Is preference for mHealth intervention delivery platform associated with delivery platform familiarity?

• Published in: BMC public health 2016-07, Vol.16 (1), p.619-619, Article 619
• Main Authors: Granger, Daniel, Vandelanotte, Corneel, Duncan, Mitch J, Alley, Stephanie, Schoeppe, Stephanie, Short, Camille, Rebar, Amanda
• Format: Article
• Language: English
• Subjects: Australia; Chronic diseases; Chronic illnesses; Community health services; Correlation analysis; Education; Electronic devices; Familiarity; Female; Humans; Internet; Internet access; Male; Management; mHealth; Middle Aged; Online; Patient Preference; Public health; Recognition, Psychology; Regression analysis; Risk factors; Smart phones; Smartphone; Smartphones; Social sciences; Studies; Tablet; Telemedicine; Web-based
• ISSN: 1471-2458; 1471-2458
• DOI: 10.1186/s12889-016-3316-2

The aim of this paper was to ascertain whether greater familiarity with a smartphone or tablet was associated with participants' preferred mobile delivery modality for eHealth interventions. Data from 1865 people who participated in the Australian Health and Social Science panel study were included into two multinomial logistic regression analyses in which preference for smartphone and tablet delivery for general or personalised eHealth interventions were regressed onto device familiarity and the covariates of sex, age and education. People were more likely to prefer both general and personalised eHealth interventions presented on tablets if they reported high or moderate tablet familiarity (compared to low familiarity) and people were more likely to prefer both general and personalised eHealth interventions presented on smartphones if they reported high or moderate smartphone familiarity, were younger, and had university education (compared to completing high school or less). People prefer receiving eHealth interventions on the mobile devices they are most familiar with. These findings have important implications that should be considered when developing eHealth interventions, and demonstrates that eHealth interventions should be delivered using multiple platforms simultaneously to optimally cater for as many people as possible.