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
{"title":"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。","authors":"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","doi":"10.1111/dar.70022","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Discussion and conclusions: </strong>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.</p>","PeriodicalId":11318,"journal":{"name":"Drug and alcohol review","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Co-Designing AI-Generated Vaping Awareness Materials With Adolescents and Young Adults: A Qualitative Study.\",\"authors\":\"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\",\"doi\":\"10.1111/dar.70022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Discussion and conclusions: </strong>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.</p>\",\"PeriodicalId\":11318,\"journal\":{\"name\":\"Drug and alcohol review\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-08-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Drug and alcohol review\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/dar.70022\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"SUBSTANCE ABUSE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Drug and alcohol review","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/dar.70022","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SUBSTANCE ABUSE","Score":null,"Total":0}
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.
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.