Abstract
Background
There is a lack of racial, ethnic, and sex diversity in recruitment research registries and Alzheimer’s disease (AD) research studies and trials. Theory-based recruitment messages may provide an opportunity to increase study participant diversity in AD research studies and trials.
Objective
To identify behavioral, normative, and control beliefs that are associated with joining an AD-focused recruitment registry among historically underrepresented groups.
Method
Using a Reasoned Action Approach, we conducted 60 semi-structured phone interviews in 2020 among White, Black, and Hispanic adults ages 49–79 years in Philadelphia, PA. Underlying beliefs were elicited for the target behavior of “signing up to be on a registry for brain health research studies in the next month.” Percentages based on counts are reported for the overall sample and by race and ethnicity and sex.
Results
Participants were most concerned that if they were to sign up for a registry, they would be asked to participate in experimental studies. Advancing science to help others was a commonly reported positive belief about signing up. Participants’ children and friends/neighbors were important from a normative perspective. Barriers to enrollment focused on logistical concerns and inconvenient sign-up processes, including using a computer. Results show generally few racial and ethnic or sex group differences.
Conclusion
The elicited beliefs from underrepresented groups offer a basis for understanding the behavior of signing up for research registries. However, there were few differences between the groups. Implications for outreach and recruitment are discussed.
MeSH Keywords: health behavior, Alzheimer’s disease, health communication, attitudes, research participant recruitment
Introduction
Approximately 6.2 million people are living with Alzheimer’s disease (AD) in the United States, projected to reach 13.8 million by 2060 barring a medical breakthrough [1]. Black and Hispanic adults are more likely than non-Hispanic White adults to have AD [2], with Blacks about twice as likely and Hispanics about one to 1.5 as likely than White adults to have AD [3–5]. Starting in 2030, the Hispanic population will have the largest projected increase in prevalent cases of AD and related dementias, followed closely by Black adults [1]. To address this growing public health burden, the National Plan to Address Alzheimer’s Disease was created in 2012 which includes a goal to ‘prevent and effectively treat AD by 2025’. To meet this ambitious goal, researchers will need hundreds of thousands of individuals from diverse communities to participate in clinical research. Participant recruitment registries can play a critical role in engaging, identifying, characterizing, and referring potentially eligible participants to studies [6–9]. Because of the increasing emphasis on identifying the earliest biological and or cognitive changes of the disease and preventing it entirely, AD-focused studies often need to enroll cognitively healthy participants who may be at risk for the disease (e.g., for observational, longitudinal studies or preventative clinical trials) or who provide important data that can be used to compare to data from people with the disease.
In the US, there are several AD-focused participant registries [10–14], many of which require participants to enroll via a website. If participant research registries are going to be critical for AD-focused study recruitment, the registries themselves need to reflect the larger population regarding race and ethnicity and sex diversity. Unfortunately, such is not currently the case, currently; approximately three-quarters of those enrolled in AD-focused registries are White women [12–14]. Although Black and Hispanic adults represent 12% and 16% of the US population, respectively, only 5% and 1% of clinical trial participants across all disease areas are Black and Hispanic [15]. The lack of diversity in clinical research to accurately represent the US population demographic distribution may limit the generalizability of study findings [16, 17] and result in an underestimation of treatment effects [16, 18]. The lack of diversity is particularly evident in the clinical trials of aducanumab, for which the US Food and Drug Administration (FDA) provided accelerated approval for the treatment of AD [17]. It is crucial to examine racial and ethnic minority populations’ perceptions of health research to address salient barriers and facilitators to research participation in these historically underrepresented demographic groups [19, 20].
One potential strategy for recruiting diverse populations is to develop theory-based, culturally sensitive messaging to encourage registry enrollment. Persuasive health messaging is most effective when it incorporates formative research based on the target audience and a clear theoretical framework [21]. Formative research can include focus groups, interviews, or surveys, in addition to sources such as peer-reviewed publications [22]. Using theory to guide formative research leads to the incorporation of theory into the message design and evaluation. Formative research offers opportunities to understand audience beliefs and behaviors as well as preferences for message dissemination (i.e., channels) [21]. This study presents results from semi-structured interviews that were conducted as the first step in a larger outreach message design study to increase enrollment of underrepresented groups into AD-focused participant recruitment registries. The interviews used the Reasoned Action Approach to understand what factors influenced participants’ decision to join an AD-focused participant recruitment registry.
Theoretical Framework
The Reasoned Action Approach (RAA) [23] is a psychosocial model of behavior that synthesizes the Theory of Reasoned Action [24], Social-Cognitive Theory [25], the Health Belief Model [26, 27], and the Theory of Planned Behavior [28]. The focus of the model is one’s intention to perform a specific behavior (the “target behavior,” i.e., joining an AD recruitment registry) as both a dependent variable and as a predictor of behavior. That is, the model is concerned with the factors influencing intention formation and the relationship between intentions and subsequent performance of the target behavior [29]. The RAA assumes that behavior is primarily determined by intentions and has been useful for developing media messages that evoke target behaviors [30]. Essentially, RAA-based communication strategies are designed to reinforce the beliefs that are positively associated with intention and counter-argue the beliefs that are negatively associated with intention [31–34]. According to RAA, changing behavior requires affecting relevant beliefs and barriers. RAA has been used to develop messaging for numerous health behaviors, including sugary drink consumption [33], indoor tanning cessation [35, 36], health care seeking for cognitive health [37], and recruitment into a glaucoma genetic study [38].
Intention formation is a function of one’s attitudes (i.e., the degree of favorableness or unfavorableness towards personally performing the behavior), perceived normative pressure (i.e., perceptions about what others think and do with regards to performing the behavior), and perceived behavioral control/self-efficacy (i.e., beliefs about one’s ability to perform the behavior assuming that one wanted to do so). Each construct is determined by a corresponding set of salient and potentially modifiable underlying beliefs; changes in beliefs and associated direct measures should work through the RAA model via intention to change behavior [30, 39, 40].
The focus of this study is to identify behavioral, normative, and control beliefs that are relevant to joining an AD-focused recruitment registry in our target audiences: Black, Hispanic, and male older adults. We conducted elicitation research [23, 41] in the form of semi-structured interviews with 60 adults ages 49–79 years old in and around Philadelphia, PA. The research questions were as follows: RQ1: What are the prevailing attitudinal, normative, and efficacy beliefs about joining a brain health registry? RQ2: How do beliefs vary by race and ethnicity and by sex?
Materials and Methods
Data were collected as part of a larger project, Study to Expand registry Participation of Underrepresented Populations (STEP-UP), to design theory-based persuasive messages to enroll diverse participants into recruitment registries connecting members to AD prevention trials and other AD-focused studies. The first step in this process was to conduct elicitation research among the identified audience subgroups. The beliefs identified from the elicitation study were used to create an RAA quantitative survey for the target behavior of joining a recruitment research registry. Results from the subsequent survey will be reported in a separate manuscript.
Sample.
Participants were purposively recruited using both in-person and remote strategies, with active and passive methods. Recruitment efforts included recruitment drives in-person at community senior centers, advertising in local newspapers and on Craigslist, as well as snowball recruitment based on referrals from other study participants. In-person recruitment was minimal, however, due to the timing of the study and the COVID-19 pandemic. Sixty semi-structured interviews and surveys were conducted with adults from January through June 2020. Inclusion criteria included age (between the ages of 49 and 79) and racial and ethnic group (Black, White, or Hispanic). Quotas were imposed for each racial and ethnic group (n=20 per group) and for sex (n=30 per group). Sample demographics, family history of AD, and access to technology and the internet can be found in Table 1.
Table 1.
Sample demographics
| Demographics | Sample (n=60) | Black (n=20) | White (n=20) | Hispanic (n=20) | Male (n=30) | Female (n=30) |
|---|---|---|---|---|---|---|
| % | ||||||
| Age | Mean 62.2 SD (9.25), range 49–79 years | 61.5 (8.51) | 67.9 (8.18) | 56.9 (7.71) | 59.47 (8.75) | 64.7 (9.01) |
| Marital Status | ||||||
| Married | 26.7 | 10.0 | 15.0 | 55.0 | 33.3 | 20.0 |
| Member of unmarried couple | 5.0 | 5.0 | 5.0 | 5.0 | 10.0 | 0.0 |
| Divorced/separated | 33.3 | 35.0 | 40.0 | 25.0 | 26.7 | 40.0 |
| Widowed | 8.3 | 5.0 | 10.0 | 10.0 | 3.3 | 13.3 |
| Never married | 26.7 | 45.0 | 30.0 | 5.0 | 26.7 | 26.7 |
| Education level | ||||||
| Did not complete high school | 1.7 | 0.0 | 5.0 | 0.0 | 3.3 | 0 |
| High school graduate or GED | 10.0 | 10.0 | 10.0 | 10.0 | 10.0 | 10.0 |
| Some college | 18.3 | 30.0 | 10.0 | 15.0 | 23.3 | 13.3 |
| Associate or technical degree | 23.3 | 40.0 | 10.0 | 20.0 | 16.7 | 30.0 |
| Bachelor’s degree | 26.7 | 5.0 | 30.0 | 45.0 | 33.3 | 20.0 |
| Graduate degree | 20.0 | 15.0 | 35.0 | 10.0 | 26.7 | 13.3 |
| Current employment status | ||||||
| Unable to work | 5.0 | 10.0 | 0.0 | 5.0 | 6.7 | 3.3 |
| Unemployed | 11.7 | 5.0 | 5.0 | 25.0 | 13.3 | 10.0 |
| Part-time | 8.3 | 20.0 | 5.0 | 0.0 | 3.3 | 13.3 |
| Full-time | 28.3 | 20.0 | 15.0 | 50.0 | 20.0 | 36.7 |
| Retired | 45.0 | 45.0 | 70.0 | 20.0 | 60.0 | 30.0 |
| Family history of Alzheimer’s disease or dementia | ||||||
| Yes | 36.7 | 50.0 | 25.0 | 35.0 | 23.3 | 50.0 |
| Not sure | 11.7 | 15.0 | 15.0 | 5.0 | 13.3 | 10.0 |
| Previous participation in research related to Alzheimer’s disease or dementia | ||||||
| Yes | 0 | - | - | - | - | - |
| Not sure | 1.7 | 0.0 | 0.0 | 5.0 | 0.0 | 3.3 |
| Previous participation in any medical research | ||||||
| Yes | 13.3 | 15.0 | 15.0 | 10.0 | 10.0 | 16.7 |
| Not sure | 0 | - | - | - | ||
| Previous participation in a research registry | ||||||
| Yes | 11.7 | 10.0 | 20.0 | 5.0 | 10.0 | 13.3 |
| Not sure | 6.7 | 0.0 | 5.0 | 15.0 | 6.7 | 6.7 |
| Ever use of internet or email at home | 90.0 | 90.0 | 85.0 | 95.0 | 86.7 | 93.3 |
| Cell phone ownership | 93.3 | 100.0 | 80.0 | 100.0 | 93.3 | 93.3 |
| Smartphone ownership | 88.3 | 100.0 | 70.0 | 95.0 | 93.3 | 83.3 |
| Tablet ownership | 46.7 | 30.0 | 30.0 | 80.0 | 46.7 | 46.7 |
| Desktop or laptop computer ownership | 68.3 | 45.0 | 75.0 | 85.0 | 70.0 | 66.7 |
Protocol.
The interviews lasted an average of 30 minutes and were conducted over the phone by researchers (M.N. and E.A.) from the Mixed Methods Research Lab (MMRL) at the University of Pennsylvania; MMRL researchers were trained by study investigators on RAA elicitation. Audio from the interviews was transcribed by Datagain Transcription Services; transcripts were then cleaned of identifying information. The interview guide was developed based on the RAA constructs and included a teach-back section to screen participants before the start of the interview, a series of close-ended questions to identify participant characteristics, and open-ended questions to elicit beliefs. As part of the informed consent process, all potential participants completed a teach-back session that explained the function and purpose of AD-focused research registries. In the teach-back section, the interviewer explained three key points: 1.) Signing up for a registry requires that participants share some personal information such as their name, date of birth, and contact information; 2.) Individuals who sign up for a registry will be connected to research studies, and; 3.) Participation in any given study is optional; participants are not required to take part in any studies they are invited to. Participants were required to pass the teach-back by demonstrating that they understood these three key aspects of brain health registries before proceeding with the rest of the interview. This served to ensure that participants would be able to answer interview questions appropriately.
Measures.
At the beginning of the interview, respondents completed a series of close-ended questions that included standard demographics, family history of dementia or AD, and frequency of computer use. Then, the research team asked open-ended questions that corresponded to each theoretical construct (attitudes, norms, and perceived control), and incorporated positive and negative framing. The interview measures are shown in Table 2. Supplemental probes were provided, and researchers were trained to probe further as needed. The interviews asked about three different behaviors relevant to research registries: “signing up to be on a registry for brain health research studies”, “giving a DNA sample to a registry for brain health research studies”, and “completing memory and thinking tests every 6 months for a registry for brain health research studies.” Here we report on the findings from only the first behavior—signing up to be on a registry. Following the elicitation measures, the interview concluded with questions on health information seeking in general and on social media use.
Table 2.
Interview measures
| Construct | Measure |
|---|---|
| Attitudes (expectancies) | What are good things that could happen if you were to sign up for a registry for brain health research studies? |
| What are bad things that could happen if you were to sign up to be on a registry for brain health research studies? | |
| Normative Pressure (normative referents) | Who would approve of you signing up to be on a registry for brain health research studies? |
| Of these people, about how many of them do you think would sign up to be on a registry for brain health research studies? | |
| Perceived behavioral control/self-efficacy (barriers and facilitators) | What might make it easy for you to sign up to be on a registry for brain health research studies? |
| What might make it difficult for you to sign up to be on a registry for brain health research studies? |
Analysis.
A codebook was developed by the study investigators with input from MMRL. The transcripts were uploaded to NVivo 12 Plus, a qualitative analysis software. Two researchers (M.N. and E.A.) applied the codebook to the transcripts and periodically refined the themes and definitions based on inter-rater reliability tests (ĸ=.89) to facilitate analysis. Approximately 20% of the final sample was double coded before coding the full set of interviews. Simple counts (percentages) were used to record how often particular beliefs were mentioned by participants. Beliefs mentioned by at least 10% of a particular subgroup were selected for inclusion in the subsequent quantitative survey [23].
Results
Participant demographics and previous experience with research are shown by racial and ethnic group and by sex in Table 1. In general, participants were highly educated, with 90% having received some education after high school. Most were either never married (26.7%), married (26.7%), or divorced (33.3%). Forty-five percent of participants reported being retired and 28.3% currently worked full-time. Over one-third of the sample (36.7%) reported a family history of AD and 11.7% reported previous participation in a research registry.
What are the prevailing attitudinal, normative, and efficacy beliefs for signing up to be on a registry for brain health research?
Attitudinal (behavioral) beliefs.
The specific beliefs for each RAA construct are shown in Table 3 by race and ethnicity and Table 4 by sex. The most frequently reported “bad thing” that would happen if participants were to sign up for a registry was being asked to participate in a study with an experimental drug that carried a potential risk of adverse outcomes.
Table 3.
Prevalence of elicited beliefs by racial/ethnic group
| Belief | Total | Black (n=20) | White (n=20) | Hispanic (n=20) |
|---|---|---|---|---|
| Behavioral beliefs | % | % | % | % |
| “Bad things that would happen” | ||||
| Concern for privacy | 15.0 | 10.0 | 10.0 | 25.0 |
| Being asked to participate in study with experimental drug or other treatment | 40.0 | 45.0 | 30.0 | 45.0 |
| Lack of transparency | 3.3 | 10.0 | 0 | 0.0 |
| Misuse or mismanagement of data | 11.7 | 10.0 | 10.0 | 15.0 |
| Confronting personal cognitive decline | 10.0 | 10.0 | 10.0 | 10.0 |
| Pressure to join study | 8.3 | 5.0 | 15.0 | 5.0 |
| Nothing or don’t know | 20.0 | 20.0 | 25.0 | 15.0 |
| “Good things that would happen” | ||||
| Advance science or find a new discovery | 60 | 65.0 | 60.0 | 55.0 |
| Help others | 36.7 | 45.0 | 20.0 | 45.0 |
| Improve personal health or memory | 21.7 | 20.0 | 30.0 | 15.0 |
| Personal interest or novelty | 21.7 | 15.0 | 40.0 | 10.0 |
| Track personal progress or brain health over time | 10.0 | 10.0 | 10.0 | 10.0 |
| Important normative referents | ||||
| Spouse or partner | 23.3 | 15.0 | 15.0 | 40.0 |
| Children | 36.7 | 40.0 | 20.0 | 50.0 |
| Siblings | 23.3 | 30.0 | 20.0 | 20.0 |
| Friends or neighbors | 28.39 | 30.0 | 25.0 | 30.0 |
| Extended family | 21.7 | 25.0 | 15.0 | 25.0 |
| Healthcare provider | 5.0 | 0 | 5.0 | 10.0 |
| Facilitators | ||||
| Convenience | 26.7 | 25.0 | 25.0 | 30.0 |
| Modality | 35.0 | 50.0 | 25.0 | 30.0 |
| Providing written information | 36.7 | 40.0 | 45.0 | 25.0 |
| Results transparency | 1.67 | 0 | 5.0 | 0 |
| Barriers | ||||
| Enrolling would be demanding or difficult | 10.0 | 15.0 | 5.0 | 10.0 |
| Health problems | 3.33 | 10.0 | 0 | 0 |
| Inconvenient | 23.3 | 25.0 | 25.0 | 20.0 |
| Technology or computer | 16.7 | 15.0 | 25.0 | 10.0 |
| Transportation | 6.7 | 5.0 | 5.0 | 10.0 |
| Having to travel to a physical location | 10.0 | 10.0 | 15.0 | 5.0 |
| Lack of information | 10.0 | 5.0 | 20.0 | 5.0 |
| Medication side effects | 5.0 | 0 | 5.0 | 10.0 |
| Nothing or don’t know | 18.3 | 25.0 | 25.0 | 5.0 |
Table 4.
Prevalence of elicited beliefs by sex
| Belief | Total | Male (n=30) | Female (n=30) |
|---|---|---|---|
| Behavioral beliefs | % | % | % |
| “Bad things that would happen” | |||
| Concern for privacy | 15.0 | 13.3 | 16.7 |
| Being asked to participate in study with experimental drug or other treatment | 40.0 | 50.0 | 30.0 |
| Lack of transparency | 3.3 | 3.3 | 3.3 |
| Misuse or mismanagement of data | 11.7 | 6.7 | 16.7 |
| Confronting personal cognitive decline | 10.0 | 13.3 | 6.7 |
| Pressure to join study | 8.3 | 6.7 | 10.0 |
| Nothing or don’t know | 20.0 | 20.0 | 20.0 |
| “Good things that would happen” | |||
| Advance science or find a new discovery | 60.0 | 60.0 | 60.0 |
| Help others | 40.0 | 40.0 | 33.3 |
| Improve personal health or memory | 21.7 | 16.7 | 26.7 |
| Personal interest or novelty | 21.7 | 20.0 | 23.3 |
| Track personal progress or brain health over time | 10.0 | 13.3 | 6.7 |
| Important normative referents | |||
| Spouse or partner | 23.0 | 20.0 | 13.3 |
| Children | 36.7 | 20.0 | 53.3 |
| Siblings | 23.3 | 33.3 | 13.3 |
| Friends or neighbors | 28.3 | 16.7 | 40.0 |
| Extended family | 21.7 | 20.0 | 23.3 |
| Healthcare provider | 5.0 | 6.7 | 3.3 |
| Facilitators | |||
| Convenience | 26.7 | 30.0 | 23.3 |
| Modality | 35.0 | 30.0 | 40.0 |
| Information | 36.7 | 40.0 | 33.3 |
| Results transparency | 1.67 | 0 | 3.3 |
| Barriers | |||
| Enrolling would be demanding or difficult | 10.0 | 13.3 | 6.7 |
| Health problems | 3.33 | 3.3 | 3.3 |
| Inconvenient | 23.3 | 36.7 | 10.0 |
| Technology or computer | 16.7 | 16.7 | 16.7 |
| Transportation | 6.7 | 0 | 13.3 |
| Having to travel to a physical location | 10.0 | 10.0 | 10.0 |
| Lack of information | 10.0 | 16.7 | 3.3 |
| No access to test results | 0 | 0 | 0 |
| Medication side effects | 5.0 | 6.7 | 3.3 |
| Nothing or don’t know | 18.3 | 16.7 | 20.0 |
“Negatives will probably be how people react to certain drugs or medication. That would be not only a negative, but a concern I would have. And I would be unlikely to participate in a study that required that I try some sort of pharmaceutical that is experimental.”
(Hispanic male, age 59 years)
The second most frequently mentioned concern was that registry information could be compromised or mismanaged in some way.
“The first thing that comes to my mind, right away, is that the information somehow gets leaked. Your personal information gets leaked to an insurance company, and it could impact your insurance coverage going forward.”
(White male, age 65 years)
Other negative sentiments included concerns about privacy, being pressured to join a study, and having to confront one’s cognitive decline. Twelve participants (20.0% of the full sample) could not think of any negative outcomes associated with signing up for a research registry.
The “good things” associated with joining a registry pertained to personal interest or benefits to society at large. Responses mentioning advancing science or finding a new discovery, or generically “helping others” were categorized as a benefit to society at large. Personal interest beliefs included improving health or memory, perceiving registries as an appealing novelty or fulfilling a personal interest, and the opportunity to track one’s brain health over time.
“Well, the information that they find could potentially be useful to me [or] useful to others. I would just say their research. I mean, what information they’re able to find or any kind of training or discoveries or findings based off analyzing [the data].”
(Hispanic male, age 51)
Normative referents.
Although respondents were asked who might approve or disapprove of their enrollment in a registry, most reported that no one in their life would disapprove of their participation. The referent groups identified as important in their lives, in general, were friends and neighbors, spouses, children, siblings, extended family, and health care providers. Children of the participants were cited most frequently (36.7%) and only 5.0% cited healthcare providers.
Barriers and facilitators (efficacy beliefs).
In general, participants identified few barriers to signing up for a research registry for brain health. Respondents explained that certain methods were inconvenient, such as having to use a computer, and were a deterrent to participation. Methods that enhanced convenience were very important facilitators of registry enrollment, including being able to participate from home, and specifically over the phone. Others noted it would be helpful to have access to written information about the registry or studies to assist in the decision-making process before committing. For example, one participant said:
“ I’m funny on the phone, sometimes, because all of the weird stuff that goes on. But if they would send me a letter inviting me and giving me a little information on what it is that they want- [the] information they want and how they want to do it. If they want to call me on the phone and do a survey, so just what you’re doing now. I wouldn’t mind, but I would have to have some information beforehand, okay? So, I could be able to read it and see if I [would] be interested in it. And then I [would] respond back via a telephone call or something like that.”
(Black woman, age 69 years)
Less tech-savvy participants specifically commented that being able to participate using modalities other than computers or smartphones would be critical.
How does the prevalence of elicited beliefs vary by race and ethnicity and by sex?
There were few notable differences in the prevalence of beliefs in all three domains across racial and ethnic groups. Black (45%) and Hispanic (45%) participants were more likely than White participants (30%) to report that a “bad thing” about enrolling would be being asked to participate in an experimental or invasive treatment. White participants (15%) were more likely than either Black (5%) or Hispanic (5%) participants to report that enrolling might result in feeling pressure to join a study. More Black (45.0%) and Hispanic (45%) participants cited “helping others” by participating in studies that could make scientific advancements as a “good thing” about enrolling compared to White participants (20%). White participants were more likely to report that enrolling would improve their health or memory (30%) and that it would be personally interesting or novel (40%). How to sign up or what technology is needed to sign up (other than a computer) was more important for Black participants (50.0%), compared to White (25%) or Hispanic participants (30%). Finally, 20% of Whites respondents mentioned a lack of information about the registry and/or enrollment process, compared to 5% of Black and Hispanic participants.
Regarding differences between men and women, men were almost twice as likely as women to mention the process of signing up for a registry being demanding or difficult as a barrier. Compared to men, women were more concerned about the misuse or mismanagement of data (6.7% versus 16.7%, respectively). Men (13.3%) were more likely than women (6.7%) to mention confronting personal cognitive decline as a bad thing that could happen if they were to participate. However, more men also believed enrolling would allow them to track their personal progress or brain health over time (13.3%) compared to women (6.5%), which was viewed as positive. Men and women equally reported (60% each) that advancing science was a good thing that would happen if they were to enroll. More women cited their children (53.3%) as important normative referents compared to men (20%); men mentioned healthcare providers (6.7%) more than women (3.3%). Men (36.7%) were more concerned about lack of study information and enrollment inconveniences, compared to women (10%). Only women (13.3%) mentioned transportation as a barrier.
Discussion
AD-focused participant recruitment registries have failed to recruit participants from underrepresented groups. Behavioral theory can be used to identify beliefs associated with registry enrollment behavior to inform persuasive recruitment messages. Formative research is a key component in the creation of effective messaging. The Reasoned Action Approach dictates that the elicitation of behavioral, normative, and control beliefs from the target audience(s) are necessary steps in ascertaining potentially modifiable beliefs to target in media campaigns. In this study, we elicited beliefs from Black, Hispanic, and White older adults who were not currently members of a research registry and were research naïve, whereas other studies tend to recruit convenience samples from their clinic or existing registry. Participants indicated that joining a research registry would be a largely positive experience, supported by important others, and could be facilitated by addressing practical concerns. Differences among racial and ethnic groups and between men and women were only evident on select beliefs, most of which met the threshold to be considered for further quantitative research.
Being asked to participate in a study with an experimental drug or other potentially invasive treatment was a consideration across all subgroups, but more so for Black and Hispanic adults and for men. This is consistent with a history of medical experimentation and mistrust in underrepresented racial and ethnic minority groups, although medical mistrust or mistrust in medical research was not mentioned directly. Concerns about drug safety and a history of discrimination may contribute to these beliefs [42, 43], as well as perceptions of feeling like a “guinea pig” [44]. However, respondents from our community sample seemed unaware that they can choose whether to join a particular study for which they are eligible. This reflects a larger issue that became apparent throughout the interviews, which was participants’ general unfamiliarity with research registries and the research process. Only 13.3% of the sample indicated they had previously participated in medical research; 11.7% reported previously being enrolled in a research registry. Although those who were interviewed passed an initial teach-back after the function and purpose of research registries were explained, more detailed knowledge of registries among older adults in this sample might have resulted in different beliefs being elicited. After completing subsequent analyses, if being asked to participate in experimental treatments is identified as a salient belief, it will be useful for messaging to reiterate enrollees’ autonomy in deciding which studies to join. These findings emphasize the importance of consent practices for informing potential participants’ obligations and rights when enrolling in a registry and other research efforts.
Other important behavioral beliefs centered around more altruistic reasons, like advancing science or helping others, compared to beliefs that focused on personal interest, like improving personal health or memory or tracking personal progress on cognitive assessments or brain health over time. Unfortunately, registries do not necessarily have the capacity to allow participants to track their health, although given the interest from participants, it may be a feature that could be incorporated to increase interest among potential participants. And somewhat surprisingly, misuse of data or privacy concerns were only mentioned by 15% of the sample or less.
Barriers and facilitators elicited from respondents focused on practical concerns and/or logistical issues such as the provision of written information and the ability to enroll over the phone. Having to use a computer or other devices like tablets was raised as a barrier, which is concerning, given that enrollment for nearly all AD-focused registries occurs online. Numerous studies that indicate structural factors like the ones reported here are barriers to Black participation in research [45–47]. One facilitator that was not commonly reported was results transparency, specifically, how knowing the results of studies or assessments might increase participation. It is of note that results transparency was not identified as a facilitator but ability to track one’s progress was a frequently cited behavioral belief.
Many of the elicited beliefs from participants in underrepresented groups echo research that demonstrates a lack of trust in medical research and researchers [42, 47–49] and beliefs about being pressured [50] are factors in willingness to participate. Other barriers, such as economic and health insurance factors, were not elicited despite being raised as possible impediments to clinical research participation in other studies [20, 51]. Altruism (e.g., would help others like me) is often a motivator [46, 52, 53] for participation, and was apparent here in many of the elicited behavioral beliefs. Unlike many other studies, perhaps except for Glover et. al (2018), racial differences in some of these beliefs and facilitators were not as apparent as anticipated.
Limitations.
Participants were recruited from a metropolitan area with a highly visible health system that focuses on teaching and research, and although we implemented our best efforts to avoid this bias, it may be that experiences with this system influenced ideas about research participation that would not be found in other urban or rural areas. Also, those who agreed to be interviewed were likely predisposed to having more positive attitudes about research and participating in research, which may have elicited more positive beliefs. It is also possible that beliefs about participating may change over time depending on life circumstances, and these interviews took place at a singular point in time. Finally, our planned recruitment strategies involving working with community organizations were altered due to the COVID-19 pandemic, which may have changed the composition of our sample. For example, respondents in the sample were more highly educated than the average American, and therefore higher health literacy, which is associated with more positive attitudes towards research [54].
Conclusion
Effective message design requires formative research among the target audience, ideally guided by a theoretical framework. Using RAA, we conducted an elicitation study among cognitively healthy older adults to ascertain beliefs about joining research registries. There were few differences across racial and ethnic groups and between men and women, but key beliefs emerged that can potentially be incorporated into outreach messages to encourage enrollment into AD-focused registries. Further quantitative research such as a national survey to identify which beliefs are relevant to intention formation (i.e., joining a registry) within each race and ethnicity and sex group is warranted.
Acknowledgements
This paper was made possible by Grant No. R01AG063954 from the National Institute of Aging (NIA). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH/NIA. The authors would like to thank Drs. Jason Karlawish, Emily Largent, and Shana Stites for their assistance with drafting the interview guide.
Conflict of Interest/Disclosure Statement
Jessica Langbaum has received consulting fees from Alector, Biogen, and Provoc.
Amy Bleakley, Erin Maloney, Kristin Harkins, Maria Nelson, and Eda Akpek have no conflict of interest to report.
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