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Updated: May 5, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
Published on: May 31, 2019
Leveraging artificial intelligence-mediated communication for cancer prevention and control and drug addiction: A
Sunny Jung Kim1,2, Viktor Clark3, Jeff T Hancock4
1Department of Social and Behavioral Sciences, School of Public Health, Virginia Commonwealth University, 830 East Main Street, Richmond, VA 23219, USA.
Objective:
To conduct a systematic review on Artificial Intelligence-Mediated Communication (AIMC) behavioral interventions in cancer prevention/control and substance use.
Methods:
Eight databases were searched from 2017 to 2022 using the Population Intervention Control Outcome Study (PICOS) framework. We synthesized findings of AIMC-based interventions for adult populations in cancer prevention/control or substance use, applying SIGN Methodology Checklist 2 for quality assessments and reviewing retention and engagement.
Results:
Initial screening identified 187 studies; seven met inclusion criteria, involving 2768 participants. Females comprised 67.6% (n = 1870). Mean participant age was 42.73 years (SD = 7.00). Five studies demonstrated significant improvements in substance use recovery, physical activity, genetic testing, or dietary habits.
Conclusions:
AIMC shows promise in enhancing health behaviors, but further exploration is needed on privacy risks, biases, safety concerns, chatbot features, and serving underserved populations.
Implications:
There is a critical need to foster comprehensive fully powered studies and collaborations between technology developers, healthcare providers, and researchers. Policymakers can facilitate the responsible integration of AIMC technologies into healthcare systems, ensuring equitable access and maximizing their impact on public health outcomes.
Insights
Artificial Intelligence-Mediated Communication (AIMC) interventions show promise for improving health behaviors in cancer prevention and substance use recovery. Further research is needed to address ethical considerations and ensure equitable access.
Area of Science:
- Digital Health
- Behavioral Science
- Public Health
Background:
- Artificial Intelligence-Mediated Communication (AIMC) offers novel approaches to behavioral interventions.
- Existing research on AIMC in cancer prevention/control and substance use requires systematic evaluation.
Approach:
- A systematic review of eight databases (2017-2022) was conducted using the PICOS framework.
- Seven studies involving 2768 participants were synthesized, assessing retention and engagement.
- Quality was assessed using the SIGN Methodology Checklist 2.
Key Points:
- Five of the seven studies reported significant improvements in areas such as substance use recovery, physical activity, and dietary habits.
- The reviewed interventions primarily targeted adult populations, with 67.6% female participants.
- Mean participant age was 42.73 years.
Conclusions:
- AIMC interventions demonstrate potential for enhancing health behaviors in cancer prevention and substance use domains.
- Further investigation into privacy, bias, safety, chatbot functionalities, and underserved populations is crucial.
- Collaboration between technologists, healthcare providers, and researchers, supported by policymakers, is essential for responsible integration and equitable access.
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