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Journal of Intergenerational Relationships Volume 21, 2023 - Issue 3
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Research Article

Study Navigation and Enrollment in a Community Sample: Does Generational Cohort Matter?

Ayodeji A Otufoworaa College of Medicine, University of Florida, Gainesville, FL, USACorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-4776-0918View further author information
, MD, PhD, MPHORCID Icon,
Catherine W Strileyb College of Public Health and Health Professions, College of Medicine, University of Florida, Gainesville, FL, USAView further author information
, PhD, MSW, MPE,
Krishna Vaddipartib College of Public Health and Health Professions, College of Medicine, University of Florida, Gainesville, FL, USAView further author information
, PhD, MPE, MSW,
Michael J. Scicchitanoc College of Liberal Arts & Sciences, University of Florida, Gainesville, FL, USAView further author information
, PhD, MPA &
Linda B Cottlerb College of Public Health and Health Professions, College of Medicine, University of Florida, Gainesville, FL, USAView further author information
, PhD, MPH, FACE
Pages 299-320 | Published online: 21 Feb 2022

ABSTRACT

The socioecological model (SEM) was used as a conceptual framework to examine the effect of generational cohorts on study navigation and enrollment in health research. The study population was 7,370 community-dwelling Gen Xers and Baby Boomers in North Central Florida. Analyses found that Leading-edge Boomers (individuals born between 1946 and 1955) [vs Gen Xers (individuals born between 1965 and 1955)] and individuals with higher trust (vs lower trust) were 41% and 25% respectively more likely to be enrolled in health research compared to their counterparts, controlling for factors at the individual, relationship, and community levels of the SEM. We conclude the study with a summary of the findings and the recruitment implications for study enrollment.

Introduction

Members of a generational group share unique historical experiences in their adolescence and young adulthood which change their perception and world view (Bristow, Citation2015; Erll & Nünning, Citation2008). According to Urie Bronfenbrenner’s bioecological model, each generation has its own unique experiences in its formative years, which shape its perceptions and values as it transitions across time (Carlson, Citation2009; Nelson et al., Citation2015). There are multiple currently living generations; the older generations are the Greatest Generation (aka the GI Generation, born between 1910 and 1924), the Silent Generation (born between1925 and 1945), and the Baby Boomer Generation (born between 1946 and1964). The younger generations are Generation X (born between 1965 and 1980), Generation Y (also known as Millennials, born between 1981 and 1996), and Generation Z (born after 1997; Black & Hyer, Citation2019). The large size of the Baby Boomers (now the second-largest living generation, having been recently surpassed by Millennials (Pew Research Center, Citation2020) and their heterogeneity in multiple domains such as work experiences, marital status, parenthood, and socioeconomic status (Iyer & Reisenwitz, Citation2015), has led to cohort sub-segmentation into Leading-Edge Boomers (LEBs,1946─1955) and Trailing-Edge Boomers (TEBs, 1956–1964; Bevan-Dye, Citation2017; Chakradhar et al., Citation2018; Reisenwitz & Iyer, Citation2007), based on attitudinal and behavioral differences (Bevan-Dye, Citation2017; Chakradhar et al., Citation2018; Dinkins, Citation1993; Rahman & Yu, Citation2018).

Generation Xers are said to place a high priority on autonomy, independence, skepticism, and individualism (Jorgensen, Citation2003; Kupperschmidt, Citation2000), Leading-Edge Boomers (LEBs) have been described as addicted to work, individualistic, adventurous, and concerned with social justice and reform and the need to make a difference to society (Morton, Citation2001; Reisenwitz & Iyer, Citation2007). Trailing-Edge Boomers (TEBs) have been described as individuals who are driven by personal-growth, are non-committal, and influenced by new technologies (Morton, Citation2001; Reisenwitz & Iyer, Citation2007). Although the two populations share similar characteristics, Baby Boomers have experienced varying levels of social and economic change from 1943 to 1964 (Kleinhans et al., Citation2015). Leading-edge boomers (LEBs) are credited for having driven significant social and political change during the 1960s. On the other hand, trailing-edge boomers (TEBs) witnessed the consequences of the actions of the LEBs, which caused them to become more politically apathetic, more pragmatic, and cynical (Bouvier & DeVita, Citation1991; Kleinhans et al., Citation2015). However, a study by Gilliam and colleagues (Gilliam et al., Citation2010), which looked into differences in the perceived risk tolerance of the two sub-cohorts, found that the LEBs were less risk-tolerant than the TEBs, perhaps as a consequence of their lived experiences. The implication of this for research volunteering, especially clinical trials involving a level of risk, may be significant, as LEBs may be less willing to volunteer for greater than minimal risk research compared to TEBs (Otufowora, Liu, Young et al., Citation2020). Promoting and recruiting for research through television advertisement is more likely to be effective with boomers (compared to Gen Xers), as their favorite media was television, given that they were the first generation to have television throughout their entire lives (Stern, Citation2002).

Gen Xers are self-sufficient individuals who grew up as latch-key kids, working alone, highly adaptable, craving independence and freedom (Chakradhar et al., Citation2018; Hahn, Citation2011; Kleinhans et al., Citation2015). As noted by Yang and colleagues (Yang & Guy, Citation2006), Gen Xers’ preference for belonging and teamwork is partly due to the isolation they experienced in their childhood. This isolation led to many of them developing skills that they needed to become more social (Yang & Guy, Citation2006). They are accustomed to various types of relationships and cultures and also tend to be more team-oriented and less individualistic (Cordeniz, Citation2002). Thus, in the context of study enrollment, they may be amenable to participating in qualitative research involving group focus studies with diverse study populations. Moreover, information technology has been an important part of their lives growing up, and they often make decisions based on a variety of information available to them via the internet (Rodriguez et al., Citation2003; Yang & Guy, Citation2006). They are expert users of social media platforms, specifically Facebook and YouTube (Sprout Social, Citation2021); hence, promoting research participation on video-based social media may yield better results compared to the traditional use of newsletters or mailshots in this cohort. However, it should be noted that Gen Xers have been shown to have issues with the credibility of digital marketing and advertisement in general (Benckendorff et al., Citation2009; Cooper et al., Citation2018). Thus, the importance of being factual and leaning on evidence-based statements cannot be overemphasized during online recruitment for research. Furthermore, higher social media usage by Gen Xers (compared to boomers) implies that they may have better access to the online research hub (“clinicalTrials.gov”) and thus more opportunity to be recruited for research (Cox, Citation2019; Hysa et al., Citation2021; Sprout Social, Citation2021).

Further, there are also differences between Baby Boomers and Gen Xers in terms of social justice and inclusion particularly as it relates to research participation. While Baby Boomers do care about social issues, as demonstrated in their involvement in the social movements of the 1960s and 1970s, Gen Xers are more comfortable with working across various racial, gender, and sexual orientation intersections.(Cordeniz, Citation2002; Kunreuther, Citation2003). This may, for example, explain the high enrollment rate of Gen Xers in sexual orientation and gender identity (SOGI) research; older adults (such as Baby Boomers) have shown higher non-response rates to SOGI survey questions compared to younger adults (Fredriksen-Goldsen & Kim, Citation2015, Citation2017). However, it should be noted that there are challenges of conducting sexuality and gender research in an aging population, as most large surveys for such populations do not include SOGI questions, and also because of erroneous assumptions that SOGI questions would be too sensitive for them or they would not understand the questions (Fredriksen-Goldsen & Kim, Citation2015, Citation2017).

Furthermore, regarding the current pandemic vis-à-vis vaccine research and vaccine hesitancy, there are generational differences in the impact of COVID-19 and the way in which different generations are responding to the pandemic (Min et al., Citation2021). For example, in terms of the enrollment in COVID-19 vaccine research and vaccine hesitancy, although older generations such as the Baby Boomers were more likely to be excluded from clinical trials (given stringent exclusion criteria) compared to younger generations (Helfand et al., Citation2020), they are however more likely to accept the vaccine (Malik et al., Citation2020). Indeed, as noted by Shih and colleagues (Shih et al., Citation2021), compared to millennials, both Baby Boomers and Gen Xers are less likely to be vaccine-hesitant; Baby Boomers however had lower odds in the study (Shih et al., Citation2021).

These generational differences also manifest themselves in participation in health research, due to generational differences in trust (Holm & Nystedt, Citation2005; Jennings & Stoker, Citation2004), as trust is a significant predictor of research participation (Kass et al., Citation1996; Khodyakov et al., Citation2017; McCaskill-Stevens et al., Citation1999; C. W. Striley et al., Citation2019). Stoker and colleagues (Jennings & Stoker, Citation2004) found minimal differences between Baby Boomers and the Greatest Generation in trust and civic engagement; but Generation X demonstrated lower trust and reduced willingness to volunteer for community duties compared to older generations. Rotolo and Wilson (Rotolo & Wilson, Citation2004) similarly found minimal differences in trust and volunteerism between the Baby Boomers and Greatest Generation, but did identify differences in the type of work the two generations volunteered for (for example, school-related vs. church-related volunteering work). Compared to older generations, Baby Boomers were more likely to pursue social engagement (Morrow-Howell & Gehlert, Citation2012), to volunteer for community activities, and to have a higher rate of illicit drug use (Han et al., Citation2015; Patterson & Jeste, Citation1999; Wu & Blazer, Citation2011). Nelson and colleagues (Nelson et al., Citation2015) found that members of Generation Y were less willing to participate in research compared to Baby Boomers. However, to our knowledge no population-based study has examined differences in participation in health research between Boomers and Generation Xers.

Of note, the preliminary stage of study participation that includes linking community members to health research, prescreening them and connecting them to a specific study coordinator is study navigation (Cottler et al., Citation2017; Webb et al., Citation2015). Study enrollment is the process wherein community members who have met the eligibility criteria are further screened. To be enrolled, a person must have completed the informed consent process (Ford et al., Citation2006; Webb et al., Citation2015). Community members who volunteer to participate in research studies, regardless of their generational cohort, can broadly be classified into three different categories, based on their study navigation and enrollment patterns: members who were never navigated (never navigated, NN), members who were navigated but not enrolled (navigated not enrolled, NNE) and members who were navigated and subsequently successfully enrolled (navigated and enrolled, NE).

This study aimed to test the effect of generational cohort (i.e Gen Xers and Baby Boomers) on study navigation and enrollment in the context of the socioecological model (SEM) which posits that community members’ perceptions, attitudes and behaviors are influenced by the interaction of factors at the individual, relationship, community and societal level (Ma et al., Citation2017; Tehrani et al., Citation2016). Given that Baby Boomers have been found to have a high rate of volunteering for community activities (Han et al., Citation2015; Patterson & Jeste, Citation1999; Wu & Blazer, Citation2011), we hypothesize that, compared to Gen Xers, both Leading-Edge Boomers (LEBs) and Trailing-Edge Boomers (TEBs) (with LEB>TEB) will be more likely to be navigated and enrolled in health research, controlling for individual, relationship and community level factors. Also, regarding research trust, and regardless of generational cohort, we also hypothesize that the odds of navigation and enrollment will be higher in individuals with higher trust in research compared to those with lower trust, controlling for individual, relationship and community level factors.

Methods

Study population

This is a cross-sectional analysis of data collected between October 2011 and March, 2020, obtained from HealthStreet, an ongoing community engagement program supported by the University of Florida’s Clinical and Translational Science Awards (CTSA). The HealthStreet model of community engagement is centered on four pillars: assessment, trustworthiness, linkage to care and research, and multidirectional communication and workforce development. Each of these pillars is designed to achieve an end goal. Assessment involves testing and screenings for health conditions and concerns in order to devise targeted interventions for the community and achieve a better community health. Trustworthiness, by utilizing concepts of community engagement, measures research perception and trust, ultimately breaking down barriers that prevent research participation in the community. Linkage to care and research involves CHWs giving social referrals and navigating community members to research at the University of Florida with the goal of improving parity in access to research and care and also increasing the relevance and impact of research. Lastly, multidirectional communication and workforce development involves training community members about research, sharing research findings, dispelling myths, and ultimately being relevant to the community.

HealthStreet uses the Community Health Worker (CHW) recruitment model to engage community members in research. Study participants were recruited by CHWs from 54 of the 67 counties in Florida, the third largest state in the country. Recruitment involves a 20–25-minute face-to-face interview conducted by the CHW after obtaining an informed consent (approved by the University of Florida’s Institutional Review Board, IRB). The CHW asks questions from the Community Health Needs Assessment (CHNA), including sociodemographic characteristics, health needs, health concerns, healthcare access, physical and mental health conditions, and drug use types and patterns.

Measurements

The individual-level factors included date of birth (DOB), sex, race, and education level (less than high school, high school and more than high school). Consistent with other studies (Lester et al., Citation2012; Moore et al., Citation2015; Twenge et al., Citation2012), we categorized study participants into generational cohorts using their birth year (obtained from their date of birth): Generation X [(1965–1980), n = 2,976]; TEB [(1956–1964), n = 2,571] and LEB [(1946–1955), n = 1,823]. The study sample consisted of 7,370 community members born between 1946 and 1980. The individual-level variables included trust in research and trust in researchers, measured using a 10-point Likert scale where 1 is no trust and 10 is complete trust, that has been used previously (Cook et al., Citation2018; Webb et al., Citation2019). Regarding access to healthcare, participants were asked if they had health insurance (yes/no) and if they had had a health checkup in the past 12 months and perceived health (excellent/good vs fair/poor). In addition, study participants were asked about mental health conditions (anxiety, depression) and lifetime drug use (marijuana, cocaine).

Relationship-level factors included marital status, employment status, currently living with at least one other person, and use of social media. Community-level was assessed with the variable rurality, defined based on zip codes and divided into rural vs suburban/urban.

Analysis

We conducted a chi square test of independence to examine differences among the study population regarding categorical variables. Multivariate logistic regression assessed relationships between navigation status and key independent variables such as generational cohorts, trust, and other predictors. The adjusted odds ratios (aORs) and the 95% confidence interval (95% CI) were reported. All statistical analyses were performed using SAS 9.4.

The dependent variable was study navigation and enrollment status. Study navigation started when the HealthStreet matching algorithm matched the community member’s profile with available health studies. The community member’s interest in participating in the study was gauged after further screening and education about the study. If the community member was interested, he/she was connected with the study coordinator. Three subgroup patterns comprised the navigation and enrollment status: Never Navigated (NN), Navigated, not enrolled (NNE), and Navigated and Enrolled (NE). The independent variables are factors at the individual, relationship, and community levels of the socio-ecological model (SEM).

Results

Bivariate analysis

As shown in , of the 7,370 community members in the Generation X and Baby Boomer generations who were interviewed between October 2011 and March 2020, 45% had never been navigated to any study (NN), 31% had been navigated but were never enrolled (NNE) and 24% had been navigated and enrolled in health research (NE). Overall, 40% were Gen Xers, 35% were Trailing-Edge Boomers (TEBs), and 25% were Leading-Edge Boomers (LEBs); about 48% had lower trust in research with the same percentage (48%) reporting lower trust in researchers. Overall, the majority of the study participants was female (58%) and Black (56%). Over one-third (38%) identified as white. About one-fifth (19%) had less than a high school education, 39% had a high school education, and 43% had more than a high school education.

Table 1. Characteristics of Gen Xers and Baby Boomers in the HealthStreet Registry by Study Navigation and Enrollment Status, 2011─2020, n = 7,370.

Regarding access to healthcare and overall health, 61% reported having health insurance and 69% had a health checkup or physical in the past 12 months. Nearly the same proportion (68%) rated their health status as fair or poor. About 29% and 35% of the study participants self-reported anxiety and depression, respectively, and about 53% and 25% endorsed lifetime use of marijuana and cocaine, respectively.

Regarding relationship-level factors, about one-third (32%) were employed, one- quarter (25%) were married and a large majority (72%) had at least one person currently living with them. Also, about 39% of study participants reported using social media. Regarding the community level factor, an overwhelming majority (93%) lived in suburban or urban areas.

Being a Leading-Edge Boomer was linearly associated with study enrollment; compared to Gen Xers, LEBs (30%) were more likely to be navigated and enrolled. Participants with higher trust vs those with lower trust, and those without health insurance vs those who had health insurance were more likely to be navigated and not enrolled. Females vs males, individuals with a post-high-school education vs those with less, those with a health checkup vs those without and those who reported depression, marijuana or cocaine use vs those who did not, were more likely to be navigated and enrolled. Compared to whites, Blacks were more likely to be “never navigated.”

Regarding the relationship-level factors, being navigated (regardless of enrollment) was associated with being employed, as participants who were employed were more likely to be navigated compared to those who were unemployed. Regarding the community-level factor, suburban or urban dwelling was linearly associated with study enrollment; participants who lived in the suburban/urban areas were more likely to be navigated and enrolled in research compared to those who lived in the rural areas. Our analyses showed that perceived health, anxiety, marital status, coinhabiting (“currently living with at least one other person”) and use of social media were not significantly different among the three enrollment/navigation groups.

Multivariate analysis

shows the adjusted odd ratios (aORs) of the regression models for predicting study navigation and enrollment. Regarding the odds of community members to be navigated and enrolled, the aOR showed that LEBs were 41% more likely to be navigated and enrolled, compared to Gen Xers. Those with higher trust were 25% more likely to be navigated and enrolled than those with lower trust. Regarding the odds of community members being in the NNE category, after controlling for multiple factors at the individual, relationship, and community levels of the SEM, the aOR showed that individuals with higher trust were 34% more likely to be navigated and not enrolled in research, as compared to those with lower trust. Compared to whites, participants who identified as Black were 19% less likely to be NNE while those who identified as “other” races were 56% more likely to be NNE. Participants with post high school education (vs less than high school), participants with health insurance (vs no insurance) and those who had health checkups in the last 12 months (vs those who did not) were 34%, 26% and 28% more likely to be navigated but not enrolled, respectively, as compared to their counterparts. Moreover, participants who endorsed lifetime marijuana use (vs no use) and those who endorsed lifetime cocaine use (vs no use) were 32% and 27% more likely to be NNE, respectively, as compared to their counterparts. Finally, participants who were unemployed (vs those employed) were 18% more likely to be navigated but not enrolled in research, as compared to their counterparts.

Table 2. Association Between Generational Cohort, Trust in Research, other Determinants and Study Navigation and Enrollment in a Sample of Gen Xers and Baby Boomers in North Central Florida, 2011–2020, N = 7,370.

Further, compared to whites, Blacks were 23% more likely to be navigated and enrolled, while participants who identified as “other” races were 73% more likely to be navigated and enrolled in research. Compared to individuals with less than a high school education, participants with a post-high school education were 80% more likely to be navigated and enrolled. Further, compared to participants who did not have a health checkup in the last 12 months, those who did were 34% more likely to be navigated and enrolled. Regarding drug use, compared to participants who did not endorse drug use, participants who endorsed lifetime marijuana use were 35% more likely to be navigated and enrolled. Similarly, compared to participants who did not endorse lifetime cocaine use, participants who endorsed lifetime cocaine use were 39% more likely to be navigated and enrolled in research.

In terms of relationship-level factors, compared to participants who did not endorse the use of social media, those who did were 23% more likely to be navigated and enrolled. Regarding the community-level factor, compared to participants who lived in rural areas, participants who lived in suburban or urban areas were twice as likely to be navigated and enrolled in research. The following variables were not significantly associated with navigation and enrollment: sex, depression, health insurance and employment status.

Discussion

This analysis supported our hypotheses that navigated and enrolled individuals (vs. NNs) were more likely to be LEBs and have higher trust in research. In comparison to Gen Xers, Leading-Edge Boomers (LEBs) were more likely to be navigated and enrolled in health research than their counterparts. Studies (Chambré & Netting, Citation2018; Einolf, Citation2009) have shown that there is a high rate of volunteerism among Baby Boomers and, given the positive relationship between volunteerism and research participation (Chen et al., Citation2017; Corrigan & Tutton, Citation2006; Hall et al., Citation2016; Liu et al., Citation2019; Milani et al., Citation2021; Otufowora, Liu, Young et al., Citation2020; Sanderson et al., Citation2017; Yamaguchi et al., Citation2018), LEBs were more willing to volunteer to participate in research. It is also possible that since Baby Boomers in general (LEBs and TEBs) are altruistic (Chahil, Citation2015) and interested in making a difference in society (Morton, Citation2001; Reisenwitz & Iyer, Citation2007; themes consistent with research (Carrera et al., Citation2018; Dubé et al., Citation2020; Williams et al., Citation2008)), they are innately more willing to volunteer for research than their counterpart Gen Xers, who have been described as individualistic (Twenge, Citation2010) and motivated primarily by intrinsic rewards (Yang & Guy, Citation2006). However, this raises a question: Why are LEBs different than TEBs? Why in this study is enrollment significant for LEBs and not for TEBs? Perhaps the answer lies in the heterogeneity of this large generational cohort, broadly classified as Baby Boomers. Indeed, the proponents of cohort segmentation into LEB and TEB have cited the heterogeneity of this group, given their large size and life experiences as they grew up (Reisenwitz & Iyer, Citation2007). Thus, one can speculate that those altruistic characteristics of Baby Boomers were driven by LEBs. Also, since the willingness to volunteer decreases with generational age (Putnam, Citation2000) and LEBs are older than TEBs, this might explain the generational differences in study navigation and enrollment.

Further, community members who were navigated into health research were more likely to have higher trust in research than those not navigated, which is consistent with many studies in the literature that have shown a positive relationship between trust and participation in research (Kass et al., Citation1996; Khodyakov et al., Citation2017; McCaskill-Stevens et al., Citation1999; C. W. C. W. Striley et al., Citation2019). Berry and Rodgers (Berry & Rodgers, Citation2003) demonstrated higher trust among Baby Boomers (LEBs and TEBs) compared to Gen Xers. Also, Berry and Rodgers (Berry & Rodgers, Citation2003) showed that older generations generally have higher trust than younger generations. In addition, Putnam and colleagues (Putnam, Citation2000) found a decrease in the willingness to volunteer with decreasing generational age. It is thus understandable that Gen Xers may be less likely to participate in research than LEBs. Also, Gen Xers have been noted to be cynical (Arnett, Citation2000), therefore, the concept of research trust becomes important since trust in researchers (Campbell et al., Citation2007) and trust in research are central to study recruitment and retention (Kass et al., Citation1996; Khodyakov et al., Citation2017; McCaskill-Stevens et al., Citation1999; C. W. Striley et al., Citation2019). Thus, effective recruitment would mean research staff making a conscious effort to establish a trusting relationship in terms of both swift and traditional trust. In the trust model of Hurd and colleagues (Hurd et al., Citation2017), trust as a concept is built sequentially, from swift trust, which involves the initial encounter between the research staff and the potential participant (critical to study recruitment), to traditional trust, which is built over time (important for study retention; Otufowora, Liu, Varma et al., Citation2020).

Both Gen Xers and Baby Boomers were better educated than older generations (Culp, Citation2009; Mitchell, Citation2000; Yang & Guy, Citation2006); since education was responsible for some of the generational differences in attitude and behaviors (in addition to historical events; Mitchell, Citation2000; Yang & Guy, Citation2006), then it is not surprising that our study showed a positive relationship between education level (more than a high school education) and both study navigation and enrollment.

This analysis showed a higher likelihood of Blacks being navigated and enrolled in health research compared to whites. This is not a surprising given the theory of reasoned action (that attitudes influence behavior); some studies (Chang et al., Citation2015; Cottler et al., Citation2013) have shown a higher willingness of Blacks compared to whites to participate in specific research types. For example, Cottler and colleagues (Cottler et al., Citation2013) demonstrated that Blacks were more willing than whites to participate in research such as studies requiring participants to give biological samples (blood or genetic samples), stay overnight in a hospital, use medical equipment, and have their medical records reviewed.

Further, we also showed that individuals who had health checkups in the past 12 months were more likely to be navigated and enrolled in health research than those who did not. This finding was not surprising as Baby Boomers constitute a majority (60%) of this study population, and previous studies have shown that older adults in the Baby Boomer generation are more health conscious (Kahana & Kahana, Citation2014) and adept at using the internet to find and evaluate health information compared to the generations before them (Tennant et al., Citation2015); they also generally embrace a health-promoting lifestyle (Cline & Haynes, Citation2001; Kahana & Kahana, Citation2014; Morrow-Howell & Gehlert, Citation2012).

Regarding drug use, the population was comprised of Gen Xers and Baby Boomers who grew up in the 60s and 70s, when marijuana (“pot”) use was gaining popularity (Relman, Citation1982) and was seen as an expression of the drug counterculture and permissive social change. On the other hand, Gen Xers had easier access to marijuana, since they were growing up in a period where the public discourse had been about the legalization of marijuana (Van Ours, Citation2012). Thus, it is not surprising that this analysis found participants who acknowledged lifetime marijuana use were more likely to be navigated into research – especially since it is consistent with the findings of Webb and colleagues (Webb et al., Citation2015) who (used the same dataset as this study) showed in a sample of community-dwelling adults than those who were current or past marijuana users were more willing to participate in research.

This analysis also showed that individuals who endorsed lifetime cocaine use were also more likely to be navigated into a study. The increasing prevalence of cocaine use (John & Wu, Citation2017; Kerridge et al., Citation2019), and the opportunity to participate in cocaine research at UF, may be partly responsible for this increase. Also, since cocaine has been associated with multiple health conditions such as heart problems and strokes (Qureshi et al., Citation2001), perhaps this provided study participants with more research opportunities particularly in specific cocaine-induced pathologies; however this is speculative. Future studies can benefit from examining the existing inconsistencies in the literature on drug use and research participation.

Baby Boomers are adept at using the internet (Tennant et al., Citation2015), and the study population also consisted of Gen Xers, it is not surprising that the present analysis found individuals using social media were more likely to be enrolled in research – a finding consistent with other studies (Cavallo et al., Citation2019; Thornton et al., Citation2016). Moreover, this analysis shows that the participants living in suburban/urban areas were twice as likely to be enrolled in research than those from rural areas, which may be related to the logistical barriers such as access to good transportation which negatively affects research participation (George et al., Citation2014); particularly in rural areas (Smith & Trevelyan, Citation2019). Also, Cottler and colleagues (Cottler et al., Citation2017) demonstrated enhanced study navigation when participants were provided with transportation services to ease the burden of transportation-related logistical barriers to research participation. Further, study participants who reside in Alachua county (one of the highest catchment areas of HealthStreet), an urban college town where an academic center (UF) is located may have more access to research opportunities compared to their counterparts in rural (Salihu et al., Citation2015).

This analysis has some strengths as well as limitations. Regarding limitations, the use of cross-sectional data in generational analysis has its limitations, especially in determining if the differences observed were due to biological aging or generational effects. Studies (Costanza et al., Citation2012; Twenge, Citation2010) have noted the majority of studies on generational differences continue to employ cross-sectional data whilst acknowledging this methodological limitations. Granted, the ideal design to use for generational analysis is the time-lag study design, where different cohorts are interviewed at the same age at different times (Salkind, Citation2010; Twenge, Citation2010; Wong et al., Citation2008); however, the problems of attrition or expenses associated with time-lag studies (or longitudinal studies) explain why few studies (Families and Work Institute, Citation2006; Kowske et al., Citation2010; Twenge & Campbell, Citation2010; Wey Smola & Sutton, Citation2002) have used this design. While a longitudinal study may account for the time and period effects, which are potential confounders, a longitudinal study can’t assess generational change since it interviews the same people (of the same generation) at different times (Salkind, Citation2010). In any case, since attitudes are formed and retained early in life (Low et al., Citation2005; Schaie, Citation1965), the period effect can be minimized. Also, since the generational cutoff years might vary slightly, according to different authorities (Pew Research Center, Citation2015), it is possible that this may influence findings from studies based on the adopted generational cutoffs.

Regarding strengths, the use of the CHW recruitment model engenders trust, thus enhancing the integrity of our data. Also, this study has a high proportion of Blacks, who are often underrepresented in research (Graham et al., Citation2018; Murphy & Thompson, Citation2009). The availability of variables from the social determinants of health and health conditions in community-based research allowed us to control for these important confounders.

Conclusions

This analysis highlighted the existence of generational differences in study enrollment and the importance of trust in research as a predictor of research participation. Particularly, it emphasized the concept of heterogeneity among a large cohort of Baby Boomers into TEBs and LEBs. Thus, there is a study recruitment implication when approaching the different generations and even within the same generational cohort (LEBs vs TEBs); hence, Gen Xers and TEBs may require targeted recruitment modality, effort and time during study recruitment. Of all the covariates at the individual, relationship and community levels of the SEM, the strongest predictor of study navigation and enrollment was the community factor. Participants living in suburban/urban areas were twice as likely to be navigated and enrolled in health research compared to their counterparts in rural areas. It is also important that, in community-based research, regardless of the generational cohort, promoting research studies that are related to common community health conditions and concerns may lead to better research participation among Gen Xers (Campbell et al., Citation2007). Also, sharing results of studies conducted with community members and giving opportunities to participate in the town hall moderated by researchers and healthcare professionals (HealthStreet, University of Florida, Citation2021) may promote trust in the research enterprise and subsequently research participation. Further, while incentivizing studies, the mode of remuneration should be appropriate for the locale, e.g., use of brand gift cards vs. cash payment (Cottler et al., Citation1995; Striley et al., Citation2008). Finally, emphasizing altruism when appropriate is a potential motivation for research participation (Williams et al., Citation2008).

This analysis used cross-sectional data and future studies can assess the same concept of generational cohort, trust and study navigation as well as enrollment using a time-lag study design, where different cohorts can be studied at the same age at different times.(Salkind, Citation2010)

Acknowledgments

The authors would like to thank the staff, volunteers and community health workers at HealthStreet for their roles in data collection and all that they do daily in the community

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by UF-FSU CTSA grant number UL1TR001427. Dr. Otufowora was funded by the Dean’s Scholarship and by the Department of Epidemiology funding from the College of Medicine and College of Public Health and Health Professions. Dr. Otufowora is supported by the Children's Miracle Network Hospitals Grant (FY22 CMN Award).

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