Evaluating an mHealth App for Health and Well-Being at Work: Mixed-Method Qualitative Study

被引:30
作者
de Korte, Elsbeth Marieke [1 ,2 ]
Wiezer, Noortje [1 ]
Janssen, Joris H. [3 ]
Vink, Peter [2 ]
Kraaij, Wessel [4 ,5 ]
机构
[1] Netherlands Org Appl Sci Res, Schipholweg 77-89, NL-2316 ZL Leiden, Netherlands
[2] Delft Univ Technol, Fac Ind Design Engn, Delft, Netherlands
[3] FocusCura, Amsterdam, Netherlands
[4] Netherlands Org Appl Sci Res, The Hague, Netherlands
[5] Leiden Univ, Fac Sci, Leiden Inst Adv Comp Sci, Leiden, Netherlands
来源
JMIR MHEALTH AND UHEALTH | 2018年 / 6卷 / 03期
关键词
mHealth; work; qualitative research methods; interview; focus group; technology acceptance; user satisfaction; usability; well-being; prevention;
D O I
10.2196/mhealth.6335
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusions: 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.
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页数:17
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共 69 条
  • [1] New research perspectives on Ambient Intelligence
    Aarts, Emile
    de Ruyter, Boris
    [J]. JOURNAL OF AMBIENT INTELLIGENCE AND SMART ENVIRONMENTS, 2009, 1 (01) : 5 - 14
  • [2] Adams A, 2008, RESEARCH METHODS FOR HUMAN-COMPUTER INTERACTION, P17
  • [3] Shakra: Tracking and sharing daily activity levels with unaugmented mobile phones
    Anderson, Ian
    Maitland, Julie
    Sherwood, Scott
    Barkhuus, Louise
    Chalmers, Matthew
    Hall, Malcolm
    Brown, Barry
    Muller, Henk
    [J]. MOBILE NETWORKS & APPLICATIONS, 2007, 12 (2-3) : 185 - 199
  • [4] A Systematic Review of Internet-Based Worksite Wellness Approaches for Cardiovascular Disease Risk Management: Outcomes, Challenges & Opportunities
    Aneni, Ehimen C.
    Roberson, Lara L.
    Maziak, Wasim
    Agatston, Arthur S.
    Feldman, Theodore
    Rouseff, Maribeth
    Tran, Thinh H.
    Blumenthal, Roger S.
    Blaha, Michael J.
    Blankstein, Ron
    Al-Mallah, Mouaz H.
    Budoff, Matthew J.
    Nasir, Khurram
    [J]. PLOS ONE, 2014, 9 (01):
  • [5] [Anonymous], 1994, USABILITY INSPECTION
  • [6] [Anonymous], 2014, PSYCH RISKS EUR PREV
  • [7] DEVELOPMENT OF A TOOL FOR MEASURING AND ANALYZING COMPUTER USER SATISFACTION
    BAILEY, JE
    PEARSON, SW
    [J]. MANAGEMENT SCIENCE, 1983, 29 (05) : 530 - 545
  • [8] Measures of Physical Activity Using Cell Phones: Validation Using Criterion Methods
    Bexelius, Christin
    Lof, Marie
    Sandin, Sven
    Lagerros, Ylva Trolle
    Forsum, Elisabet
    Litton, Jan-Eric
    [J]. JOURNAL OF MEDICAL INTERNET RESEARCH, 2010, 12 (01)
  • [9] A Synthesis of the Evidence for Managing Stress at Work: A Review of the Reviews Reporting on Anxiety, Depression, and Absenteeism
    Bhui, Kamaldeep S.
    Dinos, Sokratis
    Stansfeld, Stephen A.
    White, Peter D.
    [J]. JOURNAL OF ENVIRONMENTAL AND PUBLIC HEALTH, 2012, 2012
  • [10] Are workplace health promotion programs effective at improving presenteeism in workers? a systematic review and best evidence synthesis of the literature
    Cancelliere, Carol
    Cassidy, J. David
    Ammendolia, Carlo
    Cote, Pierre
    [J]. BMC PUBLIC HEALTH, 2011, 11