Human Aspects of IT for the Aged Population. Design for Aging

doi:10.1007/978-3-319-39943-0

Cited by 8 publications

(1 citation statement)

References 51 publications

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“…Além da dificuldade em escolher os métodos e usuários corretos, as empresas, ao possuírem recursos limitados para desenvolver produtos, entendem que envolver o usuário é um luxo de alto custo que nem sempre é necessário ou viável de realizar Zhang;Dong, 2016). No entanto, os custos para envolver o usuário estão diminuindo devido às novas e melhores ferramentas de design, facilidades pelo prototipagem, e à comunicação na internet entre os diversos grupos de usuários (VON HIPPEL; OGAWA; JONG, 2011).…”

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Mapeamento das tarefas e características dos usuários para seu envolvimento no processo de desenvolvimento de produtos para a saúde

Michelini¹,

Costa²

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Mapeamento das tarefas e características dos usuários para seu envolvimento no processo de desenvolvimento de produtos para a saúde

Michelini¹,

Costa²

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Privacy vs. Security: Trade-Offs in the Acceptance of Smart Technologies for Aging-in-Place

Schomakers

Ziefle

2022

International Journal of Human–Computer Interaction

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Applying an Extended UTAUT2 Model to Explain User Acceptance of Lifestyle and Therapy Mobile Health Apps: Survey Study

Schomakers¹,

Lidynia²,

Vervier³

et al. 2022

JMIR Mhealth Uhealth

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Background Mobile health (mHealth) care apps are a promising technology to monitor and control health individually and cost-effectively with a technology that is widely used, affordable, and ubiquitous in many people’s lives. Download statistics show that lifestyle apps are widely used by young and healthy users to improve fitness, nutrition, and more. While this is an important aspect for the prevention of future chronic diseases, the burdened health care systems worldwide may directly profit from the use of therapy apps by those patients already in need of medical treatment and monitoring. Objective We aimed to compare the factors influencing the acceptance of lifestyle and therapy apps to better understand what drives and hinders the use of mHealth apps. Methods We applied the established unified theory of acceptance and use of technology 2 (UTAUT2) technology acceptance model to evaluate mHealth apps via an online questionnaire with 707 German participants. Moreover, trust and privacy concerns were added to the model and, in a between-subject study design, the influence of these predictors on behavioral intention to use apps was compared between lifestyle and therapy apps. Results The results show that the model only weakly predicted the intention to use mHealth apps (R2=0.019). Only hedonic motivation was a significant predictor of behavioral intentions regarding both app types, as determined by path coefficients of the model (lifestyle: 0.196, P=.004; therapy: 0.344, P<.001). Habit influenced the behavioral intention to use lifestyle apps (0.272, P<.001), while social influence (0.185, P<.001) and trust (0.273, P<.001) predicted the intention to use therapy apps. A further exploratory correlation analysis of the relationship between user factors on behavioral intention was calculated. Health app familiarity showed the strongest correlation to the intention to use (r=0.469, P<.001), stressing the importance of experience. Also, age (r=–0.15, P=.004), gender (r=–0.075, P=.048), education level (r=0.088, P=.02), app familiarity (r=0.142, P=.007), digital health literacy (r=0.215, P<.001), privacy disposition (r=–0.194, P>.001), and the propensity to trust apps (r=0.191, P>.001) correlated weakly with behavioral intention to use mHealth apps. Conclusions The results indicate that, rather than by utilitarian factors like usefulness, mHealth app acceptance is influenced by emotional factors like hedonic motivation and partly by habit, social influence, and trust. Overall, the findings give evidence that for the health care context, new and extended acceptance models need to be developed with an integration of user diversity, especially individuals’ prior experience with apps and mHealth.

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Human Aspects of IT for the Aged Population. Design for Aging

Cited by 8 publications

References 51 publications

Mapeamento das tarefas e características dos usuários para seu envolvimento no processo de desenvolvimento de produtos para a saúde

Mapeamento das tarefas e características dos usuários para seu envolvimento no processo de desenvolvimento de produtos para a saúde

Privacy vs. Security: Trade-Offs in the Acceptance of Smart Technologies for Aging-in-Place

Applying an Extended UTAUT2 Model to Explain User Acceptance of Lifestyle and Therapy Mobile Health Apps: Survey Study

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