Accepted for/Published in: JMIR Human Factors
Date Submitted: Sep 10, 2020
Date Accepted: Nov 15, 2021
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Personas for Perfectly Tailored eHealth Technologies: Segmenting Heart Failure Patients using the Persona Approach Twente
ABSTRACT
Background:
The full potential of eHealth technologies to support self- and disease-management for patients with chronic diseases, is not being reached. A possible explanation for these lacking results is that during the development process, insufficient attention is paid to the needs, wishes and context of the prospective end-users. To overcome such issues, the User-Centered Design (UCD) practice of creating personas is widely accepted as a means to ensure the fit between a technology and the target group or end-users throughout all phases of development.
Objective:
In the current study, we integrate several approaches to persona-development into the Persona Approach Twente (PAT), to attain a structured approach that aligns with the iterative process of eHealth development.
Methods:
In three steps, different parts from the dataset were analyzed using the Partitioning Around Medoids clustering method. First, we used health-related EPR data only. Secondly, we added person-related data that was gathered through interviews and questionnaires. Thirdly, we added log data.
Results:
In the first step, two clusters were found, with average silhouette widths of 0.12, and 0.27. In the second step, again two clusters were found, with average silhouette widths of 0.08, and 0.12. In the third step, three clusters were identified, with average silhouette widths of 0.09, 0.12, and 0.04.
Conclusions:
The Persona Approach Twente is applicable for mixed types of data, and allows alignment of this UCD method to the iterative approach of eHealth development. Challenges lie in data quality and fitness for (quantitative) clustering.
Citation
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