Acceptability of artificial intelligence (AI)-enabled chatbots, video consultations and live webchats as online platforms for sexual health advice

Nadarzynski, Tom; Bayley, Jake; Llewellyn, Carrie; Kidsley, Sally; Graham, Cynthia A.

doi:10.1136/bmjsrh-2018-200271

Cited by 43 publications

(50 citation statements)

References 17 publications

(17 reference statements)

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“…They are able to provide useful information when healthcare providers are unavailable (e.g., after clinic hours) or the patient prefers not to discuss with a healthcare provider (e.g., too anxious or embarrassed). However, a recent study showed that less than half of the surveyed population, 257 sexual and reproductive clinic users in UK, found chatbots favorable possibly due to concerns about perceived lack of confidentiality, empathy, and security [43]. Regulation of chatbots and mobile applications is therefore essential.…”

Section: The Future Of Ehealth Tools In Delivering Laboratory Resultsmentioning

confidence: 99%

Ethical Implications of eHealth Tools for Delivering STI/HIV Laboratory Results and Partner Notifications

et al. 2021

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Purpose of Review eHealth tools are increasingly utilized for communication with patients. Although efficacious and cost-effective, these tools face several barriers that challenge their ethical use in sexual health. We reviewed literature from the past decade to pick illustrative studies of eHealth tools that deliver results of laboratory tests for sexually transmitted infections, including the human immunodeficiency virus, as well as partner notifications. We describe ethical implications for such technologies. Recent Findings Our review found that despite widespread research on the use of eHealth tools in delivering laboratory results and partner notifications, these studies rarely measured or reported on the ethical implications. Such implications can be organized according to the four major principles in bioethics: beneficence, patient autonomy, non-maleficence, and justice. The beneficence of eHealth typically measures efficacy in comparison to existing standards of care. Patient autonomy includes the ability to opt in or out of eHealth tools, right-based principles of consent, and sovereignty over healthcare data. To adhere to the principle of non-maleficence, relevant harms must be identified and measured—such as unintentional disclosure of illness, sexual orientation, or sexual activity. Justice must also be considered to accommodate all users equally, irrespective of their literacy level, with easy-to-use platforms that provide clear messages. Summary Based on case studies from this review, we developed a list of recommendations for the ethical development and evaluation of eHealth platforms to deliver STI/HIV results to patients and notifications to partners.

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Section: The Future Of Ehealth Tools In Delivering Laboratory Resultsmentioning

confidence: 99%

Ethical Implications of eHealth Tools for Delivering STI/HIV Laboratory Results and Partner Notifications

et al. 2021

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“…AI has emerged with particular strength in the medical domain over the recent years, where there are prolific proofs of its advances, strengths and opportunities in prognosis, diagnosis, healthcare or preventive medicine [49][50][51][52][53]. Besides, AI can be applied in the public health landscape by leveraging social network and Web 2.0 media data, which in turn can be exploited to control drug abuse [54,55], toxic substance consumption [56], sexual and reproductive health [57], as well as healthy life habits [58][59][60]. These data, along with those provided by wearable devices, constitute another valuable information source for developing personalized recommender systems to promote healthy habits and support better individual decision-making in terms of healthy choices [60][61][62].…”

Section: Analysis For the Economic Dimension: Lifementioning

confidence: 99%

A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects

et al. 2021

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The 17 Sustainable Development Goals (SDGs) established by the United Nations Agenda 2030 constitute a global blueprint agenda and instrument for peace and prosperity worldwide. Artificial intelligence and other digital technologies that have emerged in the last years, are being currently applied in virtually every area of society, economy and the environment. Hence, it is unsurprising that their current role in the pursuance or hampering of the SDGs has become critical. This study aims at providing a snapshot and comprehensive view of the progress made and prospects in the relationship between artificial intelligence technologies and the SDGs. A comprehensive review of existing literature has been firstly conducted, after which a series SWOT (Strengths, Weaknesses, Opportunities and Threats) analyses have been undertaken to identify the strengths, weaknesses, opportunities and threats inherent to artificial intelligence-driven technologies as facilitators or barriers to each of the SDGs. Based on the results of these analyses, a subsequent broader analysis is provided, from a position vantage, to (i) identify the efforts made in applying AI technologies in SDGs, (ii) pinpoint opportunities for further progress along the current decade, and (iii) distill ongoing challenges and target areas for important advances. The analysis is organized into six categories or perspectives of human needs: life, economic and technological development, social development, equality, resources and natural environment. Finally, a closing discussion is provided about the prospects, key guidelines and lessons learnt that should be adopted for guaranteeing a positive shift of artificial intelligence developments and applications towards fully supporting the SDGs attainment by 2030.

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“…Jaroszewski et al (2019) reported that, during clinical trials of their MLbased DDSS for mental illness prevention, only 28% of participants answered "very likely" to the question presented by the DDSS: "Be honest, how likely are you to try the resources I just shared?". Nadarzynski et al (2020) studied the acceptability of information systems dedicated to sexual health prevention. The authors reported that, for the first contact, 70% of patients preferred face-to-face consultations.…”

Section: A Questionable Acceptabilitymentioning

confidence: 99%

What does it mean to provide decision support to a responsible and competent expert?

Richard

Mayag

Talbot

et al. 2020

EURO Journal on Decision Processes

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Decision support consists in helping a decision-maker to improve his/her decisions. However, clients requesting decision support are often themselves experts and are often taken by third parties and/or the general public to be responsible for the decisions they make. This predicament raises complex challenges for decision analysts, who have to avoid infringing upon the expertise and responsibility of the decision-maker. The case of diagnosis decision support in healthcare contexts is particularly illustrative. To support clinicians in their work and minimize the risk of medical error, various decision support systems have been developed, as part of information systems that are now ubiquitous in healthcare contexts. To develop, in collaboration with the hospitals of Lyon, a diagnostic decision support system for day-today customary consultations, we propose in this paper a critical analysis of current approaches to diagnostic decision support, which mainly consist in providing them with guidelines or even full-fledged diagnosis recommendations. We highlight that the use of such decision support systems by physicians raises responsibility issues, but also that it is at odds with the needs and constraints of customary consultations. We argue that the historical choice to favor guidelines or recommendations to physicians implies a very specific vision of what it means to support physicians, and we argue that the flaws of this vision partially ex-A.

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Acceptability of artificial intelligence (AI)-enabled chatbots, video consultations and live webchats as online platforms for sexual health advice

Cited by 43 publications

References 17 publications

Ethical Implications of eHealth Tools for Delivering STI/HIV Laboratory Results and Partner Notifications

Ethical Implications of eHealth Tools for Delivering STI/HIV Laboratory Results and Partner Notifications

A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects

What does it mean to provide decision support to a responsible and competent expert?

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