I, we developed symptom reports and refined them according to expert input. End users then completed a survey containing demographics, a measure of health literacy, and items to assess visualization preferences and comprehension of reports. We then collected participants' perspectives on reports through semistructured interviews and modified them accordingly. In phase II, refined reports were evaluated in a survey that included demographics, validated measures of health and graph literacy, and items to assess preferences and comprehension of reports. Surveys were administered using a think-aloud protocol.
RESULTS: Fifty-five English- and Spanish-speaking end users, 89.1% of whom had limited health literacy, participated. In phase I, experts recommended improvements and 20 end users evaluated reports. From the feedback received, we added emojis, changed date and font formats, and simplified the y-axis scale of reports. In phase II, 35 end users evaluated refined designs, of whom 94.3% preferred reports with emojis, the favorite being a bar graph combined with emojis, which also promoted comprehension. In both phases, participants literally interpreted reports and provided suggestions for future visualizations.
CONCLUSIONS: A bar graph combined with emojis was participants' preferred format and the one that promoted comprehension. Target end users must be included in visualization design to identify literal interpretations of images and ensure final products are meaningful.