A best-worst scaling experiment to prioritize concern about ethical issues in citizen science reveals heterogeneity on people-level v. data-level issues

Assessing patient information needs for new antidiabetic medications to inform shared decision-making: A best-worst scaling experiment in China

BACKGROUND

Shared decision-making (SDM) is a patient-centred approach to improve the quality of care. An essential requirement for the SDM process is to be fully aware of patient information needs.

OBJECTIVES

Our study aimed to assess patient information needs for new antidiabetic medications using the best-worst scaling (BWS) experiment.

METHODS

BWS tasks were developed according to a literature review and the focus group discussion. We used a balanced incomplete block design and blocking techniques to generate choice sets. The final BWS contains 11 attributes, with 6-choice scenarios in each block. The one-to-one, face-to-face BWS survey was conducted among type 2 diabetic patients in Jiangsu Province. Results were analyzed using count-based analysis and modelling approaches. We also conducted a subgroup analysis to observe preference heterogeneity.

RESULTS

Data from 539 patients were available for analysis. The most desired information domain was the comparative effectiveness of new antidiabetic medications. It consists of the incidence of macrovascular complications, the length of extended life years, changes in health-related quality of life, the incidence of microvascular complications, and the control of glycated haemoglobin. Of all the attributes, the incidence of macrovascular complications was the primary concern. Patients' glycemic control and whether they had diabetes complications exerted a significant influence on their information needs.

CONCLUSIONS

Information on health benefits is of critical significance for diabetic patients. Patients have different information needs as their disease progresses. Personalized patient decision aids that integrate patient information needs and provide evidence of new antidiabetic medications are worthy of being established.

PATIENT OR PUBLIC CONTRIBUTION

Before data collection, a pilot survey was carried out among diabetic patients to provide feedback on the acceptability and intelligibility of the attributes.

Prioritization of ethical concerns regarding HIV molecular epidemiology by public health practitioners and researchers

BACKGROUND

HIV molecular epidemiology (HIV ME) can support the early detection of emerging clusters of new HIV infections by combining HIV sequence data routinely obtained during the clinical treatment of people living with HIV with behavioral, geographic, and sociodemographic information. While information about emerging clusters promises to facilitate HIV prevention and treatment efforts, the use of this data also raises several ethical concerns. We sought to assess how those working on the frontlines of HIV ME, specifically public health practitioners (PHPs) and researchers, prioritized these issues.

METHODS

Ethical issues were identified through literature review, qualitative in-depth interviews, and stakeholder engagement. PHPs and researchers using HIV ME prioritized the issues using best-worst scaling (BWS). A balanced incomplete block design was used to generate 11 choice tasks each consisting of a sub-set of 5 ethical concerns. In each task, respondents were asked to assess the most and least concerning issue. Data were analyzed using conditional logit, with a Swait-Louviere test of poolability. Latent class analysis was then used to explore preference heterogeneity.

RESULTS

In total, 57 respondents completed the BWS experiment May-June 2023 with the Swait-Louviere test indicating that researchers and PHPs could be pooled (p = 0.512). Latent class analysis identified two classes, those highlighting "Harms" (n = 29) (prioritizing concerns about potential risk of legal prosecution, individual harm, and group stigma) and those highlighting "Utility" (n = 28) (prioritizing concerns about limited evidence, resource allocation, non-disclosure of data use for HIV ME, and the potential to infer the directionality of HIV transmission). There were no differences in the characteristics of members across classes.

CONCLUSIONS

The ethical issues of HIV ME vary in importance among stakeholders, reflecting different perspectives on the potential impact and usefulness of the data. Knowing these differences exist can directly inform the focus of future deliberations about the policies and practices of HIV ME in the United States.

Navigating biosafety concerns within COVID-19 do-it-yourself (DIY) science: an ethnographic and interview study

Non-establishment or do-it-yourself (DIY) science involves individuals who may not have formal training conducting experiments outside of institutional settings. While prior scholarship has examined the motivations and values of those involved in the subset of DIY science known as "DIY biology," little research has addressed how these individuals navigate ethical issues in practice. The present study therefore aimed to understand how DIY biologists identify, approach, and resolve one particular ethical issue-biosafety-in their work. We conducted a digital ethnography of Just One Giant Lab (JOGL), the primary hub for DIY biology during the COVID-19 pandemic, and subsequently conducted interviews with individuals involved with JOGL. We found that JOGL was the first global DIY biology initiative to create a Biosafety Advisory Board and develop formal biosafety guidelines that applied to different groups in multiple locations. There was disagreement, however, regarding whether the Board should have an advisory role or provide mandatory oversight. We found that JOGL practiced ethical gatekeeping of projects that fell outside the limits defined by the Board. Our findings show that the DIY biology community recognized biosafety issues and tried to build infrastructure to facilitate the safe conduct of research.

Supplementary Information

The online version contains supplementary material available at 10.1057/s41292-023-00301-2.

Designing Equitable, Transparent Community-Engaged Disaster Research

Disaster research faces significant infrastructure challenges: regional and federal coordination, access to resources, and community collaboration. Disasters can lead to chemical exposures that potentially impact human health and cause concern in affected communities. Community-engaged research, which incorporates local knowledge and voices, is well-suited for work with communities that experience impacts of environmental exposures following disasters. We present three examples of community-engaged disaster research (CEnDR) following oil spills, hurricanes, and wildfires, and their impact on long-term social, physical, and technical community infrastructure. We highlight the following CEnDR structures: researcher/community networks; convenient research tools; adaptable data collection modalities for equitable access; and return of data.