Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Mar 23, 2020
Date Accepted: May 20, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Computer-Controlled Virtual Humans in Patient-Facing Systems: Systematic Review and Meta-Analysis
ABSTRACT
Background:
Virtual humans (VH) are computer-generated characters that appear humanlike and simulate face-to-face conversations using verbal and nonverbal cues. Although their use in patient-facing systems has garnered substantial interest, it is unknown to what extent VH are effective in health applications.
Objective:
The purpose of this review was to examine the effectiveness of VH in patient-facing systems. The design and implementation characteristics of these systems were also examined.
Methods:
Electronic bibliographic databases were searched for peer-reviewed articles with relevant key terms. Studies were included in the systematic review if they designed or evaluated VH in patient-facing systems. Out of them, studies that used a randomized controlled trial (RCT) to evaluate VH were included in a meta-analysis; they were then summarized using the PICOTS (population, intervention, comparison group, outcomes, time frame, setting) framework. Summary effect sizes, using random-effects models, were calculated and the risk of bias was assessed.
Results:
Among the 8125 unique records identified, a total of 16 articles (26 studies) with 44 primary and 22 secondary outcomes were included in the meta-analysis. Meta-analysis of the 44 primary outcome measures revealed a significant difference between intervention and control conditions favoring the virtual human intervention (SMD = .166, 95% CI =.039, .292, P = .012), but with evidence of some heterogeneity, I2 = 49.3%. The intervention time was equally split between cross-sectional (k = 13) and longitudinal (k = 13). The intervention was delivered using a personal computer in most studies (k = 18), followed by tablet (k = 3), mobile kiosk (k = 4), and desktop computer in a community center (k = 1). Additional 37 articles, describing 25 unique systems, were qualitatively, systematically reviewed. Two distinct design categories emerged—simple VH and VH augmented with health sensors and trackers.
Conclusions:
For the first time, we offer some evidence for the efficacy of VH in patient-facing systems. Considering that studies included different population and outcome types, more focused analysis is needed in the future. Future studies also need to identify what features of virtual human interventions contribute toward its effectiveness.
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Copyright
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