Summary
Objective: Artificial intelligence (AI) provides people and professionals working in the field
of participatory health informatics an opportunity to derive robust insights from
a variety of online sources. The objective of this paper is to identify current state
of the art and application areas of AI in the context of participatory health.
Methods: A search was conducted across seven databases (PubMed, Embase, CINAHL, PsychInfo,
ACM Digital Library, IEEExplore, and SCOPUS), covering articles published since 2013.
Additionally, clinical trials involving AI in participatory health contexts registered
at clinicaltrials.gov were collected and analyzed.
Results: Twenty-two articles and 12 trials were selected for review. The most common application
of AI in participatory health was the secondary analysis of social media data: self-reported
data including patient experiences with healthcare facilities, reports of adverse
drug reactions, safety and efficacy concerns about over-the-counter medications, and
other perspectives on medications. Other application areas included determining which
online forum threads required moderator assistance, identifying users who were likely
to drop out from a forum, extracting terms used in an online forum to learn its vocabulary,
highlighting contextual information that is missing from online questions and answers,
and paraphrasing technical medical terms for consumers.
Conclusions: While AI for supporting participatory health is still in its infancy, there are
a number of important research priorities that should be considered for the advancement
of the field. Further research evaluating the impact of AI in participatory health
informatics on the psychosocial wellbeing of individuals would help in facilitating
the wider acceptance of AI into the healthcare ecosystem.
Keywords
Community-based participatory research - participatory health - artificial intelligence
- social media - wearable electronic devices - mobile health
