Barriers to diverse clinical trial participation in Duchenne muscular dystrophy: Engaging Hispanic/Latina caregivers and health professionals.

BACKGROUND: Despite the increasing availability of clinical trials in Duchenne muscular dystrophy, racial/ethnic minorities and other populations facing health disparities remain underrepresented in clinical trials evaluating products for Duchenne. We sought to understand the barriers faced by Hispanic/Latino families specifically and underrepresented groups more generally to clinical trial participation in Duchenne. METHODS: We engaged two participant groups: Hispanic/Latino caregivers of children with Duchenne in the US, including Puerto Rico, and health professionals within the broader US Duchenne community. Caregiver interviews explored attitudes towards and experiences with clinical trials, while professional interviews explored barriers to clinical trial participation among socio-demographically underrepresented families (e.g., low income, rural, racial/ethnic minority, etc.). Interviews were analyzed aggregately and using a thematic analysis approach. An advisory group was engaged throughout the course of the study to inform design, conduct, and interpretation of findings generated from interviews. RESULTS: Thirty interviews were conducted, including with 12 Hispanic/Latina caregivers and 18 professionals. We identified barriers to clinical trial participation at various stages of the enrollment process. In the initial identification of patients, barriers included lack of awareness about trials and clinical trial locations at clinics that were less likely to serve diverse patients. In the prescreening process, barriers included ineligibility, anticipated non-compliance in clinical trial protocols, and language discrimination. In screening, barriers included concerns about characteristics of the trial, as well as mistrust/lack of trust. In consent and recruitment, barriers included lack of timely decision support, logistical factors (distance, time, money), and lack of translated study materials. CONCLUSIONS: Numerous barriers hinder participation in Duchenne clinical trials for Hispanic/Latino families and other populations experiencing health disparities. Addressing these barriers necessitates interventions across multiple stages of the clinical trial enrollment process. Recommendations to enhance participation opportunities include developing clinical trial decision support tools, translating prominent clinical trials educational resources such as ClinicalTrials.gov, fostering trusting family-provider relationships, engaging families in clinical trial design, and establishing ethical guidelines for pre-screening potentially non-compliant patients.

Assessing the Benefits and Harms Associated with Early Diagnosis from the Perspective of Parents with Multiple Children Diagnosed with Duchenne Muscular Dystrophy.

Duchenne muscular dystrophy (DMD) is a rare neuromuscular disorder diagnosed in childhood. Limited newborn screening in the US often delays diagnosis. With multiple FDA-approved therapies, early diagnosis is crucial for timely treatment but may entail other benefits and harms. Using a community-based survey, we explored how parents of siblings with DMD perceived early diagnosis of one child due to a prior child's diagnosis. We assessed parents' viewpoints across domains including diagnostic journey, treatment initiatives, service access, preparedness, parenting, emotional impact, and caregiving experience. We analyzed closed-ended responses on a -1.0 to +1.0 scale to measure the degree of harm or benefit parents perceived and analyzed open-ended responses thematically. A total of 45 parents completed the survey, with an average age of 43.5 years and 20.0% identifying as non-white. Younger siblings were diagnosed 2 years earlier on average (p < 0.001). Overall, parents viewed early diagnosis positively (mean: 0.39), particularly regarding school preparedness (+0.79), support services (+0.78), treatment evaluation (+0.68), and avoiding diagnostic odyssey (+0.67). Increased worry was a common downside (-0.40). Open-ended responses highlighted improved outlook and health management alongside heightened emotional distress and treatment burdens. These findings address gaps in the evidence by documenting the effectiveness of early screening and diagnosis of DMD using sibling data.

Pretesting Discrete-Choice Experiments: A Guide for Researchers.

Discrete-choice experiments (DCEs) are a frequently used method to explore the preferences of patients and other decision-makers in health. Pretesting is an essential stage in the design of a high-quality choice experiment and involves engaging with representatives of the target population to improve the readability, presentation, and structure of the preference instrument. The goal of pretesting in DCEs is to improve the validity, reliability, and relevance of the survey, while decreasing sources of bias, burden, and error associated with preference elicitation, data collection, and interpretation of the data. Despite its value to inform DCE design, pretesting lacks documented good practices or clearly reported applied examples. The purpose of this paper is: (1) to define pretesting and describe the pretesting process specifically in the context of a DCE, (2) to present a practical guide and pretesting interview discussion template for researchers looking to conduct a rigorous pretest of a DCE, and (3) to provide an illustrative example of how these resources were operationalized to inform the design of a complex DCE aimed at eliciting tradeoffs between personal privacy and societal benefit in the context of a police method known as investigative genetic genealogy (IGG).

Patient satisfaction with the quality of care received is associated with adherence to antidepressant medications.

BACKGROUND: There is a paucity of evidence on the association between satisfaction with quality of care and adherence to antidepressants. OBJECTIVES: To examine the association between patient satisfaction with healthcare and adherence to antidepressants. METHODS: A cohort study design was used to identify antidepressant users from the 2010-2016Medical Expenditure Panel Survey data, a national longitudinal complex survey study design on the cost and healthcare utilization of the noninstitutionalized population in the United States. The Consumer Assessment of Healthcare Providers and Systems were used to measure participants' satisfaction with access and quality of care, patient-provider communication and shared decision-making (SDM). Patients were considered satisfied if they ranked the quality of care at ≥9 (range: 0[worst]- 10[best]). Antidepressant adherence was measured based on medication refill and complete discontinuation. MEPS sampling survey-weighted multivariable-adjusted logistic regression models were used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between satisfaction and adherence to antidepressants. We tested for the potential presence of reverse associations by restricting the analysis to new users of antidepressants. The roles of patient-provider communication and SDM on the satisfaction-adherence association were examined through structural equation models (SEM). RESULTS: Among 4,990 (weighted counts = 8,661,953) antidepressant users, 36% were adherent while 39% discontinued antidepressants therapy. Half of antidepressant users were satisfied with the healthcare received. Satisfied patients were 26% (OR = 1.26, 95%CI: 1.08, 1.47) more likely to adhere and 17% (OR = 0.83, 95%CI: 0.71, 0.96) less likely to discontinue, compared to unsatisfied antidepressant users. Patient satisfaction was also associated with higher odds (OR = 1.41, 95%CI: 1.06, 1.88) of adherence among a subgroup of new users of antidepressants. The SEM analysis revealed that satisfaction was a manifestation of patient-provider communication (ß = 2.03, P-value<0.001) and SDM (ß = 1.14, P-value<0.001). CONCLUSIONS: Patient satisfaction is a potential predictor of antidepressant adherence. If our findings are confirmed through intervention studies, improving patient-provider communication and SDM could likely drive both patient satisfaction and adherence to antidepressants.

Establishing a clinical informatics umbilical cord: lessons learned in launching infrastructure to support dyadic mother/infant primary care.

The Multimodal Maternal Infant Perinatal Outpatient Delivery System (MOMI PODS) was developed to facilitate the pregnancy to postpartum primary care transition, particularly for individuals at risk for severe maternal morbidity, via a unique multidisciplinary model of mother/infant dyadic primary care. Specialized clinical informatics platforms are critical to ensuring the feasibility and scalability of MOMI PODS and a smooth perinatal transition into longitudinal postpartum primary care. In this manuscript, we describe the MOMI PODS transition and management clinical informatics platforms developed to facilitate MOMI PODS referrals, scheduling, evidence-based multidisciplinary care, and program evaluation. We discuss opportunities and lessons learned associated with our applied methods, as advances in clinical informatics have considerable potential to enhance the quality and evaluation of innovative maternal health programs like MOMI PODS.

Promoting patient engagement in cancer genomics research programs: An environmental scan.

Background: A national priority in the United States is to promote patient engagement in cancer genomics research, especially among diverse and understudied populations. Several cancer genomics research programs have emerged to accomplish this priority, yet questions remain about the meaning and methods of patient engagement. This study explored how cancer genomics research programs define engagement and what strategies they use to engage patients across stages in the conduct of research. Methods: An environmental scan was conducted of cancer genomics research programs focused on patient engagement. Research programs were identified and characterized using materials identified from publicly available sources (e.g., websites), a targeted literature review, and interviews with key informants. Descriptive information about the programs and their definitions of engagement, were synthesized using thematic analysis. The engagement strategies were synthesized and mapped to different stages in the conduct of research, including recruitment, consent, data collection, sharing results, and retention. Results: Ten research programs were identified, examples of which include the Cancer Moonshot Biobank, the MyPART Network, NCI-CONNECT, and the Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. All programs aimed to include understudied or underrepresented populations. Based on publicly available information, four programs explicitly defined engagement. These definitions similarly characterized engagement as being interpersonal, reciprocal, and continuous. Five general strategies of engagement were identified across the programs: 1) digital (such as websites) and 2) non-digital communications (such as radio broadcasts, or printed brochures); 3) partnering with community organizations; 4) providing incentives; and 5) affiliating with non-academic medical centers. Digital communications were the only strategy used across all stages of the conduct of research. Programs tailored these strategies to their study goals, including overcoming barriers to research participation among diverse populations. Conclusion: Programs studying cancer genomics are deeply committed to increasing research participation among diverse populations through patient engagement. Yet, the field needs to reach a consensus on the meaning of patient engagement, develop a taxonomy of patient engagement measures in cancer genomics research, and identify optimal strategies to engage patients in cancer genomics. Addressing these needs could enable patient engagement to fulfill its potential and accelerate the pace of cancer genomic discoveries.

Priorities to Promote Participant Engagement in the Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network.

BACKGROUND: Engaging diverse populations in cancer genomics research is of critical importance and is a fundamental goal of the NCI Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. Established as part of the Cancer Moonshot, PE-CGS is a consortium of stakeholders including clinicians, scientists, genetic counselors, and representatives of potential study participants and their communities. Participant engagement is an ongoing, bidirectional, and mutually beneficial interaction between study participants and researchers. PE-CGS sought to set priorities in participant engagement for conducting the network's research. METHODS: PE-CGS deliberatively engaged its stakeholders in the following four-phase process to set the network's research priorities in participant engagement: (i) a brainstorming exercise to elicit potential priorities; (ii) a 2-day virtual meeting to discuss priorities; (iii) recommendations from the PE-CGS External Advisory Panel to refine priorities; and (iv) a virtual meeting to set priorities. RESULTS: Nearly 150 PE-CGS stakeholders engaged in the process. Five priorities were set: (i) tailor education and communication materials for participants throughout the research process; (ii) identify measures of participant engagement; (iii) identify optimal participant engagement strategies; (iv) understand cancer disparities in the context of cancer genomics research; and (v) personalize the return of genomics findings to participants. CONCLUSIONS: PE-CGS is pursuing these priorities to meaningfully engage diverse and underrepresented patients with cancer and posttreatment cancer survivors as participants in cancer genomics research and, subsequently, generate new discoveries. IMPACT: Data from PE-CGS will be shared with the broader scientific community in a manner consistent with participant informed consent and community agreement.

Increasing Access to Buprenorphine for Opioid Use Disorder in Primary Care: an Assessment of Provider Incentives.

BACKGROUND: Primary care providers (PCPs) are essential to increasing access to office-based buprenorphine medication treatment for opioid use disorder (B-MOUD). Barriers to B-MOUD prescribing are well-documented, but there is little information regarding incentives to overcome these barriers. OBJECTIVE: To identify optimal incentives for PCPs to promote B-MOUD prescribing and compare incentive preferences across provider and practice characteristics. DESIGN: We surveyed PCPs using best-worst scaling (BWS) to prioritize seven potential incentives for B-MOUD prescribing (monetary compensation, paid vacation, protected time, professional development, reduced workload, service recognition, clinical resources). We then used a direct elicitation approach to determine preferred incentive levels (e.g., monetary thresholds) and types (e.g., specific clinical resources). PARTICIPANTS: Primary care physicians and advanced practice providers (APPs) at a large Department of Veterans Affairs healthcare system. MAIN MEASURES: B-MOUD prescribing incentive preferences and relative preference levels using descriptive statistics and conditional logistic regression with relative importance scale transformation (coefficients sum to 100, higher coefficient=greater importance). KEY RESULTS: Fifty-three PCPs responded (73% response), including 47% APPs and 36% from community-based clinics. Reduced workload (relative importance score=26.8), protected time (18.7), and clinical resources (16.8) were significantly more preferred (Ps < 0.001) than professional development (10.5), paid vacation (10.3), or service recognition (1.5). Relative importance of monetary compensation varied between physicians (12.6) and APPs (17.5) and between PCPs located at a medical center (11.4) versus community clinic (22.3). APPs were more responsive than physicians to compensation increases of $5000 and $12,000 but less responsive to $25,000; trends were similar for medical center versus community clinic PCPs. The most frequently requested clinical resource was on-demand consult access to an addiction specialist. CONCLUSIONS: Interventions promoting workload reductions, protected time, and clinical resources could increase access to B-MOUD in primary care. Monetary incentives may be additionally needed to improve B-MOUD prescribing among APPs and within community clinics.

Guidelines for Artificial Intelligence in Medicine: Literature Review and Content Analysis of Frameworks.

BACKGROUND: Artificial intelligence (AI) is rapidly expanding in medicine despite a lack of consensus on its application and evaluation. OBJECTIVE: We sought to identify current frameworks guiding the application and evaluation of AI for predictive analytics in medicine and to describe the content of these frameworks. We also assessed what stages along the AI translational spectrum (ie, AI development, reporting, evaluation, implementation, and surveillance) the content of each framework has been discussed. METHODS: We performed a literature review of frameworks regarding the oversight of AI in medicine. The search included key topics such as "artificial intelligence," "machine learning," "guidance as topic," and "translational science," and spanned the time period 2014-2022. Documents were included if they provided generalizable guidance regarding the use or evaluation of AI in medicine. Included frameworks are summarized descriptively and were subjected to content analysis. A novel evaluation matrix was developed and applied to appraise the frameworks' coverage of content areas across translational stages. RESULTS: Fourteen frameworks are featured in the review, including six frameworks that provide descriptive guidance and eight that provide reporting checklists for medical applications of AI. Content analysis revealed five considerations related to the oversight of AI in medicine across frameworks: transparency, reproducibility, ethics, effectiveness, and engagement. All frameworks include discussions regarding transparency, reproducibility, ethics, and effectiveness, while only half of the frameworks discuss engagement. The evaluation matrix revealed that frameworks were most likely to report AI considerations for the translational stage of development and were least likely to report considerations for the translational stage of surveillance. CONCLUSIONS: Existing frameworks for the application and evaluation of AI in medicine notably offer less input on the role of engagement in oversight and regarding the translational stage of surveillance. Identifying and optimizing strategies for engagement are essential to ensure that AI can meaningfully benefit patients and other end users.

Diagnostic experiences of Duchenne families and their preferences for newborn screening: A mixed-methods study.

Duchenne muscular dystrophy is the most common form of muscular dystrophy diagnosed in childhood but is not routinely screened for prenatally or at birth in the United States. We sought to characterize the diagnostic experiences of families and describe their preferences for newborn screening (NBS). We conducted a registry-based survey of families with Duchenne and Becker muscular dystrophy that included open- and closed-ended questions regarding the journey to a diagnosis, preferences for when to learn of a diagnosis, and how knowledge of a diagnosis would impact life decisions. Open-ended responses were analyzed thematically, and closed-ended responses were analyzed descriptively. Sixty-five families completed the survey. The average ages of first concern and diagnosis were 2 and 4 years, respectively. One-third of families (30%) indicated that they would prefer to receive a diagnosis in the newborn period irrespective of treatment options available, and nearly all of the remaining families (93%) indicated that they would want to learn about a diagnosis if there were treatments that worked well during the newborn period. All families (100%) indicated that a diagnosis in the newborn period would impact life decisions. We identified three overarching themes, which described the stages of the diagnostic journey, including having concerns about the child, seeking answers, and receiving the diagnosis. NBS can facilitate improved health outcomes through early access to care, and inform families on major health and nonhealth decisions. The preferences and experiences of families and other stakeholders should be considered when determining the potential value and benefit of expanding NBS programs.

Best-Worst Scaling and the Prioritization of Objects in Health: A Systematic Review.

BACKGROUND AND OBJECTIVE: Best-worst scaling is a theory-driven method that can be used to prioritize objects in health. We sought to characterize all studies of best-worst scaling to prioritize objects in health, to assess trends of using best-worst scaling in prioritization over time, and to assess the relationship between a legacy measure of quality (PREFS) and a novel assessment of subjective quality and policy relevance. METHODS: A systematic review identified studies published through to the end of 2021 that applied best-worst scaling to study priorities in health (PROSPERO CRD42020209745), updating a prior review published in 2016. The PubMed, EBSCOhost, Embase, Scopus, APA PsychInfo, Web of Science, and Google Scholar databases were used and were supplemented by a hand search. Data describing the application, development, design, administration/analysis, quality, and policy relevance were summarized and we tested for trends by comparing articles before and after 1 January, 2017. Multivariate statistics were then used to assess the relationships between PREFS, subjective quality, policy relevance, and other possible indicators. RESULTS: From a total of 2826 unique papers identified, 165 best-worst scaling studies were included in this review. Applications of best-worst scaling to study priorities in health have continued to grow (p < 0.01) and are now used in all regions of the world, most often to study the priorities of patients/consumers (67%). Several key trends can be observed over time: increased use of pretesting (p < 0.05); increased use of online administration (p < 0.01), and decreased use of paper self-administered surveys (p = 0.02); increased use of heterogeneity analysis (p = 0.02); an increase in having a clearly stated purpose (p < 0.01); and a decrease in comparing respondents to non-respondents (p = 0.01). The average sample size has more than doubled, from 228 to 472 respondents, but formal sample size justifications remain low (5.3%) and unchanged over time (p = 0.68). While the average PREFS score remained unchanged at 3.1/5, both subjective quality and policy relevance trended up, but changes were not statistically significant (p = 0.06 and p = 0.13). Most of the variation in subjective quality was driven by PREFS (R2 = 0.42), but it was also positively assosciated with policy relevance, heterogeneity analysis, and using a balanced incomplete block design, and was negatively associated with not using developmental methods and an increasing sample size. CONCLUSIONS: Using best-worst scaling to prioritize objects is now commonly used around the world to assess the priorities of patients and other stakeholders in health. Best practices are clearly emerging for best-worst scaling. Although legacy measures (PREFS) to measure study quality are reasonable, there may need to be new tools to assess both study quality and policy relevance.

Listening to the Patient Voice Adds Value to Cancer Clinical Trials.

Randomized clinical trials are critical for evaluating the safety and efficacy of interventions in oncology and informing regulatory decisions, practice guidelines, and health policy. Patient-reported outcomes (PROs) are increasingly used in randomized trials to reflect the impact of receiving cancer therapies from the patient perspective and can inform evaluations of interventions by providing evidence that cannot be obtained or deduced from clinicians' reports or from other biomedical measures. This commentary focuses on how PROs add value to clinical trials by representing the patient voice. We employed 2 previously published descriptive frameworks (addressing how PROs are used in clinical trials and how PROs have an impact, respectively) and selected 9 clinical trial publications that illustrate the value of PROs according to the framework categories. These include 3 trials where PROs were a primary trial endpoint, 3 trials where PROs as secondary endpoints supported the primary endpoint, and 3 trials where PROs as secondary endpoints contrast the primary endpoint findings in clinically important ways. The 9 examples illustrate that PROs add valuable data to the care and treatment context by informing future patients about how they may feel and function on different treatments and by providing clinicians with evidence to support changes to clinical practice and shared decision making. Beyond the patient and clinician, PROs can enable administrators to consider the cost-effectiveness of implementing new interventions and contribute vital information to policy makers, health technology assessors, and regulators. These examples provide a strong case for the wider implementation of PROs in cancer trials.

A Framework for Promoting Diversity, Equity, and Inclusion in Genetics and Genomics Research.

IMPORTANCE: Research into the genetic and genomic ("genomics") foundations of disease is central to our understanding of disease prevention, early detection, diagnostic accuracy, and therapeutic intervention. Inequitable participation in genomics research by historically excluded populations limits the ability to translate genomic knowledge to achieve health equity and ensure that findings are generalizable to diverse populations. OBSERVATIONS: We propose a novel framework for promoting diversity, equity, and inclusion in genomics research. Building on principles of community-based participatory research and collective impact frameworks, the framework can guide our understanding of the social, cultural, health system, policy, community, and individual contexts in which engagement and genomics research are being done. Our framework highlights the involvement of a multistakeholder team, including the participants and communities to be engaged, to ensure robust methods for recruitment, retention, return of genomic results, quality of engagement, follow-up, and monitoring of participants. CONCLUSIONS AND RELEVANCE: The proposed engagement framework will guide investigators in optimizing equitable representation in research and enhancing the rigor of genomics investigation.

A Comparison of Caregiver and Patient Preferences for Treating Duchenne Muscular Dystrophy.

BACKGROUND AND OBJECTIVES: Caregivers routinely inform medical and regulatory decision making in rare pediatric diseases. While differences in treatment preferences across caregivers and patients have been observed for Duchenne muscular dystrophy, this evidence was limited by small samples of patients and results were confounded by patient age and disease progression. We tested caregiver and patient preference concordance for treating Duchenne. METHODS: Preferences and demographic/clinical information from 115 caregivers and 107 patients were collected in an international study (response = 80%) using a previously developed discrete-choice experiment consisting of 12 experimentally controlled choice tasks. Each task presented two profiles that varied across four attributes: disease progression, drug failure probability, kidney damage risk, and fracture risk. Caregivers and patients were matched 1:1 based on patient age. We tested for concordance across each task and by comparing caregivers' and patients' maximum acceptable risk of drug failure, kidney damage, and fracture for a slowing of disease progression. RESULTS: The final analysis included 77 caregivers and 77 patients. No differences were observed in nationality (p = 0.969), disease stage (p = 0.180), or demographic/clinical factors (p = 0.093-0.857); however, patients were more optimistic (p = 0.030). Caregivers and patients chose similarly across tasks (p = 0.101-0.993). To slow disease progression by 1 year, caregivers and patients would tolerate a 9% and 11% increase in drug failure probability, respectively (p = 0.267). Alternatively, they would accept a 3% and 4% increase in the risk of kidney damage (p = 0.719) or a 15% and 20% increase in the risk of fracture (p = 0.534). CONCLUSIONS: Caregivers and patients had concordant preferences for treating Duchenne. Providers and regulators can trust both caregiver and patient report of preferences to inform medical decision making.

Unmet Therapeutic Needs of Non-Ambulatory Patients with Duchenne Muscular Dystrophy: A Mixed-Method Analysis.

OBJECTIVE: Duchenne muscular dystrophy has been a launching pad for patient-focused drug development (PFDD). Yet, PFDD efforts have largely neglected non-ambulatory patients. To support PFDD efforts in this population, we primarily sought to understand the needs of non-ambulatory Duchenne patients and, secondarily, to examine these needs in the context of the PUL-PROM-a validated patient-reported outcome measure of upper limb functioning. METHODS: Non-ambulatory Duchenne patients or their caregivers from eight countries answered open-ended survey questions about patients' needs related to their most significant symptoms and important benefits of new treatments. The PUL-PROM was used to evaluate patients' upper limb functioning and was compared to data collected on non-ambulatory stage and quality of life. We thematically analyzed open-ended data, descriptively analyzed close-ended data, and compared themes by non-ambulatory stage. RESULTS: The study included 275 participants. Mean patient age was 24. Most patients were early-stage non-ambulatory (67%). Thematic analysis identified three congruent themes between significant symptoms and important benefits of new treatments: muscle functioning, especially upper limb function; body system functioning; and quality of life. Muscle functioning and body system functioning were endorsed more frequently in responses from early- and late-stage patients, respectively. Mean PUL-PROM total score was 22 with higher scores in early-stage patients (p ≤ 0.001). Upper limb function positively correlated with quality of life (r = 0.42, p ≤ 0.001). DISCUSSION: Non-ambulatory Duchenne patients want new treatments that improve upper limb functioning and body system functioning, and not exclusively regaining ambulation. The PUL-PROM can be used as a patient-centric measure that accounts for the needs of later-stage Duchenne patients.

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

"Citizen science" refers to the participation of lay individuals in scientific studies and other activities having scientific objectives. Citizen science gives rise to unique ethical issues that stem from the potentially multifaceted contributions of citizen scientists to the research process. We sought to explore the ethical issues that are most concerning to citizen scientist practitioners, participants, and scholars to support ethical practices in citizen science. We developed a best-worst scaling experiment using a balanced incomplete block design and fielded it with respondents recruited through the U.S.-based Citizen Science Association. Respondents were shown repeated subsets of 11 ethical issues and identified the most and least concerning issues in each subset. Latent class analysis revealed two respondent classes. The "Power to the People" class was most concerned about power imbalance between project leaders and participants, exploitation of participants, and lack of diverse participation. The "Show Me the Data" class was most concerned about the quality of data generated by citizen science projects and failure of projects to share data and other research outputs.