Difference between revisions of "Template:Article of the week"

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Tab2 Al-Jefri FrontInMedicine2018 5.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Čartolovni DigitalHealth2023 9.jpeg|240px]]</div>
'''"[[Journal:What Is health information quality? Ethical dimension and perception by users|What Is health information quality? Ethical dimension and perception by users]]"'''
'''"[[Journal:Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study|Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study]]"'''


The popularity of seeking health [[information]] online makes information quality (IQ) a public health issue. The present study aims at building a theoretical framework of health information quality (HIQ) that can be applied to websites and defines which IQ criteria are important for a website to be trustworthy and meet users' expectations. We have identified a list of HIQ criteria from existing tools and assessment criteria and elaborated them into a questionnaire that was promoted via social media and, mainly, the university. Responses (329) were used to rank the different criteria for their importance in trusting a website and to identify patterns of criteria using hierarchical cluster analysis. HIQ criteria were organized in five dimensions based on previous theoretical frameworks, as well as on how they cluster together in the questionnaire response. We could identify a top-ranking dimension (scientific completeness) that describes what the user is expecting to know from the websites (in particular: description of symptoms, treatments, side effects). ('''[[Journal:What Is health information quality? Ethical dimension and perception by users|Full article...]]''')<br />
This qualitative study aims to present the aspirations, expectations, and critical analysis of the potential for [[artificial intelligence]] (AI) to transform the patient–physician relationship, according to multi-stakeholder insight. This study was conducted from June to December 2021, using an anticipatory ethics approach and sociology of expectations as the theoretical frameworks. It focused mainly on three groups of stakeholders, namely physicians (''n'' = 12), patients (''n'' = 15), and healthcare managers (''n'' = 11), all of whom are directly related to the adoption of AI in medicine (''n'' = 38). In this study, interviews were conducted with 40% of the patients in the sample (15/38), as well as 31% of the physicians (12/38) and 29% of health managers in the sample (11/38) ... ('''[[Journal:Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study|Full article...]]''')<br />
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Latest revision as of 15:48, 26 May 2024

Fig1 Čartolovni DigitalHealth2023 9.jpeg

"Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study"

This qualitative study aims to present the aspirations, expectations, and critical analysis of the potential for artificial intelligence (AI) to transform the patient–physician relationship, according to multi-stakeholder insight. This study was conducted from June to December 2021, using an anticipatory ethics approach and sociology of expectations as the theoretical frameworks. It focused mainly on three groups of stakeholders, namely physicians (n = 12), patients (n = 15), and healthcare managers (n = 11), all of whom are directly related to the adoption of AI in medicine (n = 38). In this study, interviews were conducted with 40% of the patients in the sample (15/38), as well as 31% of the physicians (12/38) and 29% of health managers in the sample (11/38) ... (Full article...)
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