Journal Article

DKFZ-2025-02518

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Generative AI in social media health communication: systematic review and meta-analysis of user engagement with implications for cancer prevention.

Merl, N. B. (First author)DKFZ* ; Schramm, F.DKFZ* ; Wies, C.DKFZ* ; Winterstein, J. T.DKFZ* ; Brinker, T. (Last author)DKFZ*

2026
Elsevier Amsterdam [u.a.]

Abstract: Artificial intelligence (AI) is increasingly used to generate digital health communication, but its impact on user engagement and message perception in oncology prevention remains unclear. Understanding how AI-generated content influences attitudes and behaviors is critical for designing effective and trustworthy prevention strategies.We conducted a systematic review and meta-analysis following PRISMA 2020 guidelines (PROSPERO CRD420251021036). PubMed, Scopus, Web of Science, and Google Scholar were searched for studies published between 2020 and 2025 that compared AI-generated and human-generated social media content regarding user attitudes, interaction, or health-related outcomes. Risk of bias was assessed using RoB 2, ROBINS-I, AXIS, MMAT, and CASP tools. Random-effects meta-analyses pooled standardized effect sizes for user interaction and perceived quality.Thirty-three studies (28 quantitative, five qualitative) met inclusion criteria across health, marketing, political, and social media domains. AI-generated content significantly increased user interaction compared with human-generated content (pooled ratio = 1.12; 95 % CI 1.04-1.20), while perceived quality showed a positive but nonsignificant trend. Credibility and emotional resonance consistently mediated user engagement across modalities.AI-generated communication can expand the reach and personalization of cancer prevention messages but carries risks when transparency and factual accuracy are lacking. Ethical frameworks emphasizing disclosure, credibility cues, and expert verification are essential to ensure safe use. Integrating AI tools into oncology prevention strategies may strengthen engagement, trust, and adherence to evidence-based health communication.

Keyword(s): Artificial intelligence ; Cancer prevention ; Digital public health ; GenAI ; Generative AI ; Health communication ; Public health ; Social media ; User engagement ; health

Note: #EA:C140#LA:C140# / Volume 232, January 2026, 116114

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Contributing Institute(s):

1. Digitale Prävention, Diagnostik und Therapiesteuerung (C140)

Research Program(s):

1. 313 - Krebsrisikofaktoren und Prävention (POF4-313) (POF4-313)

Appears in the scientific report 2025

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Database coverage:
; ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; Current Contents - Life Sciences ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 5 ; JCR ; Nationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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