Na Sun1, Pei-Luen Patrick Rau2. 1. Institute of Human Factors and Ergonomics, Department of Industrial Engineering, Tsinghua University, Beijing 100084, China. 2. Institute of Human Factors and Ergonomics, Department of Industrial Engineering, Tsinghua University, Beijing 100084, China. Electronic address: rpl@mail.tsinghua.edu.cn.
Abstract
BACKGROUND: Personal health devices (PHDs) are rapidly developing and getting smarter. But little is known about chronic patients' acceptance of such PHDs. OBJECTIVE: The objective of this study is to explore how chronic patients accept PHDs and what are the main factors that predict use intention of PHDs. The results will provide suggestions for the design of PHDs and e-health services. METHOD: A questionnaire survey was conducted to identify the main factors that affect chronic patients' acceptance of PHDs. Three hundred and forty-six valid responses from chronic patients were collected and the data were analyzed using exploratory factor analysis and regression analysis method. The questionnaire also included questions about respondents' experience of PHDs and preference of PHD functions. These questions help to understand lived experience of PHD users and to explain the factors that influence their use intention. RESULT: Five influencing factors that predict use intention of PHDs were identified: attitude toward technology, perceived usefulness, ease of learning and availability, social support, and perceived pressure. An acceptance model of PHDs was proposed based on these factors, and suggestions for PHD designers and e-health service designers were discussed. The exploration of PHD experience indicated that ease of learning and social norm significantly influenced PHD use intention, and many respondents expressed negative opinions on the accuracy, durability and maintenance service of PHDs. Besides, people generally expressed positive attitude toward future functions of a PHD.
BACKGROUND: Personal health devices (PHDs) are rapidly developing and getting smarter. But little is known about chronic patients' acceptance of such PHDs. OBJECTIVE: The objective of this study is to explore how chronic patients accept PHDs and what are the main factors that predict use intention of PHDs. The results will provide suggestions for the design of PHDs and e-health services. METHOD: A questionnaire survey was conducted to identify the main factors that affect chronic patients' acceptance of PHDs. Three hundred and forty-six valid responses from chronic patients were collected and the data were analyzed using exploratory factor analysis and regression analysis method. The questionnaire also included questions about respondents' experience of PHDs and preference of PHD functions. These questions help to understand lived experience of PHD users and to explain the factors that influence their use intention. RESULT: Five influencing factors that predict use intention of PHDs were identified: attitude toward technology, perceived usefulness, ease of learning and availability, social support, and perceived pressure. An acceptance model of PHDs was proposed based on these factors, and suggestions for PHD designers and e-health service designers were discussed. The exploration of PHD experience indicated that ease of learning and social norm significantly influenced PHD use intention, and many respondents expressed negative opinions on the accuracy, durability and maintenance service of PHDs. Besides, people generally expressed positive attitude toward future functions of a PHD.
Authors: Kevin Moore; Emma O'Shea; Lorna Kenny; John Barton; Salvatore Tedesco; Marco Sica; Colum Crowe; Antti Alamäki; Joan Condell; Anna Nordström; Suzanne Timmons Journal: JMIR Mhealth Uhealth Date: 2021-06-03 Impact factor: 4.773
Authors: Lieneke Fm Ariens; Florine Ml Schussler-Raymakers; Cynthia Frima; Annebeth Flinterman; Eefje Hamminga; Bernd Wm Arents; Carla Afm Bruijnzeel-Koomen; Marjolein S de Bruin-Weller; Harmieke van Os-Medendorp Journal: J Med Internet Res Date: 2017-09-05 Impact factor: 5.428
Authors: J G Timmerman; M G H Dekker-van Weering; M M Stuiver; W G Groen; M W J M Wouters; T M Tönis; H J Hermens; M M R Vollenbroek-Hutten Journal: J Cancer Surviv Date: 2017-04-10 Impact factor: 4.442
Authors: Hui-Lung Hsieh; Yu-Ming Kuo; Shiang-Ru Wang; Bi-Kun Chuang; Chung-Hung Tsai Journal: Int J Environ Res Public Health Date: 2016-12-23 Impact factor: 3.390
Authors: Thanos G Stavropoulos; Ioulietta Lazarou; Ana Diaz; Dianne Gove; Jean Georges; Nikolay V Manyakov; Emilio Merlo Pich; Chris Hinds; Magda Tsolaki; Spiros Nikolopoulos; Ioannis Kompatsiaris Journal: Front Aging Neurosci Date: 2021-04-12 Impact factor: 5.750