Communication and Recruitment to Clinical Research Studies
Summary and Keywords
Strategic communication is an essential component in the science and practice of recruiting participants to clinical research studies. Unfortunately, many clinical research studies do not consider the role of communication in the recruitment process until efforts to enroll patients in a timely manner have failed. The field of communication is rich with theory and research that can inform the development of an effective recruitment plan from the inception of a clinical research study through informed consent. The recruitment context is distinct from many other health contexts in that there is often not a behavioral response that can be universally promoted to patients. The appropriateness of a clinical research study for an individual is based on a number of medical, psychological, and contextual factors, making it impossible to recommend that everyone who is eligible for a clinical research study enroll. Instead, clinical research study recruitment efforts must utilize strategic communication principles to ensure that messages promote awareness of clinical research, maximize personal relevance, minimize information overload, and facilitate informed choice. This can be accomplished through careful consideration of various aspects of the communication context described in this chapter, including audience segmentation, message content, message channels, and formative, process, and outcome evaluation, as well as the enrollment encounter.
Keywords: health communication, clinical research, clinical trials, patient recruitment, cancer communication, message design, translational communication, patient navigation, tailoring, eHealth, mHealth
Clinical research is essential for translating biomedical discoveries into patient care (Byrne, Tannenbaum, Gluck, Hurley, & Antoni, 2014). However, access to new treatments is often slow due to the difficulties in recruiting patients to research studies. Less than 5% of cancer patients in the United States participate in clinical research studies, with even lower rates for ethnic minorities (Jimenez et al., 2013). As a result, approximately 75% of investigators do not meet their enrollment goals, and 90% fail to meet their recruitment goals within the expected time period (Institute of Medicine (US) Forum on Drug Discovery, Development, and Translation, 2010). For this reason, Rorie, Flynn, McConnachie, Mackenzie, and Macdonald (2015) have described patient recruitment as, “The most important, most difficult, and least predictable aspect of clinical trials” (p. 325).
Overview of Clinical Research
Clinical research is the scientific study of human disease using human subjects, human populations, or materials from humans, with the goal of comparing outcomes of different interventions on human health (Rubio et al., 2010). The types of clinical interventions tested in research studies can include medical products (e.g., drugs, devices), procedures, or behavior change (e.g., diet), and can occur across the wellness spectrum (Röhrig, du Prel, Wachtlin, & Blettner, 2009). Some interventions are designed to help people prevent disease. For example, researchers may be interested in how physical activity or healthy eating reduce an individual’s risk for cancer. Other interventions are designed to aid in the early diagnosis of an illness or disease, when treatment might be more effective. Some interventions intend to improve medical therapies for people who have a disease or illness (treatment interventions), while others are designed to help people cope with their disease or illness through medications to manage side effects, or activities to assist with psychosocial adjustment (quality-of-life interventions).
There are two methods for comparing outcomes in clinical research (Grimes & Schulz, 2002). Observational (also called noninterventional) clinical studies refer to research in which patients receive an intervention as part of their routine medical care. This means that the decision as to whether or not a patient will receive a particular intervention is based on the discretion of the healthcare provider (HCP) and patient. Conversely, clinical trials (also called interventional studies) refer to research studies in which the treatment a patient receives is determined by the research plan developed by the study investigators and not by a patient’s HCP. In some cases, such as when clinical trials are used to develop new treatments, the term phase is used to describe the type of research plan being used.
Phases of Clinical Trials
Within clinical trials, there are four distinct phases, or types of intervention designs (Pocock, 2013). Phase I clinical trials are conducted to determine the safety of a new treatment. This phase includes a small number of patients (typically 15–30), who can have different types of disease; this phase helps researchers determine what dose of the new treatment patients should be given and the best way to give it (e.g., by mouth, through a vein). Phase II clinical trials are conducted to determine the effect of a new treatment on the disease or illness it is designed to treat. This phase usually involves less than 100 patients. Phase III clinical trials use an experimental research plan to compare the effectiveness of the new drug as compared to an existing treatment. In an experimental research plan, patients are picked at random to either receive or not receive the new treatment. In some cases, placebos may be used in Phase III clinical trials, but only in addition to an effective treatment if one exists. Phase III clinical trials typically enroll between 300 and 3,000 patients. Finally, Phase IV clinical trials, conducted after a treatment receives approval to be sold to patients, monitor the long-term outcomes associated with a treatment. Typically, clinical recruitment is most challenging in Phases I–III and is the primary focus of studies that seek to determine how researchers may efficiently identify and confirm consent of a sufficient number of patients to participate in their studies. Next, we turn to a discussion of the factors that present core communication challenges in the realm of participant recruitment.
Reconceptualizing Recruitment Barriers as Communication Challenges
The ongoing challenges to patient accrual in clinical research studies has resulted in numerous investigations into barriers to participation as well as factors that facilitate enrollment (for a review, see Mills et al., 2006). A common feature of this literature is conceptualizing the success of recruitment efforts as whether or not an individual consents to participate in a research study. This approach has an intuitive appeal because it corresponds directly to the strategic goal of patient enrollment in a study. A potential problem with this perspective, however, is that effective recruitment plans become synonymous with accrual, rather than awareness, facilitating comprehension of the treatment options and promoting informed decision-making. We propose reframing recruitment as a communication process, to gain a more complete understanding of the challenges and opportunities inherent in developing and disseminating effective messages that empower patients to make decisions about participating in clinical research. Next, we provide an overview of each step of the recruitment process.
Clinical Research Recruitment Process
Research recruitment is a task that requires complex communication. Although the desired endpoint is accrual to a particular clinical study, researchers are ethically bound by Institutional Review Boards to provide potential participants with the opportunity to make an informed choice about whether to enroll. As with all strategic messages, the clinical research recruitment process begins with audience segmentation and identification of whom recruitment messages are intended to reach. The content of the recruitment messages should be designed for these audiences. Then, consideration must be given to how message content can be most effectively disseminated to target audiences and the degree to which recruitment messages can and should be customized to the recipients. Once that has been determined, we discuss strategies for pretesting recruitment materials for effectiveness as well as potential unintended outcomes. Finally, we overview the importance of evaluation of outcomes after recruitment efforts have launched in order to understand the failure or success of that strategy, and inform future efforts.
Audience segmentation is an important, but commonly overlooked factor in the design of clinical research recruitment efforts (for a notable exception, see Quinn et al., 2013). For many, it may seem obvious that the intended audience for recruitment would be patients who are eligible to participate on a particular protocol. While medical eligibility is one factor, there are many others to consider, such as potential variation in the demographic composition of the target audience (e.g., race, ethnicity, payer status, age, gender, language), psychographic composition (e.g., attitudes toward clinical research, message channel preferences), and abilities (e.g., health literacy, numeracy). We can add another level of complexity by considering non-patients (e.g., primary healthcare provider, family members) as potential audiences for recruitment messages because they may influence a patient’s decision-making process or may become a patient in the future (Krieger et al., 2015). These additional audiences are important not only at the beginning of the recruitment process, when researchers are trying to raise awareness of the opportunity to participate, but also during the informed consent phase, when patients make their final decision about whether or not to enroll in a study.
Obtaining a demographically representative sample in clinical studies is often a challenge. Even when participants from underrepresented groups are included, many studies do not include a large enough sample for comparisons to be made with the majority group (Hall, 1999). This can have serious consequences for study results, which can only be generalized to the degree that the research participants are representative of the groups of people suffering from the disease (Di Maio & Perrone, 2003). Recruitment efforts designed to reach patients from underrepresented groups should be sensitive to the social and historical factors that have contributed to a lack of representation. For example, the perceived risks (i.e., unknown side effects, reduced treatment efficacy) associated with clinical research participation may be more salient among patients who are members of medically underserved groups in which clinical research participation has been historically low, such as rural Appalachians and ethnic minorities (Baquet, Commiskey, Daniel Mullins, & Mishra, 2006).
Although clinical studies are essential to the development of new and more effective treatments for diseases, public attitudes toward research are often negative. Some of the negative attitudes are based on egregious examples of investigator negligence in the conduct of clinical research. For example, concern about the safety of clinical research increased following the death of Ellen Roche in 2011, a healthy volunteer who died as a result of participating in a study at Johns Hopkins University. Other well-known examples of investigator misconduct include a 1930’s study on the progress of untreated syphilis with African American men, a 1950’s study designed to investigate the psychological effects of LSD on soldiers in the U.S. Army, and a study of the human immune system, in which prison inmates and the terminally ill were injected with live cancer cells.
Negative attitudes toward clinical research are not the only barrier preventing patients from enrolling. Four additional barriers that can impede accrual of particular patient populations include knowledge, fiscal, cultural, and access (Durant et al., 2014; Hawk et al., 2014; Symonds, Lord, Mitchell, & Raghavan, 2012). Knowledge barriers among patients are defined as both a lack of comprehension of what cancer is and the different treatment modalities available. By contrast, knowledge barriers among providers include insufficient knowledge of the specifics of cancer in ethnic minority populations as a result of years of underrepresentation in clinical research. This problem is compounded by a lack of local and national databases to monitor disparities in care and implement community outreach programs. Fiscal barriers include patient concerns about the cost of treatment provided through a clinical study or the future costs if the treatment is proven to be successful. Moreover, many potential participants lack the professional support and financial stability to be able to miss time from work to participate in clinical research.
In some cases, potential participants may be dissuaded from participation based on factors associated with their cultural group membership, which we refer to as cultural factors. A recent meta-analysis identified mistrust as a major factor inhibiting participation in clinical research among African Americans, Latinos, Asian Americans, and Asian-Pacific Islanders in clinical research (George, Duran, & Norris, 2014). Although the importance of mistrust was common across groups, the specific concerns of each ethnic group differed. For example, African Americans were more likely to be concerned that research would benefit whites and not people of color, while Native Hawaiians were concerned that the research would benefit the investigator’s research agenda but not the community. Examples of access barriers, the fourth type of barrier, might include a patient’s lack of a primary healthcare provider to give referrals, or the logistics associated with a research study, such as transportation to and from appointments.
Once researchers understand their intended audience and the potential barriers to recruiting that audience, the next step is developing effective, culturally sensitive recruitment messages. To do so, we will consider various strategies for the development of message content, such as the degree of customization to individual patients, and review literature on linguistic considerations associated with recruitment messages.
An important feature of message content is the degree to which it is customized to the receiver. Over the last 50 years, messages in the communication environment have become increasingly adapted to the unique characteristics of the individual for whom they are intended. The proliferation of message customization has been driven primarily by technological advances. One form of customization is to identify group-level characteristics of patients and use those similarities to construct messages addressing the specific information needs of the intended audience. The practice of designing messages for particular audience segments is known as message targeting (Kreuter, Strecher, & Glassman, 1999; Noar, Harrington, Aldrich, & Beck, 2009). Targeting can focus on the demographic, geographic, cultural, risk, and cognitive factors of a patient subgroup. Targeted health messages have proven to be more successful at changing attitudes and behaviors across a myriad of health topics than the mass dissemination of health messages (Noar et al., 2009).
The inception of interactive technology has brought with it the ability to create and disseminate highly customized, culturally sensitive, patient-specific behavioral interventions more easily and cost effectively than ever before. As a result, recruitment interventions can now be designed to determine which components of a message work best for a particular individual (Hawkins, Kreuter, Resnicow, Fishbein, & Dijkstra, 2008). The practice of designing messages for a particular individual is known as message tailoring (Kreuter et al., 1999; Noar et al., 2009).
The process of message tailoring begins with designing survey questions that measure key attitudinal and behavioral predictors. Algorithmic survey software has the capacity to generate dynamic text that reflects key survey responses, allowing messages to be constructed that are instantaneous and personally relevant. Tailored messages are commonly disseminated through a variety of media channels including SMS (short message service) text messages, e-mail, social media, and eHealth/mHealth applications (Lustria et al., 2013). Disseminating messages that reframe an individual patient’s misperceptions of clinical research to reduce their fear and distrust, or to promote greater comprehension of what clinical research entails, can reduce patient-perceived barriers to clinical research participation.
Whether recruitment messages utilize tailored, targeted, or more generic message strategies, the success of the message will be based, at least in part, on the way language is used to convey that content. Explaining the causes and nature of a disease to lay audiences is inherently challenging; however, there is added difficulty when conveying this information to a patient while simultaneously educating them on the key elements of research design that are required for informed consent. One linguistic strategy that is commonly used to overcome the challenges associated with explaining research design in recruitment is metaphor. Metaphors are pervasive in explaining illness to patients. The experience of illness is often described using machine metaphors (e.g., illness as a result of “faulty parts”), while treatment is described using war (e.g., “fight the disease”) and sports metaphors (e.g., treatment as an alternative to “quitting”) (Periyakoil, 2008). Metaphors are also commonly used to bridge gaps between patients’ knowledge of research and the complexity of experimental design. This is particularly true in the case of randomization.
Randomization is a highly technical term for which there are no lay language synonyms, so it is unsurprising that communicators often turn to metaphorical language to help bridge the knowledge gap. The most common comparisons health care providers use includes describing randomization as like the toss of a coin, like the lottery, and picking a number from a hat (Jenkins, Leach, Fallowfield, Nicholls, & Newsham, 2002). Healthcare providers undoubtedly use metaphors, such as those that refer to gambling, because they are believed to be accurate and familiar explanations for relevant concepts. However, there is some evidence that the use of metaphor may bias patients against participation in clinical research studies. Research has shown that patients sometimes extrapolate the randomization analogy to the clinical research study experience in general, such that they conclude that clinical research study participation is akin to gambling with one’s health (Krieger, 2014).
Once core decisions have been made about how much to customize message content and the key content of the message, including decisions about how to communicate difficult concepts, a good clinical research study recruitment plan should address the channels that will be used to deliver the message. Below, we describe two dissemination strategies. One relies on interpersonal interaction by a research representative, such as a clinician, nurse navigator, or community health worker. Another relies on more mass mediates channels, such as TV, radio, billboards, and the Internet.
Channel Considerations in Clinical Research Recruitment
Determining which channel is most appropriate for recruiting participants is largely dependent upon how patients are being identified. There are two general approaches for identifying potential participants. One strategy is for the investigator to identify eligible patients using integrated data repositories (IDRs) or research registries. An IDR is “a data warehouse integrating various sources of clinical data to support queries for a range of research-like functions” (Wade, Zelarney, Hum, McGee, & Batson, 2014, p. 72). IDRs allow investigators to efficiently query large amounts of data for patients who meet certain criteria based on particular attributes.
The second strategy is to allow investigators to search patient registries for individuals who are eligible for studies. For example, ResearchMatch is a national, web-based patient registry that enrolls patients across the United States, regardless of medical condition, and supports investigators within the national Clinical and Translational Sciences Awards consortium (Harris et al., 2012). Rather than rely on a model that weighs heavily on patients being willing and capable of navigating clinical research study search tools, such as the National Institutes of Health ClinicalTrials.gov, or other independent websites like MyClinicalTrialLocator.com and TrialReach, registries can function as a more reciprocal process of matching patients with studies and investigators with patients. When cohort discovery tools are used to identify potential participants, contact with the patient typically relies on channels that can allow interpersonal connection, such as face-to-face interaction or telephone calls.
There are times when cohort identification is not possible or may not be the most efficient means of recruitment. In these cases, investigators must rely on making information about research studies available in the communication environment either through interpersonal interaction (e.g., healthcare providers, navigators) or via more mediated channels (e.g., mass media, internet). Next, we describe the various interpersonal and mass mediated channels that can be used to either recruit a pre-identified cohort or to generate a pool of prospective patients that can be screened for study eligibility.
Many clinical research studies rely on interpersonal interaction with patients as a primary strategy for recruiting potential participants. Face-to-face or other types of “high touch” approaches are particularly useful when patients and community participants are afraid, suspicious, or distrustful of researchers and/or medical research. Below, we discuss the potential benefits and barriers with different types of interpersonal strategies for recruitment, including providers, family members and friends, and community-engagement techniques.
Physicians are often considered an obvious choice for clinical research study recruitment, especially for treatment trials. Recruiting physicians from diverse clinical practices is often attractive because it can increase the representativeness of clinical research study participants (Ellis et al., 2007). When a recruitment plan designates physicians as a primary strategy for recruitment, it is important to consider what strategies will be used to recruit the providers and, in some cases, their practices. A recent meta-analysis found that only about a third of studies relying on clinicians as a key component of the research recruitment plan had a primary investigator, community research staff, or coordinator meet with providers face-to-face (Heller et al., 2014). This is unfortunate, as recruiting physicians via in-person meetings or contacting clinicians based on established relationships is less expensive and has a higher return on investment as compared to more generic recruitment strategies, such as advertising in mass media (Ellis et al., 2007). Developing interpersonal relationships are particularly important for generating patient referrals when the clinician serves disparate populations (Durant et al., 2014).
Although obtaining a physician’s agreement to refer patients to a clinical study is useful, it does not guarantee that this will be an effective patient recruitment strategy. Previous research has identified a number of reasons physicians may choose not to refer patients to a clinical research study, with 60% of cancer patients being discouraged from research study participation by an oncologist, and 50% being discouraged by a family physician (Virani, Burke, Remick, & Abraham, 2011). There are a number of reasons why physicians either do not make patients aware of open clinical studies or discourage them from participating (Townsley, Selby, & Siu, 2005). One reason is the scientific design of the study, such as the perception that the research question being investigated is weak, or a strong preference for one of the treatments being tested. Physicians also have pragmatic concerns, such as a lack of sufficient time to execute the protocol, lack of staff, and absence of perceived personal or institutional benefit. Other issues include negative perceptions associated with how clinical research study enrollment would affect the physician-patient relationship, the ability of patients to participate (e.g., time, travel, and cost) and the quality of patient care.
When clinicians do not perform well as recruiters, there are two potential courses of action. One systematic review of studies utilizing clinicians as clinical research study recruiters found that successful clinician interventions embedded a qualitative design in their overall recruitment strategy (Fletcher, Gheorghe, Moore, Wilson, & Damery, 2012). As part of this design, researchers investigated all aspects of the clinical recruitment process to identify potential barriers and then interviewed clinicians to understand what aspects were amenable to change in order to improve recruitment yield (Donovan et al., 2002; Donovan et al., 2009). The benefit of this approach is that it is adaptive and allows for the continuous monitoring and improvement of recruitment efforts.
Physicians, in particular, can take on many roles in the recruitment process: the investigator, concerned with meeting accrual goals; the researcher, interested in the knowledge obtained from the clinical research; and, chiefly, the provider, focused on treating the patient with the best care available and in a way the patient is comfortable with. Yet, it is not uncommon for patients to be diagnosed and consented in the same interaction. The ability for clinicians to wear multiple hats and uphold the ethical requirements of this interaction is made more difficult by how brief these interactions can be during a busy appointment schedule (Howerton et al., 2007). To overcome this challenge, other research finds that it is more useful to rely on other forms of communication with patients, such as participant response cards, presence of research staff in the clinic, sending letters signed by providers and followed up with phone calls by study staff, or having clinicians opt patients out of a study rather than opt-in (Heller et al., 2014).
Patient and Nurse Navigators
Given the challenges in effectively utilizing physicians to recruit patients for clinical research studies during their one-on-one interactions with patients, attention has turned to the potential for other interpersonal recruitment strategies, such as the use of patient navigators. Patient navigators, also called community health workers (CHWs) or promotoras, help patients overcome barriers to medical care (Ghebre et al., 2014). In many cases, patient navigators work with newly diagnosed patients to help ensure continuity of care. One study employed bilingual cancer survivors to navigate Chinese women with breast and gynecological cancer into treatment, including clinical treatment trials (McClung et al., 2013).
In some cases, nurses are being asked to perform a similar function. Nurse navigators merge the roles of oncology research nurse and patient navigator as they help patients overcome barriers to their medical care (Ghebre et al., 2014), including potential obstacles to study enrollment and retention (e.g., transportation) (Wujcik & Wolff, 2010). Overall, nurses have been found to be as effective as surgeons in recruiting patients to a clinical research study, but much more cost effective (Donovan et al., 2003). Nurse navigators have been found to be particularly effective for increasing minority patient participation (Holmes, Major, Lyonga, Alleyne, & Clayton, 2012).
In addition to helping newly diagnosed patients navigate the healthcare system, there are other potential ways in which patient navigators can help recruit patients to clinical research studies. There are a growing number of community-engaged research (CEnR) programs that utilize CHWs to provide outreach in the community. These programs are designed to increase the diversity of research participants, help meet community needs, and reduce disparities in care. University of Florida’s HealthStreet is an example of a CEnR program in Northeast Florida that provides community members with medical and social service referrals and opportunities to participate in health research (Cottler, Striley, O’Leary, Ruktanonchai, & Wilhelm, 2012). CHWs within HealthStreet approach community members at laundromats, grocery stores, libraries, hair salons, bus stops, senior centers, community centers, health fairs, and other places to assess their medical and social needs and to discuss medical problems and other health concerns. They then link people to opportunities for participation in research based on these needs and concerns. Community members receive a follow-up phone call at 30 and 60 days for services and for research participation.
Family and Friends
Previous research shows that family members and friends serve as both facilitators and barriers to recruitment for clinical research studies (Albrecht et al., 2008; Ford et al., 2008; Kornblith et al., 2002; Lara et al., 2001). For example, one study reported that 51% of eligible patients were discouraged from participating in a research study by family and friends (Virani et al., 2011). While it is useful to know if social networks facilitate enrollment in clinical studies, it is more important to know whether family and friends facilitate informed treatment decision making. Making decisions about cancer treatment can be stressful, and patients and members of their social network may have different views about how the process should go (Krieger, 2014). When this happens, the decision about whether to participate in a research study can cause conflict between patients and their loved ones.
Family conflict about clinical research participation can come in various forms. Some patients who ask family and friends for their opinions on treatment options receive the support they seek. Others, however, find that caregivers refuse to participate in the decision-making process in any form. Some patients choose not to seek the opinions of the family and friends on their treatment decisions. While certain members of the social network will respect this choice, others may feel compelled to volunteer their opinion. Patients who do not receive the decisional support they desire from the social network in the treatment decision-making process may be less likely than those who do to enroll in a research study when they wish to do so; conversely, patients who receive more decisional support than they desire from the social network may be more likely to enroll in a research study when they do not wish to do so than those who receive the desired amount (Krieger et al., in press).
The importance of decisional support from family and friends related to clinical study participation may differ among patient populations. For example, one study found that the majority of the Hispanic focus group participants preferred family members and healthcare providers to have an active role in the decision making in cancer clinical research study enrollment (Quinn et al., 2013). Another found that rural and remote patients were significantly more likely than patients living in more urbanized areas to report that having a family member or friend attend medical appointments was important to their ability to participate in a research study (Sabesan et al., 2011). The importance of the social network in the decision-making process among underrepresented groups likely reflects a combination of cultural norms regarding interdependence in decision making in addition to the pragmatic concerns, such as transportation to and from appointments. While it is important to appreciate the potential for variation among different patient populations with regard to family communication about the clinical trial decision-making process, these factors are also relevant when considering the best channels for generating awareness about the availability of research studies.
Mass Media Strategies
Attempts to improve patient recruitment rates have relied largely on increasing public awareness of ongoing clinical research by disseminating recruitment information via mass media (Jennings et al., 2015). Posters, in-clinic brochures, and radio/television advertisements are all examples of how study teams attempt to increase awareness of research studies in hopes that patients will feel compelled to enroll. Focusing on the message channel to the exclusion of the message content often results in poor outcomes. Campaigns that rely exclusively on increasing awareness of research studies tend to show either no significant improvement in participation rates, or improved rates of accrual are deemed insufficiently cost-effective and consequently unsustainable (Institute of Medicine, Public Engagement and Clinical Trials: New Models and Disruptive Technologies: Workshop Summary, 2012). As such, a poor association remains between increasing patient awareness of clinical research and increasing individual intentions to participate (Stiles et al., 2011).
An example is the “Get Randomised” campaign, which was the first in the United Kingdom to use a media campaign to raise public awareness of clinical research (Mackenzie et al., 2010). The campaign employed television, radio, and newspaper advertising to showcase leading clinical researchers, general practitioners, and patients informing the public about the importance of clinical trials. To assess the impact of the campaign, adults in Scotland were surveyed prior to the campaign launch and again six months later. Although awareness of the campaign and comprehension of clinical trials increased dramatically (an increase of approximately 40%), there was no significant improvement on behavioral intention to participate in a clinical trial in the future.
Similar studies in the United Kingdom have also found it equally difficult to translate awareness into participation, despite utilizing well-funded media campaigns. The Standard Care vs. Celecoxib Outcome Trial (SCOT) investigated the cardiovascular safety of non-steroidal anti-inflammatory drugs in patients with osteoarthritis or rheumatoid arthritis (Hapca et al., 2014). To increase recruitment rates, the research team placed ads in national and regional newspapers across Scotland over a six-month period. In spite of a total of $71,429 spent on advertising, recruitment efforts to SCOT indicated no significant improvement in accrual. The campaign resulted in successfully enrolling only 15 eligible participants, at a cost of $4,759 per patient.
Multi-faceted media recruitment campaigns have proven to be more effective when strategically targeting individuals within high-yield areas. Dew et al. (2013), who aimed to improve accrual rates of minorities to clinical research studies in Chicago, combined traditional mass media methods with strategic advertising placements at clinics, wellness events, and most importantly, on public transportation that connected with the clinic locations. The internal referral strategy, in which study information and contact details were displayed through a series of brochures and posters at the Northwestern Memorial Hospital (NMH) network, proved to be the most effective source of generating study contacts, consents, and minority consents. However, it was also the most expensive strategy. Public transportation ads, by contrast, generated the second largest number of minority contacts and minority consents at almost one tenth of the overall NMH cost. This study demonstrates that strategic placement, rather than the size and cost of the campaign, can prove more efficacious and sustainable for recruitment within an urban setting.
One of the limitations of focusing primarily on the use of traditional media to increase minority recruitment to cancer clinical research studies has been the inability to track awareness efforts outside of enrollment (Rivers, August, Sehovic, Lee Green, & Quinn, 2013). A growing number of research teams now rely on online media to provide both a more cost-effective and metric-based approach to recruitment. Recent studies have evolved from general social marketing efforts to using social media as a key means of connecting with potential clinical research studies participants (UyBico, Pavel, & Gross, 2007). With an increased ability to track users’ online interactions in response to awareness strategies, digital media can act as a platform for highly specific and nuanced insights into the best methods for information dissemination.
Despite patients becoming increasingly familiar with online health-information seeking, the success of digital outreach efforts relies heavily on patient access to, and utilization of, certain online media. To date, digital media has proven to be popular for patients seeking general health information (Diaz et al., 2002; Fox & Duggan, 2013), self-diagnosis (Castleton et al., 2011), and easily accessing educational material about cancer and its risk factors (Xiao, Sharman, Rao, & Upadhyaya, 2014). But its role in recruiting currently underrepresented patient demographics to cancer clinical research studies often reflects the wider socio-economic challenges facing underserved patient populations. Generally speaking, Internet utilization among African Americans is high, with 62% having some broadband connection at home as compared to 74% of Caucasians (Smith, 2014).
eHealth refers to interventions that “transfer health resources and health care by electronic means” (The Royal Australian College of General Practitioners). While eHealth interventions have shown some promising results to improve recruitment and retention to research studies, the findings are mixed for cultural and methodological reasons (Glasgow, Phillips, & Sanchez, 2014; Norman et al., 2007). Criticisms of eHealth interventions often focus on the lack of longitudinal data that indicate they are capable of maintaining improved health decision making in the long term. For example, despite support for the use of eHealth interventions to enhance treatment for weight loss prevention, there is insufficient evidence on the effectiveness of sustaining behavioral change and providing long-term weight loss maintenance (Hutchesson, Morgan, Jones, & Collins, 2014; Lewis, 2015). Contrary to what might be expected, participant retention in an online weight loss study was lower among younger people, African Americans, and participants with higher self-efficacy to manage their weight when stressed (Glasgow et al., 2007).
Similar uncertainty has been reported in the success of eHealth interventions in advancing recruitment and retention to cancer clinical research studies. In comparison to opportunistic recruitment, studies show that African Americans sought information less often, and rates of recruitment were lower via online enrollment efforts (Langford, Griffith, Beasley, & Braxton, 2014; Wood, Wei, Hampshire, Devine, & Metz, 2006), while other studies have suggested that African American patients do benefit from online interventions when they include culturally sensitive narrative and didactic information (Wise, Han, Shaw, McTavish, & Gustafson, 2008).
One area that hopes to offer greater promise for improving minority participation in research is mHealth, which is defined as “the use of portable devices with the capability to create, store, retrieve, and transmit data in real time between end users for the purpose of improving patient safety and quality of care” (Akter & Ray, 2010, p. 75). There is a growing body of research on the use of texting interventions to provide support for improving daily decision making for chronic health conditions, to facilitate appointment making and completion, and to provide motivational and educational support, in both the Western and developing worlds (Bobrow et al., 2014; Chen, Fang, Chen, & Dai, 2008; de Jongh, Gurol-Urganci, Vodopivec-Jamsek, Car, & Atun, 2012). Within this context, mHealth has materialized as a wide-reaching, low-cost solution to serve the pressing healthcare needs of those who most require them. The United Nations estimate that cell-phone ownership currently exceeds five billion, with more than 50% of mobile users living in developing countries (Pew Research Center, 2014). The rapid diffusion of cellular phones across low- and middle-income countries is expected to play a crucial role in meeting the healthcare needs of patients in at-risk and underserved areas. As Akter and Ray (2010) highlight, only 5% of the world’s population has regular access to a computer, but 43% own mobile phones.
Trends for increased utilization of mHealth technologies as compared to computers are similar among minority populations in the United States. For example, African Americans are equally as likely as Caucasians to own a cell phone of any kind (Smith, 2014). In line with the ever-increasing capabilities of smartphones, the NIH has identified mHealth as fundamental to revolutionizing the way at-risk patients receive preventive care (Collins & Varmus, 2015). Whether through biometric data collection and transmission, fitness tracking, or communication between providers and remote patients, mHealth presents a greater ability to keep in constant contact with patients and monitor their overall wellbeing (Lupton, 2013). It is hoped, therefore, that cellular devices have the potential to play similarly critical roles not only in improving patient decision making, but also in the improved patient recruitment to clinical research.
Spruijt-Metz, Nilsen, and Pavel (2014) contend that the rapid development of mHealth technologies has outpaced the empirical evidence supporting their successful integration into applied healthcare research. When analyzed holistically, the recent proliferation of studies indicates weak support for influencing behavior change, to the point that “the hype of mHealth has far exceeded the actual scientific justification, leaving many concerned that mHealth may not meet its expected potential” (p. 120). In a recent meta-analysis, LoPresti et al. (2015) offer a more measured approach, concluding that the use of mHealth applications is a growing field with broad implications for the improvement of clinical practice. Although the authors admit that the current evidence is unclear, they confidently state, “mHealth applications, devices and technology most assuredly have a role in chronic disease management and work to improve patient engagement” (p. 17). As a result, researchers are continuing to exploit not only increased patient access to smart phones, but also the wide array of digital channels available within mHealth recruitment interventions such as social networking capabilities.
Social networking platforms are another way that digital technology expands the scope of clinical research recruitment. As research teams generate crucial data on the comparative effectiveness of outreach efforts among minority patients, differing social media platforms are being tested as a means for increasing the exposure of a study and to provide a dialogue with patients, especially those of color. Adoption of social networking sites is identical among white and African Americans Internet users (72% vs. 73% of online adults), but African Americans have exhibited relatively higher levels of Twitter use (22% vs. 16% of online adults) (Smith, 2014). Although some success has been witnessed across popular social media sites to aid recruitment, there remains a lack of evidence to indicate which is the best platform and whether they will ever be as successful in recruitment as they are in disseminating health information (Attai et al., 2015; Dizon et al., 2012; Grajales III, Sheps, Ho, Novak-Lauscher, & Eysenbach, 2014).
It is not surprising, then, that with a greater ability to cheaply increase the mechanism and the magnitude of a study’s promotional information, both for-profit companies and not-for-profit researchers have shown a concentrated effort to experiment with digital outreach strategies. In 2012, Canadian company Qu Biologics successfully recruited patients to their phase I/II trial of a new Crohn’s disease treatment through dedicated Twitter (@QuCrohnsTrial) and Facebook accounts. The goal of the study was to increase awareness of Crohn’s disease as a whole, while also encouraging study enrollment (Tyer, 2013). Through the use of metrics provided by their social media accounts, the research team was able to track online interaction with prospective participants and, as a result, enroll patients. Other studies, such as those conducted by U.K.-based Lilly Research Center, have piloted social media recruitment for research studies on diabetes as well as head and neck cancer. They found an increase in accrual rates by shifting the purpose of messages on existing digital channels from creating awareness to strategic recruitment. This change reduced overall recruitment costs by 10–15% (Tyer, 2012).
The exponential growth of social networks and/or mobile device usage represents fertile ground for researchers to refine recruitment strategies to target more rural and hard-to-reach areas. In 2012, however, Pfizer found that the fragmented landscape of online patient behaviors could be just as unpredictable as clinic recruitment. The REMOTE trial aimed to test the efficacy of Detrol LA—a drug to treat overactive bladders—that was dubbed by the research team as the “trial in a box.” It was the first randomized clinical trial that permitted patient participation entirely from their homes through the use of cell phone and web-based technology. The researchers hoped that recruitment length would be reduced, rates of patient attrition would decrease, and patient tracking could improve the robustness of the study in comparison to self-reported data. Unfortunately, the study failed, as Pfizer was unable persuade sufficient numbers of patients to take part in the study. The company, however, has expressed its commitment to pursing future digital recruitment strategies (Tyer, 2012).
Other companies, such as TrialX, a healthcare IT company that functions across various platforms, combine social media and web-based recruitment tools by allowing patients to simply tweet “CT” at the @TrialX Twitter handle with some basic personal health profile details included. Almost instantly, patients receive a reply tweet with a link to the TrialX page containing matching trials. Prospective subjects can also import personal health records to find studies and send emails to investigators. Patient matching based on eligibility and proximity has proven successful, and it has evolved to include university hospitals developing and disseminating their own clinical trial apps to improve campus recruitment efforts (Albrecht, 2012; Swan, 2012).
While there are different strategies for evaluating the success of recruitment campaigns, they often focus solely on outcome evaluation. Driven by the need to meet a study’s minimum patient enrollment requirement, which is a key metric to measure any clinical research studies recruitment strategy, this form of evaluation is myopic and does little to inform future campaigns on how they can improve recruitment strategies. Without strategically planning a multi-stage evaluation framework that encompasses the design, implementation, and ongoing assessment of recruitment messages, message design and dissemination efforts are maladaptive. Unlike other public communication campaigns, such as elections, where candidates change strategy quickly based on voter polling and/or opposition strategy, clinical research study recruitment efforts can often be adapted to be more effective without completely changing the overall set of strategies being employed. Therefore, over the length of a recruitment campaign, researchers should clearly identify methods that rigorously implement formative, process, and outcome evaluations to provide a more nuanced determination of campaign effectiveness.
The formative evaluation of recruitment messages involves the input of key stakeholders to help guide the design and execution of recruitment efforts. Primarily broken down into two sub-phases, preproduction research and production testing, this form of evaluation allows researchers to systematically and confidently design interventions that are reflective of the cultural and personal characteristics of the patients they are trying to recruit. Palmer (1981) describes preproduction research as a means of aggregating “audience characteristics that relate importantly to the medium, the message, and the situation within which the desired behavior will occur” (p. 227). With this information gathered, Atkin & Freimuth (2013) outline how production testing, also known as pretesting, involves the presentation of prototype messages to be evaluated by stakeholders from the intended audience on their comprehension, representativeness, and predicted success.
This phase of evaluation often includes the use of in-depth individual interviews and/or focus group interviews. Although individual interviews allow researchers to probe more deeply into specific issues, especially ones involving interventions that address sensitive topics (e.g., sexual history, mental illness, breast cancer), the semi-structured, multi-insight format of focus groups can often be beneficial. By allowing participants who reflect the key demographics of your target audience to freely provide personal opinions on the message prototypes, researchers can better identify and correct underlying problems within the design and execution of messages that may inhibit the success of the recruitment campaign.
As researchers rarely reflect the characteristics of their target audiences—especially when trying to recruit minority patients to research studies—it is critical that the cognitive, affective, and functional barriers to message acceptance are pre-identified and taken into account when both the message and delivery channel are designed. Atkin and Freimuth (2013) highlight the importance of the formative evaluation phase in allowing researchers to identify the pre-existing knowledge of patients; the capacity they have to understand the messages you are disseminating (i.e., levels of literacy and numeracy); the preformed beliefs and perceptions patients have about your issue; the attitudes and values they have personally generated or socially learned about it; how salient they see the issue in comparison to competing issues; the level of confidence they have in being able to complete the requirements detailed in your message (i.e., self-efficacy), and the level of confidence they have in benefits derived from completing the requirements in your message (i.e., response-efficacy).
Formative evaluation is also critical in distinguishing failures in the usability of the message channel. As previously discussed, multi-faceted digital recruitment efforts employ differing media platforms to increase patient accrual rates. Studies have shown marked differences between the preproduction and production phases after usability evaluation sessions (Flagg, 2013). For example, Kirwan, Duncan, Vandelanotte, & Mummery (2012) found that participant input was critical to redesigning their smartphone application fitness tracker before it launched. To increase the functionality of iStepLog, key changes were made not just to the interface design (i.e. the quality of feedback provided to users, navigability), but also in the understanding of basic terminology and certain language used within the app. These changes increased usability and extended patterns of usage. Likewise, other health promotion and disease prevention studies have shown how critical this phase is to implementation research (Baranowski, Cerin, & Baranowski, 2009; Dehar, Casswell, & Duignan, 1993; Stetler et al., 2006).
Process evaluation of clinical research studies is primarily thought of as the collection of interim data on the effectiveness and safety of a clinical intervention for participants. Although the end goals are different, process evaluations of recruitment strategies reflect reasons for evaluation similar to those of clinical process outcomes. Process evaluation can provide researchers foresight into interventions that are inherently faulty, either due to inappropriate use of a theoretical framework, an ill-fitting methodology, or a failure of implementation. This form of evaluation is critical for understanding why an intervention fails, helps explain the production of unexpected results, and gives researchers a stronger argument for why an intervention’s hypotheses were successfully met (Craig et al., 2008).
As is often the case for multisite trials, process evaluations of multifaceted recruitment strategies are especially necessary to determine whether the same intervention has been successfully implemented and received across different sites (or channels). Unlike mid-point or continual clinical evaluation, recruitment strategies must place more focus on interventions reaching the intended population. If interpersonal communication is the primary method of recruitment, it is important to monitor what percentage of eligible patients are being approached about the study—when, where, and in what way? If mass media is the primary method of recruitment, monitoring who is being exposed to recruitment messages, and whether this is the most effective method of communicating their eligibility and trial objectives to prospective participants, is essential.
Process evaluation is a particularly important strategy for fine-tuning ongoing recruitment efforts among rural and minority participants. A recent group-randomized trial to test the effectiveness of county-level colorectal cancer (CRC) intervention among adult rural populations found that the intervention made no impact on screening behaviors (Krok-Schoen et al., 2015). The intervention was conducted over four waves, with process evaluations conducted after wave 2 and wave 4. In wave 2, a subset of participants (80 adults per county) responded to a mail-in survey asking if they had seen the campaign messages (billboards/posters used in the media campaign) during the past year. In wave 4, another subset of participants (80 adults per county) responded to a phone survey asking if they had seen the clinic-based educational materials (posters, brochures) during the past year. In this study, fewer participants (14.4%) living in high-risk counties reported seeing CRC screening billboards than the nutritional billboard (15.4%); those who reported seeing the CRC screening billboards had, on average, significantly shorter distances from their residences to the billboards (14,125 meters vs. 17,516 meters; p < 0.01) compared to those who did not see real billboards (Katz et al., in press).
When mass media campaigns fail, process evaluations can provide important information to unveil underlying reasons for failure. For example, if exposure is low, especially in rural populations, geographical context might be the reason (i.e., people who live closer to billboards are more likely to report seeing them). Although process evaluations can be used to assess the reliability recruitment campaign messages have at reaching target audiences, they can also address the quality of recruitment intervention. A process evaluation is critical in clarifying causal mechanisms throughout the recruitment campaign, and it identifies contextual reasoning for outcome variation across recruitment strategies. However, it is not a substitute for evaluation of outcomes.
Smith (2013) outlines several key metrics for campaign evaluation: awareness, acceptance, and action objectives. However, unlike other strategic messaging campaigns, clinical research recruitment faces unique cultural, patient-perceived, and structural barriers to participation. Nonetheless, evaluation of these objectives provides data useful in the improvement of future recruitment campaigns. To evaluate whether the awareness objectives of a campaign were met, analyzing outside media coverage of the clinical research study, in combination with calculating unique impressions of the study’s recruitment channels, can provide recruiters with awareness data that can be tracked. It is also often beneficial to conduct a post-campaign awareness survey focused on the study’s target recruitment audience. To evaluate acceptance objectives, tabulation of participant interest and method of response is essential. This includes letters, e-mails, and phone calls expressing interest, support, or dissatisfaction for the study, whether or not they agreed to participate or met study criteria. Additionally, a post-campaign attitude survey goes beyond simple awareness of the study and can glean valuable opinions on how recruitment efforts may be improved and streamlined. Finally, to evaluate action objectives, it is critical to measure the study’s primary outcome goal—patient enrollment. However, it is occasionally difficult to determine which recruitment channels had the largest impact on patient enrollment; and, from a budgetary standpoint, which were most cost-effective for accrual.
As modern campaigns tend to use multiple channels of recruitment, it can be challenging to decipher which channel was not only most effective but also most cost-effective. One useful tool for comparing outreach efforts across various resources is the cost–time index (CTI). Hapca et al. (2014) describes this as a method for simultaneously measuring the cost and time efficiency of each specific recruitment approach by the number of eligible patients inducted into a clinical research study. CTI is calculated by:
Ota et al. (2006), who were the first to demonstrate the use of CTI, provide a working example as they compare the CTI of four paid resources (local-daily newspaper, major regional newspaper, local-weekly newspaper, and fliers) used to recruit subjects for a clinical study of insomnia patients (Table 1). As the table indicates, a low CTI figure represents a more efficient recruitment method, but it should be noted that this figure does not factor in design, staffing, or other administrative costs. It does, however, provide an objective measure to identify the most cost-effective method to recruit participants. Rather than focus purely on the number of eligible patients enrolled, researchers are able to calculate the return on investment (ROI) of multiple media strategies. From this study, the local-daily newspaper proved to have the lowest CTI (57.3 × 102), primarily as a result of a low-cost, high-yield ROI. The major regional newspapers, despite recruiting the second highest number of patients (n = 10), were not as cost-effective as fliers (CTI = 106.6 × 102 vs. 63.7 × 102), even though fliers provided the lowest yield number (n = 3).
Table 1. Cost-Time Index Working Example: Four Paid-Resources Used to Recruit Subjects for a Clinical Study of Insomnia
CTI ($–days × 102/patient)
Major regional newspaper
TC = total cost for a given advertisement; Z = the number of days the advertisement was published in a week; W = the number of weeks the advertisement was run; S = the number of subjects who were considered suitable recruited from each advertisement.
Recruitment is an essential component of clinical research. Thus, the ways in which we communicate about research with potential participants deserve careful scrutiny (Tomlin, deSalis, Toerien, & Donovan, 2014). The recruitment process commonly focuses on generating awareness of research studies through informed consent, with each stage presenting unique challenges. One such challenge is ensuring that all strategic communication efforts are ethically sound. Communication about clinical studies should be informative and not directive, reassuring without being manipulative, and patient-centered rather than recruitment-oriented. Communication ought to be structured so that patients who choose to enroll in clinical research studies understand the advantages and disadvantages of participation, including study requirements and whether they will be randomized to treatment. Given the complexities associated with translating scientific information for lay publics, employing basic tenets of message processing and social influence is vital to the achievement of successful and ethical recruitment efforts.
Another important ethical concern related to recruitment is the reduction of health disparities. For clinical research to be truly reflective of the patient demographics they wish to benefit, new treatments must be assessed across all eligible patients—especially those who identify as racial and ethnic minorities. A strategic communication approach is particularly important when clinical research studies seek to enroll underserved patient populations. Careful audience analysis is vital in identifying cultural, educational, and communication preferences among each target audience group. For example, it may be important to develop a message that addresses specific types of mistrust among a particular target audience. However, using the same message with other groups that have more trust may create the inaccurate impression that research participation is riskier than it actually is. Executed correctly, communication strategies can convey respect for cultural diversity while mitigating socio-economic disparities to increase patient comprehension and promote research participation. This can also lead to a decline in the inequalities associated with literacy, numeracy, and misperceptions.
Unfortunately, well-intentioned recruitment efforts can also backfire. One strategy for preventing potential problems is to engage stakeholders in the development of the strategic recruitment plan. Stakeholder engagement can include activities such as helping identify research priorities and develop study designs, or community-based participatory research. Recruitment communication plans should also include complementary plans for the retention of participants in studies, with for example, a strategy to keep participants informed of study developments and thus maintain their investment in the study. After clinical research data are collected and analyzed, communication expertise is needed to help translate findings back to stakeholders.
Despite the many advances associated with applying strategic communication theory and research to clinical research recruitment, there are several areas in need of improvement. One is more accountability on the return on investment associated with various recruitment studies. At present, the costs associated with clinical research recruitment are difficult to estimate because so few studies report this information. The literature provides a few notable exceptions, with Ellis and colleagues reporting that recruiting physician practices to participate in a clinical research study costs approximately $613 per practice, while hiring a nurse navigator to recruit African American patients to clinical research studies costs approximately $5,677 per enrolled patient (Holmes et al., 2012). Other studies report costs in terms of time. For example, one study reported that patient navigators spend an average of 317 minutes with each patient, while patients with a more advanced disease require more contact time (McClung et al., 2013). The lack of common metrics being consistently reported in the literature makes it difficult to know what the absolute cost of recruiting participants will be, causing difficulty when comparing costs across studies and regions. Tracking the costs of recruitment and identifying which strategies yield the highest return on investment is an important step for future research.
Another important goal for future research is to integrate emerging information technology techniques with effective communication strategies to overcome patient disparities, facilitate accrual goals, and maintain the voluntary process of patient consent. One area that is particularly ripe for this type of innovation is the adaption of the informed consent process to better suit the needs and interests of the patient. This would require moving away from the hard copy, fixed-template, informed consent documents to an electronic format able to provide interactive functionality that creates a digital, patient-centered discussion (Branson, Davis Jr., & Butler, 2007). An adaptive format could allow patients to access information that is of most importance to them, thus reducing the likelihood of information overload and increasing perceived self-efficacy for decision making. Adaptive consent forms could also allow researchers to correct potential misconceptions about clinical research, increase perceived trust in the research team, and reduce mistrust in research (Corbie-Smith, Thomas, Williams, & Moody-Ayers, 1999; George et al., 2014).
In summary, employing behavioral theories and communication strategies to improve existing methods—or to develop entirely new ones—enables health communication researchers to increase rates of patient recruitment, participation, retention, and successful completion of clinical research studies. Although the broader application of health communication is used to, among others, study how patients and family members make sense of illness, improve provider-patient communication, or enhance the success of health education messages, its role in the clinical research process is being steadily recognized as essential by all stakeholders involved.
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