Hostname: page-component-59f8fd8595-tmn4r Total loading time: 0 Render date: 2023-03-22T14:06:51.137Z Has data issue: true Feature Flags: { "useRatesEcommerce": false } hasContentIssue true

Improving community participation in clinical and translational research: CTSA Sentinel Network proof of concept study

Published online by Cambridge University Press:  10 March 2020

Deepthi S. Varma*
Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
Alvin H. Strelnick
Division of Community Health, Department of Family and Social Medicine, College of Medicine, Albert Einstein, Montefiore Medical Center, Bronx, NY, USA
Nancy Bennett
Department of Medicine, University of Rochester Medical Center School of Medicine and Dentistry, Rochester, NY, USA
Patricia Piechowski
Michigan Institute for Clinical and Health Research, University of Michigan, Ann Arbor, MI, USA
Sergio Aguilar-Gaxiola
Center for Reducing Health Disparities (CRHD), Clinical Internal Medicine, University of California, Davis School of Medicine, Sacramento, CA, USA
Linda B. Cottler
Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
Address for correspondence: D. S. Varma, PhD, MSW, MPhil, Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, 2004 Mowry Rd., Gainesville, FL32610, USA. Email:
Rights & Permissions[Opens in a new window]



Research participation by members of racial or ethnic minority groups continues to be less than optimum resulting in difficulties to generalization of research findings. Community-engaged research that relies on a community health worker (CHW) model has been found effective in building trust in the community, thereby motivating people to participate in health research. The Sentinel Network study aimed at testing the feasibility of utilizing the CHW model to link community members to appropriate health research studies at each of the research sites.


The study was conducted at six Clinical and Translational Science Award institutions (N = 2371) across the country; 733 (30.9%) of the participants were from the University of Florida, 525 (22.0%) were from Washington University in St. Louis, 421 (17.8%) were from the University of California, Davis, 288 (12.1%) were from the University of Michigan, Ann Arbor, 250 (10.5%) were from Rochester, and 154 (6.5%) from Albert Einstein College of Medicine. Trained CHWs from each of these sites conducted regular community outreach where they administered a Health Needs Assessment, provided medical and social referrals, and linked to eligible research studies at each of those sites. A 30-day follow-up assessment was developed to track utilization of services satisfaction with the services and research study participation.


A large majority of people, especially African Americans, expressed willingness to participate in research studies. The top two health concerns reported by participants were hypertension and diabetes.


Findings on the rate of navigation and enrollment in research from this study indicate the effectiveness of a hybrid CHW service and research model of directly engaging community members to encourage people to participate in research.

Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (, which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
© The Association for Clinical and Translational Science 2020


Participation in research by members of racial or ethnic minority groups and women, older adults, and rural populations continues to be monitored by researchers through ongoing efforts [Reference Cortés1Reference Cottler3]. Underrepresentation of these populations in research has occurred, potentially generating findings which cannot be generalized [Reference Gilmore-Bykovskyi4Reference Link6]. Community-engaged research that relies on a community health worker (CHW) model has been shown to be effective in building trust in the community, thereby motivating people to participate in health research [Reference Krok-Schoen7Reference Brown11].

In 2009, the first phase of the Clinical and Translational Science Award (CTSA) Sentinel Network (SN) was funded, consisting of five collaborating CTSA sites (Washington University in St. Louis (WUSTL), University of California at Davis (UC Davis), University of Michigan, University of Rochester, and Albert Einstein) and two partner community organizations (Community-Campus Partnerships for Health and Patient Advocates in Research). HealthStreet, the community-engaged research initiative of the CTSA founded by Dr. Cottler in 1989, formed the basis on which the SN was planned and implemented. More detailed information regarding the conception of the first phase of SN and its results has been published elsewhere and showed how we assess, in real time, concerns and needs of underrepresented populations in order to give people a voice in research [Reference Cottler3].

The SN Phase I found that historically underrepresented community members were more interested in taking part in health research and oftentimes were willing to participate in a research study for less compensation than their counterparts [Reference Cottler3,Reference Gill12,Reference Ejiogu13]. Based on these findings, a Phase II was implemented to (a) develop procedures to include informed consent to link community members to appropriate health research studies in sites that had not previously been doing so, (b) increase the thoroughness of community health evaluations and research, (c) detect emerging community issues regarding participation of underrepresented populations in health research, (d) build capacity for CHWs and expand their role in research, and (e) build connections with the community. This paper, a proof of concept, reports on the expanded SN Phase II, which not only assessed the health needs and concerns of community members and connected them to relevant medical and social services and health research opportunities but also followed up participants for 30 days to assess research enrollment status, service utilization, and satisfaction with services referred.

Materials and Methods

The SN built the capacity of CHWs to engage individuals within their own communities by discussing their health concerns and priorities, past research experiences, and current expectations and linked them to potential research participation opportunities. The first phase of SN included five CTSA institutions across the country: Washington University in St. Louis, St. Louis (WUSTL); University of Rochester, Rochester, New York (Rochester); University of Michigan, Ann Arbor (U-M); Albert Einstein College of Medicine, Bronx, New York; and UC Davis. In 2012, a Phase II of SN was implemented and added the University of Florida (UF), where the Principal Investigator (Dr. Cottler) relocated. SN sites were geographically and demographically diverse. By the conclusion of Phase II recruitment, the SN had assessed over 8000 community members across the country, utilizing the CHW model to assess community members’ actual medical conditions and concerns in real time and to link them to social and medical services and opportunities to participate in health research within their own communities.


The Health Intake assessment for SN Phase II was scaled up from that of the SN Phase I assessment [Reference Cottler3]; it assessed head-to-toe health conditions over the lifetime (e.g., arthritis, asthma, cancer, depression, diabetes, muscle and bone, heart conditions, blood pressure, and kidney diseases). During the course of the intake, CHWs asked each respondent for at least two means of contact, such as a cell/home/business phone number, email address, and a physical mailing address. The intake was vigorously pilot tested by all sites before it was used. All baseline assessments were done in a face-to-face interview by the CHW.

A 30-day follow-up assessment by phone was developed to track utilization of services to which each participant was referred during the initial Health Intake assessment. In addition, participants were asked if they sought any medical or social services on their own within the past 30 days. If the respondent reported obtaining a service referral or self-referral, satisfaction with the service obtained was assessed. Conversely, if a respondent reported not obtaining a service, the reason for such was elicited. Lastly, participants who were linked to potential research opportunities were asked if they were contacted by the corresponding research study coordinator and whether they were enrolled into the study.

CHW Recruitment and Training

CHWs underwent rigorous training for all assessments and 30-day follow-up protocols. Biweekly meetings were held with all participating sites to monitor data collection procedures and ensure fidelity to protocols. CHWs approached community members off-campus (i.e., “in the community”) at barbershops, laundromats, bus stops, community agencies, churches, parks, health care facilities, and other sites. Each site obtained institutional review board approval from their corresponding institution. After clearly describing the study, CHWs obtained the informed consent, then conducted the Health Intake assessment, and where appropriate, made referrals.

Data Management and Analysis

All Health Intakes were scanned and sent to WUSTL (lead site but later to UF) in an encrypted, password-protected format. Data were entered using REDCap (Research Electronic Data Capture) software [Reference Harris14]. Data Coordinators at participating sites collaborated with WUSTL to obtain a security certificate and REDCap user account by which to access and view the data. Data entry and quality control were performed on a regular basis to ensure protocol fidelity.

Data were analyzed for site and race/ethnicity using SAS version 9.2 software (SAS Institute, Cary, NC, USA). Means and standard deviations were calculated for continuous variables, and binomial proportions reported with corresponding confidence intervals for categorical variables.


Demographic Characteristics

Table 1 shows the demographic characteristics of SN Phase II participants by site. Overall, a total of 2371 participants were assessed across the six collaborating sites: 733 (30.9%) of the participants were from UF, 525 (22.0%) were from WUSTL, 421 (17.8%) were from UC Davis, 288 (12.1%) were from U-M, 250 (10.5%) were from Rochester, and 154 (6.5%) from Albert Einstein College of Medicine. The sample in Phase II was ethnically diverse with the majority of respondents reporting Black or African-American race (53.1%), followed by White (25.2%) and Hispanic/Latino ethnicity (14.1%). Frequency of “Other” races, such as Asian (2.1%), American Indian/Alaska native (1.1%), and others (3.9%), was low. Women comprised a majority (54.8%) of the Phase II sample, regardless of site, with the exception of Rochester. The mean age of the sample was 43 years (standard deviation ±14.9); Phase II participants tended to have a high-school diploma (a mean of 12.8 years of education ±2.6), and an average body mass index of 29.1 (±7.1).

Table 1. Demographic characteristics of Sentinel Network phase II participants by site

SD, standard deviation.

Health Concerns of Participants

Shown in Table 2 are the top five health concerns among those with a concern. The top concerns were heart problems, hypertension, and diabetes. Hypertension was among the top health concerns among all but White participants. Cancer was reported by all races as a top health concern except for Asians. Concerns regarding “weight” were reported among the top five health concerns for all. Mental health was the second most mentioned concern among White participants.

Table 2. Top five health concerns of participants by race/ethnicity (among those with a concern)

Health Conditions

Table 3 shows the health conditions that participants reported in the Health Intakes regarding their own health. Diseases and symptoms of the muscles and bones were reported at the highest rate among all five racial and ethnic groups (i.e., “Others” (51.9%), Whites (49.2%), Hispanic/Latinos (48%), and African Americans (44.0%), and Asians (29.2%)). Conditions that were next most relevant were depression (Whites), high blood pressure (African Americans), heart conditions (Hispanics), and arthritis (other race). Asians reported both muscle and bone and heart conditions as their most common condition but at a rate which was considerably lower than the other four groups.).

Table 3. Health conditions reported by Sentinel Network Phase II participants, by race/ethnicity: 2012–2013 (n = 2371)a

a N = 11 participants with missing race/ethnicity information.

Research Experiences and Perceptions

Findings on participant’s research experiences and perceptions (Fig. 1) revealed that a large majority (89.6%–94.0%) expressed considerable interest in participating in a health research study (i.e., “definitely” and “maybe”). While only 17.1% reported participating in health research in Phase I, 23.5% of Phase II participants reported participation. African Americans expressed slightly higher rates of interest in participation (94.0% vs 91% in Phase I) compared to Whites and other races (both 92.4%), and Latinos (91.2%) with Asians having the lowest rate of interest in research participation (89.6%). More Whites (82.3%) agreed to participate in research without any payment compared to all other participants. All participants except for Asians reported high willingness to participate in a study with a blood sample for genetic studies. Participants mentioned mean $87.46 as a fair amount of remuneration to participate in a study that lasted 1.5 hours with a blood sample compared to $73.54 reported by Phase I participants. Across different ethnicities, the highest mean expected compensation was reported by African Americans ($105.88 ± $173.97) and the least by Whites ($48.36 + $74.95).

Fig. 1. Research experience and perceptions reported by Sentinel Network Phase II participants, by race/ethnicity: 2012–2013 (n = 2371)a. aN = 11 participants with missing race/ethnicity information.

When asked about what types of studies they would be willing to participate in, participants reported the highest willingness to participate in a study that only asked about their health (86.7%–93.9%). Having to take medicine was the least likely to hold the interest of the participants with a willingness rate ranging from 27.1% (Asians) to 61.7% (“Other”).

Service Referrals

Newly implemented in Phase II was utilization of medical and social service referrals provided to study participants (Table 4). Overall, 65.3% of all participants were referred by the CHW to at least one social or medical service for a total of about 4000 service referrals made. 61.6% of the participants were contacted for 30 days for a follow-up survey assessing utilization of and satisfaction with services to which they were referred. Follow-up rates range from a high of 75.7% (UF) to a low of 39% (Einstein).

Table 4. Referrals at baseline and 30-day follow-up among total participants (n = 2371 people)

Follow-up at 30 Days

Among 2174 social service referrals given at all sites, 386 (17.8%) were reported as obtained over a 30-day period (Table 5). Of note, among these services obtained, 91.2% were reported as “helpful” to the respondent; 94.8% of participants reported high satisfaction.

Table 5. Rate of referral utilization reported at 30-day follow-up (N = 2174 referral events)

Study Referrals and Enrollment

A total of 1619 participants from all sites were given a research study referral at the baseline (Table 6). We were able to contact 955 (59%) out of 1619 participants for a 30-day follow-up; 355 participants (37.2%) reported that they had been contacted by the study coordinator. Table 6 also shows the rate of enrollment of participants into an eligible study. At the 30-day follow-up, 42.3% of participants contacted by a study coordinator reported that they were enrolled in a research study. Across collaborating sites, UF had the highest rate of study referrals for the participants (64%); U-M had the highest rate of 30-day follow-up (64.1%); and WUSTL reported the highest percent of study coordinator contacts (66.7%) and of study enrollments (50.7%) compared with other sites. Four of five participants enrolled in a study (80.7%) reported satisfaction regarding the navigation and linking process to research studies at their respective universities, but with only one study enrolled at both Einstein and Rochester and none at UC Davis, these rates of satisfaction are limited in their generalizability even to the six Sentinel sites.

Table 6. Rate of research study enrollment by the participants at 30-day follow-up


The goal of the second phase of the SN study was to assess the impact of CHWs offering social service and research study referrals to racial and ethnic group members who are underrepresented in clinical and translational research and to strengthen the ongoing collaboration across the six CTSA sites.

Findings from this study show that a large majority of people, especially African Americans, express willingness to participate in research studies. This highlights a paradigm shift from historical mistrust toward research and researchers toward a more positive attitude [Reference Bardach15Reference Scharff20]. The wide gap seen in this study between those who expressed an interest in participating in a health research study (93%) and those who have actually participated in any type of research study (23.5%), whether clinical- or community-based research, indicates that there are a large number of community members who are willing to participate in research studies but do not get to a study. Many reasons could be cited for this: lack of diversity in staff, ineligible, no studies for their condition, and/ or bias on the part of the coordinator. This is similar to previous findings reported regarding the willingness to participate [Reference Fisher and Kalbaugh21,Reference Durant22]. Moreover, the findings also show that though they are interested in research, the participants clearly distinguish the types of research in which they would be willing to participate. Successful enrollment of 42% of the participants reinforces the previous findings that willingness of community members to participate in research can be translated to actual enrollment by contacting them directly and navigating them to eligible studies [Reference Ghebre23Reference Natale-Pereira25]. The fair compensation mentioned by participants in this study is higher than what most studies currently provide. This shows the expectation of the community members. It also shows the importance of reimbursing community members adequately and appropriately not only to increase research study enrollment and retention but also to improve the community-academic relationships.

The top two health concerns reported by participants – hypertension and diabetes – remained the same in both Phase I and II, highlighting the salience of these conditions in people’s minds as well as the public health significance of screening individuals regularly for these conditions [Reference Cottler and Nagarajan26]. This finding is especially significant since the majority of the participants of this study (53.1%) were Black or African American, and previous studies have consistently indicated a higher prevalence of these two conditions among them compared to Whites and other ethnic groups in the USA [Reference Harman27Reference Flack29]. Further, this also indicates the increased awareness regarding chronic diseases among the public, especially among African Americans.

Over one-third of the participants reported existing health conditions were muscle and bone diseases, heart conditions, arthritis, and mental health conditions such as depression/bipolar disorder. Further, 34% of African Americans reported high blood pressure as the second top health condition followed by heart conditions (32%). As reported in previous studies, smoking continues to be one of the strongest risk factors for noncommunicable diseases among African Americans with 48.7% of the participants reporting smoking a cigarette in the past 30 days [Reference Ezzati and Riboli30,Reference Webb31]. This is much higher than the current cigarette smoking rate of 15.1% among adults in the USA [32].

Findings from this study highlighted the continuing disparity in access to medical care that exists among different race/ethnicity groups. Phase II showed African Americans reporting the lowest proportion (64.3%) having any medical insurance, which is a shift from what we observed in Phase I, where the Hispanic/Latino community had the lowest proportion with medical insurance. Findings from this study also support the previous research on benefits of utilizing the CHW model to improve access to care and research participation [Reference Allen33]. Increased referral rates indicate that with adequate screening, CHWs could facilitate medical and social service referrals to local resources that are easily accessible and affordable for community members. However, the low referral utilization rate shows the various barriers that are personal and systemic. It also highlights the need for additional follow-ups by CHWs, provision of free or low-cost transportation to improve access to services, and reminders to ensure the utilization of the provided referrals to community members. However, it is encouraging to see that those who utilized the provided referrals reported highest level of satisfaction with the services obtained. We acknowledge that the lack of data on the types of barriers to utilization of the referrals provided is one of the limitations of this study.

Limitations and Strengths

This was a cross sectional study and was conducted using a convenience sampling strategy. However, we were able to include culturally and ethnically diverse sample by conducting the study at different sites that offsets the limitations due to convenience sampling. Another important strength of this study is that it proved the feasibility of a new model utilizing CHWs in building academic-community partnerships, thereby increasing the participation of all community members in health research studies.


Building on Phase I of the SN study, we deployed a hybrid model for CHWs building relationships by learning about community members’ health concerns and making both social service and research study referrals. Those referrals were evaluated by a 30-day follow-up assessment of the success of community members receiving those social services and their satisfaction with them. We also assessed the rate they were contacted by research study coordinators and actually enrolled in clinical research studies. One might describe this as a hybrid model of combined social service and research navigation by CHWs. Findings based on the rate of navigation and enrollment in research from this study indicate that the hybrid CHW service and research model of directly engaging community members and encouraging people to participate in research is effective. Phase II of the SN may be considered a “proof of concept” for the hybrid CHW model that better integrates service and research in order to recruit more diverse research volunteers and those underrepresented in our current human research studies.


We acknowledge our team of CHWs from each of the sites.

This work was supported by federal funds from the National Center for Research Resources and the National Center for Advancing Translational Sciences through the CTSA Program (grants NCRR UL1 RR024992-03S2, NCRR 2 UL1 RR024146-06, NCRR UL1RR024986, NCRR UL1RR025750, P60MD00514, NCRR UL1RR024992-03S3, NCRR UL1RR024992-05S1, and NCRR UL1RR029890).


The authors have no conflicts of interest to disclose.


Cortés, YI, et al.Urban-dwelling community members’ views on biomedical research engagement. Qualitative Health Research 2017; 27(1): 130137. doi:10.1177/1049732315627650.CrossRefGoogle ScholarPubMed
Friedman, DB, et al.A qualitative study of recruitment barriers, motivators, and community-based strategies for increasing clinical trials participation among rural and urban populations. American Journal of Health Promotion 2015; 29(5): 332338. doi:10.4278/ajhp.130514-qual-247.CrossRefGoogle ScholarPubMed
Cottler, LB, et al.Nonmedical opioid pain relievers and all-cause mortality: a 27-year follow-up from the epidemiologic catchment area study. American Journal of Public Health 2016; 106(3): 509516. doi:10.2105/AJPH.2015.302961.CrossRefGoogle ScholarPubMed
Gilmore-Bykovskyi, AL, et al.Recruitment and retention of underrepresented populations in Alzheimer’s disease research: a systematic review. Alzheimer’s & dementia (New York, N. Y.) 2019; 5: 751770. doi:10.1016/j.trci.2019.09.018Google ScholarPubMed
Goff, SL, et al.Successful strategies for practice-based recruitment of racial and ethnic minority pregnant women in a randomized controlled trial: the IDEAS for a healthy baby study. Journal of Racial and Ethnic Health Disparities 2016; 3(4): 731737. doi:10.1007/s40615-015-0192-x.CrossRefGoogle Scholar
Link, MW, et al.Race, ethnicity, and linguistic isolation as determinants of participation in public health surveillance surveys. Preventing Chronic Disease 2006; 3(1): A09.Google ScholarPubMed
Krok-Schoen, JL, et al.Involving community health workers in the centers for population health and health disparities research projects: benefits and challenges. Journal of Health Care for the Poor and Underserved 2016; 27(3): 12521266. doi:10.1353/hpu.2016.0145.CrossRefGoogle ScholarPubMed
Kok, MC, et al.Which intervention design factors influence performance of community health workers in low- and middle-income countries? A systematic review. Health Policy Plan 2015; 30(9): 12071227. doi:10.1093/heapol/czu126.CrossRefGoogle ScholarPubMed
Callaghan-Koru, JA, et al.Health workers’ and managers’ perceptions of the integrated community case management program for childhood illness in Malawi: the importance of expanding access to child health services. The American Journal of Tropical Medicine and Hygiene 2012; 87(5 Suppl): 6168. doi:10.4269/ajtmh.2012.11-0665.CrossRefGoogle ScholarPubMed
Alam, K, Tasneem, S, Oliveras, E. Performance of female volunteer community health workers in Dhaka urban slums. Social Science & Medicine 2012; 75(3): 511515. doi:10.1016/j.socscimed.2012.03.039.CrossRefGoogle ScholarPubMed
Brown, LD, et al.Evaluation of healthy fit: a community health worker model to address hispanic health disparities. Preventing Chronic Disease 2018; 15: 170347. doi:10.5888/pcd15.170347.CrossRefGoogle ScholarPubMed
Gill, PS, et al.Under-representation of minority ethnic groups in cardiovascular research: a semi-structured interview study. Family Practice 2012; 30(2): 233241. doi:10.1093/fampra/cms054.CrossRefGoogle ScholarPubMed
Ejiogu, N, et al.Recruitment and retention strategies for minority or poor clinical research participants: lessons from the healthy aging in neighborhoods of diversity across the life span study. Gerontologist 2011; 51(Suppl 1): S33S45. doi:10.1093/geront/gnr027.CrossRefGoogle ScholarPubMed
Harris, PA, et al.Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics 2009; 42(2): 377381. doi:10.1016/j.jbi.2008.08.010.CrossRefGoogle ScholarPubMed
Bardach, SH, et al.Insights from African American older adults on brain health research engagement: “Need to See the Need”. Innovation in Aging 2019; 3(Suppl 1): S433S434.CrossRefGoogle Scholar
Brown, RF, et al.Perceptions of participation in a phase I, II, or III clinical trial among African American patients with cancer: what do refusers say? Journal of Oncology Practice 2013; 9(6): 287293. doi:10.1200/JOP.2013.001039.CrossRefGoogle ScholarPubMed
Corbie-Smith, G, Thomas, SB, George, DM. Distrust, race, and research. Archives of Internal Medicine 2002; 162(21): 24582463. doi:10.1001/archinte.162.21.2458.CrossRefGoogle ScholarPubMed
Gadegbeku, CA, et al.Factors associated with enrollment of African Americans into a clinical trial: results from the African American study of kidney disease and hypertension. Contemporary Clinical Trials 2008; 29(6): 837842. doi:10.1016/j.cct.2008.06.001.CrossRefGoogle ScholarPubMed
Owens, OL, et al.African American men’s and women’s perceptions of clinical trials research: focusing on prostate cancer among a high-risk population in the South. Journal of Health Care for the Poor and Underserved 2013; 24(4): 17841800. doi:10.1353/hpu.2013.0187.CrossRefGoogle ScholarPubMed
Scharff, DP, et al.More than Tuskegee: understanding mistrust about research participation. Journal of Health Care for the Poor and Underserved 2010; 21(3): 879897. doi:10.1353/hpu.0.0323.CrossRefGoogle ScholarPubMed
Fisher, JA, Kalbaugh, CA. Challenging assumptions about minority participation in US clinical research. American Journal of Public Health 2011; 101(12): 22172222. doi:10.2105/AJPH.2011.300279.CrossRefGoogle ScholarPubMed
Durant, RW, et al.Different types of distrust in clinical research among whites and African Americans. Journal of the National Medical Association 2011; 103(2): 123130. doi:10.1016/s0027-9684(15)30261-3.CrossRefGoogle ScholarPubMed
Ghebre, RG, et al.State-of-the-science of patient navigation as a strategy for enhancing minority clinical trial accrual. Cancer 2014; 120(Suppl 7): 11221130. doi:10.1002/cncr.28570.CrossRefGoogle ScholarPubMed
Paskett, ED, Harrop, JP, Wells, KJ. Patient navigation: an update on the state of the science. CA: A Cancer Journal for Clinicians 2011; 61(4): 237249. doi:10.3322/caac.20111.Google ScholarPubMed
Natale-Pereira, A, et al.The role of patient navigators in eliminating health disparities. Cancer 2011; 117(15 Suppl): 35433552. doi:10.1002/cncr.26264.CrossRefGoogle ScholarPubMed
Cottler, LB, Nagarajan, R. Real-time assessment of community health needs and concerns. Science Translational Medicine 2012; 4(119): 119mr2. doi:10.1126/scitranslmed.3003367.CrossRefGoogle ScholarPubMed
Harman, J, et al.Treatment of hypertension among African Americans: the Jackson Heart Study. The Journal of Clinical Hypertension (Greenwich) 2013; 15(6): 367374. doi:10.1111/jch.12088.CrossRefGoogle ScholarPubMed
Selvin, E, et al.Racial differences in glycemic markers: a cross-sectional analysis of community-based data. Annals of Internal Medicine 2011; 154(5): 303309. doi:10.7326/0003-4819-154-5-201103010-00004.CrossRefGoogle ScholarPubMed
Flack, JM, et al.Management of high blood pressure in blacks. Hypertension 2010; 56(5): 780800. doi:10.1161/hypertensionaha.110.152892.CrossRefGoogle ScholarPubMed
Ezzati, M, Riboli, E. Behavioral and dietary risk factors for noncommunicable diseases. New England Journal of Medicine 2013; 369(10): 954964. doi:10.1056/nejmra1203528.CrossRefGoogle ScholarPubMed
Webb, HM, et al.Effects of a culturally specific tobacco cessation intervention among African American Quitline enrollees: a randomized controlled trial. BMC Public Health 2018; 18(1): 123. doi:10.1186/s12889-017-5015-z.CrossRefGoogle Scholar
Centers for Disease Control and Prevention. African Americans and tobacco use [Internet], November 18, 2019 [cited Dec 16, 2019]. ( Scholar
Allen, JK, et al.COACH trial: a randomized controlled trial of nurse practitioner/community health worker cardiovascular disease risk reduction in urban community health centers: rationale and design. Contemporary Clinical Trials 2011; 32(3): 403411. doi:10.1016/j.cct.2011.01.001.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Demographic characteristics of Sentinel Network phase II participants by site

Figure 1

Table 2. Top five health concerns of participants by race/ethnicity (among those with a concern)

Figure 2

Table 3. Health conditions reported by Sentinel Network Phase II participants, by race/ethnicity: 2012–2013 (n = 2371)a

Figure 3

Fig. 1. Research experience and perceptions reported by Sentinel Network Phase II participants, by race/ethnicity: 2012–2013 (n = 2371)a. aN = 11 participants with missing race/ethnicity information.

Figure 4

Table 4. Referrals at baseline and 30-day follow-up among total participants (n = 2371 people)

Figure 5

Table 5. Rate of referral utilization reported at 30-day follow-up (N = 2174 referral events)

Figure 6

Table 6. Rate of research study enrollment by the participants at 30-day follow-up