Purpose: The aim of this study was to assess physiotherapists’ clinical use and acceptance of a novel telemonitoring platform to facilitate the recording of measurements during rehabilitation of patients following anterior cruciate ligament reconstruction. Additionally, suggestions for platform improvement were explored. Methods: Physiotherapists from seven Dutch private physiotherapy practices participated in the study. Data were collected through log files, a technology acceptance questionnaire and focus group meetings using the “buy a feature” method. Data regarding platform use and acceptance (7-point/11-point numeric rating scale) were descriptively analysed. Total scores were calculated for the features suggested to improve the platform, based on the priority rating (1 = nice to have, 2 = should have, 3 = must have). Results: Participating physiotherapists (N = 15, mean [SD] age 33.1 [9.1] years) together treated 52 patients during the study period. Platform use by the therapists was generally limited, with the number of log-ins per patient varying from 3 to 73. Overall, therapists’ acceptance of the platform was low to moderate, with average (SD) scores ranging from 2.5 (1.1) to 4.9 (1.5) on the 7-point Likert scale. The three most important suggestions for platform improvement were: (1) development of a native app, (2) system interoperability, and (3) flexibility regarding type and frequency of measurements. Conclusions: Even though health care professionals were involved in the design of the telemonitoring platform, use in routine care was limited. Physiotherapists recognized the relevance of using health technology, but there are still barriers to overcome in order to successfully implement eHealth in routine care.
Introduction: Many adults do not reach the recommended physical activity (PA) guidelines, which can lead to serious health problems. A promising method to increase PA is the use of smartphone PA applications. However, despite the development and evaluation of multiple PA apps, it remains unclear how to develop and design engaging and effective PA apps. Furthermore, little is known on ways to harness the potential of artificial intelligence for developing personalized apps. In this paper, we describe the design and development of the Playful data-driven Active Urban Living (PAUL): a personalized PA application.Methods: The two-phased development process of the PAUL apps rests on principles from the behavior change model; the Integrate, Design, Assess, and Share (IDEAS) framework; and the behavioral intervention technology (BIT) model. During the first phase, we explored whether location-specific information on performing PA in the built environment is an enhancement to a PA app. During the second phase, the other modules of the app were developed. To this end, we first build the theoretical foundation for the PAUL intervention by performing a literature study. Next, a focus group study was performed to translate the theoretical foundations and the needs and wishes in a set of user requirements. Since the participants indicated the need for reminders at a for-them-relevant moment, we developed a self-learning module for the timing of the reminders. To initialize this module, a data-mining study was performed with historical running data to determine good situations for running.Results: The results of these studies informed the design of a personalized mobile health (mHealth) application for running, walking, and performing strength exercises. The app is implemented as a set of modules based on the persuasive strategies “monitoring of behavior,” “feedback,” “goal setting,” “reminders,” “rewards,” and “providing instruction.” An architecture was set up consisting of a smartphone app for the user, a back-end server for storage and adaptivity, and a research portal to provide access to the research team.Conclusions: The interdisciplinary research encompassing psychology, human movement sciences, computer science, and artificial intelligence has led to a theoretically and empirically driven leisure time PA application. In the current phase, the feasibility of the PAUL app is being assessed.
BACKGROUND: Older adults want to preserve their health and autonomy and stay in their own home environment for as long as possible. This is also of interest to policy makers who try to cope with growing staff shortages and increasing health care expenses. Ambient assisted living (AAL) technologies can support the desire for independence and aging in place. However, the implementation of these technologies is much slower than expected. This has been attributed to the lack of focus on user acceptance and user needs.OBJECTIVE: The aim of this study is to develop a theoretically grounded understanding of the acceptance of AAL technologies among older adults and to compare the relative importance of different acceptance factors.METHODS: A conceptual model of AAL acceptance was developed using the theory of planned behavior as a theoretical starting point. A web-based survey of 1296 older adults was conducted in the Netherlands to validate the theoretical model. Structural equation modeling was used to analyze the hypothesized relationships.RESULTS: Our conceptual model showed a good fit with the observed data (root mean square error of approximation 0.04; standardized root mean square residual 0.06; comparative fit index 0.93; Tucker-Lewis index 0.92) and explained 69% of the variance in intention to use. All but 2 of the hypothesized paths were significant at the P<.001 level. Overall, older adults were relatively open to the idea of using AAL technologies in the future (mean 3.34, SD 0.73).CONCLUSIONS: This study contributes to a more user-centered and theoretically grounded discourse in AAL research. Understanding the underlying behavioral, normative, and control beliefs that contribute to the decision to use or reject AAL technologies helps developers to make informed design decisions based on users' needs and concerns. These insights on acceptance factors can be valuable for the broader field of eHealth development and implementation.
