Leung Janni, Sun Tianze, Stjepanovic Daniel, Vu Giang, Yimer Tesfa, Connor Jason P, Hall Wayne, Chan Gary C K
The National Centre for Youth Substance Use Research, School of Psychology, The University of Queensland, St Lucia, Queensland, Australia.
Queensland Alliance for Environmental Health Science, The University of Queensland, St Lucia, Queensland, Australia.
JAMA Netw Open. 2025 Jul 1;8(7):e2514040. doi: 10.1001/jamanetworkopen.2025.14040.
Traditional approaches to developing youth vaping awareness campaigns are time-consuming and can create critical delays in public health response. Although generative artificial intelligence (AI) offers promising capabilities for health communication, research has been limited to text-only messages.
To evaluate (1) the perceived message effectiveness (PME) of AI-generated, youth-codesigned vaping awareness social media advertisements (ads) compared with existing ads from official health agencies and (2) how different source labeling is associated with PME.
DESIGN, SETTING, AND PARTICIPANTS: This randomized clinical trial used a 2 (ad source) by 4 (source labeling) design and was conducted online from September 2 to September 19, 2024. Participants were individuals aged 16 to 25 years.
All participants evaluated 50 ads from 2 sources (within-participants; 25 AI-generated, 25 existing) in random order.
The primary outcome, PME, was measured using the validated PME Scale for Youth, which assessed 2 effects perceptions (vaping perception and behavioral intent) and 3 ad perceptions (attention, information, and convincingness) on 7-point scales, with lower scores indicating better effectiveness for effects perceptions and higher scores indicating better effectiveness for ad perceptions.
Six hundred fourteen individuals (mean [SD] age, 20.5 [2.9] years; 300 female [48.9%]; 300 male [48.9%]; 14 other [2.3%]) provided 30 700 observations. Participants were randomly allocated to 1 of 4 experimentally manipulated labeling conditions (between-participants): (1) no source label (147 participants), (2) made with AI (158 participants), (3) made by the World Health Organization (WHO) (151 participants), or (4) made with AI by the WHO (158 participants). AI-generated ads demonstrated noninferiority to existing ads across all measures. AI-generated ads received better ratings for discouraging vaping (b = 0.09; 95% CI, 0.01 to 0.17), attention-grabbing qualities (b = -0.15; 95% CI, -0.26 to -0.03), and convincingness (b = -0.18; 95% CI, -0.30 to -0.07) (all P for noninferiority tests <.001). Source labeling showed no significant association with PME scores (χ2 values ranging from 0.10 to 4.19; all P > .20).
In this randomized clinical trial of vaping awareness social media ads, AI-generated, youth-codesigned ads achieved superior effectiveness ratings compared with existing ads. These findings support the potential for leveraging generative AI technology in public health campaigns, while indicating the need for appropriate governance frameworks as AI-generated health materials become increasingly prevalent.
ClinicalTrials.gov Identifier: NCT07042789.
开展青少年电子烟防范宣传活动的传统方法耗时较长，可能会在公共卫生应对方面造成严重延误。尽管生成式人工智能（AI）为健康传播提供了有前景的能力，但相关研究仅限于纯文本信息。
评估（1）与官方卫生机构的现有广告相比，由人工智能生成、青少年共同设计的电子烟防范社交媒体广告的感知信息效果（PME），以及（2）不同的来源标注如何与PME相关联。
设计、背景和参与者：这项随机临床试验采用2（广告来源）×4（来源标注）设计，于2024年9月2日至9月19日在线进行。参与者为16至25岁的个体。
所有参与者以随机顺序评估来自2个来源的50则广告（参与者内；25则由人工智能生成，25则为现有广告）。
主要结局PME使用经过验证的青少年PME量表进行测量，该量表在7分制上评估2种效果感知（对电子烟的感知和行为意图）和3种广告感知（注意力、信息和说服力），效果感知得分越低表明效果越好，广告感知得分越高表明效果越好。
614名个体（平均[标准差]年龄，20.5[2.9]岁；300名女性[48.9%]；300名男性[48.9%]；14名其他性别[2.3%]）提供了30700条观察数据。参与者被随机分配到4种实验性操作的标注条件之一（参与者间）：（1）无来源标注（147名参与者），（2）由人工智能制作（158名参与者），（3）由世界卫生组织（WHO）制作（151名参与者），或（4）由WHO使用人工智能制作（158名参与者）。在所有测量指标上，由人工智能生成的广告表现出不劣于现有广告。由人工智能生成的广告在劝阻吸电子烟方面获得了更好的评分（b = 0.09；95%置信区间，0.01至0.17）、吸引注意力的特质（b = -0.15；95%置信区间，-0.26至-0.03）和说服力（b = -0.18；95%置信区间，-0.30至-0.07）（所有非劣效性检验的P <.001）。来源标注与PME得分无显著关联（卡方值范围为0.10至4.19；所有P >.20）。
在这项关于电子烟防范社交媒体广告的随机临床试验中，由人工智能生成、青少年共同设计的广告与现有广告相比，获得了更高的效果评分。这些发现支持了在公共卫生宣传活动中利用生成式人工智能技术的潜力，同时表明随着人工智能生成的健康材料日益普及，需要适当的治理框架。
ClinicalTrials.gov标识符：NCT07042789。
