S Vosbergen1, J M R Mulder-Wiggers2, J P Lacroix3, H M C Kemps4, R A Kraaijenhagen5, M W M Jaspers6, N Peek2. 1. Department of Medical Informatics, Academic Medical Center, Amsterdam, The Netherlands. Electronic address: svosbergen@gmail.com. 2. Department of Medical Informatics, Academic Medical Center, Amsterdam, The Netherlands. 3. Department of Brain, Body & Behavior, Philips Research, Eindhoven, The Netherlands. 4. Department of Medical Informatics, Academic Medical Center, Amsterdam, The Netherlands; Department of Cardiology, Máxima Medical Centre, Veldhoven, The Netherlands. 5. NIPED Research Foundation, Amsterdam, The Netherlands. 6. Department of Medical Informatics, Academic Medical Center, Amsterdam, The Netherlands; Center for Human Factors Engineering of Health Information Technology (HIT Lab), Academic Medical Center, Amsterdam, The Netherlands.
Abstract
PURPOSE: Although tailoring health education messages to individual characteristics of patients has shown promising results, most patient education materials still take a one-size-fits-all approach. The aim of this study was to develop a method for tailoring health education messages to patients' preferences for various message features, using the concept of personas. This is a preliminary study focused on education for coronary heart disease (CHD) patients. METHODS: This study used a three-step approach. First, we created personas by (i) performing k-means cluster analysis on data from an online survey that assessed the preferences of 213 CHD patients for various message features and, (ii) creating a vivid description of the preferences per patient cluster in an iterative process with the research team. Second, we developed adaptation rules to tailor existing educational messages to the resulting personas. Third, we conducted a pilot validation by adapting nine existing educational messages to each of the personas. These messages and the resulting personas were then presented to a separate group of 38 CHD patients who visited the cardiology outpatient clinic. They were first asked to choose their most preferred, second most preferred, and least preferred persona. Subsequently, they were asked to rate three of the adapted messages; one for every of the persona choices. RESULTS: We created five personas that pertained to five patient clusters. Personas varied mainly on preferences for medical or lay language, current or future temporal perspective, and including or excluding explicit health risks. Fifty-five different adaptation rules were developed, primarily describing adaptations to the message's perspective, level of detail, sentence structure, and terminology. Most participants in the validation study could identify with one of the five personas, although some of them found it hard to choose. On average, 68.5% of all participants rated the messages that matched their most preferred persona more positively than, or in the same way as, the messages that matched their least preferred persona. CONCLUSIONS: The persona-based method developed in this study can be used to create a manageable set of patient-centered tailored messages, while additionally using the developed personas to assess patients' preferences.
PURPOSE: Although tailoring health education messages to individual characteristics of patients has shown promising results, most patient education materials still take a one-size-fits-all approach. The aim of this study was to develop a method for tailoring health education messages to patients' preferences for various message features, using the concept of personas. This is a preliminary study focused on education for coronary heart disease (CHD) patients. METHODS: This study used a three-step approach. First, we created personas by (i) performing k-means cluster analysis on data from an online survey that assessed the preferences of 213 CHD patients for various message features and, (ii) creating a vivid description of the preferences per patient cluster in an iterative process with the research team. Second, we developed adaptation rules to tailor existing educational messages to the resulting personas. Third, we conducted a pilot validation by adapting nine existing educational messages to each of the personas. These messages and the resulting personas were then presented to a separate group of 38 CHD patients who visited the cardiology outpatient clinic. They were first asked to choose their most preferred, second most preferred, and least preferred persona. Subsequently, they were asked to rate three of the adapted messages; one for every of the persona choices. RESULTS: We created five personas that pertained to five patient clusters. Personas varied mainly on preferences for medical or lay language, current or future temporal perspective, and including or excluding explicit health risks. Fifty-five different adaptation rules were developed, primarily describing adaptations to the message's perspective, level of detail, sentence structure, and terminology. Most participants in the validation study could identify with one of the five personas, although some of them found it hard to choose. On average, 68.5% of all participants rated the messages that matched their most preferred persona more positively than, or in the same way as, the messages that matched their least preferred persona. CONCLUSIONS: The persona-based method developed in this study can be used to create a manageable set of patient-centered tailored messages, while additionally using the developed personas to assess patients' preferences.
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