| 1. |
- Drevin, Jennifer, et al.
(author)
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Patients' views on using human embryonic stem cells to treat Parkinson's disease : an interview study
- 2022
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In: BMC Medical Ethics. - : Springer Nature. - 1472-6939. ; 23
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Journal article (peer-reviewed)abstract
- 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.
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| 2. |
- Schölin Bywall, Karin, et al.
(author)
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Patients accept therapy using embryonic stem cells for Parkinson's disease : a discrete choice experiment
- 2023
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In: BMC Medical Ethics. - : BioMed Central (BMC). - 1472-6939. ; 24:1
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Journal article (peer-reviewed)abstract
- Background: New disease-modifying ways to treat Parkinson's disease (PD) may soon become a reality with intracerebral transplantation of cell products produced from human embryonic stem cells (hESCs). The aim of this study was to assess what factors influence preferences of patients with PD regarding stem-cell based therapies to treat PD in the future.Methods: Patients with PD were invited to complete a web-based discrete choice experiment to assess the importance of the following attributes: (i) type of treatment, (ii) aim of treatment, (iii) available knowledge of the different types of treatments, (iv) effect on symptoms, and (v) risk for severe side effects. Latent class conditional logistic regression models were used to determine preference estimates and heterogeneity in respondents' preferences.Results: A substantial difference in respondents' preferences was observed in three latent preference patterns (classes). "Effect on symptoms" was the most important attribute in class 1, closely followed by "type of treatment," with medications as preferred to other treatment alternatives. Effect on symptoms was also the most important attribute in class 2, with treatment with hESCs preferred over other treatment alternatives. Likewise for class 3, that mainly focused on "type of treatment" in the decision-making. Respondents' class membership was influenced by their experience in treatment, side effects, and advanced treatment therapy as well as religious beliefs.Conclusions: Most of the respondents would accept a treatment with products emanating from hESCs, regardless of views on the moral status of embryos. Preferences of patients with PD may provide guidance in clinical decision-making regarding treatments deriving from stem cells.
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| 3. |
- Biasiotto, Roberta, et al.
(author)
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Public Preferences for Digital Health Data Sharing : Discrete Choice Experiment Study in 12 European Countries.
- 2023
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In: Journal of Medical Internet Research. - : JMIR Publications. - 1438-8871. ; 25
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Journal article (peer-reviewed)abstract
- 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.
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| 4. |
- Huls, Samare P. I., et al.
(author)
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Preference Variation : Where Does Health Risk Attitude Come Into the Equation?
- 2022
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In: Value in Health. - : Elsevier. - 1098-3015 .- 1524-4733. ; 25:12, s. 2044-2052
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Journal article (peer-reviewed)abstract
- ObjectivesDecisions 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.MethodsTo 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.ResultsOur 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.ConclusionsModeling 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.
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| 5. |
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| 6. |
- Schölin Bywall, Karin, et al.
(author)
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Physical function and severe side effects matter most to patients with RA (< 5 years) : a discrete choice experiment assessing preferences for personalized RA treatment
- 2023
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In: BMC Rheumatology. - : BioMed Central Ltd. - 2520-1026. ; 7:1
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Journal article (peer-reviewed)abstract
- Aim: Early assessment of patient preferences has the potential to support shared decisions in personalized precision medicine for patients with rheumatoid arthritis (RA). The aim of this study was to assess treatment preferences of patients with RA (< 5 years) with previous experience of inadequate response to first-line monotherapy. Method: Patients were recruited (March–June 2021) via four clinics in Sweden. Potential respondents (N = 933) received an invitation to answer a digital survey. The survey included an introductory part, a discrete choice experiment (DCE) and demographic questions. Each respondent answered 11 hypothetical choice questions as part of the DCE. Patient preferences and preference heterogeneity were estimated using random parameter logit models and latent class analysis models. Results: Patients (n = 182) assessed the most important treatment attributes out of physical functional capacity, psychosocial functional capacity, frequency of mild side effects and likelihood of severe side effects. In general, patients preferred a greater increase in functional capacity and decreased side effects. However, a substantial preference heterogeneity was identified with two underlying preference patterns. The most important attribute in the first pattern was the ‘likelihood of getting a severe side effect’. Physical functional capacity was the most important attribute in the second pattern. Conclusion: Respondents focused their decision-making mainly on increasing their physical functional capacity or decreasing the likelihood of getting a severe side effect. These results are highly relevant from a clinical perspective to strengthen communication in shared decision making by assessing patients’ individual preferences for benefits and risks in treatment discussions.
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| 7. |
- Shah, N., et al.
(author)
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Governing health data across changing contexts : A focus group study of citizen’s views in England, Iceland, and Sweden
- 2021
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In: International Journal of Medical Informatics. - : Elsevier. - 1386-5056 .- 1872-8243. ; 156
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Journal article (peer-reviewed)abstract
- BackgroundThe governance structures associated with health data are evolving in response to advances in digital technologies that enable new ways of capturing, using, and sharing different types of data. Increasingly, health data moves between different contexts such as from healthcare to research, or to commerce and marketing. Crossing these contextual boundaries has the potential to violate societal expectations about the appropriate use of health data and diminish public trust. Understanding citizens’ views on the acceptability of and preferences for data use in different contexts is essential for developing information governance policies in these new contexts.MethodsFocus group design presenting data sharing scenarios in England, Iceland, and Sweden.ResultsSeventy-one participants were recruited. Participants supported the need for data to help understand the observable world, improve medical research, the quality of public services, and to benefit society. However, participants consistently identified the lack of information, transparency and control as barriers to trusting organisations to use data in a way that they considered appropriate. There was considerable support for fair and transparent data sharing practices where all parties benefitted.ConclusionData governance policy should involve all stakeholders’ perspectives on an ongoing basis, to inform and implement changes to health data sharing practices that accord with stakeholder views. The Findings showed that (1) data should be used for ethical purposes even when there was commercial interest; (2) data subjects and/or public institutions that provide and share data should also receive benefits from the sharing of data; (3) third parties use of data requires greater transparency and accountability than currently exists, (4) there should be greater information provided to empower data subjects.
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| 8. |
- Soekhai, Vikas, et al.
(author)
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Comparing Outcomes of a Discrete Choice Experiment and Case 2 Best-Worst Scaling : An Application to Neuromuscular Disease Treatment
- 2023
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In: Patient. - : Springer Nature. - 1178-1653 .- 1178-1661. ; 16:3, s. 239-253
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Journal article (peer-reviewed)abstract
- Background and ObjectivesCase 2 best-worst scaling (BWS-2) is an increasingly popular method to elicit patient preferences. Because BWS-2 potentially has a lower cognitive burden compared with discrete choice experiments, the aim of this study was to compare treatment preference weights and relative importance scores.MethodsPatients with neuromuscular diseases completed an online survey at two different moments in time, completing one method per occasion. Patients were randomly assigned to either first a discrete choice experiment or BWS-2. Attributes included: muscle strength, energy endurance, balance, cognition, chance of blurry vision, and chance of liver damage. Multinomial logit was used to calculate overall relative importance scores and latent class logit was used to estimate heterogeneous preference weights and to calculate the relative importance scores of the attributes for each latent class.ResultsA total of 140 patients were included for analyses. Overall relative importance scores showed differences in attribute importance rankings between a discrete choice experiment and BWS-2. Latent class analyses indicated three latent classes for both methods, with a specific class in both the discrete choice experiment and BWS-2 in which (avoiding) liver damage was the most important attribute. Ex-post analyses showed that classes differed in sex, age, level of education, and disease status. The discrete choice experiment was easier to understand compared with BWS-2.ConclusionsThis study showed that using a discrete choice experiment and BWS-2 leads to different outcomes, both in preference weights as well as in relative importance scores, which might have been caused by the different framing of risks in BWS-2. However, a latent class analysis revealed similar latent classes between methods. Careful consideration about method selection is required, while keeping the specific decision context in mind and pilot testing the methods.
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| 9. |
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| 10. |
- Veldwijk, Jorien, et al.
(author)
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Mimicking Real-Life Decision Making in Health : Allowing Respondents Time to Think in a Discrete Choice Experiment
- 2020
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In: Value in Health. - : Elsevier BV. - 1098-3015 .- 1524-4733. ; 23:7, s. 945-952
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Journal article (peer-reviewed)abstract
- Objective: To empirically test the impact of allowing respondents time to think (TTT) about their choice options on the outcomes of a discrete choice experiments (DCE). Methods: In total, 613 participants of the Swedish CArdioPulmonary bioImage Study (SCAPIS) completed a DCE questionnaire that measured their preferences for receiving secondary findings of a genetic test. A Bayesian D-efficient design with 60 choice tasks divided over 4 questionnaires was used. Each choice task contained 2 scenarios with 4 attributes: type of disease, disease penetrance probability, preventive opportunities, and effectiveness of prevention. Respondents were randomly allocated to the TTT or no TTT (NTTT) sample. Latent class models (LCMs) were estimated to determine attribute-level values and their relative importance. In addition, choice certainty, attribute-level interpretation, choice consistency, and potential uptake rates were compared between samples. Results: In the TTT sample, 92% of the respondents (245 of 267) indicated they used the TTT period to (1) read the information they received (72%) and (2) discuss with their family (24%). In both samples, respondents were very certain about their choices. A 3-class LCM was fitted for both samples. Preference reversals were found for 3 of the 4 attributes in one class in the NTTT sample (34% class-membership probability). Relative importance scores of the attributes differed between the 2 samples, and significant scale effects indicating higher choice consistency in TTT sample were found. Conclusions: Offering respondents TTT influences decision making and preferences. Developers of future DCEs regarding complex health-related decisions are advised to consider this approach to enhance the validity of the elicited preferences.
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