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Development and testing of a digital health acceptability model to explain the intention to use a digital diabetes prevention programme
Author(s) -
Van Rhoon Luke,
McSharry Jenny,
Byrne Molly
Publication year - 2022
Publication title -
british journal of health psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.05
H-Index - 88
eISSN - 2044-8287
pISSN - 1359-107X
DOI - 10.1111/bjhp.12569
Subject(s) - ehealth , psychological intervention , health literacy , digital health , psychology , structural equation modeling , population , mhealth , gerontology , medicine , applied psychology , clinical psychology , environmental health , nursing , health care , statistics , mathematics , economics , economic growth
Objectives Digitally‐delivered diabetes prevention programmes (DPPs) may improve population health by reversing the escalating trend of type 2 diabetes (T2D) incidence. Understanding the factors which determine digital health acceptability is critical to developing effective interventions. This study aimed to develop and test a digital health acceptability model of the factors influencing the intention of adults living in Ireland to use a digital DPP. Design A 61‐item cross‐sectional survey was issued online or in hard copy to a sample of adults. Methods Participants viewed a brochure for a smartphone‐based digital DPP. The FINDRISC assessed their risk of developing T2D, and Likert scale items assessed the personal health, social influence, eHealth literacy, and intervention factors of the model. Structural equation modelling was used to assess the relationships between these factors. Result Three‐hundred‐and‐sixteen eligible participants ( M age = 36) completed the survey, 42% of which had a slightly elevated T2D risk or higher. Twelve direct factor relationships were statistically significant. Subjective norm had a moderate‐to‐large impact on T2D risk perceptions. Health status, perceived susceptibility to T2D, eHealth readiness, communicative eHealth literacy and image had significant impacts on use intentions through mediators of perceived ease of use and perceived usefulness. The model explained 65% of the variance in digital DPP use intentions. Conclusion Personal health beliefs, social influence, and eHealth literacy collectively influence a digital DPP’s acceptability. These findings may inform the development of future digital DPPs and other digital health interventions. Future research should test the model with adults that have a higher T2D risk status.