Newer data platforms offer increased opportunity to share multidimensional health data with research participants, but the preferences of participants for which data to receive and how is evolving. Our objective is to describe the preferences and expectations of participants for the return of individual research results within Project Baseline Health Study (PBHS). The PBHS is an ongoing, multicenter, longitudinal cohort study with data from four initial enrollment sites. PBHS participants are recruited from the general population along with groups enriched for heart disease and cancer disease risk. Cross-sectional data on return of results were collected in 2017–2018 from an (1) in-person enrollment survey (n = 1,890), (2) benchmark online survey (n = 1,059), and (3) participant interviews (n = 21). The main outcomes included (1) preferences for type of information to be added next to returned results, (2) participant plans for sharing returned results with a non-study clinician, and (3) choice to opt-out of receiving genetic results. Results were compared by sociodemographic characteristics. Enrollment and benchmark survey respondents were 57.1% and 53.5% female, and 60.0% and 66.2% white, respectively. Participants preferred the following data types be added to returned results in the future: genetics (29.9%), heart imaging, (16.4%), study watch (15.8%), and microbiome (13.3%). Older adults (OR 0.60, 95% CI: 0.41–0.87) were less likely to want their genetic results returned next. Forty percent of participants reported that they would not share all returned results with their non–study clinicians. Black (OR 0.64, 95% CI 0.43–0.95) and Asian (OR 0.47, 95% CI 0.30–0.73) participants were less likely, and older participants more likely (OR 1.45–1.61), to plan to share all results with their clinician than their counterparts. At enrollment, 5.8% of participants opted out of receiving their genetics results. The study showed that substantial heterogeneity existed in participant’s preferences and expectations for return of results, and variations were related to sociodemographic characteristics.
Citation: Sayeed S, Califf R, Green R, Wong C, Mahaffey K, Gambhir SS, et al. (2021) Return of individual research results: What do participants prefer and expect? PLoS ONE 16(7): e0254153. https://doi.org/10.1371/journal.pone.0254153
Editor: Helena Kuivaniemi, Stellenbosch University Faculty of Medicine and Health Sciences, SOUTH AFRICA
Received: August 4, 2020; Accepted: June 21, 2021; Published: July 29, 2021
Copyright: © 2021 Sayeed et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: Verily sponsored the Project Baseline Health Study and has been involved in the study design and execution. The corresponding author had final approval for the manuscript. Robert Califf, Celeste Wong, Jessica Mega, Kaylyn Frazier, and Scarlet Shore are employed, have equity, and/or have a leadership role at Verily Life Sciences, which funded the Project Baseline Health Study and was involved in the study design and execution. Bray Patrick-Lake is employed by Evidation Health, which had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: R.C. and J.H. are employed or have a leadership role at Google Health. R.C. is also a board member, Cytokinetics. R.G. has received compensation for advising the following companies: AIA, Grail, Humanity, Kneed Media, Plumcare, UnitedHealth, Verily, VibrentHealth, Wamberg; and is co-founder of Genome Medical, Inc, a technology and services company providing genetics expertise to patients, providers, employers and care systems. M.P. receives research funding from Celgene, Abbvie, United Therapeutics, Varian, Genzyme, Novartis, Verily Inc., and consults or receives honoraria from Astra Zeneca, Bristol Myer Squibb. A.H. receives research funding from American Regent, AstraZeneca, Merck, Novartis, Verily Inc., and consults for Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientific, Merck, Novartis, and Sanofi. S.S.G. was a consultant or received funding from several companies that work in the healthcare space although none of these companies are directly involved in the current work. K.M.’s financial disclosure can be viewed at https://urldefense.com/v3/__ http://med.stanford.edu/profiles/kenneth-mahaffey__;!!OToaGQ!4SYwO-_7EFsgVgGjoEtGV5OZTQgzazIn4bBVxpao-jf7LFD1GAVa-7ce_-V04z69C1Nj$. J.M., D.M., and S. Shore are employed, have a leadership role, or receive equity from Verily Inc. J.M. is also a Board Member, Danaher. These affiliations do not alter our adherence to PLOS ONE policies on sharing data and materials.
The availability of broad health data generated through research, electronic health records, biobanks, and wearable devices has changed the health landscape in important ways [1,2]. By transforming our understanding of the constituents of health, these endeavors have paved the way for harnessing big data and developing a richer understanding of the transition from health to disease [3,4]. Central to these initiatives are longitudinal studies that allow for the collection and analysis of large volumes of data from participants. In addition to the logistical challenges inherent to such studies, their success is dependent upon the willingness of participants to engage in research, follow up for a predefined period, and derive a sense of value from their participation . The motives for participant engagement, such as altruism or the desire to gain actionable health information, have emerged as important issues requiring characterization .
In recent years, calls for a more participant-centric research approach have included support for the belief that participants have a right to their health data and that investigators have an obligation to return research results to participants [7–10]. Prior work on returning single data types, such as imaging and genetic data, has shown promising but mixed results, with the opportunity to create value intermixed with cautionary notes of potential harms [11–15]. However, there remains a lack of clarity regarding the optimal mechanics of returning research results, with imaging and genetics paving the way while other data types remain in more nascent stages. Nevertheless, the enthusiasm for returning research results continues to grow, while several questions remain unanswered surrounding what to return, when, and how [16–18].
The Project Baseline Health Study (PBHS) is a multicenter, prospective, longitudinal cohort study that aims to characterize the multidimensional nature of health and disease by collecting and analyzing deep and diverse types of participant data, including imaging, digital device, and molecular data (projectbaseline.com/). The return of multiple types of individual research results has been an important value within PBHS since its inception in 2017. The objective of the current study is to describe the baseline preferences and expectations of participants on the return of individual research results within the PBHS. As one of the first studies to return multiple domains of participant data to several thousand participants, these findings can inform efforts to return individual research results in a way that creates value for participation.
Project baseline health study design
The PBHS is an ongoing, prospective, longitudinal cohort study across multiple sites; the initial sites were Stanford, Duke (two sites, one in Durham [Duke-Durham] and one in Kannapolis [Duke-Kannapolis]), and the California Health and Longevity Institute (CHLI) in the United States. The PBHS is a research partnership between Verily Life Sciences, Google, and the participating sites. The study was approved by the Western Institutional Review Board (WIRB) and local IRBs as required, and participants signed a consent form in order to participate in the study. The WIRB was the IRB for the study overall.
Research data collected from participants includes, but is not limited to, clinical and demographic characteristics, genetics, molecular, biochemical, imaging, behavioral, psychological, and physiological (e.g., a sleep sensor and study watch) data. Potential participants are identified through advertising, care provider recommendation, or community outreach activities. The goal is to recruit a population similar to the U.S. general census (standard cohort) with certain subcohorts enriched for the following disease risk areas: breast/ovarian cancer, lung cancer, and atherosclerotic cardiovascular disease. These enriched groups have an approximately 60% higher relative risk of disease compared to participants of the same age and sex, and were selected for enrichment because these are the leading causes of death in the U.S. and globally . Participants have a two-day enrollment visit followed by annual visits for at least four years.
At enrollment, participants review and sign a consent form that indicates that participants will receive results from certain tests conducted as part of the PBHS. Participants are notified that the PBHS is a research study and not clinical care, and that it is not possible to fully opt-out of receiving some returned results. The consent form indicates that participants will have the option to decide whether they would like to receive genetic results. The return of research results policies and procedures were informed by a PBHS Return of Results Committee, which comprised clinicians, researchers, and participant advocates across the participating sites and external groups.
Data for the current study were collected from three sources: (1) enrollment in-person survey, (2) benchmark online survey, and (3) participant interviews. The enrollment in-person survey was administered during the participant’s first two-day visit. Data were collected by trained study staff for all participants enrolled between 3/30/17 and 11/30/18 on a case report form. The benchmark online survey was made available to participants one to 11 months post-enrollment through a digital app or website; data collected from 3/29/18 to 11/30/18 were included in this analysis. During the period between these two surveys, most participants received traditional clinical lab results (e.g., complete blood count) from the study, and some participants received results from imaging and onsite testing that were deemed to be critical or time sensitive (e.g., stress echocardiography results suggesting ischemia, or chest x-ray with large pulmonary nodule). Semi-structured interviews were conducted from 10/20/17 to 12/7/17 among a convenience sample of participants across sites before participants received any results. These interviews were conducted by the same study team member for approximately one hour with each study participant, and the interviews were later transcribed and analyzed independently by two other study team members.
We examined three main outcomes: (1) preferences for type of result to be added next to the portfolio of returned results (benchmark survey), (2) participant plans for sharing returned results with a non-study clinician (benchmark survey), (3) choice to opt-out of receiving genetic results (enrollment survey). The survey items for the main outcomes were as follows: (1) Which of the following results would you be most interested in getting back next? (response options: genetics, microbiome, vital signs, physical assessment, cognitive assessments, heart imaging, eye imaging, sleep sensor data, study watch activity data), (2) Does the participant wish to opt out of genetic return of results? (response options: Yes or No), and (3) Which results from your site visits would you be likely to share with a doctor or nurse if you got them back? (response options: all results, results I do not understand, abnormal results, results my doctor or nurse is interested in having, results that are relevant for an existing health condition, I do not plan to share results with a doctor or nurse, I do not have access to a doctor or nurse).
Other outcomes in the benchmark survey included participant preferences regarding how results should be returned (i.e., phone call, email, mail or text), the benefits anticipated from receiving results (i.e., have ownership of my data, improve my health, identify my risks for disease, learn new or interesting things about my health, others, and I do not want my results or do not care about these benefits), and how participants feel about receiving results (i.e., excited to learn more about my health, nervous about the possibility of receiving an abnormal results, indifferent about getting my results backs, curious about the results, other, and none). All survey items are included in the Supplement.
The responses to all survey questions were mutually exclusive (i.e., participants could only select one answer) aside from the outcome question on sharing results, which allowed multiple answer selections.
The semi-structured interviews included questions on expectations and preferences for the return of research results, including their expectations on what they would receive and how it would be returned.
Descriptive statistics are presented for survey responses, stratified by sociodemographic and clinical covariates: sex, age, study site, cohort (enriched or standard), self-reported race (white, black, Asian, or other) and ethnicity (Hispanic or non-Hispanic), income, and education level. For the three main outcomes, multivariable logistic regression models adjusted for these a priori selected sociodemographic and clinical covariates, based on the researcher’s knowledge and prior literature, are presented as odds ratios with 95% confidence intervals [7–15]. All quantitative analyses were conducted on Python (v2.7.1); a nominal p-value (i.e., unadjusted for multiple comparisons) of <0.05 was considered statistically significant.
Transcribed interview data were analyzed using an inductive thematic analysis approach . Two authors (Sayeed, Wong) independently examined each transcript to identify and categorize relevant themes according to their frequency of appearance in the transcripts. The codebook was modified through an iterative process to account for newly emerging and unanticipated themes, consolidate themes, and revise code definitions. Content identified from the transcripts was sorted into different content sheets by themes and subthemes using Google Sheets, and coding disagreements were resolved via consensus. Illustrative quotes are presented to complement the quantitative results. Given the exploratory nature of this study, we did not apply adjustment for multiple comparisons.
The baseline enrollment survey included 1,890 participants, representing all those enrolled in the study at the time of analysis. The majority were female (57.1%), white (60.0%), and reported a yearly income over $50,000 (Table 1). Approximately one quarter (24.5%) had attended college and 26.2% had an advanced degree. Similar distributions were seen in the benchmark survey (N = 1,059, response rate 56.0%). In the subset who were interviewed (N = 21), 76% were white, 62% were advanced degree holders, and 52% were men. The overall study participants were similar to the general U.S. population with the exceptions of higher income and education distributions (Table 1).
Return of results preferences
When selecting among options of data types that participants preferred to receive after having received initial medical testing results, genetics (29.9%), heart imaging (16.4%), study watch (15.8%), and microbiome (13.3%) were the most common selections (Table 2). Participants over 60 years old (OR 0.60, 95% CI: 0.41–0.87) were less likely to want their genetic results returned next, while Hispanic participants (OR 1.55, 95% CI:1.01–2.39) were more likely than white participants to prefer their genetic data. Preferences differed by study site: participants at the Duke-Kannapolis site were more likely to want their study watch data next, while Stanford site participants had a strong preference for microbiome data compared to other sites. The majority of participants indicated that they would prefer to receive their results via phone (55.6%), followed by email (27.4%), text (13.9%), and mail (2.1%).
Return of results expectations
When asked to describe how they felt about the possibility of receiving results back from their site visits, 54.9% of study participants said they were “excited to learn more about [their] health,” and 36.4% said they were “curious about the results.” Among survey respondents, 7.4% said they were “nervous” about receiving their results.
The most commonly selected expected benefits of receiving results were: “learning new things about my health” (72.5%), “improving my health” (72.0%), and “identifying my risks for disease” (70.1%). Fewer participants anticipated the benefit of having ownership of their data (38.1%).
With regard to the structured interview results (N = 21), while some participants desired and expected to receive all data related to their health returned to them, including in raw form, others expected only results that were actionable (Table 3). Other key themes from the structured interviews were expectations for results to be presented in a way that made them actionable and empowered participants to change their behavior. Participants also expressed that a motivator for their study participation was the desire to be able to track their health data, for example: “Since it sounds like most of the tests will be repeated every year, it would be interesting to see if there’s any changes, or progression year-over-year.”
Sharing returned results
In the benchmark survey (n = 1059), 40% of participants (n = 426) reported not wanting to share all returned results with their own (i.e., non-study) clinicians (Table 4). Black (OR 0.64, 95% CI:0.43–0.95) and Asian (OR 0.47, 95% CI:0.30–0.73) participants were less likely to want to share all their results when compared to white participants. Compared with younger participants 18–39 years old, those in the 40–59 years (OR 1.59, 95% CI:1.16–2.17) and over 60 years (OR 1.45, 95% CI: 1.03–2.04) age groups were more likely to report wanting to share all their results.
Of the 426 participants not wanting to share all results, 27.4% said they would share abnormal results, 19.8% said they would share results relevant to existing medical conditions, and 15.9% would share results they do not understand (Table 4). Compared to participants with advanced degrees, those with a high school diploma or less were less likely to report wanting to share abnormal results (OR 0.24, 95% CI: 0.08–0.69). Younger participants were more likely to report wanting to share results they did not understand than their older counterparts. Differences were noted by study site; participants at Duke-Kannapolis were more likely to report wanting to share all results and less likely to share abnormal results.
Interviewed participants stated that they did not expect clinical recommendations with their returned results, though they did express a desire to see their data benchmarked against normative data to inform whether they should see their own non-study clinician: “I expected to see the data with norms. Then if I saw something that was outside of the norm, I could decide to follow up with my medical practitioner. I wasn’t looking for any sort of recommendations, unless there was something that was egregiously wrong” (Table 3).
At enrollment, 5.5% of participants opted-out of receiving their genetics results (Table 5). Participants at the Duke-Durham (OR 8.62, 95% CI:4.44–16.73) and CHLI (OR 2.29, 95% CI: 1.06–4.96) sites or those with a high school education or less (OR 3.37, 95% CI:1.44–7.91) were more likely to opt out of receiving their genetic results.
In a diverse sample of participants within the Project Baseline Health Study across four U.S. sites, individuals were excited and curious about receiving individual research results across various types of data streams. The majority of participants elected to receive their genetics results, while perhaps surprisingly, over a third said that they would not share all their results with their own clinicians. Participant expectations were heterogeneous, with younger participants preferring to receive their genetic results returned next while other participant preferences differed by sociodemographic characteristics.
Most participants in the PBHS were excited and curious to learn more about their health through the return of research results, mirroring previously described eagerness and curiosity about returned research results [21–23]. A growing literature recognizes that returning results serves a two-fold purpose: participants’ enthusiasm for returned results can help maintain their engagement for meeting the scientific goals of a study, while researchers can fulfill the increasingly accepted ethical obligation to share participants’ personal health data with them. Though the processes for returning individual results are in nascent stages of development, the scientific community has begun convening groups to outline recommendations and frameworks to guide the field, such as the proposed criteria of validity and actionability for deciding what to return [24,25]. Our qualitative results support the need for continued development of processes to return research results and highlights the importance of asking participants about their preferences and expectations early in the study protocol. Determining what is actionable and how to share data to facilitate appropriate action will require further work, especially when considering non-standard of care research tests for which there is no precedent consensus .
While participants were enthusiastic about receiving research results, 40% of survey respondents reported not planning to share all of their results with their non-study clinicians. Participants in the PBHS are voluntarily consenting to share their personal health data for research purposes, so their choice to not share all of their returned data with clinicians was surprising. Lower enthusiasm for sharing results with clinicians among black, Asian, and lower income participants may reflect differing levels of trust in healthcare and research, and suggests a need to monitor the impact of returning results on long-standing and continued health inequities, many of which have been exacerbated during the COVID-19 pandemic [26,27]. Moreover, prior work has hinted at mixed readiness among clinicians to receive research results; concerns include inadequate physician time for processing large quantities of research information [28–31]. Some participants stated they would only share abnormal results or results relevant to existing medical conditions, which could reduce the burden placed upon clinician time. Other strategies include co-designing processes with clinicians to understand how to incorporate returned research results into clinical workflows, such as within electronic medical records or by utilizing other team members (e.g., genetics counselors) [32,33].
The diversity of participant preferences and expectations will be a key challenge to returning research results in large clinical studies . Participants in this survey differed not only in how much data they wanted returned, but also in the types of data they wanted to access. The heterogeneity of participant expectations on receiving results is similar to the diversity of patient preferences seen in clinical care, including differences seen by race and ethnicity [35–37]. Technology and data science advances can support individualizing how data are returned to participants, such as allowing participants to toggle result reports on and off or to select preferences on how their results are returned [11,38].
While participant preferences should be considered, there may be situations in which not returning results would be ethically inappropriate (e.g., a life-threatening finding with treatment options) where the duty to warn may come into conflict with participant wishes. The line is poorly defined between research participant autonomy to receive what they deem desirable, and the responsibility of researchers to highlight for participants the implications of clinically important results. Delineating what should be responsibly returned is even more difficult for results derived from non-standard data types, such as wearable device data or metabolomic results, where the limits of normalcy, or even the evidence for any sort of benefit, are ill-defined. Additionally, characterizing the ethical issues and complexities surrounding sharing potentially life-threatening results with relatives will also require further work . In all cases, the importance of clearly explaining to participants the implications of choosing whether to receive individual research results cannot be overstated.
The results of this study should be interpreted in the context of several limitations. While the PBHS sample for this analysis included a diverse group of participants from multiple U.S. sites, the preferences and expectations of participants who chose to join this study may not be representative of research participants in different studies or other segments of the general population. While our study population was well matched to the overall U.S. population in most regards, differences were seen in income and educational levels, particularly among the interviewed subsample with higher proportions of white and highly educated individuals. Examining preferences by participant characteristics, including race and ethnicity, is critical given the historic and persistent racial and ethnic disparities in the quality and access to health care in the United States . Despite these notable differences, interviewees in-depth insights provide richness to the quantitative results. Finally, the preferences and expectations described in this study were collected before participants had received results in most cases; participants’ perspectives and planned actions, such as sharing results with their clinicians, may change as results are returned in the study.
The novelty of the PBHS includes the commitment to asking participants directly what research results they would like to see returned and returning individual research results as a core element of the research endeavor. These early findings on the participants’ preferences and expectations for receiving research results will help the PBHS investigators refine the process. These data may also inform the broader research community in discussions about policies and practices that will promote a culture of partnership between researchers and study participants. The need for such partnerships will be accelerated as learning health systems align science, data, and clinical care , and biobanks accumulate and test a wider array of samples .
In the midst of growing rhetoric to free data, the diversity of participant perspectives and the nascent stage of returning research results at scale underscores the challenges ahead. These findings among a national cohort of participants in the PBHS provide an empirical basis for how research data can and should be returned in ways that may add impact and value to healthcare and research participation. While general trends in preferences exist as a function of age, race, ethnicity, sex, and geography, an important realization is that there is no substitute for asking people about their preferences.
S1 File. Return of individual research results and data dictionary.
Baseline health study team
American Society of Clinical Oncology, Alexandria, VA, USA: Richard L. Schilsky. Duke University, School of Medicine, Durham, NC, USA: Jennifer Allen, MaryAnn Anderson, Kevin Anstrom, Lucus Araujo, Kristine Arges, Kaveh Ardalan, Bridget Baldwin, Suresh Balu, Mustafa R. Bashir, Manju Bhapkar, Robert Bigelow, Tanya Black, Rosalia Blanco, Gerald Bloomfield, Durga Borkar, Leah Bouk, Ebony Boulware, Nikki Brugnoni, Erin Campbell, Paul Campbell, Larry Carin, Tammy Jo Cassella, Tina Cates, Ranee Chatterjee Montgomery, Victoria Christian, John Choong, Michael Cohen-Wolkowiez, Elizabeth Cook, Scott Cousins, Ashley Crawford, Nisha Datta, Melissa Daubert, James Davis, Jillian Dirkes, Isabelle Doan, Marie Dockery, P. Murali Doraiswamy, Pamela S. Douglas, Shelly Duckworth, Ashley Dunham, Gary Dunn, Ryan Ebersohl, Julie Eckstrand, Vivienne Fang, April Flora, Emily Ford, Lucia Foster, Elizabeth Fraulo, John French, Geoffrey S. Ginsburg, Cindy Green, Latoya Greene, Jeffrey Guptill, Donna Hamel, Jennifer Hamill, Chris Harrington, Rob Harrison, Lauren Hedges, Brooke Heidenfelder, Adrian F. Hernandez, Cindy Heydary, Tim Hicks, Lina Hight, Deborah Hopkins, Erich S. Huang, Grace Huh, Jillian Hurst, Kelly Inman, Gemini Janas, Glenn Jaffee, Janace Johnson, Tiffanie Keaton, Michel Khouri, Daniel King, Jennifer Korzekwinski, Lynne H. Koweek, Anthony Kuo, Lydia Kwee, Dawn Landis, Rachele Lipsky, Desiree Lopez, Carolyn Lowry, Kelly Marcom, Keith Marsolo, Paige McAdams, Shannon McCall, Robert McGarrah, John McGugan, Dani Mee, Sabrena Mervin-Blake, Prithu Mettu, Mathias Meyer, Justin Meyers, Calire N. Miller, Rebecca Moen, Lawrence H. Muhlbaier, Michael Murphy, Ben Neely, L. Kristin Newby, Jayne Nicoldson, Hoang Nguyen, Maggie Nguyen, Lori O’Brien, Sumru Onal, Jeremey O’Quinn, David Page, Neha J. Pagidipati, Kishan Parikh, Sarah R. Palmer, Bray Patrick-Lake, Brenda Pattison, Michael Pencina, Eric D. Peterson, Jon Piccini, Terry Poole, Tom Povsic, Alicia Provencher, Dawn Rabineau, Annette Rich, Susan Rimmer, Fides Schwartz, Angela Serafin, Nishant Shah, Svati Shah, Kelly Shields, Steven Shipes, Peter Shrader, Jon Stiber, Lynn Sutton, Geeta Swamy, Betsy Thomas, Sandra Torres, Debara Tucci, Anthony Twisdale, Brooke Walker, Susan A. Whitney, Robin Williamson, Lauren Wilverding, Charlene A. Wong, Lisa Wruck. Ellen Young Gemini Group, USA: Jane Perlmutter. Health Collaboratory and Cancer 101, New York, NY, USA: Sarah Krug. Rare Dots, Inc., USA: S. Whitney Bowman-Zatzkin. Society of Participatory Medicine, USA: Sarah Krug. Stanford University, School of Medicine, Stanford, CA, USA: Themistocles Assimes, Vikram Bajaj, Maxwell Cheong, Millie Das, Manisha Desai, Alice C. Fan, Dominik Fleischmann, Sanjiv S. Gambhir, Garry Gold, Francois Haddad, David Hong, Curtis Langlotz, Yaping J. Liao, Rong Lu, Kenneth W. Mahaffey, David Maron, Rebecca McCue, Rajan Munshi, Fatima Rodriguez, Sumana Shashidhar, George Sledge, Susie Spielman, Ryan Spitler, Sue Swope, Donna Williams. University of Florida, College of Medicine, Gainesville, FL, USA: Carl J Pepine. University of Missouri, Children’s Mercy Hospital, Kansas City, MO, USA: John D Lantos. University of Texas, Dell Medical School, Austin, TX, USA: Michael Pignone. University of Washington, Department of Biostatistics, Seattle, WA, USA: Patrick Heagerty. Vanderbilt University, School of Medicine, Nashville, TN, USA: Laura Beskow, Gordon Bernard. Verily Inc., South San Francisco, CA, USA: Kelley Abad, Giulia Angi, Robert M. Califf, Lawrence Deang, Joy Huynh, Manway Liu, Cherry Mao, Michael Magdaleno, William J. Marks, Jr., Jessica Mega, David Miller, Nicole Ong, Darshita Patel, Vanessa Ridaura, Scarlet Shore, Sarah Short, Michelle Tran, Veronica Vu, Celeste Wong. Harvard University, School of Medicine, Boston, MA, USA: Robert C. Green. Google Inc., Mountain View, CA, USA: John Hernandez. California Health and Longevity Institute, Westlake Village, CA, USA: Jolene Benge, Gislia Negrete, Gelsey Sierra, Terry Schaack
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