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. 2022 Apr 26;63(6):1067–1077. doi: 10.1093/geront/gnac060

Assessing Equitable Inclusion of Underrepresented Older Adults in Alzheimer’s Disease, Related Cognitive Disorders, and Aging-Related Research: A Scoping Review

Nisha Godbole 1, Simona C Kwon 2, Jeannette M Beasley 3,4, Timothy Roberts 5, Julie Kranick 6, Jessica Smilowitz 7, Agnes Park 8, Scott E Sherman 9,10,11, Chau Trinh-Shevrin 12, Joshua Chodosh 13,14,15,✉
Editor: Patricia C Heyn
PMCID: PMC10353042  PMID: 35472166

Abstract

Background and Objectives

The rapidly aging and diversifying U.S. population is challenged by increases in prevalence of Alzheimer’s disease (AD) and aging-related disorders. We conducted a scoping review to assess equitable inclusion of diverse older adult populations in aging research focused on National Institutes of Health (NIH)-sponsored research.

Research Design and Methods

The scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol. The search was limited to NIH-funded studies focusing on aging, AD, and Alzheimer’s disease-related dementias (ADRD) and included adults aged 55 and older. The priority populations and health disparities put forth by the National Institute on Aging Health Disparities Framework serve as a model for guiding inclusion criteria and for interpreting the representation of these underrepresented groups, including racial-ethnic minorities, socioeconomically disadvantaged, rural populations, groups with disabilities, and lesbian, gay, bisexual, transgender, and queer or questioning (LGBTQ) communities.

Results

Our search identified 1,177 records, of which 436 articles were included in the analysis. Inclusion of individuals with ADRD and mild cognitive impairment, racial-ethnic minorities, rural populations, socioeconomically disadvantaged, groups with disabilities, and LGBTQ communities were poorly specified in most studies. Studies used multiple recruitment methods, conducting studies in community settings (59%) and hospitals/clinics (38%) most frequently. Incentives, convenience factors, and sustained engagement via community-based and care partners were identified as key strategies for improved retention.

Discussion and Implications

This scoping review identified gaps in existing literature and aims for future work, including stronger research focus on, better inclusion of, and improved data collection and reporting of older adults from underrepresented groups.

Keywords: Minority racial and ethnic groups, Research engagement, Underrepresented

Background and Objectives

The proportion of the U.S. population aged 65 and older is projected to increase to 23.4% of the total population by 2060, a substantial jump from the 15.2% in 2016 (Lim, Mohaimin et al., 2020; United States Census Bureau, 2017, 2018). Moreover, racial and ethnic minorities (American Indian/Native Alaskan, Black/African American, Asians, Latino/Hispanic, and Native Hawaiian/Pacific Islander) are the fastest-growing segment of older adults (65 and older), and will make up nearly 40% of all older Americans by 2050 (Federal Interagency Forum on Aging-Related Statistics [FIFAS], 2008; Gelman et al., 2013; Lim, Mohaimin et al., 2020; Ta Park et al., 2021; United States Census Bureau, 2017, 2018). These demographic shifts are accompanied by increasing prevalence of aging-associated diseases, such as Alzheimer’s disease (AD) and Alzheimer’s disease-related dementias (ADRD) as well as cardiovascular disease, diabetes, and cancer (Forsat et al., 2020; National Research Council (US) Panel on a Research Agenda and New Data for an Aging World, 2001). In fact, the population of Americans with AD is projected to increase to 14 million and become increasingly diverse by the year 2050 (Ta Park et al., 2021). As the proportion of adults aged 65 years and older grows, so too will the burden of AD/ADRD and other chronic diseases (Lim, Chong et al., 2021). Health inequities faced by underrepresented groups will be further exacerbated by the higher prevalence of chronic disease and rates of premature death compared with White populations (National Academies of Sciences et al., 2017). A consideration of social determinants of health, such as racial discrimination, is essential. Epidemiological studies indicate that racial and ethnic populations, including Black/African Americans and Latino/Hispanics, have a higher prevalence of dementia than their White counterparts, as well as greater cognitive impairment with accelerated decline in cognitive function (Majoka & Schimming, 2021). Minoritized racial and ethnic status is inextricably linked with other determinants of food insecurity, poor living situation, inequitable health care access, and low socioeconomic status, all of which are also associated with an accelerated decline in cognitive function (Gordon et al., 2020; Majoka & Schimming, 2021).

Racial and ethnic minority communities are burdened by environmental and health factors disproportionate to nonminority groups; however, there are still many gaps in our understanding of these differences (Konkel, 2015). Older adults and racial and ethnic minorities participate in research studies at levels far below their population prevalence (Flores et al., 2021; Gilmore-Bykovskyi et al., 2019; Herrera et al., 2010; Konkel, 2015; Ortega et al., 2019; Ta Park et al., 2021). For example, Black/African Americans and Latino/Hispanics comprise 30% of the U.S. population; however, they only make up 6% of all participants in government-funded clinical trials (Konkel, 2015). Health interventions and engagement strategies used for the general population may not be applicable for racial and ethnic communities as these communities have a greater risk of disease and different barriers to participation due to socioeconomic and cultural factors. Without targeted and tailored outreach and engagement, these groups are underreached despite meeting research eligibility (Eggly et al., 2015; Konkel, 2015). This limitation may lead to biased study findings and scientific errors that overstate beneficial outcomes for particular populations; however, in clinical practice they may not have the same effect for minoritized groups, thereby limiting medical advancements and research innovations to further health care equity (Elliot, 2020; Forsat et al., 2020; Herrera et al., 2010; Kasenda et al., 2014; Konkel, 2015; Vellas et al., 2011). Therefore, substantial demographic shifts and greater burdens underscore the need for inclusive and equitable representation of diverse populations in research to assess the applicability of pertinent therapies, treatments, and prevention programs.

Many studies have identified major barriers to research participation for underrepresented older adults as well as specific strategies that have been utilized to address these barriers (Deane et al., 2020; Forsat et al., 2020; Harawa, 2020; Lacey et al., 2017; Marshall et al., 2020; Portacolone et al., 2020; Robison et al., 2020; Stewart et al., 2020). Study exclusion criteria, such as age cutoffs and presence of comorbid conditions frequently found in older adults, are commonly cited barriers to recruitment of older adults (Elliot, 2020; Forsat et al., 2020). Underrepresented older adults face more specific barriers, including mistrust of researchers and medical staff. This is a commonly cited barrier especially among African American individuals, who cite a history of racism in research stemming from the infamous Tuskegee study (Forsat et al., 2020; Gilmore-Bykovskyi et al., 2019; Portacolone et al., 2020). Asian Americans, among others, may hold negative beliefs about AD/ADRD-related research (Lim, Mohaimin et al., 2020). Socioeconomic barriers, commonly associated with geographic strata, and transportation limitations impair participation of many diverse populations (Forsat et al., 2020; Gilmore et al., 2019).

Engaging community-based partners has been identified as a best practice strategy for recruitment and retention, and specifically to address issues of mistrust among people from underrepresented communities (Ajrouch et al., 2020; Deane et al., 2020; Forsat et al., 2020; Gilmore et al., 2019; Lim, Mohaimin et al., 2020; Marshall et al., 2020; Mitchell et al., 2020; Portacolone et al., 2020; Ta Park et al., 2021). Research recruiters are typically the first point of interaction for those deciding to participate in a research study. Recruiters who are empathetic, explain study procedures and purpose in plain language, and are able to build rapport with participants are found to be more successful in recruiting diverse groups (Forsat et al., 2020; Gilmore-Bykovskyi et al., 2019; Portacolone et al., 2020). Specifically, researchers who are able to speak in a manner with which potential participants are most comfortable or those who are racially and ethnically concordant with participants can improve recruitment and retention among people from underrepresented groups (Ajrouch et al., 2020; Gilmore-Bykovskyi et al., 2019; Portacolone et al., 2020).

The National Institute on Aging (NIA) Health Disparities Research Framework highlights priority population groups and health disparities, serving as a conceptual model to assess the inclusion of minority groups in research (Hill et al., 2015). To the best of our knowledge, a limited number of studies have used the NIA Health Disparities Research Framework to assess the extant literature on the involvement of underrepresented older adults in aging and AD/ADRD research. The framework’s lifecourse perspective also guides indicators and outcome measures that were interpreted to assess the scope of population-level health disparities in the older adult population (Hill et al., 2015). Our work aims to apply this framework in interpreting the results of a scoping review of NIH-sponsored research to review the quality and quantity of inclusion of underrepresented older adults in AD/ADRD and aging research and summarize recruitment and retention strategies used to achieve inclusion. This scoping review is part of a larger NIA-funded effort to address recruitment and retention of older adults from underrepresented groups in NIH studies focused on aging, with a particular focus on AD/ADRD. The objectives of this review are to summarize what is currently known about inclusion and representation of underrepresented groups, identify gaps that remain in NIH-sponsored research, and to inform strategies to achieve equitable inclusion in AD/ADRD and aging research.

Research Design and Methods

Methodological and Conceptual Design

To examine whether underrepresented older adult populations in AD/ADRD and aging research are evolving with current demographic changes, we determined that a scoping review was a preferable methodological design compared with a systematic review. This scoping review follows the methodological framework put forth by Arksey and O’Malley (2005) and Heyn (2019). Indications for a scoping review, which are consistent with the goals of this paper, are to identify gaps in knowledge and literature and assess the strengths and weaknesses in representation, recruitment, and retention of diverse older adults. Scoping reviews, unlike systematic reviews, do not critically appraise or answer a specific question, but instead serve to provide an overview of existing evidence in order to inform future study goals (Arksey & O’Malley, 2005; Heyn et al., 2019; Munn et al., 2018).

Inclusion and Exclusion Criteria

The priority populations and health disparities highlighted by the NIA Health Disparities Research Framework guides our inclusion criteria for underrepresented groups. This scoping review includes peer-reviewed, completed or in progress NIH-sponsored, human participants research, published from January 2000 to February 2020. Studies with any percentage of NIH funding were included. Inclusion of studies was indicated by a focus on AD/ADRD or other aging-related topics, inclusion of diverse racial and ethnic populations and groups that are underrepresented in research (defined as limited English proficiency, disability status, low-income, low-health literacy, lesbian, gay, bisexual, transgender, and queer or questioning (LGBTQ), women, and/or rural), mention of recruitment/retention efforts, and participation of individuals aged 55 and older. We also included studies that did not report participants from underrepresented groups in order to further identify gaps and insight into inclusion, representation, and reporting of underrepresented older adults in aging research. Studies were excluded if they were letters to the editor, based outside of the United States, published in languages other than English, included only caregivers, or were classified as secondary data analyses, such as systematic reviews.

Search Strategy

We conducted the literature search in February 2020 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-Scr) Protocol for Scoping Reviews (Tricco et al., 2018). We used PubMed and Ovid Medline (MEDLINE® 2021 Database Guide. Ovid Database Guide 2021., n.d.) to ensure completeness (see Appendix [Supplementary Material] for complete search syntax).

Review Process

To determine study quality and relevance, we used a two-step screening process supported by Covidence systematic review software, Veritas Health Innovation (Melbourne, Australia). The study team screened titles and abstracts to include NIH-funded, U.S. human studies that employed primary data analyses. Reviewers were trained through a protocol review test of 50 articles to assure high interrater reliability. Two reviewers reviewed each citation for a decision on inclusion; disagreements were resolved by a third party. Two reviewers then reviewed the full text of articles that passed the initial screening; disagreements were again resolved by a third party. Reasons for exclusion of citations at this stage are noted in Figure 1. The data extraction process of selected articles consisted of coding each article’s content for variables of interest using a form developed in REDCap (Harris et al., 2009).

Figure 1.

Figure 1.

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PRISMA flow diagram of study selection and inclusion process.

Outcome measures included both participant characteristics represented in the studies and study characteristics. Participant characteristics included racial and ethnic categories, income status, cognitive state, disability status, gender identity or sexual orientation, and rurality. Study characteristics included study design, study setting, recruitment strategies, and retention strategies. Data collection did not include how cognitive state was determined in each study, but rather its presence or absence of reporting.

Recruitment and Retention

We applied recently published literature from experts in the field on best practices for recruitment and retention to probe for these strategies in studies identified in our scoping review (see Table 1 for related references). This literature serves as a useful guide for ensuring representation of participants from underrepresented groups but is not included among those studies identified in the scoping review.

Table 1.

Summary of Strategies to Address Barriers for Recruitment of Underrepresented Older Adults in Research

Category Barriers or challenges Best practices to address recruitment
Attitudes and perceptions Distrust in research or medical staff (Forsat et al., 2020; Gilmore-Bykovskyi et al., 2021; Mitchell et al., 2020; Portacolone et al., 2020)
Fear of injury, complication, or invasiveness of procedures (Gilmore-Bykovskyi et al., 2021)
Stigma or negative belief associated with topic (Jang et al., 2018; Lim, Mohaimin et al., 2020)		 Include racially and ethnically concordant researchers and recruiters (Gilmore-Bykovskyi et al., 2021; Portacolone et al., 2020)
Recruiters show empathy and work to build trust and rapport with participants (Gilmore-Bykovskyi et al., 2021; Portacolone et al., 2020)
Researchers break down information patiently, clarify participant confusion, and are explicit and transparent about research process (Forsat et al., 2020; Mitchell et al., 2020; Portacolone et al., 2020)
Find community-based partners and liaisons who can be involved with study planning and connect with members of underrepresented populations (Ajrouch et al., 2020; Forsat et al., 2020; Gilmore-Bykovskyi et al., 2021; Lim, Mohaimin et al., 2020; Marshall et al., 2020; Mitchell et al., 2020; Portacolone et al., 2020)
Engage researchers who speak language within target community (Lim, Mohaimin et al., 2020; Ta Park et al., 2021)
Communication and outreach Receiving insufficient information about study procedures and processes (Gilmore-Bykovskyi et al., 2021)
Lack of bilingual researchers or translators (Lim, Mohaimin et al., 2020)
Lack of age-appropriate communication tools (Forsat et al., 2020; Lacey et al., 2017)		 Careful selection of words/languages and semantics (Ajrouch et al., 2020)
Telephone calls and personal mail rather than email or text messaging reminders (Forsat et al., 2020; Lacey et al., 2017)
Use of unique social media platforms used by particular cultural groups (e.g., Kakao Talk used by many Koreans; Ta Park et al., 2021)
Ease of explanations: participants can understand research process and goals (Portacolone et al., 2020)
Outreach and engagement conducted at culturally specific or familiar community spaces such as grocery stores, festivals, cultural centers, and spiritual centers (Ta Park et al., 2021)
Researchers break down information patiently, clarify participant confusion, and are explicit and transparent about research process (Forsat et al., 2020; Mitchell et al., 2020; Portacolone et al., 2020)
Find community-based partners and liaisons who can be involved with study planning and connect with members of underrepresented populations (Ajrouch et al., 2020; Forsat et al., 2020; Gilmore-Bykovskyi et al., 2021; Lim, Mohaimin et al., 2020; Marshall et al., 2020; Mitchell et al., 2020; Portacolone et al., 2020)
Engage researchers who speak language within target community (Lim, Mohaimin et al., 2020; Ta Park et al., 2021)
Cognition and understanding Impaired understanding of consent form (Forsat et al., 2020)
Impaired understanding of study and use of technology due to problems with cognition, vision, and hearing (Lacey et al., 2017)		 Engage with role of caregiver (Brodaty & Green, 2002; Gilmore et al., 2019; Portacolone et al., 2020; Tuijt et al., 2021; Vick et al., 2018; Wolff et al., 2015, 2017
Utilize the Triadic encounter approach (e.g., 1. participant, 2. trusted family member or close friend, and 3. recruiter) for recruitment (Dudley et al., 2015; Wolff & Roter, 2012)
Mobility and access Lack of transportation (Forsat et al., 2020; Gilmore-Bykovskyi et al., 2021)
Socioeconomic status associated with geographic strata (Gilmore-Bykovskyi et al., 2021)
Participant work schedules (Forsat et al., 2020)		 Provision of transportation for participants (Forsat et al., 2020; Gilmore-Bykovskyi et al., 2021)
Locations and timings of events that are convenient for participants (Gilmore-Bykovskyi et al., 2021)
Rotating location of events to address residential socioeconomic variation and communities (Ajrouch et al., 2020)
Study design Arbitrary age limits in protocol (Deane et al., 2020; Forsat et al., 2020)
Deficiency in recruitment procedures (Forsat et al., 2020; Lacey et al., 2017)
Falling short of achieving target recruitment numbers for a particular race/ethnicity or socioeconomic status (Stewart et al., 2020)		 Age range modification based on topic of study (Deane et al., 2020; Forsat et al., 2020)
Test recruitment methods in pilot feasibility studies before implementing on large scale (Stewart et al., 2020)
Opt-out instead of opt-in recruitment approach (Forsat et al., 2020)
Open randomized study instead of blinded randomized study (Deane et al., 2020; Forsat et al., 2020)
Incentive Socioeconomic status and financial barriers (Forsat et al., 2020; Gilmore-Bykovskyi et al., 2021)
Seeing no relevance or benefit of conducting study (Forsat et al., 2020; Gilmore et al., 2019; Portacolone et al., 2020; Ta Park et al., 2021)		 Educational statements about research topic and how participation will help members of their own communities (Forsat et al., 2020; Gilmore-Bykovskyi et al., 2021; Portacolone et al., 2020)
Monetary incentive or provision of payment (Forsat et al., 2020; Gilmore-Bykovskyi et al., 2021)
Utilize existing database of volunteers who may already understand value of research (Deane et al., 2020; Forsat et al., 2020; Jang et al., 2018)
Use of personal stories and narratives and pictures to evoke emotional response (Ta Park et al., 2021)
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Results

Of the 1,177 citations identified with our literature search, 475 were excluded based on title/abstract, and 266 were excluded after full article review for reasons listed in Figure 1. Ultimately, 436 were included in this review. The full bibliography is included in the Appendix (Supplementary Material). The analysis focused on understanding the extent of representation of diverse older adults in research studies funded by the NIH.

Participant Characteristics

The “Racial and Ethnic Categories and Definitions for NIH Diversity and for Other Reporting Purposes” denotes the following standardized NIH framework for reporting racial and ethnic categories: American Indian or Alaska Native, Asian, Black or African American, Hispanic or Latino, Native Hawaiian or Other Pacific Islander, and White (National Institutes of Health [NIH], 2019). However, not all studies consistently use these categories, with some reports limiting their descriptions to “White and Non-White” or “Blacks and Whites.” Racial and ethnic category reporting is notably varied across different medical journals. The data presented here and in Table 2 provide a summary of participant characteristics based on information reported in the publications.

Table 2.

Summary of Participant Characteristics as Reported in Individual Studies (n = 436)

Characteristic Number of studiesa
Minority race
 Blacks/African Americans 273
 Native Hawaiian/Pacific Islanders 28
 American Indians/Alaska Natives 33
 Asians 81
 Not reported 131
Ethnicity
 Latino/Hispanic 159
 Not reported 249
Cognitive state
 Participants with AD/ADRD 62
 Participants with mild cognitive impairment 82
 Participants with AD/ADRD who were 
actively excluded 125
 Cognitive state not reported 245
Socioeconomic status
 Low-income 174
 Income status not reported 233
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Note: AD = Alzheimer’s disease; ADRD = Alzheimer’s disease-related dementias.

aThe number of studies including these characteristics only accounts for what was reported, and may not necessarily reflect inclusion that was not reported by studies.

We found that 131 (30.0%) studies did not specify racial categorization of the study population. Of the 305 (69.9%) studies that did specify racial breakdown, 273 (n = 305, 89.5%) reported representation of Blacks/African Americans, 81 (n = 305, 26.6%) studies reported representation of Asian American participants, 28 (n = 305, 9.2%) studies reported representation of Native Hawaiian/Pacific Islander populations, and 33 (n = 305, 10.8%) studies reported representation of American Indian or Alaska Native populations.

A majority of studies, 249 (57.1%), also did not specify study population ethnicity but 159 (36.5%) represented Latino/Hispanic individuals. Most studies, 233 (53.4%) did not report income status, but low-income individuals were included in 174 (39.9%) studies. Even among studies investigating AD/ADRD topics, most studies, 245 (56.2%) did not specify whether they included individuals with AD/ADRD. Just 62 (14.2%) studies reported including individuals with AD/ADRD and 125 (28.7%) actively excluded individuals with AD/ADRD in the study population. Just under one fifth of the studies (n = 82; 18.8%) included individuals with mild cognitive impairment in the study population. These results are displayed in Table 2.

Our review found very few or no studies that focused on recruiting populations within disparity groups based on urbanity (specifically rural), disability status, and gender or sexual orientation. We specifically examined all studies beginning in 2015 when the NIA first published the NIA Health Disparities Research Framework for addressing these specific health disparities and priority populations. From the subset of studies (n = 105) reviewed since this research framework was published, only two studies reported on minority sexual orientation, no studies reported on alternative gender identities, three studies reported on rural groups, and seven studies reported on disability status.

Study Characteristics

Study design

Of the 436 studies reviewed, cross-sectional studies (n = 137, 31.4%) were most frequent. Randomized control trials (n = 99; 22.7%) were the next most frequent, and cohort (n = 53; 12.2%) and longitudinal (n = 53; 12.2%) studies were third in frequency. An array of other study designs were reported less frequently, and included retrospective and case–control studies.

Study setting

Of the studies included in the review, the study setting was classified as either “community-based” for 257 (59.0%) studies, “hospital-/clinic-based” for 167 (38.3%), or “population-based” for 84 (19.3%), with some studies inclusive of more than one setting.

Recruitment strategies

Expert perspectives on recommended strategies leading to successful recruitment of participants from racial and ethnic minorities were derived from recently published reviews (not included among studies in the scoping review analysis) and are summarized in Table 1. These best practices address barriers concerning participant attitudes and perceptions, communication and outreach, cognition and understanding, mobility and access, study design, and incentives. Some recommended strategies are inclusion of racially and ethnically concordant researchers who can speak the language that desired participants are most comfortable with (Gilmore-Bykovskyi et al., 2019; Lim, Mohaimin et al., 2020; Portacolone et al., 2020; Ta Park et al., 2021), engaging community-based partners for recruitment and retention (Ajrouch et al., 2020; Forsat et al., 2020; Gilmore-Bykovskyi et al., 2019; Lim, Mohaimin et al., 2020; Marshall et al., 2020; Mitchell et al., 2020; Portacolone et al., 2020), and using an empathetic and understanding approach from researchers that allows for open communication with participants (Forsat et al., 2020; Gilmore-Bykovskyi et al., 2019; Mitchell et al., 2020; Portacolone et al., 2020). Engaging with the care partner during the consent process, providing transportation for participants, and adapting study design to appropriately expand inclusion criteria are additionally highlighted recruitment strategies (Ajrouch et al., 2020; Brodaty & Green, 2002; Deane et al., 2020; Forsat et al., 2020; Gilmore et al., 2019; Gilmore-Bykovskyi et al., 2019; Portacolone et al., 2020).

Studies included in this scoping review used multiple recruitment methods, many incorporating the successful strategies noted previously. Almost half of all studies relied on personal interactions in community settings (n = 198; 45.4%). The next most commonly reported strategy was recruiting hospital- and clinic-affiliated patients (n = 192; 44.0%). Social media, including news-based media, television broadcasts, telephone calls, and e-mail, was used in 132 (30.3%) studies. One hundred fourteen (26.1%) studies utilized patient registries or existing databases to recruit participants. Some studies recruited participants via traditional mailing (n = 72; 16.5%) and from religious settings (n = 46; 11.7%). Only five studies explicitly mentioned involvement of care partners in the recruitment process. These results are outlined in Table 3.

Table 3.

Summary of Study Characteristics (n = 436)

Characteristic Number of studiesa (%)
Study design
 Cross-sectional 137 (31.4%)
 Randomized controlled trials 99 (22.7%)
 Cohort studies 53 (12.2%)
 Longitudinal studies 53 (12.2%)
 Qualitative studies 36 (8.3%)
 Other 58 (13.3%)
Study setting
 Community-based 257 (59.0%)
 Hospital-/clinic-based 167 (38.3%)
 Population-basedb 84 (19.3%)
Recruitment strategy
 Community settings 198 (45.4%)
 Hospital- and clinic-affiliated 192 (44.0%)
 Media-based 132 (30.3%)
 Patient registries and existing databases 114 (26.1%)
 Traditional mailing 72 (16.5%)
 Religious settings 46 (11.7%)
Retention strategies
 Incentives 70 (16.1%)
 Participant connection 70 (16.1%)
 Participant convenience factors 50 (11.5%)
 Community involvement 15 (3.4%)
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Note:

aStudies reported multiple strategies, thus the sum of studies reviewed do not sum to the total number of studies reviewed.

bPopulation-based study settings were epidemiological studies in which a defined study population was followed and observed longitudinally to assess exposure and outcome relationships.

Retention strategies

Following successful recruitment, continued engagement with participants is critical for maintaining racial and ethnic minority participant representation. Retention strategies highlighted in prior literature include: maintaining positive relationships between researchers and participants (Forsat et al., 2020); updating participants on study progression and results (Forsat et al., 2020; Gilmore-Bykovskyi et al., 2021; Portacolone et al., 2020); maintaining high contact with participants, care partners and/or caregivers, and community-based partners (Ajrouch et al., 2020; Deane et al., 2020; Forsat et al., 2020; Gilmore-Bykovskyi et al., 2021; Lim, Mohaimin et al., 2020; Marshall et al., 2020; Mitchell et al., 2020; Portacolone et al., 2020); collecting regular feedback from participants (Forsat et al., 2020); continuing to provide translations or translators to complete follow-up questionnaires and tests (Ajrouch et al., 2020); providing advance notification before sending follow-up questionnaires (Forsat et al., 2020); displaying appreciation for participants (Forsat et al., 2020); and continuing provision of payment or monetary incentive (Forsat et al., 2020).

Discussion and Implications

This scoping review sought to characterize the current state of NIH-sponsored research by summarizing the extant literature available on the engagement of older adults from underrepresented groups in aging and AD/ADRD research. To the best of our knowledge, this is the first review of its kind.

This review identified critical gaps in inclusion of participants from underrepresented groups and a lack of detail to better characterize study populations. Our review also highlights the paucity of details on recruitment and retention strategies. Improvements in research reporting are a necessary first step to advance equitable inclusion in research studies and to improve our efforts in recruitment and retention. We sought to identify inclusion of participants from groups specifically identified in the NIA Health Disparities Research Framework––racial and ethnic minorities, cognitively impaired participants and caregivers, disabled populations, rural populations, LGBTQ and alternative gender identity and sexual orientation populations, and diverse socioeconomic classes. The paucity of data on certain underrepresented groups may represent either a deficit in inclusion or representation, a lack of studies focused on these populations, or an absence of reporting.

As noted previously, the NIH outlines specific racial and ethnic category reporting guidelines (NIH, 2019). Several studies in this scoping review reported categories that were not in alignment with these guidelines. In fact, many studies reported dichotomous categories such as “White and Non-White” or “White and Black.” These limited categorizations make it difficult to determine actual representativeness. Native Hawaiian/Pacific Islander, Asian Americans, and American Indian or Alaska Native populations were not well-represented despite being among the fastest-growing groups in the United States (Lim, Chong et al., 2021). Over half of included studies did not specify racial and ethnic characteristics of the study population. Inclusivity cannot be measured or monitored without such characterization and study generalizations are not possible without this information. This scoping review has captured current limitations and the diverse ways in which articles report on racial and ethnic categories, and underscores the need to improve the collection and standardization of reporting.

Moreover, individual studies did not provide sufficient level of detail regarding age, further limiting analysis of results by age category. Most articles noted mean age rather than a breakdown by age category. This hindered our ability to examine which age categories, within the older age group, were represented.

A majority of studies did not specify inclusion/exclusion of participants with AD/ADRD, cognitive state, or the involvement of care partners in the recruitment and retention stages. Where specified, these studies were few in number. Ethical challenges related to managing capacity for participant consent or the need to involve care partners present barriers to participation (Gelman et al., 2013). Likely adding to the challenges of participant recruitment are clinicians’ and researchers’ reported lack of confidence in communicating with people living with dementia (Alzheimer, 2019; Tuijt et al., 2021). In the presence of care partners, patient–provider and patient–
researcher interactions can create complexity in communication strategies; requiring a care partner in studies may create a barrier to participation especially where patients might not require a proxy. However, care partners or proxy informants are relied upon for establishing a diagnosis. Greater involvement of care partners may improve participant comfort, communication (especially with language differences), and can offer a trustworthy party who can relay concerns or questions to researchers (Brodaty & Green, 2002).

A majority of the studies reviewed did not include information on participant income status. Populations of lower socioeconomic status, often times uninsured and minority populations, have historically been underrepresented in clinical trials, leading to limited knowledge on the impact of certain therapies for these populations (Murthy et al., 2004; Nipp et al., 2019; Talarico et al., 2004; Townsley et al., 2005; Umutyan et al., 2008). Information on income and socioeconomic status could better inform what strategies of recruitment and retention are most effective and beneficial for supporting participants. While incentives in the form of monetary payments are a popular engagement strategy, adjusting study accessibility in terms of transportation and convenience might be more impactful (Forsat et al., 2020; Gilmore et al., 2019). For those within a lower socioeconomic group, participating in research may be prevented by transportation costs and event timings that conflict with work schedules (Forsat et al., 2020; Gilmore-Bykovskyi et al., 2021). Strategies to make participation more accessible include provision of transportation, providing event locations and timings that are convenient according to work schedule, and rotating location of events to address socioeconomic-related variation in geographic settings (Ajrouch et al., 2020; Forsat et al., 2020; Gilmore-Bykovskyi et al., 2021).

Reported recruitment and retention strategies relied heavily on recruiting from community settings, hospitals, and clinics. Recruitment from trusted community spaces was a best practice strategy used to address mistrust, misperceptions, and misunderstandings. Recruitment in hospitals and clinical settings provided a convenience factor and referral by one’s health care provider was cited as a strong incentive. Also important to note is that differing referral sources (e.g., primarily community vs. clinic-based) by racial/ethnic subgroup could result in selection bias if the systematic differences in recruitment source are associated with the exposure and outcome of interest (Gleason et al., 2019). Retention strategies for a majority of studies were not reported. In studies where retention strategies could be assessed, monetary compensation and maintaining participant connections by updates and involvement in study process were seen as effective. While this scoping review identified the most commonly used recruitment and retention strategies in these NIH-sponsored studies, we were unable to assess which of the reported strategies were most effective. As racial and ethnic populations face differing barriers to access health care services and research, further study is necessary to investigate outcomes of targeted recruitment and retention strategies by subgroups and different populations.

Limitations

Our scoping review has several limitations. First, this review was limited to NIH-sponsored studies to inform a research collaborative funded by the NIA. We acknowledge that this framing may have limited generalizability of findings as studies funded by other institutes or agencies might provide additional insight into the barriers and strategies for engaging diverse older adults in aging research. Participant diversity was analyzed from reported data, but might not reflect actual inclusion of participants from diverse populations. Nonetheless, we present a comprehensive scoping review of NIH-sponsored work, the largest funder of aging and AD/ADRD research. We identify critical literature gaps, including opportunities to improve data collection and reporting, which is needed to improve equitable inclusion of older adults from underrepresented groups.

Conclusions

Improved engagement of diverse older adults in research is critical to achieving broadly applicable evidence. This scoping review has identified gaps in reporting of critical information regarding participant characteristics that can serve as a barrier to generalizing study findings. Future work should aim to (a) prioritize research to focus on underrepresented older adult groups including racial and ethnic minorities, LGBTQ and alternative gender and sexual identity groups, rural populations, low-socioeconomic status groups, disabled populations, and cognitively impaired populations and caregivers; (b) improve collection and reporting of participant characteristics for aforementioned groups; (c) assess proportional extent of participation for specific racial and ethnic groups; and (d) investigate outcomes of commonly used and targeted recruitment and retention strategies for aforementioned groups.

Future Work and Implications.

Consistent with the aims of a scoping review to highlight gaps in extant literature and inform areas of future work (Heyn et al., 2019), this review motivates numerous areas of future research. It is important to note that our study sought to investigate the extent of representation of underrepresented populations. Given the paucity of studies including participants from these groups, future work should focus on the intersectionality of the many factors associated with underrepresentation in research (e.g., geography, disability, gender, and income) irrespective of funding source. Additional work should also investigate recruitment and retention outcomes using different strategies applied to specific racial and ethnic groups. Such work will help researchers strive toward equitable inclusion of diverse older adults in aging and AD/ADRD research and advance population health outcomes.

Supplementary Material

gnac060_suppl_Supplementary_Material
Click here for additional data file. (132.3KB, docx)

Acknowledgments

The authors would like to thank Annalie Brody, Lena Finucane, Arlene Hernandez, Diana Hernandez, Daniel Chong, and Jade Refuerzo for their contributions to the project.

Contributor Information

Nisha Godbole, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, USA.

Simona C Kwon, Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA.

Jeannette M Beasley, Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA; Department of Nutrition and Food Studies, New York University Steinhardt School of Culture, Education, and Human Development, New York, NY, USA.

Timothy Roberts, Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA.

Julie Kranick, Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA.

Jessica Smilowitz, Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA.

Agnes Park, Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA.

Scott E Sherman, Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA; Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA; VA New York Harbor Healthcare System, New York, NY, USA.

Chau Trinh-Shevrin, Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA.

Joshua Chodosh, Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA; Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA; VA New York Harbor Healthcare System, New York, NY, USA.

Funding

This project was funded by the National Institute on Aging sponsored Engagement and Longevity in Medicine Initiative (R24AG06372 to J. Chodosh, S. E. Sherman, C. Trinh-Shevrin, S. C. Kwon, J. M. Beasley, and J. Smilowitz), the National Center for Advancing Translational Sciences sponsored Clinical Translational Science Award (UL1TR001445 to S. E. Sherman and S. C. Kwon), the National Institute on Aging Academic Leadership Award (K07AG068186 to C. Trinh-Shevrin), the Centers For Disease Control and Prevention sponsored NYU BOLD Public Health Center of Excellence on Early Detection of Dementia (NU58DP006911 to J. Chodosh, C. Trinh-Shevrin, and S. C. Kwon), the National Institute on Aging sponsored NYU Alzheimer’s Disease Research Center (1P30AG066512-01 to J. Chodosh), the National Institute of Diabetes and Digestive and Kidney Diseases Summer Research Fellowship for MD Students (5T35DK007421 to N. Godbole), and R01 (R01DK127916 to J. M. Beasley and J. Chodosh). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the Centers For Disease Control and Prevention.

Conflict of Interest

None declared.

References

  1. Ajrouch, K. J., Vega, I. E., Antonucci, T. C., Tarraf, W., Webster, N. J., & Zahodne, L. B. (2020). Partnering with middle Eastern/Arab American and Latino immigrant communities to increase participation in Alzheimer’s disease research. Ethnicity and Disease, 30(Suppl 2), 765–774. doi: 10.18865/ed.30.S2.765 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Alzheimer’s Association. (2019). 2019 Alzheimer’s disease facts and figures. Alzheimer’s and Dementia, 15(3), 321–387. doi: 10.1016/j.jalz.2019.01.010 [DOI] [Google Scholar]
  3. Arksey, H., & O’Malley, L. (2005). Scoping studies: Towards a methodological framework. International Journal of Social Research Methodology, 8(1), 19–32. doi: 10.1080/1364557032000119616 [DOI] [Google Scholar]
  4. Brodaty, H., & Green, A. (2002). Defining the role of the caregiver in Alzheimer’s disease treatment. Drugs and Aging, 19(12), 891–898. doi: 10.2165/00002512-200219120-00001 [DOI] [PubMed] [Google Scholar]
  5. Deane, C. S., Phillips, B. E., Smith, K., Steele, A. M., Libretto, T., Statton, S. A., Atherton, P. J., & Etheridge, T. (2020). Challenges and practical recommendations for successfully recruiting inactive, statin-free older adults to clinical trials. BMC Research Notes, 13(1), 174. doi: 10.1186/s13104-020-05017-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Dudley, L., Gamble, C., Preston, J., Buck, D., Hanley, B., Williamson, P., & Young, B. (2015). What difference does patient and public involvement make and what are its pathways to impact? Qualitative study of patients and researchers from a cohort of randomised clinical trials. PLoS One, 10(6), e0128817. doi: 10.1371/journal.pone.0128817 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Eggly, S., Barton, E., Winckles, A., Penner, L. A., & Albrecht, T. L. (2015). A disparity of words: Racial differences in oncologist-patient communication about clinical trials. Health Expectations, 18(5), 1316–1326. doi: 10.1111/hex.12108 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Elliot, C. (2020). Together we make the difference: National strategy for recruitment and participation in Alzheimer’s and related dementias clinical research. Ethnicity & Disease, 30(Suppl), 705–708. doi: 10.18865/ed.30.S2.705 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Federal Interagency Forum on Aging-Related Statistics [FIFAS]. (2008). Older Americans 2008: Key indicators of well-being.https://nepis.epa.gov/Exe/ZyNET.exe/P1001XK3.TXT?ZyActionD=ZyDocument&Client=EPA&Index=2006+Thru+2010&Docs=&Query=&Time=&EndTime=&SearchMethod=1&TocRestrict=n&Toc=&TocEntry=&QField=&QFieldYear=&QFieldMonth=&QFieldDay=&IntQFieldOp=0&ExtQFieldOp=0&XmlQuery=&File=D%3A%5Czyfiles%5CIndex%20Data%5C06thru10%5CTxt%5C00000005%5CP1001XK3.txt&User=ANONYMOUS&Password=anonymous&SortMethod=h%7C-&MaximumDocuments=1&FuzzyDegree=0&ImageQuality=r75g8/r75g8/x150y150g16/i425&Display=hpfr&DefSeekPage=x&SearchBack=ZyActionL&Back=ZyActionS&BackDesc=Results%20page&MaximumPages=1&ZyEntry=1&SeekPage=x&ZyPURL
  10. Flores, L. E., Frontera, W. R., Andrasik, M. P., del Rio, C., Mondríguez-González, A., Price, S. A., Krantz, E. M., Pergam, S. A., & Silver, J. K. (2021). Assessment of the inclusion of racial/ethnic minority, female, and older individuals in vaccine clinical trials. Journal of the American Medical Association Network Open, 4(2), e2037640. doi: 10.1001/jamanetworkopen.2020.37640 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Forsat, N. D., Palmowski, A., Palmowski, Y., Boers, M., & Buttgereit, F. (2020). Recruitment and retention of older people in clinical research: A systematic literature review. Journal of the American Geriatrics Society, 68(12), 2955–2963. doi: 10.1111/jgs.16875 [DOI] [PubMed] [Google Scholar]
  12. Gelman, C., Faul, A. C., & Yankeelov, P. A. (2013). Intervention research with minority older adults: Challenges encountered, solutions enacted, and implications for future work. Journal of Applied Gerontology, 32(2), 207–225. doi: 10.1177/0733464811416812 [DOI] [PubMed] [Google Scholar]
  13. Gilmore, N. J., Canin, B., Whitehead, M., Sedenquist, M., Griggs, L., Finch, L., Grossman, V., Targia, V., Wells, M., Kamen, C., Flannery, M., Magnuson, A., Plumb, S., Obrecht, S., Lowenstein, L. M., Lopez, G., Anderson, J., Berenberg, J., Vogel, V., & Mohile, S. G. (2019). Engaging older patients with cancer and their caregivers as partners in cancer research. Cancer, 125(23), 4124–4133. doi: 10.1002/cncr.32402 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Gilmore-Bykovskyi, A., Croff, R., Glover, C. M., Jackson, J. D., Resendez, J., Perez, A., Zuelsdorff, M., Green-Harris, G., & Manly, J. J. (2021). Traversing the aging research and health equity divide: Toward intersectional frameworks of research justice and participation. The Gerontologist, 62(5), 711–720. doi: 10.1093/geront/gnab107 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Gilmore-Bykovskyi, A. L., Jin, Y., Gleason, C., Flowers-Benton, S., Block, L. M., Dilworth-Anderson, P., Barnes, L. L., Shah, M. N., & Zuelsdorff, M. (2019). Recruitment and retention of underrepresented populations in Alzheimer’s disease research: A systematic review. Alzheimer’s and Dementia (New York, N. Y.), 5, 751–770. doi: 10.1016/j.trci.2019.09.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Gleason, C. E., Norton, D., Zuelsdorff, M., Benton, S. F., Wyman, M. F., Nystrom, N., Lambrou, N., Salazar, H., Koscik, R. L., Jonaitis, E., Carter, F., Harris, B., Gee, A., Chin, N., Ketchum, F., Johnson, S. C., Edwards, D. F., Carlsson, C. M., Kukull, W., & Asthana, S. (2019). Association between enrollment factors and incident cognitive impairment in Blacks and Whites: Data from the Alzheimer’s disease center. Alzheimer’s and Dementia, 15(12), 1533–1545. doi: 10.1016/j.jalz.2019.07.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Gordon, N. P., Banegas, M. P., & Tucker-Seeley, R. D. (2020). Racial-ethnic differences in prevalence of social determinants of health and social risks among middle-aged and older adults in a Northern California health plan. PLoS One, 15(11), e0240822. doi: 10.1371/journal.pone.0240822 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Harawa, N. T. (2020). Lessons from my elders on recruitment and retention into health research. Ethnicity and Disease, 30(Suppl 2), 781–784. doi: 10.18865/ed.30.S2.781 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde, J. G. (2009). Research Electronic Data Capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics, 42(2), 377–381. doi: 10.1016/j.jbi.2008.08.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Herrera, A. P., Snipes, S. A., King, D. W., Torres-Vigil, I., Goldberg, D. S., & Weinberg, A. D. (2010). Disparate inclusion of older adults in clinical trials: Priorities and opportunities for policy and practice change. American Journal of Public Health, 100(Suppl 1), S105–S 112. doi: 10.2105/AJPH.2009.162982 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Heyn, P. C., Meeks, S., & Pruchno, R. (2019). Methodological guidance for a quality review article. The Gerontologist, 59(2), 197–201. doi: 10.1093/geront/gny123 [DOI] [PubMed] [Google Scholar]
  22. Hill, C., Pérez-Stable, E., Anderson, N., & Bernard, M. A. (2015). The national institute on aging health disparities research framework. Ethnicity and Disease, 25(3), 245–2 54. doi: 10.18865/ed.25.3.245 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Jang, Y., Yoon, H., Park, N. S., Rhee, M. K., & Chiriboga, D. A. (2018). Asian Americans’ concerns and plans about Alzheimer’s disease: The role of exposure, literacy and cultural beliefs. Health and Social Care in the Community, 26(2), 199–206. doi: 10.1111/hsc.12509 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Kasenda, B., von Elm, E., You, J., Blümle, A., Tomonaga, Y., Saccilotto, R., Amstutz, A., Bengough, T., Meerpohl, J. J., Stegert, M., Tikkinen, K. A. O., Neumann, I., Carrasco-Labra, A., Faulhaber, M., Mulla, S. M., Mertz, D., Akl, E. A., Bassler, D., Busse, J. W., & Briel, M. (2014). Prevalence, characteristics, and publication of discontinued randomized trials. Journal of the American Medical Association, 311(10), 1045–1051. doi: 10.1001/jama.2014.1361 [DOI] [PubMed] [Google Scholar]
  25. Konkel, L. (2015). Racial and ethnic disparities in research studies: The challenge of creating more diverse cohorts. Environmental Health Perspectives, 123(12), A297–A 302. doi: 10.1289/ehp.123-A297 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Lacey, R. J., Wilkie, R., Wynne-Jones, G., Jordan, J. L., Wersocki, E., & McBeth, J. (2017). Evidence for strategies that improve recruitment and retention of adults aged 65 years and over in randomised trials and observational studies: A systematic review. Age and Ageing, 46(6), 895–903. doi: 10.1093/ageing/afx057 [DOI] [PubMed] [Google Scholar]
  27. Lim, S., Chong, S., Min, D., Mohaimin, S., Roberts, T., Trinh-Shevrin, C., & Kwon, S. C. (2021). Alzheimer’s disease screening tools for Asian Americans: A scoping review. Journal of Applied Gerontology, 40(10), 1389–1398. doi: 10.1177/0733464820967594 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Lim, S., Mohaimin, S., Min, D., Roberts, T., Sohn, Y. J., Wong, J., Sivanesathurai, R., Kwon, S. C., & Trinh-Shevrin, C. (2020). Alzheimer’s Disease and its related dementias among Asian Americans, native hawaiians, and pacific islanders: A scoping review. Journal of Alzheimer’s Disease, 77(2), 523–537. doi: 10.3233/JAD-200509 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Majoka, M. A., & Schimming, C. (2021). Effect of social determinants of health on cognition and risk of Alzheimer Disease and related dementias. Clinical Therapeutics, 43(6), 922–929. doi: 10.1016/j.clinthera.2021.05.005 [DOI] [PubMed] [Google Scholar]
  30. Marshall, L. W., Carrillo, C. A., Reyes, C. E., Thorpe, C. L., Trejo, L., & Sarkisian, C. (2020). Evaluation of recruitment of older adults of color into a community-based chronic disease self-management wellness pathway program in Los Angeles County. Ethnicity and Disease, 30(Suppl 2), 735–744. doi: 10.18865/ed.30.S2.735 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. MEDLINE® 2021 database guide. Ovid database guide 2021. (n.d.). Retrieved September 29, 2021, from https://ospguides.ovid.com/OSPguides/medline.htm
  32. Mitchell, J., Perry, T., Rorai, V., Ilardo, J., Lichtenberg, P. A., & Jackson, J. S. (2020). Building and Sustaining a Community Advisory Board of African American older adults as the foundation for volunteer research recruitment and retention in health sciences. Ethnicity and Disease, 30(Suppl 2), 755–764. doi: 10.18865/ed.30.S2.755 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Munn, Z., Peters, M. D. J., Stern, C., Tufanaru, C., McArthur, A., & Aromataris, E. (2018). Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Medical Research Methodology, 18(1), 143. doi: 10.1186/s12874-018-0611-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Murthy, V. H., Krumholz, H. M., & Gross, C. P. (2004). Participation in cancer clinical trials: Race-, sex-, and age-based disparities. Journal of the American Medical Association, 291(22), 2720–2726. doi: 10.1001/jama.291.22.2720 [DOI] [PubMed] [Google Scholar]
  35. National Academies of Sciences, Engineering, and Medicine; Health and Medicine Division; Board on Population Health and Public Health Practice; Committee on Community-Based Solutions to Promote Health Equity in the United States. (2017). The state of health disparities in the United States. In Baciu A., Negussie Y., Geller A., & Weinstein J. N. (Eds.), Communities in action: Pathways to health equity. National Academies Press.http://www.ncbi.nlm.nih.gov/books/NBK425844/ [PubMed] [Google Scholar]
  36. National Research Council (US) Panel on a Research Agenda and New Data for an Aging World. (2001). Preparing for an aging world: The case for cross-national research. National Academies Press. http://www.ncbi.nlm.nih.gov/books/NBK98379/ [PubMed] [Google Scholar]
  37. Nipp, R. D., Hong, K., & Paskett, E. D. (2019). Overcoming barriers to clinical trial enrollment. American Society of Clinical Oncology Educational Book, 39, 105–114. doi: 10.1200/EDBK_243729 [DOI] [PubMed] [Google Scholar]
  38. National Institutes of Health (NIH). (2019). NOT-OD-15-089: Racial and Ethnic Categories and Definitions for NIH Diversity Programs and for Other Reporting Purposes. (2015). https://grants.nih.gov/grants/guide/notice-files/NOT-OD-20-031.html
  39. Ortega, R. F., Yancy, C. W., Mehran, R., & Batchelor, W. (2019). Overcoming lack of diversity in cardiovascular clinical trials: A new challenge and strategies for success. Circulation, 140(21), 1690–1692. doi: 10.1161/CIRCULATIONAHA.119.041728 [DOI] [PubMed] [Google Scholar]
  40. Portacolone, E., Palmer, N. R., Lichtenberg, P., Waters, C. M., Hill, C. V., Keiser, S., Vest, L., Maloof, M., Tran, T., Martinez, P., Guerrero, J., & Johnson, J. K. (2020). Earning the trust of African American communities to increase representation in dementia research. Ethnicity and Disease, 30(Suppl 2), 719–734. doi: 10.18865/ed.30.S2.719 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Robison, J., Powell, W., & Kenyon-Pesce, L. (2020). Practical guidance for recruiting older adults in clinical research: Building on principles of social justice and equity. Journal of the American Geriatrics Society, 68(12), 2757–2758. doi: 10.1111/jgs.16873 [DOI] [PubMed] [Google Scholar]
  42. Stewart, A. L., Nápoles, A. M., Piawah, S., Santoyo-Olsson, J., & Teresi, J. A. (2020). Guidelines for evaluating the feasibility of recruitment in pilot studies of diverse populations: An overlooked but important component. Ethnicity and Disease, 30(Suppl 2), 745–754. doi: 10.18865/ed.30.S2.745 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Ta Park, V., Grill, J. D., Zhu, J., Nguyen, K., Nam, B., Tsoh, J., Kanaya, A., Vuong, Q., Bang, J., Nguyen, N. C. Y., Cho, I. H., Gallagher-Thompson, D., Hinton, L., & Meyer, O. L. (2021). Asian Americans and Pacific Islanders’ perspectives on participating in the CARE recruitment research registry for Alzheimer’s disease and related dementias, aging, and caregiving research, Alzheimer’s and Dementia, 7(1), e12195. doi: 10.1002/trc2.12195 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Talarico, L., Chen, G., & Pazdur, R. (2004). Enrollment of elderly patients in clinical trials for cancer drug registration: A 7-year experience by the US Food and drug administration. Journal of Clinical Oncology, 22(22), 4626–4631. doi: 10.1200/JCO.2004.02.175 [DOI] [PubMed] [Google Scholar]
  45. Townsley, C. A., Selby, R., & Siu, L. L. (2005). Systematic review of barriers to the recruitment of older patients with cancer onto clinical trials. Journal of Clinical Oncology, 23(13), 3112–3124. doi: 10.1200/JCO.2005.00.141 [DOI] [PubMed] [Google Scholar]
  46. Tricco, A. C., Lillie, E., Zarin, W., O’Brien, K. K., Colquhoun, H., Levac, D., Moher, D., Peters, M. D. J., Horsley, T., Weeks, L., Hempel, S., Akl, E. A., Chang, C., McGowan, J., Stewart, L., Hartling, L., Aldcroft, A., Wilson, M. G., Garritty, C., & Straus, S. E. (2018). PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and explanation. Annals of Internal Medicine, 169(7), 467–473. doi: 10.7326/M18-0850 [DOI] [PubMed] [Google Scholar]
  47. Tuijt, R., Rees, J., Frost, R., Wilcock, J., Manthorpe, J., Rait, G., & Walters, K. (2021). Exploring how triads of people living with dementia, carers and health care professionals function in dementia health care: A systematic qualitative review and thematic synthesis. Dementia, 20(3), 1080–1104. doi: 10.1177/1471301220915068 [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Umutyan, A., Chiechi, C., Beckett, L. A., Paterniti, D. A., Turrell, C., Gandara, D. R., Davis, S. W., Wun, T., Chen, M. S., & Lara, P. N. (2008). Overcoming barriers to cancer clinical trial accrual. Cancer, 112(1), 212–219. doi: 10.1002/cncr.23170 [DOI] [PubMed] [Google Scholar]
  49. United States Census Bureau. (2017). 2017 National population projections tables: Main series.https://www.census.gov/data/tables/2017/demo/popproj/2017-summary-tables.html
  50. United States Census Bureau. (2018). An aging nation: Projected number of children and older adults.https://www.census.gov/library/visualizations/2018/comm/historic-first.html
  51. Vellas, B., Pesce, A., Robert, P. H., Aisen, P. S., Ancoli-Israel, S., Andrieu, S., Cedarbaum, J., Dubois, B., Siemers, E., Spire, J. P., Weiner, M. W., & May, T. S. (2011). AMPA workshop on challenges faced by investigators conducting Alzheimer’s disease clinical trials. Alzheimer’s and Dementia, 7(4), e109–e 117. doi: 10.1016/j.jalz.2010.05.2020 [DOI] [PubMed] [Google Scholar]
  52. Vick, J. B., Amjad, H., Smith, K. C., Boyd, C. M., Gitlin, L. N., Roth, D. L., Roter, D. L., & Wolff, J. L. (2018). “Let him speak:” a descriptive qualitative study of the roles and behaviors of family companions in primary care visits among older adults with cognitive impairment. International Journal of Geriatric Psychiatry, 33(1), e103–e112. doi: 10.1002/gps.4732 [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Wolff, J. L., Clayman, M. L., Rabins, P., Cook, M. A., & Roter, D. L. (2015). An exploration of patient and family engagement in routine primary care visits. Health Expectations, 18(2), 188–198. doi: 10.1111/hex.12019 [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Wolff, J. L., Guan, Y., Boyd, C. M., Vick, J., Amjad, H., Roth, D. L., Gitlin, L. N., & Roter, D. L. (2017). Examining the context and helpfulness of family companion contributions to older adults’ primary care visits. Patient Education and Counseling, 100(3), 487–494. doi: 10.1016/j.pec.2016.10.022 [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Wolff, J. L., & Roter, D. L. (2012). Older adults’ mental health function and patient-centered care: Does the presence of a family companion help or hinder communication? Journal of General Internal Medicine, 27(6), 661–668. doi: 10.1007/s11606-011-1957-5 [DOI] [PMC free article] [PubMed] [Google Scholar]

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