Ethical dilemmas in conducting qualitative, public health research on social media: using a study on Facebook as a case.

Aim: Platforms on social media are increasingly used for public health research. While social media provides an exceptional opportunity to explore communication about public health topics, this practice is not without ethical dilemmas. Our aim was to identify and unfold some of these dilemmas and to suggest possible solutions and ways forward for future research.

Population preferences for AI system features across eight different decision-making contexts.

Artificial intelligence systems based on deep learning architectures are being investigated as decision-support systems for human decision-makers across a wide range of decision-making contexts. It is known from the literature on AI in medicine that patients and the public hold relatively strong preferences in relation to desirable features of AI systems and their implementation, e.g.

The impact of influences in a medical screening programme invitation: a randomized controlled trial.

Background: Invitations to screening programmes may include influences that are intending to increase the participation rates. This study had two objectives: (i) to assess if different categories of influences had a significant effect on the intention to participate in a screening programme for a fictitious disease and (ii) whether participants were aware of the influences, and if the intention to participate was associated to this awareness.

Methods: A seven-armed randomized controlled trial.

The right to a second opinion on Artificial Intelligence diagnosis-Remedying the inadequacy of a risk-based regulation.

In this paper, we argue that patients who are subjects of Artificial Intelligence (AI)-supported diagnosis and treatment planning should have a right to a second opinion, but also that this right should not necessarily be construed as a right to a physician opinion. The right to a second opinion could potentially be satisfied by another independent AI system. Our considerations on the right to second opinion are embedded in the wider debate on different approaches to the regulation of AI, and we conclude the article by providing a number of reasons for preferring a rights-based approach over a risk-based approach.

Population Preferences for Performance and Explainability of Artificial Intelligence in Health Care: Choice-Based Conjoint Survey.

Background: Certain types of artificial intelligence (AI), that is, deep learning models, can outperform health care professionals in particular domains. Such models hold considerable promise for improved diagnostics, treatment, and prevention, as well as more cost-efficient health care. They are, however, opaque in the sense that their exact reasoning cannot be fully explicated.

Do journals and corporate sponsors back certain views in topics where disagreement prevails?

The article focuses on scientific disagreement about the use of statin-related drugs in the prevention of cardiovascular events. The study forms part of an exploration of the broader principle of research polarization, foremost in medicine. The hypothesis is that statin-positive and statin-critical researchers publish in different committed central journals, and that they are financially supported by different dedicated corporate sources.

Categories of systematic influences applied to increase cancer screening participation: a literature review and analysis.

Background: Health authorities can influence citizens in subtle ways that render them more likely to participate in cancer screening programmes, and thereby possibly increase the beneficial effects. If the influences become too severe, the citizens' ability to make a personal choice may be lost on the way. The purpose of this analysis was to identify and categorize the influences while questioning whether they still permit the citizens to make their own choices regarding participation.

Control, trust and the sharing of health information: the limits of trust.

Clinical information about patients is increasingly being stored in electronic form and has therefore become more easily shareable. Data are collected as part of clinical care but have multiple other potential uses in relation to health system planning, audit and research. The use of clinical information for these secondary uses is controversial, and the ability to safeguard personal and sensitive data under current practices is contested.

The four dimensions of contestable AI diagnostics - A patient-centric approach to explainable AI.

The problem of the explainability of AI decision-making has attracted considerable attention in recent years. In considering AI diagnostics we suggest that explainability should be explicated as 'effective contestability'. Taking a patient-centric approach we argue that patients should be able to contest the diagnoses of AI diagnostic systems, and that effective contestation of patient-relevant aspect of AI diagnoses requires the availability of different types of information about 1) the AI system's use of data, 2) the system's potential biases, 3) the system performance, and 4) the division of labour between the system and health care professionals.

In Defence of informed consent for health record research - why arguments from 'easy rescue', 'no harm' and 'consent bias' fail.

Background: Health data holds great potential for improved treatments. Big data research and machine learning models have been shown to hold great promise for improved diagnostics and treatment planning. The potential is tied, however, to the availability of personal health data.

The 'Expiry Problem' of broad consent for biobank research - And why a meta consent model solves it.

In this response to Neil Manson's latest intervention in our debate about the best consent model for biobank research we show, contra Manson that the 'expiry problem' that affects broad consent models because of changes over time in methods, purposes, types of data used and governance structures is a real and significant problem. We further show that our preferred implementation of meta consent as a national consent platform solves this problem and is not subject to the cost and burden objections that Manson raises.

The right to refuse diagnostics and treatment planning by artificial intelligence.

In an analysis of artificially intelligent systems for medical diagnostics and treatment planning we argue that patients should be able to exercise a right to withdraw from AI diagnostics and treatment planning for reasons related to (1) the physician's role in the patients' formation of and acting on personal preferences and values, (2) the bias and opacity problem of AI systems, and (3) rational concerns about the future societal effects of introducing AI systems in the health care sector.

The biobank consent debate: why 'meta-consent' is still the solution!

In a recent article in the Neil Manson sets out to show that the meta-consent model of informed consent is not the solution to perennial debate on the ethics of biobank participation. In this response, we shall argue that (i) Manson's considerations on the costs of a meta-consent model are incomplete and therefore misleading; (ii) his view that a model of broad consent passes a threshold of moral acceptability rests on an analogy that misconstrues how biobank research is actually conducted and (iii) a model of meta-consent is more in tune with the nature of biobank research and enables autonomous choice.

Should all medical research be published? The moral responsibility of medical journal editors.

This article reinvigorates a key question in publication ethics: Is there research that it is permissible to conduct but that ought not to be published? The article raises the question in relation to two recent medical studies. It is argued (1) that the publication of these studies may cause significant harm to individuals, (2) that editors of medical journals have a moral responsibility for such harm, (3) that denial of publication is inadequate as an instrument to fulfil this moral responsibility and (4) that internationally acknowledged publication ethics codes should incorporate this aspect of editors' moral responsibility.

Big Data and Health Research-The Governance Challenges in a Mixed Data Economy.

Denmark is a society that has already moved towards Big Data and a Learning Health Care System. Data from routine healthcare has been registered centrally for years, there is a nationwide tissue bank, and there are numerous other available registries about education, employment, housing, pollution, etcetera. This has allowed Danish researchers to study the link between exposures, genetics and diseases in a large population.

Informed consent and registry-based research - the case of the Danish circumcision registry.

Background: Research into personal health data holds great potential not only for improved treatment but also for economic growth. In these years many countries are developing policies aimed at facilitating such research often under the banner of 'big data'. A central point of debate is whether the secondary use of health data requires informed consent if the data is anonymised.

Eliciting meta consent for future secondary research use of health data using a smartphone application - a proof of concept study in the Danish population.

Background: The increased use of information technology in every day health care creates vast amounts of stored health data that can be used for research. The secondary research use of routinely collected data raises questions about appropriate consent mechanisms for such use. One option is meta consent where individuals state their own consent preferences in relation to future use of their data, e.

Clinical genome sequencing and population preferences for information about 'incidental' findings-From medically actionable genes (MAGs) to patient actionable genes (PAGs).

Whole genome or exome sequencing is increasingly used in the clinical contexts, and 'incidental' findings are generated. There is need for an adequate policy for the reporting of these findings to individuals. Such a policy has been suggested by the American College of Medical Genetics and Genomics (ACMG).