与青少年和年轻人共同设计人工智能生成的电子烟意识材料:一项定性研究。

IF 2.6 3区 医学 Q2 SUBSTANCE ABUSE
Tianze Sun, Gary Chung Kai Chan, Daniel Stjepanović, Tesfa Yimer, Giang Thu Vu, Carmen Lim, Caitlin McClure-Thomas, Charlotte Russel, Jason Connor, Wayne Hall, Leanne Hides, David Hammond, Timo Dietrich, Daniel Erku, Benjamin Johnson, Janni Leung
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引用次数: 0

摘要

导言:发展大众媒体运动来解决澳大利亚不断上升的青少年电子烟率是及时和资源密集型的。生成式人工智能提供可扩展的内容生产,但对于年轻人对人工智能生成的多媒体材料的看法,以及他们的反馈如何为协同设计过程提供信息,我们知之甚少。方法:我们在澳大利亚昆士兰州进行了两阶段的定性研究。第一阶段研究了青少年(n = 10,年龄在13-20岁)对120份使用自动化人工智能框架制作的电子烟意识材料的反应。焦点小组参与者将材料分为“有效”和“无效”两类,并提供反馈。基于反馈和质量标准,使用人工智能协同设计框架创建了25个修订材料,该框架包含迭代,少量提示和手动文本图像集成。第二阶段通过半结构化访谈探讨年轻人(n = 9,年龄18-25岁)对修订材料的看法。进行归纳主题分析。结果:第一阶段的参与者拒绝了自动人工智能生成的材料,原因是文本图像组合不对齐、人工图像、不现实的电子烟设备和不真实的语言。第二阶段确定了有效的人工智能协同设计材料的六个关键特征,这些特征符合既定的健康传播原则,包括视觉吸引力;关注眼前的结果;与青年相关;提供切实可行的意见;避免模棱两可和制造恐慌;并结合多个主题,以吸引不同的青年受众。讨论和结论:人工智能工具可以快速生成信息,但需要一个包含专家意见和受众反馈的人工智能协同设计框架,以生成相关、真实和基于证据的材料。该框架为制定及时、可扩展的应对措施以应对青少年吸电子烟等公共卫生挑战提供了一条有希望的途径;尽管需要继续研究才能在不同背景下有效和合乎道德地实施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Co-Designing AI-Generated Vaping Awareness Materials With Adolescents and Young Adults: A Qualitative Study.

Introduction: Developing mass meda campaigns to address rising youth vaping rates in Australia is timely and resource-intensive. Generative AI offers scalable content production, but little is known about youth perceptions of AI-generated multimedia materials or how their feedback can inform co-design processes.

Methods: We conducted a two-phase qualitative study in Queensland, Australia. Phase 1 explored adolescent (n = 10, ages 13-20) responses to 120 vaping awareness materials produced using an automated-AI framework. Focus group participants sorted materials into 'effective' and 'ineffective' piles and provided feedback. Based on feedback and quality criteria, 25 revised materials were created using an AI co-design framework incorporating iterative, few-shot prompting and manual text-image integration. Phase 2 explored young adult (n = 9, ages 18-25) perceptions of revised materials via semi-structured interviews. Inductive thematic analysis was conducted.

Results: Phase 1 participants rejected automated-AI-generated materials due to misaligned text-image combinations, artificial imagery, unrealistic vaping devices, and inauthentic language. Phase 2 identified six key characteristics of effective AI-co-designed materials that aligned with established health communication principles including visual appeal; focus on immediate consequences; relevance to youth; provision of practical advice; avoidance of ambiguity and fearmongering; and integration of multiple themes to reach diverse youth audiences.

Discussion and conclusions: AI tools can rapidly generate messages but an AI-co-design framework incorporating expert input and audience feedback is required to produce materials that are relevant, authentic, and evidence-based. This framework offers a promising pathway for developing timely, scalable responses to public health challenges such as youth vaping; though continued research is needed for effective and ethical implementation across diverse contexts.

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来源期刊
Drug and alcohol review
Drug and alcohol review SUBSTANCE ABUSE-
CiteScore
4.80
自引率
10.50%
发文量
151
期刊介绍: Drug and Alcohol Review is an international meeting ground for the views, expertise and experience of all those involved in studying alcohol, tobacco and drug problems. Contributors to the Journal examine and report on alcohol and drug use from a wide range of clinical, biomedical, epidemiological, psychological and sociological perspectives. Drug and Alcohol Review particularly encourages the submission of papers which have a harm reduction perspective. However, all philosophies will find a place in the Journal: the principal criterion for publication of papers is their quality.
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