Syed Ali Hussain, Ralf Schmälzle, Sue Lim, Nassir Bouali
{"title":"在阿拉伯文化背景下比较人工智能和人类产生的健康信息。","authors":"Syed Ali Hussain, Ralf Schmälzle, Sue Lim, Nassir Bouali","doi":"10.1080/16549716.2025.2464360","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>AI is rapidly transforming the design of communication messages across various sectors, including health and safety. However, little is known about its effectiveness for roughly 420 million native Arabic speakers worldwide.</p><p><strong>Objective: </strong>This study examined characteristics of AI vs. human-generated road safety messages for a potential roadside billboard campaign in the United Arab Emirates.</p><p><strong>Method: </strong>The study includes a computational analysis and an online evaluation with 186 participants from the United Arab Emirates (UAE), comparing messages generated by AI with those created by humans. To achieve this, an AI model (GPT-4) was utilized to generate 15 road safety messages, while three human experts created another set of 15 messages. Computational text analysis was employed to examine these messages, followed by an online study in which human participants evaluated all messages based on message clarity and message quality.</p><p><strong>Results: </strong>The computational analysis revealed that AI-generated messages exhibited more positive sentiment with no significant differences in terms of readability/text difficulty. Participants evaluated both AI- and human-generated messages highly in terms of message quality and clarity, but human-generated messages were rated as slightly and significantly higher in terms of clarity.</p><p><strong>Conclusion: </strong>These results add to a rapidly growing body of research demonstrating that AI-generated messages can augment public communication campaigns and point towards the need to assess how diverse, international audiences respond to AI-generated content.</p>","PeriodicalId":49197,"journal":{"name":"Global Health Action","volume":"18 1","pages":"2464360"},"PeriodicalIF":2.2000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11837920/pdf/","citationCount":"0","resultStr":"{\"title\":\"Comparing AI and human-generated health messages in an Arabic cultural context.\",\"authors\":\"Syed Ali Hussain, Ralf Schmälzle, Sue Lim, Nassir Bouali\",\"doi\":\"10.1080/16549716.2025.2464360\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>AI is rapidly transforming the design of communication messages across various sectors, including health and safety. However, little is known about its effectiveness for roughly 420 million native Arabic speakers worldwide.</p><p><strong>Objective: </strong>This study examined characteristics of AI vs. human-generated road safety messages for a potential roadside billboard campaign in the United Arab Emirates.</p><p><strong>Method: </strong>The study includes a computational analysis and an online evaluation with 186 participants from the United Arab Emirates (UAE), comparing messages generated by AI with those created by humans. To achieve this, an AI model (GPT-4) was utilized to generate 15 road safety messages, while three human experts created another set of 15 messages. Computational text analysis was employed to examine these messages, followed by an online study in which human participants evaluated all messages based on message clarity and message quality.</p><p><strong>Results: </strong>The computational analysis revealed that AI-generated messages exhibited more positive sentiment with no significant differences in terms of readability/text difficulty. Participants evaluated both AI- and human-generated messages highly in terms of message quality and clarity, but human-generated messages were rated as slightly and significantly higher in terms of clarity.</p><p><strong>Conclusion: </strong>These results add to a rapidly growing body of research demonstrating that AI-generated messages can augment public communication campaigns and point towards the need to assess how diverse, international audiences respond to AI-generated content.</p>\",\"PeriodicalId\":49197,\"journal\":{\"name\":\"Global Health Action\",\"volume\":\"18 1\",\"pages\":\"2464360\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11837920/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Global Health Action\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/16549716.2025.2464360\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/2/18 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Health Action","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/16549716.2025.2464360","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/18 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Comparing AI and human-generated health messages in an Arabic cultural context.
Background: AI is rapidly transforming the design of communication messages across various sectors, including health and safety. However, little is known about its effectiveness for roughly 420 million native Arabic speakers worldwide.
Objective: This study examined characteristics of AI vs. human-generated road safety messages for a potential roadside billboard campaign in the United Arab Emirates.
Method: The study includes a computational analysis and an online evaluation with 186 participants from the United Arab Emirates (UAE), comparing messages generated by AI with those created by humans. To achieve this, an AI model (GPT-4) was utilized to generate 15 road safety messages, while three human experts created another set of 15 messages. Computational text analysis was employed to examine these messages, followed by an online study in which human participants evaluated all messages based on message clarity and message quality.
Results: The computational analysis revealed that AI-generated messages exhibited more positive sentiment with no significant differences in terms of readability/text difficulty. Participants evaluated both AI- and human-generated messages highly in terms of message quality and clarity, but human-generated messages were rated as slightly and significantly higher in terms of clarity.
Conclusion: These results add to a rapidly growing body of research demonstrating that AI-generated messages can augment public communication campaigns and point towards the need to assess how diverse, international audiences respond to AI-generated content.
期刊介绍：
Global Health Action is an international peer-reviewed Open Access journal affiliated with the Unit of Epidemiology and Global Health, Department of Public Health and Clinical Medicine at Umeå University, Sweden. The Unit hosts the Umeå International School of Public Health and the Umeå Centre for Global Health Research.
Vision: Our vision is to be a leading journal in the global health field, narrowing health information gaps and contributing to the implementation of policies and actions that lead to improved global health.
Aim: The widening gap between the winners and losers of globalisation presents major public health challenges. To meet these challenges, it is crucial to generate new knowledge and evidence in the field and in settings where the evidence is lacking, as well as to bridge the gaps between existing knowledge and implementation of relevant findings. Thus, the aim of Global Health Action is to contribute to fuelling a more concrete, hands-on approach to addressing global health challenges. Manuscripts suggesting strategies for practical interventions and research implementations where none already exist are specifically welcomed. Further, the journal encourages articles from low- and middle-income countries, while also welcoming articles originated from South-South and South-North collaborations. All articles are expected to address a global agenda and include a strong implementation or policy component.
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