Accepted for/Published in: JMIR Human Factors
Date Submitted: Feb 4, 2020
Date Accepted: May 14, 2020
Integration of conversion factors for the development of an inclusive eHealth tool that contributes to curbing social health inequalities: exploration and experimentation with caregivers of functionally dependent older persons.
ABSTRACT
Background:
eHealth can help to reduce social health inequalities (SHI) as much as it can exacerbate them. Several conversion factors can be integrated into the development of an eHealth tool to make it inclusive: 1) providing physical, technical, and financial access to eHealth; 2) enabling the integration of people at risk of SHI into the research and development of digital projects targeting such populations (co-design or participatory research); 3) promoting consistency between the digital health literacy level of future users (FU) and the eHealth tool; 4) developing an eHealth tool that respects the technological skills of FU; 5) ensuring that the eHealth tool is consistent with FUs’ help-seeking process; 6) respecting the learning capacities of FU, and 7) being sensitive to FUs’ cultural context. However, there is little empirical evidence pointing at how these conversion factors can be integrated into an eHealth tool.
Objective:
Based on Amartya Sen's theoretical framework of social justice, the objective of this study is to explore how 7 conversion factors can be integrated into an eHealth tool for caregivers of functionally dependent older persons.
Methods:
This study is based on a social justice design and participant observation as part of a large-scale research project funded by the Ministère de la Famille through the Quebec Ami des Aînés program. Data was collected by recording the preparation sessions, the co-design and advisory committee sessions, as well as the debriefing sessions. The results are analyzed following Miles and Huberman’s method.
Results:
A total of 78 co-designers participated in 11 co-design sessions, as well as 24 preparation sessions and 11 debriefing sessions. Five of the 7 conversion factors could be explored in this experiment. The integration of conversion factors has been uneven. The participation of future users in the development of the tool supports the other conversion factors. Respecting the learning abilities of FU is also respecting their eHealth literacy level and technological skills because they are closely related; they are therefore operationally difficult to distinguish.
Conclusions:
Conversion factors can be integrated into the development of eHealth tools that are intended to be inclusive and contribute to curbing SHI by integrating FU participation into the tool design process.
Citation
Per the author's request the PDF is not available.
Copyright
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