Patient-Facing AI-Enabled Digital Health Technologies and Quality of Life in Cancer: Systematic Review and...

Area of Science:

• Oncology
• Digital Health
• Artificial Intelligence

Background:

• Cancer significantly impacts survivors' physical, psychological, and social well-being, often leaving unmet needs.
• Patient-facing digital health technologies (DHTs) increasingly incorporate artificial intelligence (AI) in oncology.
• The impact of AI in DHTs on cancer survivors' health-related quality of life (HRQOL) requires further investigation.

Purpose of the Study:

• To systematically review AI integration in patient-facing DHTs for cancer survivors.
• To synthesize the effects of these technologies on HRQOL and other patient-reported outcomes (PROs).
• To conduct an exploratory meta-analysis on HRQOL domains.

Main Methods:

• Systematic search of multiple databases (PubMed, PsycINFO, Embase, Scopus, CINAHL, Cochrane Library) for studies published January 2020–August 2025.
• Inclusion of studies evaluating AI-enabled patient-facing DHTs for cancer survivors assessing HRQOL.
• Narrative synthesis of HRQOL and PROs, with exploratory random-effects meta-analyses for HRQOL domains; risk of bias assessment using RoB 2 and ROBINS-I V2.

Main Results:

• Seven studies (N=2867) were included; three (n=292) contributed to meta-analysis, showing moderate positive effects on global health (g=0.77) and social functioning (g=0.75).
• AI applications included symptom monitoring and education, with positive effects on general health noted, particularly in studies from China.
• Other PROs indicated high user satisfaction, improved mental health, and reduced physical symptoms, with minor adverse events.

Conclusions:

• Limited evidence suggests AI-enabled patient-facing DHTs may positively impact cancer survivors' HRQOL and PROs, especially in early survivorship.
• Findings should be interpreted cautiously due to small, heterogeneous study samples and potential biases.
• Further robust trials with larger sample sizes and appropriate controls are necessary to ascertain AI's specific contribution.