Department of Industrial and Manufacturing Systems Engineering, University of Hong Kong, Hong Kong, China (Hong Kong).
JMIR Mhealth Uhealth. 2023 Sep 13;11:e25908. doi: 10.2196/25908.
BACKGROUND: There is growing interest in mobile health apps; however, not all of them have been successful. The most common issue has been users' nonadoption or abandonment of health apps because the app designs do not meet their preferences. Therefore, to facilitate design-preference fit, understanding consumers' preferences for health apps is necessary, which can be accomplished by using a discrete choice experiment. OBJECTIVE: This study aims to examine consumer preferences for health apps and how these preferences differ across individuals with different sociodemographic characteristics and health app usage and purchase experiences. METHODS: A cross-sectional discrete choice experiment questionnaire survey was conducted with 593 adults living in Hong Kong. A total of 7 health app attributes that might affect consumers' preferences for health apps were examined, including usefulness, ease of use, security and privacy, health care professionals' attitudes, smartphone storage consumption, mobile data consumption, and cost. Mixed-effect logit regressions were used to examine how these attributes affected consumer preferences for health apps. Fixed effects (coefficient β) of the attributes and random effects of individual differences were modeled. Subgroup analyses of consumer preferences by sex, age, household income, education level, and health app usage and purchase experiences were conducted. RESULTS: Cost was the attribute that had the greatest effect on consumers' choice of health apps (compared to HK $10 [US $1.27]-HK $50 [US $6.37]: β=-1.064; P<.001; HK $100 [US $12.75]: β=-2.053; P<.001), followed by security and privacy (compared to no security insurance-some security policies: β=.782; P<.001; complete security system: β=1.164; P<.001) and usefulness (compared to slightly useful-moderately useful: β=.234; P<.001; very useful: β=.979; P=.007), mobile data consumption (compared to data-consuming-a bit data-consuming: β=.647; P<.001; data-saving: β=.815; P<.001), smartphone storage consumption (compared to >100 MB-around 38 MB: β=.334; P<.001; <10 MB: β=.511; P<.001), and attitudes of health care professionals (compared to neutral-moderately supportive: β=.301; P<.001; very supportive: β=.324; P<.001). In terms of ease of use, consumers preferred health apps that were moderately easy to use (compared to not easy to use-moderately easy to use: β=.761; P<.001; very easy to use: β=.690; P<.001). Our results also showed that consumers with different sociodemographic characteristics and different usage and purchase experiences with health apps differed in their preferences for health apps. CONCLUSIONS: It is recommended that future health apps keep their mobile data and phone storage consumption low, include a complete security system to protect personal health information, provide useful content and features, adopt user-friendly interfaces, and involve health care professionals. In addition, health app developers should identify the characteristics of their intended users and design and develop health apps to fit the preferences of the intended users.
背景:移动健康应用越来越受到关注;然而,并非所有应用都取得了成功。最常见的问题是用户不接受或放弃使用健康应用,因为应用设计不符合他们的偏好。因此,为了促进设计偏好契合,了解消费者对健康应用的偏好是必要的,这可以通过使用离散选择实验来实现。
目的:本研究旨在考察消费者对健康应用的偏好,以及这些偏好如何因个体的不同社会人口特征和健康应用使用和购买经验而有所不同。
方法:对 593 名居住在香港的成年人进行了横断面离散选择实验问卷调查。共考察了 7 种可能影响消费者对健康应用偏好的健康应用属性,包括有用性、易用性、安全性和隐私性、医疗保健专业人员的态度、智能手机存储消耗、移动数据消耗和成本。使用混合效应逻辑回归来检验这些属性如何影响消费者对健康应用的偏好。对属性的固定效应(系数β)和个体差异的随机效应进行了建模。对性别、年龄、家庭收入、教育水平以及健康应用使用和购买经验不同的消费者偏好进行了亚组分析。
结果:成本是影响消费者选择健康应用的最大因素(与 HK $10 [US $1.27]-HK $50 [US $6.37]相比:β=-1.064;P<.001;与 HK $100 [US $12.75]相比:β=-2.053;P<.001),其次是安全性和隐私性(与没有安全保险-有一些安全政策相比:β=.782;P<.001;有完整的安全系统相比:β=1.164;P<.001)和有用性(与稍微有用-中等有用相比:β=.234;P<.001;非常有用相比:β=.979;P=.007)、移动数据消耗(与数据消耗-有点数据消耗相比:β=.647;P<.001;数据节省相比:β=.815;P<.001)、智能手机存储消耗(与>100 MB-约 38 MB相比:β=.334;P<.001;<10 MB相比:β=.511;P<.001)以及医疗保健专业人员的态度(与中立-中等支持相比:β=.301;P<.001;非常支持相比:β=.324;P<.001)。就易用性而言,消费者更喜欢中等易用程度的健康应用(与不容易使用-中等易用程度相比:β=.761;P<.001;非常容易使用相比:β=.690;P<.001)。我们的研究结果还表明,具有不同社会人口特征和不同健康应用使用和购买经验的消费者对健康应用的偏好存在差异。
结论:建议未来的健康应用将其移动数据和手机存储消耗保持在较低水平,包含完整的安全系统以保护个人健康信息,提供有用的内容和功能,采用用户友好的界面,并让医疗保健专业人员参与其中。此外,健康应用开发者应识别其目标用户的特征,并设计和开发适合目标用户偏好的健康应用。
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