Arif Jetha, Hyunmi Lee, Maxwell J Smith, Victoria H Arrandale, Aviroop Biswas, Cameron Mustard, Peter M Smith
{"title":"人工智能在加拿大两个省职业健康和安全实践中的应用景观。","authors":"Arif Jetha, Hyunmi Lee, Maxwell J Smith, Victoria H Arrandale, Aviroop Biswas, Cameron Mustard, Peter M Smith","doi":"10.1002/ajim.70018","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI) can modernize occupational health and safety (OHS) practice and provide solutions to the most complex health and safety challenges. Empirical data on firm-level AI utilization in OHS practice remain limited. The objective of this study was to examine AI use for OHS and firm-level descriptive and OHS characteristics associated with AI use.</p><p><strong>Methods: </strong>A total of 810 OHS professionals in British Columbia and Ontario, Canada were surveyed in the summer of 2024. Surveys asked about firm-level AI use for OHS and items asked about descriptive and OHS characteristics. Participants were also asked about perceived AI concerns and OHS impact. A multivariate logistic regression model was fitted to examine factors associated with firm-level AI use for OHS.</p><p><strong>Results: </strong>In total, 29% reported firm-level AI use for OHS. Larger-sized firms and those with hybrid work arrangements had a greater odds of AI use for OHS. Also, firms with high workplace hazard exposure had a greater odds of AI OHS use. More positive perceptions of AI's impact on OHS were associated with firm-level AI use for OHS.</p><p><strong>Conclusions: </strong>AI use for OHS may be concentrated among hazardous firms and those with the conditions to support technological adoption. Research examining AI's effectiveness in OHS settings is needed to guide evidence-based implementation in occupational health practice.</p>","PeriodicalId":7873,"journal":{"name":"American journal of industrial medicine","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Landscape of Artificial Intelligence Use for Occupational Health and Safety Practice in Two Canadian Provinces.\",\"authors\":\"Arif Jetha, Hyunmi Lee, Maxwell J Smith, Victoria H Arrandale, Aviroop Biswas, Cameron Mustard, Peter M Smith\",\"doi\":\"10.1002/ajim.70018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Artificial intelligence (AI) can modernize occupational health and safety (OHS) practice and provide solutions to the most complex health and safety challenges. Empirical data on firm-level AI utilization in OHS practice remain limited. The objective of this study was to examine AI use for OHS and firm-level descriptive and OHS characteristics associated with AI use.</p><p><strong>Methods: </strong>A total of 810 OHS professionals in British Columbia and Ontario, Canada were surveyed in the summer of 2024. Surveys asked about firm-level AI use for OHS and items asked about descriptive and OHS characteristics. Participants were also asked about perceived AI concerns and OHS impact. A multivariate logistic regression model was fitted to examine factors associated with firm-level AI use for OHS.</p><p><strong>Results: </strong>In total, 29% reported firm-level AI use for OHS. Larger-sized firms and those with hybrid work arrangements had a greater odds of AI use for OHS. Also, firms with high workplace hazard exposure had a greater odds of AI OHS use. More positive perceptions of AI's impact on OHS were associated with firm-level AI use for OHS.</p><p><strong>Conclusions: </strong>AI use for OHS may be concentrated among hazardous firms and those with the conditions to support technological adoption. Research examining AI's effectiveness in OHS settings is needed to guide evidence-based implementation in occupational health practice.</p>\",\"PeriodicalId\":7873,\"journal\":{\"name\":\"American journal of industrial medicine\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2025-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American journal of industrial medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/ajim.70018\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of industrial medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/ajim.70018","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Landscape of Artificial Intelligence Use for Occupational Health and Safety Practice in Two Canadian Provinces.
Background: Artificial intelligence (AI) can modernize occupational health and safety (OHS) practice and provide solutions to the most complex health and safety challenges. Empirical data on firm-level AI utilization in OHS practice remain limited. The objective of this study was to examine AI use for OHS and firm-level descriptive and OHS characteristics associated with AI use.
Methods: A total of 810 OHS professionals in British Columbia and Ontario, Canada were surveyed in the summer of 2024. Surveys asked about firm-level AI use for OHS and items asked about descriptive and OHS characteristics. Participants were also asked about perceived AI concerns and OHS impact. A multivariate logistic regression model was fitted to examine factors associated with firm-level AI use for OHS.
Results: In total, 29% reported firm-level AI use for OHS. Larger-sized firms and those with hybrid work arrangements had a greater odds of AI use for OHS. Also, firms with high workplace hazard exposure had a greater odds of AI OHS use. More positive perceptions of AI's impact on OHS were associated with firm-level AI use for OHS.
Conclusions: AI use for OHS may be concentrated among hazardous firms and those with the conditions to support technological adoption. Research examining AI's effectiveness in OHS settings is needed to guide evidence-based implementation in occupational health practice.
期刊介绍：
American Journal of Industrial Medicine considers for publication reports of original research, review articles, instructive case reports, and analyses of policy in the fields of occupational and environmental health and safety. The Journal also accepts commentaries, book reviews and letters of comment and criticism. The goals of the journal are to advance and disseminate knowledge, promote research and foster the prevention of disease and injury. Specific topics of interest include: occupational disease; environmental disease; pesticides; cancer; occupational epidemiology; environmental epidemiology; disease surveillance systems; ergonomics; dust diseases; lead poisoning; neurotoxicology; endocrine disruptors.
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