Artificial Intelligence for Participatory Health: Applications, Impact, and Future Implications

Area of Science:

• Participatory Health Informatics
• Artificial Intelligence Applications
• Digital Health

Background:

• Artificial intelligence (AI) offers significant potential for extracting valuable insights from diverse online sources within participatory health informatics.
• Understanding the current state and applications of AI is crucial for advancing this interdisciplinary field.

Purpose of the Study:

• To identify the state-of-the-art applications of artificial intelligence (AI) in participatory health.
• To explore the diverse areas where AI is currently being utilized within the participatory health landscape.

Main Methods:

• A comprehensive literature search was performed across seven major academic databases, including PubMed, Embase, and SCOPUS, for articles published since 2013.
• Clinical trials related to AI in participatory health were identified and analyzed using data from clinicaltrials.gov.

Main Results:

• Twenty-two articles and 12 clinical trials were selected, highlighting AI's role in participatory health.
• The primary application identified was the secondary analysis of social media data, encompassing patient experiences, adverse drug reactions, and medication perceptions.
• Additional applications included forum moderation, user retention prediction, vocabulary extraction, information gap identification, and medical term simplification for consumers.

Conclusions:

• AI in participatory health informatics is an emerging field with significant potential for growth.
• Further research is essential to evaluate AI's impact on individual psychosocial well-being.
• Investigating AI's influence on psychosocial well-being is key to its broader acceptance within the healthcare ecosystem.