Women's perceptions and attitudes towards the use of AI in mammography in Sweden: a qualitative interview study.

BACKGROUND: Understanding women's perspectives can help to create an effective and acceptable artificial intelligence (AI) implementation for triaging mammograms, ensuring a high proportion of screening-detected cancer. This study aimed to explore Swedish women's perceptions and attitudes towards the use of AI in mammography. METHOD: Semistructured interviews were conducted with 16 women recruited in the spring of 2023 at Capio S:t Görans Hospital, Sweden, during an ongoing clinical trial of AI in screening (ScreenTrustCAD, NCT04778670) with Philips equipment. The interview transcripts were analysed using inductive thematic content analysis. RESULTS: In general, women viewed AI as an excellent complementary tool to help radiologists in their decision-making, rather than a complete replacement of their expertise. To trust the AI, the women requested a thorough evaluation, transparency about AI usage in healthcare, and the involvement of a radiologist in the assessment. They would rather be more worried because of being called in more often for scans than risk having overlooked a sign of cancer. They expressed substantial trust in the healthcare system if the implementation of AI was to become a standard practice. CONCLUSION: The findings suggest that the interviewed women, in general, hold a positive attitude towards the implementation of AI in mammography; nonetheless, they expect and demand more from an AI than a radiologist. Effective communication regarding the role and limitations of AI is crucial to ensure that patients understand the purpose and potential outcomes of AI-assisted healthcare.

Experiences of individuals with rheumatoid arthritis interacting with health care and the use of a digital self-care application: a qualitative interview study.

OBJECTIVES: Over the last few decades, there have been significant improvements in the treatment of rheumatoid arthritis (RA), with the development of new treatments and guidelines for teamwork and patient self-care and access to digital tools. This study aimed to explore the experiences of individuals with RA interacting with healthcare. It also looked at how a self-care application, an educational programme called the 'healthcare encounter', improved patient-doctor communication. DESIGN: Semistructured interviews were conducted, and qualitative content analysis was performed. SETTING: The potential participants, individuals with established, or under investigation for, RA diagnosis at rheumatology clinics in Sweden, were asked to participate in the study via a digital self-care application called the Elsa Science Self-care app. PARTICIPANTS: Ten interviews were performed with participants from nine clinics following a meeting with the rheumatologist or other healthcare personnel between September 2022 and October 2022. Phrases, sentences or paragraphs referring to experiences from healthcare meetings and opinions about the digital programme were identified and coded. Codes that reflected similar concepts were grouped; subcategories were formulated, and categories were connected to their experiences and opinions. RESULTS: Among our participants, three main categories emerged: the availability of healthcare, individual efforts to have a healthier life and personal interaction with healthcare. Participants described that the 'healthcare encounter' educational programme can be a source of information, which confirms, supports and creates a sense of control. CONCLUSION: The participants valued being seen and taking part in a dialogue when they had prepared themselves (observed symptoms over time and prepared questions). The implementation of digital self-care applications might need to be incorporated into the healthcare setting, so that both the patients and the healthcare personnel have a shared understanding. Collaboration is essential in this context.

Public Preferences for Digital Health Data Sharing: Discrete Choice Experiment Study in 12 European Countries.

BACKGROUND: With new technologies, health data can be collected in a variety of different clinical, research, and public health contexts, and then can be used for a range of new purposes. Establishing the public's views about digital health data sharing is essential for policy makers to develop effective harmonization initiatives for digital health data governance at the European level. OBJECTIVE: This study investigated public preferences for digital health data sharing. METHODS: A discrete choice experiment survey was administered to a sample of European residents in 12 European countries (Austria, Denmark, France, Germany, Iceland, Ireland, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom) from August 2020 to August 2021. Respondents answered whether hypothetical situations of data sharing were acceptable for them. Each hypothetical scenario was defined by 5 attributes ("data collector," "data user," "reason for data use," "information on data sharing and consent," and "availability of review process"), which had 3 to 4 attribute levels each. A latent class model was run across the whole data set and separately for different European regions (Northern, Central, and Southern Europe). Attribute relative importance was calculated for each latent class's pooled and regional data sets. RESULTS: A total of 5015 completed surveys were analyzed. In general, the most important attribute for respondents was the availability of information and consent during health data sharing. In the latent class model, 4 classes of preference patterns were identified. While respondents in 2 classes strongly expressed their preferences for data sharing with opposing positions, respondents in the other 2 classes preferred not to share their data, but attribute levels of the situation could have had an impact on their preferences. Respondents generally found the following to be the most acceptable: a national authority or academic research project as the data user; being informed and asked to consent; and a review process for data transfer and use, or transfer only. On the other hand, collection of their data by a technological company and data use for commercial communication were the least acceptable. There was preference heterogeneity across Europe and within European regions. CONCLUSIONS: This study showed the importance of transparency in data use and oversight of health-related data sharing for European respondents. Regional and intraregional preference heterogeneity for "data collector," "data user," "reason," "type of consent," and "review" calls for governance solutions that would grant data subjects the ability to control their digital health data being shared within different contexts. These results suggest that the use of data without consent will demand weighty and exceptional reasons. An interactive and dynamic informed consent model combined with oversight mechanisms may be a solution for policy initiatives aiming to harmonize health data use across Europe.

Patients' views on using human embryonic stem cells to treat Parkinson's disease: an interview study.

BACKGROUND: Human embryonic stem cells (hESC) as a source for the development of advanced therapy medicinal products are considered for treatment of Parkinson's disease (PD). Research has shown promising results and opened an avenue of great importance for patients who currently lack a disease modifying therapy. The use of hESC has given rise to moral concerns and been the focus of often heated debates on the moral status of human embryos. Approval for marketing is still pending. OBJECTIVE: To Investigate the perspectives and concerns of patients with PD, patients being the directly concerned stakeholders in the ethical discussion. METHODS: Qualitative semi-structured interviews related to this new therapy in seventeen patients from two Swedish cities. RESULTS: The participants expressed various interests related to the use of human embryos for development of medicinal therapies; however, overall, they were positive towards the use of hESC for treatment of PD. It was deemed important that the donating woman or couple made the choice to donate embryos voluntarily. Furthermore, there were concerns that the industry does not always prioritise the patient over profit; thus, transparency was seen as important.

Preference Variation: Where Does Health Risk Attitude Come Into the Equation?

OBJECTIVES: Decisions about health often involve risk, and different decision makers interpret and value risk information differently. Furthermore, an individual's attitude toward health-specific risks can contribute to variation in health preferences and behavior. This study aimed to determine whether and how health-risk attitude and heterogeneity of health preferences are related. METHODS: To study the association between health-risk attitude and preference heterogeneity, we selected 3 discrete choice experiment case studies in the health domain that included risk attributes and accounted for preference heterogeneity. Health-risk attitude was measured using the 13-item Health-Risk Attitude Scale (HRAS-13). We analyzed 2 types of heterogeneity via panel latent class analyses, namely, how health-risk attitude relates to (1) stochastic class allocation and (2) systematic preference heterogeneity. RESULTS: Our study did not find evidence that health-risk attitude as measured by the HRAS-13 distinguishes people between classes. Nevertheless, we did find evidence that the HRAS-13 can distinguish people's preferences for risk attributes within classes. This phenomenon was more pronounced in the patient samples than in the general population sample. Moreover, we found that numeracy and health literacy did distinguish people between classes. CONCLUSIONS: Modeling health-risk attitude as an individual characteristic underlying preference heterogeneity has the potential to improve model fit and model interpretations. Nevertheless, the results of this study highlight the need for further research into the association between health-risk attitude and preference heterogeneity beyond class membership, a different measure of health-risk attitude, and the communication of risks.

What ethical approaches are used by scientists when sharing health data? An interview study.

BACKGROUND: Health data-driven activities have become central in diverse fields (research, AI development, wearables, etc.), and new ethical challenges have arisen with regards to privacy, integrity, and appropriateness of use. To ensure the protection of individuals' fundamental rights and freedoms in a changing environment, including their right to the protection of personal data, we aim to identify the ethical approaches adopted by scientists during intensive data exploitation when collecting, using, or sharing peoples' health data. METHODS: Twelve scientists who were collecting, using, or sharing health data in different contexts in Sweden, were interviewed. We used systematic expert interviews to access these scientists' specialist knowledge, and analysed the interviews with thematic analysis. Phrases, sentences, or paragraphs through which ethical values and norms were expressed, were identified and coded. Codes that reflected similar concepts were grouped, subcategories were formulated, and categories were connected to traditional ethical approaches. RESULTS: Through several examples, the respondents expressed four different ethical approaches, which formed the main conceptual categories: consideration of consequences, respect for rights, procedural compliance, and being professional. CONCLUSIONS: To a large extent, the scientists' ethical approaches were consistent with ethical and legal principles. Data sharing was considered important and worth pursuing, even though it is difficult. An awareness of the complex issues involved in data sharing was reflected from different perspectives, and the respondents commonly perceived a general lack of practical procedures that would by default ensure ethical and legally compliant data collection and sharing. We suggest that it is an opportune time to move on from policy discussions to practical technological ethics-by-design solutions that integrate these principles into practice.

Public perceptions of myocardial infarction: Do illness perceptions predict preferences for health check results.

Illness perceptions are associated with attitudes towards preventive behaviors and are therefore crucial to consider in the context of prevention of cardiovascular diseases. We investigated illness perceptions of the public about myocardial infarction, and whether they predict public preferences for health check test results. A randomly selected sample (N = 423) of the Swedish public aged 40-70 completed an online-survey. It included the brief illness perception questionnaire, items assessing sociodemographic, lifestyle and health factors and a discrete choice experiment incorporating six attributes of health checks (written results, notification method, consultation time, waiting time, lifestyle recommendation and cost). Associations between illness perceptions and sociodemographic- and cardiovascular risk factors were analyzed using multivariate linear regression. Preference data were analyzed with a mixed multinomial logit model. Presence of smoking, hypertension, obesity and lack of physical activity were associated with weaker causal beliefs for the relevant risk factor, while presence of a high stress level was associated with stronger causal beliefs for stress. Low control predicted unwillingness to receive lifestyle recommendations. Attributing family history as the most important personal cause of MI predicted unwillingness to participate in health checks. Illness perceptions differed due to presence of risk factors, age, sex and health literacy. Furthermore, illness perceptions influenced preferences for health check test results and willingness to participate in health checks. Illness perceptions should therefore be addressed when designing health communication and preventive interventions such as health checks, and methods for promoting accurate illness perceptions should be developed.

Preferences of the Public for Sharing Health Data: Discrete Choice Experiment.

BACKGROUND: Digital technological development in the last 20 years has led to significant growth in digital collection, use, and sharing of health data. To maintain public trust in the digital society and to enable acceptable policy-making in the future, it is important to investigate people's preferences for sharing digital health data. OBJECTIVE: The aim of this study is to elicit the preferences of the public in different Northern European countries (the United Kingdom, Norway, Iceland, and Sweden) for sharing health information in different contexts. METHODS: Respondents in this discrete choice experiment completed several choice tasks, in which they were asked if data sharing in the described hypothetical situation was acceptable to them. Latent class logistic regression models were used to determine attribute-level estimates and heterogeneity in preferences. We calculated the relative importance of the attributes and the predicted acceptability for different contexts in which the data were shared from the estimates. RESULTS: In the final analysis, we used 37.83% (1967/5199) questionnaires. All attributes influenced the respondents' willingness to share health information (P<.001). The most important attribute was whether the respondents were informed about their data being shared. The possibility of opting out from sharing data was preferred over the opportunity to consent (opt-in). Four classes were identified in the latent class model, and the average probabilities of belonging were 27% for class 1, 32% for class 2, 23% for class 3, and 18% for class 4. The uptake probability varied between 14% and 85%, depending on the least to most preferred combination of levels. CONCLUSIONS: Respondents from different countries have different preferences for sharing their health data regarding the value of a review process and the reason for their new use. Offering respondents information about the use of their data and the possibility to opt out is the most preferred governance mechanism.

A study protocol for quantifying patient preferences in neuromuscular disorders: a case study of the IMI PREFER Project.

Objectives: Patient preference studies are increasingly used to inform decision-making during the medical product lifecycle but are rarely used to inform early stages of drug development.  The primary aim of this study is to quantify treatment preferences of patients with neuromuscular disorders, which represent serious and debilitating conditions with limited or no treatment options available. Methods: This quantitative patient preferences study was designed as an online survey, with a cross-over design.  This study will target two different diseases from the neuromuscular disorders disease group, myotonic dystrophy type 1 (DM1) and mitochondrial myopathies (MM). Despite having different physio-pathological pathways both DM1 and MM manifest in a clinically similar manner and may benefit from similar treatment options.  The sample will be stratified into three subgroups: two patient groups differentiated by age of symptom onset and one caregivers group.   Each subgroup will be randomly assigned to complete two of three different preference elicitation methods at two different time points: Q-methodology survey, discrete choice experiment, and best-worst scaling type 2, allowing cross-comparisons of the results across each study time within participants and within elicitation methods. Additional variables such as sociodemographic, clinical and health literacy will be collected to enable analysis of potential heterogeneity. Ethics and Dissemination: This study protocol has undergone ethical review and approval by the Newcastle University R&D Ethics Committee (Ref: 15169/2018). All participants will be invited to give electronic informed consent to take part in the study prior accessing the online survey. All electronic data will be anonymised prior analysis. This study is part of the Patient Preferences in Benefit-Risk Assessments during the Drug Life Cycle (IMI-PREFER) project, a public-private collaborative research project aiming to develop expert and evidence-based recommendations on how and when patient preferences can be assessed and used to inform medical product decision making.

Research participants' preferences for receiving genetic risk information: a discrete choice experiment.

PURPOSE: This study aims to determine research participants' preferences for receiving genetic risk information when participating in a scientific study that uses genome sequencing. METHODS: A discrete choice experiment questionnaire was sent to 650 research participants (response rate 60.5%). Four attributes were selected for the questionnaire: type of disease, disease penetrance probability, preventive opportunity, and effectiveness of the preventive measure. Panel mixed logit models were used to determine attribute level estimates and the heterogeneity in preferences. Relative importance of the attribute and the predicted uptake for different information scenarios were calculated from the estimates. In addition, this study estimates predicted uptake for receiving genetic risk information in different scenarios. RESULTS: All characteristics influenced research participants' willingness to receive genetic risk information. The most important characteristic was the effectiveness of the preventive opportunity. Predicted uptake ranged between 28% and 98% depending on what preventive opportunities and levels of effectiveness were presented. CONCLUSION: Information about an effective preventive measure was most important for participants. They valued that attribute twice as much as the other attributes. Therefore, when there is an effective preventive measure, risk communication can be less concerned with the magnitude of the probability of developing disease.

Making sense of genetic risk: A qualitative focus-group study of healthy participants in genomic research.

OBJECTIVE: It is well known that research participants want to receive genetic risk information that is about high risks, serious diseases and potential preventive measures. The aim of this study was to explore, by qualitative means, something less well known: how do healthy research participants themselves make sense of genetic risk information? METHOD: A phenomenographic approach was chosen to explore research participants' understanding and assessment of genetic risk. We conducted four focus-group (N=16) interviews with participants in a research programme designed to identify biomarkers for cardiopulmonary disease. RESULTS: Among the research participants, we found four ways of understanding genetic risk: as a binary concept, as an explanation, as revealing who I am (knowledge of oneself) and as affecting life ahead. CONCLUSION: Research participants tend to understand genetic risk as a binary concept. This does not necessarily imply a misunderstanding of, or an irrational approach to, genetic risk. Rather, it may have a heuristic function in decision-making. PRACTICAL IMPLICATIONS: Risk communication may be enhanced by tailoring the communication to the participants' own lay conceptions. For example, researchers and counselors should address risk in binary terms, maybe looking out for how individual participants search for threshold figures.