Testing the comparative effects of physical activity advice by humans vs. computers in underserved populations: The COMPASS trial design, methods, and baseline characteristics

Abstract

While physical inactivity is a key risk factor for a range of chronic diseases and conditions associated with aging, a significant proportion of midlife and older adults remain insufficiently active. This is particularly true for ethnic minority populations such as Latino adults for whom few culturally adapted programs have been developed and tested. The major objective of this 12-month cluster-randomized controlled trial is to test the comparative effectiveness of two linguistically and culturally adapted, community-based physical activity interventions with the potential for broad reach and translation. Ten local community centers serving a sizable number of Latino residents were randomized to receive one of two physical activity interventions. The Virtual Advisor program employs a computer-based embodied conversational agent named “Carmen” to deliver interactive, individually tailored physical activity advice and support. A similar intervention program is delivered by trained Peer Advisors. The target population consists of generally healthy, insufficiently active Latino adults ages 50 years and older living within proximity to a designated community center. The major outcomes are changes in walking and other forms of physical activity measured via self-report and accelerometry. Secondary outcomes include physical function and well-being variables. In addition to these outcome analyses, comparative cost analysis of the two programs, potential mediators of intervention success, and baseline moderators of intervention effects will be explored to better determine which subgroups do best with which type of intervention. Here we present the study design and methods, including recruitment strategies and yield as well as study baseline characteristics. Trial Registration: clinicaltrial.gov Identifier = NCT02111213.

Virtual Coaches for Older Adults’ Wellbeing: A Systematic Review

“…Randomized trial [2,3,11,48,55,56] Pilot study [12,13,14,21,26,31,35,39,40,43,44,45,46,47,53,54] Observational study [28,30] Preliminary studies for assessing usability or codesign choices [1,5,9,15,18,20,23,24,27,34,49] System proposal (no user study) [6,16,17,19,22,25,29,36,52] Study protocol [4,7,8,32,33,41] Field study [10,…”

“…However, from Table II, we can conclude that the personalization of content is the most frequent technique implemented in the analyzed studies. Examples of content personalization in some research papers are: history of previous interaction of the user [2,11,19,20,25,47], barriers negotiation with users [3,30], ability of users to choose modalities for the interaction [6,12], content display based on personal needs and preferences [41,32,33,34,49,47,40], local news information [16], advice and recommendations for behavioral change based on the user's preferences and needs [26,49,50,51,55], or other [10,17,35]. It is worth noting that articles [24,38,34,53] had a minimized personalization of content (e.g., the system using only the user's name in its communication), and this was considered in the analysis but noted as a low degree of content personalization.…”

“…Techniques for recognizing user activities are diverse: a step counter [1,2,3,11,18,32], self-monitoring [36], goal achievement [37], weight measurement and blood pressure with weekly telephone calls by a nurse [4], motion capture [12] and more specifically a camera [27], as well as a Microsoft Kinect camera to assess the movement of the user [35,42]. In [39], Razer Hydra and a Microsoft Kinect camera were used for activity recognition, whereas in [14], Microsoft Kinect V2 camera was used to recognize and provide real time feedback on body posture of the trainee and the ideal postures that trainees should imitate.…”

“…Web or mobile application [14,28,33,35,36,44,37,45,38,53,46,47,48,49,55,56] Conversational agents in software apps [3,6,11,20,21,30,32] Conversational agents in physical devices [10,15,16,17,24,27,31,35,39,41,43,50,51,54] Several studies showed the importance of technology in delivering wellbeing interventions to older users. This section presents the different delivery media: coaching embodiments and coaching systems that are displayed to the user.…”

Human-Computer Interaction, Ethics, and Biomedical Informatics

“…The importance of considering the perspectives of distinct patient populations is seen in a range of efforts, including preliminary inquiries into potential designs for managing opioid abuse risk in military settings [58], teen smoking prevention tools [59], electronic system decision aids for depression [60], apps for menstrual tracking [61], personal health records for young adults leaving foster care [62], and identification of research areas for informatics support of families experiencing challenges of hospitalization and subsequent care [63]. A proposed clinical trial of the potential use of computer-delivered advice for encouraging physical activity in underserved populations [64] illustrates issues at the intersection of trust, inclusivity, and HCI, as different groups may have different responses to these automated agents. Although social media may play a role, as in a project using analysis of blog posts to understand the sentiments and attitudes of individuals undergoing gender transitions [65], in-depth work with individuals and groups representing these diverse perspectives is likely to be critical to both successful design and responsible use of informatics tools.…”