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DOI 10.1002/cncr.70491

Медицинская библиотека · Cancer · 2026

Alcohol consumers' receptivity to artificial intelligence-generated alcohol-cancer risk messages: An experimental study.

Asfar Taghrid, Brown Eric Christopher, Penedo Frank J, Abrams Ian, Jayakumaran Jayanthi, Oluwole Olusanya Joshua, Ferdous Tarana, Naimi Timothy, Avendano Daniela, Maziak Wasim

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Аннотация

BACKGROUND

Alcohol is a group 1 carcinogen linked to seven cancers, yet awareness of this risk remains low in the United State. Identifying effective alcohol-cancer communication strategies is a public health priority. The objective of this study was to test the effects of message specificity (general vs. cancer-specific) and visual intensity (text-only, neutral pictorial, graphic pictorial) on message receptivity (attention, emotional reactions) and precursors of behavior (harm perception; intentions to reduce, limit, or stop drinking) among moderate and heavy alcohol consumers.

METHODS

Eight evidence-based text messages were created across two topics: general and cancer-specific harm. Artificial intelligence was used to generate pictorial versions at two intensities: neutral (symbolic, no visible disease) and graphic (explicit health consequences). In a 2025 online within-subject/between-subject crossover experiment, 639 US adult consumers (aged 21 years and older; 49.3% female) each viewed two randomly selected messages (one general, one cancer-specific) presented in three formats (text-only, neutral, and graphic; for six total formats), with counterbalanced order. Linear mixed-effects models were used to estimate differences by intensity, specificity, and drinking levels, reporting regression coefficients (β, 95% confidence intervals).

RESULTS

Cancer-specific messages produced greater attention, emotional reactions, and intentions to reduce drinking than general messages (β = 0.10-0.19; p < .05). Graphic pictorials outperformed neutral images on emotional and behavioral outcomes (β = 0.19-0.22; p < .05). Moderate consumers showed stronger perceived harm and message responsiveness than heavy consumers (β = 0.29-0.77; p < .05).

CONCLUSIONS

Artificial intelligence-generated alcohol-cancer messages are feasible and effective in strengthening precursors to behavior change. Cancer-specific content and higher visual intensity enhance impact, particularly among moderate consumers, highlighting the importance of tailoring alcohol-cancer communication strategies to different audience characteristics.

Для цитирования: Asfar Taghrid, Brown Eric Christopher, Penedo Frank J, Abrams Ian, Jayakumaran Jayanthi, Oluwole Olusanya Joshua, Ferdous Tarana, Naimi Timothy, Avendano Daniela, Maziak Wasim. Alcohol consumers' receptivity to artificial intelligence-generated alcohol-cancer risk messages: An experimental study.. Cancer. 2026. DOI: 10.1002/cncr.70491.

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