[This corrects the article DOI: 10.1371/journal.pone.0279857.].

BackgroundAs criteria for diagnosing Alzheimer's disease and Alzheimer's disease related dementias (AD/ADRD) evolves, AD-related biological measures of biomarkers (e.g., amyloid, tau) and genetic status (e.g., APOE) have gained heightened value in research, and, notably, increased personal significance for participants.ObjectiveTo identify recommended approaches for sharing individual research results with participants in AD/ADRD research and determine expert consensus on best practices for sharing individual research results to participants in AD/ADRD research.MethodsThis online, modified Delphi study consisted of four rounds of surveys conducted with Alzheimer's disease research experts, including neurologists, ethicists, neuropsychologists, geneticists, clinical trialists, and other research stakeholders. The Delphi survey was informed by a targeted literature review of previously published recommendations on sharing individual research results in AD/ADRD research. A total of 81 experts were surveyed across all rounds, ranking statements on a 7-point Likert scale and providing feedback in short answer responses. After each round, feedback reports were shared to inform subsequent responses. Proportion of agreement and qualitative feedback were analyzed, with consensus defined as 75% or greater agreement.Results41 initial statements were evaluated and refined based on consensus and feedback. Concluding the final round (round 3), consensus (≥75% agreement) was achieved on 25 statements, resulting in a set of recommendations related to: study design, clinical relevance, results sharing processes, communication and understanding of results, counseling and support, and follow-up.ConclusionsThe findings of this online, modified Delphi study provide a foundation for developing standardized, ethically grounded practices for returning individual research results in Alzheimer's disease studies.

Background:Public deliberation is a qualitative research method that has successfully been used to solicit laypeople's perspectives on health ethics topics, but it remains unclear whether this traditionally in-person method can be translated to the online context. The MindKind Study conducted public deliberation sessions to gauge the concerns and aspirations of young people in India, South Africa, and the United Kingdom with regard to a prospective mental health databank. This paper details our adaptations to and evaluation of the public deliberation method in an online context, especially in the presence of a digital divide. Objective:The purpose of this study was to assess the quality of online public deliberation and share emerging learnings in a remote, disseminated qualitative research context. Methods:We convened 2-hour structured deliberation sessions over an online video conferencing platform (Zoom). We provided participants with multimedia informational materials describing different ways to manage mental health data. We analyzed the quality of online public deliberation in variable resource settings on the basis of (1) equal participation, (2) respect for the opinions of others, (3) adoption of a societal perspective, and (4) reasoned justification of ideas. To assess the depth of comprehension of the informational materials, we used qualitative data that pertained directly to the materials provided. Results:The sessions were broadly of high quality. Some sessions were affected by an unstable internet connection and subsequent multimodal participation, complicating our ability to perform a quality assessment. English-speaking participants displayed a deep understanding of complex informational materials. We found that participants were particularly sensitive to linguistic and semiotic choices in the informational materials. A more fundamental barrier to understanding was encountered by participants who used materials translated from English. Conclusions:Although online public deliberation may have quality outcomes similar to those of in-person public deliberation, researchers who use remote methods should plan for technological and linguistic barriers when working with a multinational population. Our recommendations to researchers include budgetary planning, logistical considerations, and ensuring participants' psychological safety.

To identify disease-modifying therapies and drug targets for Alzheimer's disease (AD), it is necessary to assess the impact of cellular and molecular dysfunction on disease aetiology. The AD Knowledge Portal (Portal) ( https://adknowledgeportal.org ), Exceptional Longevity Portal (ELITE) and Agora ( https://agora.adknowledgeportal.org ) are community-driven resources that support researchers as they: 1) identify new molecular hypotheses and mechanisms, 2) evaluate hypotheses via independent experimental assessments, and 3) prioritise new molecular mechanisms for therapeutic development. The Portals and Agora are free, open-access tools built to maximise therapeutic discovery by enabling researchers to re-use data from 41,000+ biospecimens collected from 12,000+ individuals across four species and browse or access analytical results related to putative drug targets. The Portals and Agora empower the research community with a trusted repository of data, computational and experimental tools and potential gene targets to test target hypotheses and therapeutics. The portals are also integrated with external Trusted Research Environments (TREs) like CAVATICA and integrate the portals with Terra and AD Workbench. The Portal supports research outputs from 55 grants (including the Accelerating Medicines Partnership-Alzheimer's Disease), each generating data and computational/experimental tools related to dementia and ageing. Utilizing samples from brain banks, longitudinal cohorts, and model systems, available data spans 55+ assays, including genomics, metabolomics, imaging, cognitive assessments, and more. Model systems in the Portal include iPSC-derived cell types and organoids and novel Late-Onset AD mouse models based on gene targets identified from human data. These mouse models are available with no limitation on use. The Portal also features a cloud-based analytical workspace providing access to preconfigured computational resources to process, integrate, and analyse data. A subset of the processed data is also presented in Agora, a visual results explorer that compiles evidence of genes' association with AD. Agora hosts a list of nominated targets and presents the results of omics analyses generated from Portal data. It also includes a catalogue of details and results from targeted validation studies. The AD Knowledge Portal, the ELITE Portal and Agora offer the research community an accessible, rich data source, tools, and results.

Data from the first phase of the Human Tumor Atlas Network (HTAN) are now available, comprising 8,425 biospecimens from 2,042 research participants profiled with more than 20 molecular assays. The data were generated to study the evolution from precancerous to advanced disease. The HTAN Data Coordinating Center (DCC) has enabled their dissemination and effective reuse. We describe the diverse datasets, how to access them, data standards, underlying infrastructure and governance approaches, and our methods to sustain community engagement. HTAN data can be accessed through the HTAN Portal, explored in visualization tools-including CellxGene, Minerva and cBioPortal-and analyzed in the cloud through the NCI Cancer Research Data Commons. Infrastructure was developed to enable data ingestion and dissemination through the Synapse platform. The HTAN DCC's flexible and modular approach to sharing complex cancer research data offers valuable insights to other data-coordination efforts and researchers looking to leverage HTAN data.

Objective: Determine the incidence of vestibular disorders in patients with SARS-CoV-2 compared to the control population. Study Design: Retrospective. Setting: Clinical data in the National COVID Cohort Collaborative database (N3C). Methods: Deidentified patient data from the National COVID Cohort Collaborative database (N3C) were queried based on variant peak prevalence (untyped, alpha, delta, omicron 21K, and omicron 23A) from covariants.org to retrospectively analyze the incidence of vestibular disorders in patients with SARS-CoV-2 compared to control population, consisting of patients without documented evidence of COVID infection during the same period. Results: Patients testing positive for COVID-19 were significantly more likely to have a vestibular disorder compared to the control population. Compared to control patients, the odds ratio of vestibular disorders was significantly elevated in patients with untyped (odds ratio [OR], 2.39; confidence intervals [CI], 2.29–2.50; P < 0.001), alpha (OR, 3.63; CI, 3.48–3.78; P < 0.001), delta (OR, 3.03; CI, 2.94–3.12; P < 0.001), omicron 21K variant (OR, 2.97; CI, 2.90–3.04; P < 0.001), and omicron 23A variant (OR, 8.80; CI, 8.35–9.27; P < 0.001). Conclusions: The incidence of vestibular disorders differed between COVID-19 variants and was significantly elevated in COVID-19-positive patients compared to the control population. These findings have implications for patient counseling and further research is needed to discern the long-term effects of these findings.

INTRODUCTION:Engaging youth in mental health research and intervention design has the potential to improve their relevance and effectiveness. Frameworks like Roger Hart's ladder of participation, Shier's pathways to participation and Lundy's voice and influence model aim to balance power between youth and adults. Hart's Ladder, specifically, is underutilized in global mental health research, presenting new opportunities to examine power dynamics across various contexts. Drawing on Hart's ladder, our study examined youth engagement in mental health research across high- and middle-income countries using Internet-based technologies, evaluating youth involvement in decision-making and presenting research stages that illustrate these engagements. METHODS:We conducted a directed content analysis of youth engagement in the study using primary data from project documents, weekly AirTable updates and discussions and interviews with youth and the research consortium. Using Hart's Ladder as a framework, we describe youth engagement along rungs throughout different research stages: cross-cutting research process, onboarding, formative research and quantitative and qualitative study designs. RESULTS:Youth engagement in the MindKind study fluctuated between Rung 4 ('Assign, but informed') and Rung 7 ('Youth initiated and directed') on Hart's Ladder. Engagement was minimal in the early project stages as project structures and goals were defined, with some youth feeling that their experiences were underutilized and many decisions being adult-led. Communication challenges and structural constraints, like tight timelines and limited budget, hindered youth engagement in highest ladder rungs. Despite these obstacles, youth engagement increased, particularly in developing recruitment strategies and in shaping data governance models and the qualitative study design. Youth helped refine research tools and protocols, resulting in moderate to substantial engagement in the later research stages. CONCLUSION:Our findings emphasize the value of youth-adult partnerships, which offer promise in amplifying voices and nurturing skills, leadership and inclusiveness of young people. Youth engagement in project decision-making progressed from lower to higher rungs on Hart's Ladder over time; however, this was not linear. Effective youth engagement requires dynamic strategies, transparent communication and mutual respect, shaping outcomes that authentically reflect diverse perspectives and mental health experiences. PATIENT OR PUBLIC CONTRIBUTION:There was substantial patient and public involvement in this study. This paper reports findings on youth engagement conducted with 35 young people from India, South Africa and the United Kingdom, all of whom had lived experience of mental health challenges. Youth engagement in the MindKind study was coordinated and led by three professional youth advisors (PYAs) in these contexts, who were also young people with lived experience of mental health challenges. Each of the three study sites embedded a full-time, community-based PYA within their study team to inform all aspects of the research project, including the development of informational materials and the facilitation of Young People's Advisory Group (YPAG) sessions referenced in this paper. Each PYA also consulted with a site-specific YPAG that met bi-monthly throughout the project, shaping the formation of study materials and serving as a test group in both the quantitative and qualitative studies. Youth participants in this study also contributed extensively, engaging in data collection and manuscript writing. The following youth advisory panels members (J.B., L.B., D.O.J., M.V.) and all PYAs (E.B., S.R., R.S.) in the MindKind study contributed to the writing of this manuscript and are acknowledged as co-authors.

Mobile devices offer a scalable opportunity to collect longitudinal data that facilitate advances in mental health treatment to address the burden of mental health conditions in young people. Sharing these data with the research community is critical to gaining maximal value from rich data of this nature. However, the highly personal nature of the data necessitates understanding the conditions under which young people are willing to share them. To answer this question, we developed the MindKind Study, a multinational, mixed methods study that solicits young people's preferences for how their data are governed and quantifies potential participants' willingness to join under different conditions. We employed a community-based participatory approach, involving young people as stakeholders and co-researchers. At sites in India, South Africa, and the UK, we enrolled 3575 participants ages 16-24 in the mobile app-mediated quantitative study and 143 participants in the public deliberation-based qualitative study. We found that while youth participants have strong preferences for data governance, these preferences did not translate into (un)willingness to join the smartphone-based study. Participants grappled with the risks and benefits of participation as well as their desire that the "right people" access their data. Throughout the study, we recognized young people's commitment to finding solutions and co-producing research architectures to allow for more open sharing of mental health data to accelerate and derive maximal benefit from research.

The National COVID Cohort Collaborative (N3C) is a public-private-government partnership established during the Coronavirus pandemic to create a centralized data resource called the "N3C data enclave." This resource contains individual-level health data from participating healthcare sites nationwide to support rapid collaborative analytics. N3C has enabled analytics within a cloud-based enclave of data from electronic health records from over 17 million people (with and without COVID-19) in the USA. To achieve this goal of a shared data resource, N3C implemented a shared governance strategy involving stakeholders in decision-making. The approach leveraged best practices in data stewardship and team science to rapidly enable COVID-19-related research at scale while respecting the privacy of data subjects and participating institutions. N3C balanced equitable access to data, team-based scientific productivity, and individual professional recognition - a key incentive for academic researchers. This governance approach makes N3C research sustainable and effective beyond the initial days of the pandemic. N3C demonstrated that shared governance can overcome traditional barriers to data sharing without compromising data security and trust. The governance innovations described herein are a helpful framework for other privacy-preserving data infrastructure programs and provide a working model for effective team science beyond COVID-19.

Background: The global ubiquity of smartphone use among young people makes them excellent candidates for collecting data about individuals’ lived experiences and their relationships to mental health. However, to-date most app-based studies have been conducted in North America and Europe. Understanding young people’s willingness to participate in app-based research and share information about their mental health is key to understanding the feasibility of broad-scale research using these approaches. We aimed to understand the recruitment and engagement approaches influencing young peoples’ (aged 16-24) participation in app-based studies of mental health. We hypothesised that providing a choice of study topics will improve engagement. Methods: We developed a 12-week pilot study of mental health implemented in the MindKind app, designed to assess participants’ willingness to engage in remote mental health research, both actively and passively. Enrollees were randomised to one of two different engagement arms, either selecting their study topics of interest or receiving a fixed assignment of study topics, in order to understand the role of choice in study engagement. This pilot study was conducted in India, South Africa, and the United Kingdom. Different recruitment strategies were employed in each location. Results: The MindKind Study recruited 1,034 (India), 932 (South Africa) and 1,609 (UK) participants. Engagement differed by country with median days of activity = 2, 6, and 11 for India, South Africa, and UK, respectively. Most surprisingly, participants given a choice of study topics showed lower engagement relative to participants assigned to fixed topics (Hazard Ratio = 0.82). Conclusions: We observe equal or better engagement compared to previous comparable app-based studies of mental health. While providing participants a choice of study topics showed no advantage in our study, our qualitative analysis of participant feedback provides additional suggestions for improving engagement in future studies.

Most people with mental health disorders cannot receive timely and evidence-based care despite billions of dollars spent by healthcare systems. Researchers have been exploring using digital health technologies to measure behavior in real-world settings with mixed results. There is a need to create accessible and computable digital mental health datasets to advance inclusive and transparently validated research for creating robust real-world digital biomarkers of mental health. Here we share and describe one of the largest and most diverse real-world behavior datasets from over two thousand individuals across the US. The data were generated as part of the two NIMH-funded randomized clinical trials conducted to assess the effectiveness of delivering mental health care continuously remotely. The longitudinal dataset consists of self-assessment of mood, depression, anxiety, and passively gathered phone-based behavioral data streams in real-world settings. This dataset will provide a timely and long-term data resource to evaluate analytical approaches for developing digital behavioral markers and understand the effectiveness of mental health care delivered continuously and remotely.

The recent Dobbs decision and current political landscape surrounding abortion rights in the United States has the potential to dramatically disrupt progress in women’s health research. The typical safeguards to ensure confidentiality and privacy of research participants may not hold against criminal investigations surrounding suspected pregnancy terminations. This puts women participating in health research that collects sensitive reproductive information at an increased risk of having this information being used against them by some states or other individuals. There are additional risks to women participating in women’s digital health research studies involving the use of wearable devices capable of tracking physiological measures such as body temperature and heart rate as these have shown promise for tracking conception and could be used to identify pregnancy termination signatures. There are strategies researchers can take to protect the safety of female participants in reproductive health research, while also maintaining integrity of research methods. Here, we discuss potential strategies, and invite others to join this discussion so as not let the current political landscape impede progress in women’s health research, while also protecting research participants.

The recent Supreme Court decision (ie, Dobbs v. Jackson Women’s Health Organization), revoking the constitutional right to abortion in the United States, has the potential to dramatically disrupt progress in women’s health research. The typical safeguards to ensure confidentiality and privacy of research participants in studies that collect certain types of personal health information may not hold against criminal investigations surrounding suspected pregnancy terminations. There are additional risks to participants in digital health research studies involving the use of wearable devices capable of tracking physiological measures, such as body temperature and heart rate, as these have shown promise for tracking conception and could be used to identify pregnancy termination signatures. There are strategies researchers can use to protect the safety of participants in health research who could get pregnant, while also maintaining integrity of research methods. The objective of this viewpoint is to discuss potential strategies to protect research participants’ privacy that include the minimization of nonessential sensitive personal health information and anonymization protocols in the event of miscarriage or termination of pregnancy. We invite others to join this discussion so as to not let the current political landscape impede progress in women’s health and reproductive research, while also protecting research participants.

Electronic platforms provide an opportunity to improve the informed consent (IC) process by permitting elements shown to increase research participant understanding and satisfaction, such as graphics, self-pacing, meaningful engagement, and access to additional information on demand. However, including these elements can pose operational and regulatory challenges for study teams and institutional review boards (IRBs) responsible for the ethical conduct and oversight of research. We examined the experience of two study teams at Alzheimer's Disease Research Centers who chose to move from a paper-based IC process to an electronic informed consent (eIC) process to highlight some of these complexities and explore how IRBs and study teams can navigate them. Here, we identify the key regulations that should be considered when developing and using an eIC process as well as some of the operational considerations eIC presents related to IRB review and how they can be addressed.

Abstract Objective Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. Materials and Methods The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. Results Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. Conclusions The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19.

Remote health assessments that gather real-world data (RWD) outside clinic settings require a clear understanding of appropriate methods for data collection, quality assessment, analysis and interpretation. Here we examine the performance and limitations of smartphones in collecting RWD in the remote mPower observational study of Parkinson’s disease (PD). Within the first 6 months of study commencement, 960 participants had enrolled and performed at least five self-administered active PD symptom assessments (speeded tapping, gait/balance, phonation or memory). Task performance, especially speeded tapping, was predictive of self-reported PD status (area under the receiver operating characteristic curve (AUC) = 0.8) and correlated with in-clinic evaluation of disease severity (r = 0.71; P < 1.8 × 10−6) when compared with motor Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). Although remote assessment requires careful consideration for accurate interpretation of RWD, our results support the use of smartphones and wearables in objective and personalized disease assessments. Smartphone sensors that monitor disease symptoms enable remote assessment of Parkinson’s patients.

The use of digital health technologies is changing the ways people monitor and manage their health and well-being. There is increasing interest in using wearables and smartphone health apps to collect health-related data, a domain within digital health referred to as mHealth. Wearables and health apps can continuously monitor metrics such as physical activity, sleep, and heart rate, to name a few. These mHealth data can supplement the measures taken by healthcare professionals during regular doctor’s visits, with mHealth having the advantage of a much greater frequency of collection. But what are the privacy considerations with mHealth? This paper explores global data privacy protections, enumerates principles to guide regulations, discusses the tension between anonymity and data utility, and proposes ways to improve how we as a society talk about and safeguard data privacy. We include brief discussions about inadvertent or unintended consequences of digital data collection and the trade-off between privacy and public health interests, such as is illustrated by COVID-19 contract tracing apps. This paper concludes by offering suggestions for consideration about improving privacy and confidentiality notices.

The informed consent (IC) process offers an opportunity for researchers to promote participant autonomy and facilitate decision making. However, the traditional IC experience is often tedious, requiring study coordinators to present information in long IC documents. Paper IC documents can be difficult to understand and do not necessarily meet the needs of participants or study coordinators. The COVID-19 pandemic underscores the need to provide an alternative to the in-person, paper-based IC process to minimize person-to-person contact. We worked with IRBs to revise how we engage and consent people in Alzheimer’s Disease Research Centers at the University of Wisconsin-Madison and Emory University. In an ongoing effort to improve the IC process for adults at risk of developing memory and cognitive deficit, our team has been building and testing an electronic IC experience. We interviewed a total of 63 participants with a median age of 72. Participants underwent both the eConsent prototype and the paper consent. Seventy (70) percent of those participants preferred the eConsent over the traditional paper copy. We adapted into REDCap the electronic IC experience (eConsent). We collected input on the project from IRBs and study coordinators, and measured participant’s understanding of key elements of the IC through questions distributed throughout the eConsent. Each interested study participant received a unique link to the eConsent in REDCap. We observed which participants selected to review the eConsent information on their own, and which ones preferred to be guided remotely with the Study coordinators. We evaluated level of engagement with the eConsent and scored comprehension. The insights provided by this informed consent approach were used to determine whether it would be well suited for at-home self-administration across a diverse population. Study participants and study coordinators alike prefer an electronic consent process and participants retain information better as opposed to the typical paper consent form. While the REDCap consent survey is a temporary solution for our study team, it is a cost-effective solution that facilitates a better experience for the participants. We believe that this REDCap eConsent could be a beneficial solution for the virtual recruitment and consent process at other ADRC sites.

Digital technologies such as smartphones are transforming the way scientists conduct biomedical research using real-world data. Several remotely-conducted studies have recruited thousands of participants over a span of a few months. Unfortunately, these studies are hampered by substantial participant attrition, calling into question the representativeness of the collected data including generalizability of findings from these studies. We report the challenges in retention and recruitment in eight remote digital health studies comprising over 100,000 participants who participated for more than 850,000 days, completing close to 3.5 million remote health evaluations. Survival modeling surfaced several factors significantly associated(P < 1e-16) with increase in median retention time i) Clinician referral(increase of 40 days), ii) Effect of compensation (22 days), iii) Clinical conditions of interest to the study (7 days) and iv) Older adults(4 days). Additionally, four distinct patterns of daily app usage behavior that were also associated(P < 1e-10) with participant demographics were identified. Most studies were not able to recruit a representative sample, either demographically or regionally. Combined together these findings can help inform recruitment and retention strategies to enable equitable participation of populations in future digital health research.