de Korte Elsbeth Marieke, Wiezer Noortje, Janssen Joris H, Vink Peter, Kraaij Wessel
Netherlands Organisation for Applied Scientific Research, Leiden, Netherlands.
Faculty Industrial Design Engineering, Delft University of Technology, Delft, Netherlands.
JMIR Mhealth Uhealth. 2018 Mar 28;6(3):e72. doi: 10.2196/mhealth.6335.
To improve workers' health and well-being, workplace interventions have been developed, but utilization and reach are unsatisfactory, and effects are small. In recent years, new approaches such as mobile health (mHealth) apps are being developed, but the evidence base is poor. Research is needed to examine its potential and to assess when, where, and for whom mHealth is efficacious in the occupational setting. To develop interventions for workers that actually will be adopted, insight into user satisfaction and technology acceptance is necessary. For this purpose, various qualitative evaluation methods are available.
The objectives of this study were to gain insight into (1) the opinions and experiences of employees and experts on drivers and barriers using an mHealth app in the working context and (2) the added value of three different qualitative methods that are available to evaluate mHealth apps in a working context: interviews with employees, focus groups with employees, and a focus group with experts.
Employees of a high-tech company and experts were asked to use an mHealth app for at least 3 weeks before participating in a qualitative evaluation. Twenty-two employees participated in interviews, 15 employees participated in three focus groups, and 6 experts participated in one focus group. Two researchers independently coded, categorized, and analyzed all quotes yielded from these evaluation methods with a codebook using constructs from user satisfaction and technology acceptance theories.
Interviewing employees yielded 785 quotes, focus groups with employees yielded 266 quotes, and the focus group with experts yielded 132 quotes. Overall, participants muted enthusiasm about the app. Combined results from the three evaluation methods showed drivers and barriers for technology, user characteristics, context, privacy, and autonomy. A comparison between the three qualitative methods showed that issues revealed by experts only slightly overlapped with those expressed by employees. In addition, it was seen that the type of evaluation yielded different results.
Findings from this study provide the following recommendations for organizations that are planning to provide mHealth apps to their workers and for developers of mHealth apps: (1) system performance influences adoption and adherence, (2) relevancy and benefits of the mHealth app should be clear to the user and should address users' characteristics, (3) app should take into account the work context, and (4) employees should be alerted to their right to privacy and use of personal data. Furthermore, a qualitative evaluation of mHealth apps in a work setting might benefit from combining more than one method. Factors to consider when selecting a qualitative research method are the design, development stage, and implementation of the app; the working context in which it is being used; employees' mental models; practicability; resources; and skills required of experts and users.
为改善工人的健康和福祉，已开发出工作场所干预措施，但利用率和覆盖面不尽人意，效果也较小。近年来，诸如移动健康（mHealth）应用程序等新方法正在开发中，但证据基础薄弱。需要进行研究以检验其潜力，并评估mHealth在职业环境中何时、何地以及对谁有效。为了开发出实际会被采用的针对工人的干预措施，了解用户满意度和技术接受度是必要的。为此，有各种定性评估方法可供使用。
本研究的目的是深入了解：（1）员工和专家对在工作环境中使用mHealth应用程序的驱动因素和障碍的看法及体验；（2）三种不同定性方法在工作环境中评估mHealth应用程序的附加价值：对员工的访谈、员工焦点小组以及专家焦点小组。
一家高科技公司的员工和专家被要求在参与定性评估之前至少使用一款mHealth应用程序3周。22名员工参与了访谈，15名员工参与了三个焦点小组，6名专家参与了一个焦点小组。两名研究人员使用来自用户满意度和技术接受度理论的构建，通过一本编码手册对这些评估方法产生的所有引述进行独立编码、分类和分析。
对员工的访谈产生了785条引述，员工焦点小组产生了266条引述，专家焦点小组产生了132条引述。总体而言，参与者对该应用程序的热情不高。三种评估方法的综合结果显示了技术、用户特征、环境、隐私和自主性的驱动因素和障碍。三种定性方法之间的比较表明，专家揭示的问题与员工表达的问题仅有轻微重叠。此外，可以看出评估类型产生了不同的结果。
本研究结果为计划向其员工提供mHealth应用程序的组织以及mHealth应用程序开发者提供了以下建议：（1）系统性能影响采用率和依从性；（2）mHealth应用程序的相关性和益处应对用户清晰明了，并应考虑用户特征；（3）应用程序应考虑工作环境；（4）应提醒员工其隐私权和个人数据的使用。此外，在工作环境中对mHealth应用程序进行定性评估可能受益于多种方法的结合。选择定性研究方法时要考虑的因素包括应用程序的设计、开发阶段和实施；其使用的工作环境；员工的心智模式；实用性；资源；以及专家和用户所需的技能。
