We identified 6374 records and an additional eight through citation searching; 2972 further records were identified via the search updates, resulting in a total of 9354 articles. We retrieved 156 articles for full text review and finally included 26 articles. Exclusions are detailed in Fig. 1.
Quality of the evidence
Six reviews (23.1%) were rated as high quality (AMSTAR score 8–11), and 20 reviews (72.9%) were of moderate quality (AMSTAR score 4–7) (see Table 1). Most involved a comprehensive literature search, employed duplicate study selection and data extraction and provided a list of included studies alongside their characteristics. The results of reviews were largely synthesised appropriately, and most authors stated whether there were any conflicts of interest. Just over half of the reviews assessed the scientific quality of the included studies, but only two assessed publication bias. The majority of reviews did not provide any evidence of a priori design, such as a published protocol.
Table 1 Characteristics of included systematic reviews Characteristics of included studies
The 26 reviews incorporated a total of 489 relevant primary studies, of which 179 (36.6%) had been undertaken in the USA; 80 (16.4%) in the UK; 19 (3.9%) in Australia; 17 (3.5%) in Canada; 12 (2.4%) in South Africa; 10 (2.0%) in Thailand; whilst 28 (5.7%) had been undertaken in more than one country (see Table 1). Country of origin was not reported in the source review for 82 (16.8%) studies, and the remaining 62 studies had been undertaken in one of 23 countries. Of the 489 primary studies, 56 (11.5%) were included in more than one review, leaving a total of 429 unique studies.This degree of overlap in the primary studies is low, incorporating a covered area of 4.4% and a corrected covered area of 0.5% [43]. Six (23.1%) reviews [10, 21, 26, 27, 34, 35] explicitly stated that they included only qualitative studies; the remainder included both quantitative and qualitative research. The focus of reviews varied in terms of health setting and types of research participation. Sixteen (61.5%) reviews were limited to studies of trial participation [10, 18,19,20, 22,23,24,25,26,27, 29, 32, 33, 35, 38, 39], and the remaining ten either included a mix of primary research designs or the design was unclear [21, 28, 30, 31, 34, 36, 37, 40,41,42]. Fifteen (57.7%) reviews were related to specific health conditions or settings: cancer (n = 6), HIV (n = 3), mental health (n = 2), chronic obstructive pulmonary disease (COPD), emergency medicine, pregnancy and bio-banking (each n = 1). Four studies focused on child or adolescent participants and their parents/caregivers [18, 21, 22, 40]; one study focused on ‘hard to reach’ older patients [19]; and four reviews focused on ethnic minority groups [24, 28, 29, 39]. Fifteen reviews (57.7%) only included real research scenarios [19,20,21, 23, 24, 26, 28,29,30, 32,33,34,35,36,37]; whereas 11 (42.3%) included both real and hypothetical scenarios. Most reviews (19; 73.1% considered both facilitators and barriers to research participation; three (11.5%) were limited to facilitators and four (15.4%) to barriers. The reviews were published during 1999–2019; their included primary studies were published during 1982–2016. Characteristics are further detailed in Table 1.
Identified psychosocial themes
Facilitators of research participation
A number of themes were identified which reported facilitators of research participation (see Table 2). The most commonly reported was perceived personal benefits, including the perception of therapeutic benefits, closer monitoring and access to new treatments [10, 20,21,22, 25,26,27, 29,30,31,32,33,34,35,36,37, 39,40,41].
Table 2 Identified psychosocial facilitators and barriers to research participation, mapped to the Theoretical Domains Framework (TDF) and tested recruitment interventions Whilst altruism was the second most commonly reported factor, discussed in terms of benefitting science [10, 20, 29,30,31, 34, 36, 37, 39,40,41], helping others [10, 20, 21, 26, 27, 30, 31, 34, 35, 37, 40, 41] or altruism more generally [22], this was sometimes linked to personal benefit [27, 31, 33]. For example, patients with depression were less likely to participate if it might risk their own mental health, despite wanting to help others [27]. Further, two reviews highlighted that the desire to help others was not always concerned with helping all people, but specifically benefitting people who were personally important [32, 37]. Finally, a review involving research with children and adolescents concluded that the importance of altruism depended on the child’s health state; altruistic motives were given as a primary reason for participation by parents with healthy children, but for parents whose children had life-threatening conditions, altruism was secondary [21].
The influence of others was also important. Potential participants’ confidence in the physician and/or the research was motivating [18, 23, 25,26,27,28, 30,31,32,33, 35,36,37]. Having a positive, trusting relationship with the doctor was commonly cited as a facilitator; for example, the idea that the ‘doctor knows best’ was expressed [38]. The opinions of family and friends also facilitated participation [27,28,29, 35, 40, 41].
The impact of the potential participant’s knowledge of trials and the quality of the study information was mixed. For example, knowing you could leave the trial increased participation [10], but one review highlighted that enhanced knowledge and understanding could decrease participation [32]. A study with children and parents highlighted the need for age-appropriate information [18], whilst another highlighted the need for cultural appropriateness [24]. However, knowledge could act as a barrier when too much complex information was provided [10, 22, 30] or when information was vague [36]. Gaining knowledge of their health condition was a participation facilitator for children [40] and those invited to biobank studies [37].
Financial benefits were discussed in three reviews, but did not appear to be a primary determinant [29, 34, 40]; rather, financial benefits were seen as an added bonus [34]. However financial constraints and costs could inhibit participation [28, 39, 40].
Barriers to research participation
Fear was identified as a barrier in a large number of reviews, often related to perceived risks of treatments or interventions being tested and possible side effects [19, 21, 22, 25, 27, 31, 33,34,35,36, 39,40,41,42]. Assessment of risk varied with the severity of the patient’s illness [21]; for example, patients with a life-limiting diagnosis were more tolerant of research risk, potentially because of the access that participation granted them to new medication [21]. This was also linked to a perceived lack of choice imposed by the terminal diagnoses: patients stated the view that there seemed no option but to participate [21, 26, 35, 40]. More specific fears regarding the safety of interventions were common in reviews of HIV vaccine trials [19, 29]: potential trial participants were concerned about vaccine efficacy, or whether it could increase their susceptibility to HIV [29]. Other fears included discovering their HIV status [34] or being reported to immigration [39].
Distrust in research was common across patient groups [24, 27, 29, 30, 32, 34, 39,40,41,42], but was particularly prominent amongst minority ethnic groups [27, 39], minority indigenous populations [24] and people in sub-Saharan Africa [34]. In one review, distrust was linked to a lack of knowledge and understanding [29]. Specific distrust concerns included potential breaching of privacy or confidentiality [24, 29, 42], being a ‘guinea pig’ [30, 40] and a general mistrust of researchers’ intentions [34]. Nevertheless, trust in the safety of research was also reported as a motivating factor [21, 40].
Treatment preference, either for or against a specific treatment, was a reported barrier in several reviews [10, 25, 32, 38, 40]. Preferences included not wanting to change medication or not wanting to receive a placebo or experimental treatment [38]. However, preference for a specific treatment could also be a facilitator; in one mental health systematic review participants wanted access to the non-pharmaceutical, talking therapies on offer [27].
Perceived stigma was a commonly reported barrier to recruitment to trials in HIV [19, 34] or mental health [27, 42]. People did not want others to know their HIV status or to assume it as a result of trial participation [19, 34]. In mental health studies, stigma was largely due to people not wanting to be perceived as ‘crazy’, ‘weak’ or ‘vulnerable’ [27].
Practical difficulties were highlighted including the perceived inconvenience of trial participation (for example, additional procedures and appointments) [19, 22, 27, 32, 38, 40], a lack of time [19, 28, 32, 38, 41], travel or transport issues [10, 19, 24, 25, 28, 31, 32, 38, 39, 41, 42], costs [10, 25, 28, 38,39,40], as well as employment [10, 39] or childcare responsibilities [10, 28].
Concerns about trial methods were highlighted as barriers, including the inherent uncertainty [10, 21, 36, 38] and randomisation [22, 27, 32, 33, 36, 40, 41]. Potential participants also stated concerns about possible unknown side effects [10] and uncertain treatment effectiveness [21, 38]. There was some evidence of confusion about the meaning of randomisation [32], whilst other reviews noted that patients understood the concept but felt that randomisation signified a loss of control [25, 38] or that the doctor should choose treatments based on clinical expertise. In contrast to the inhibiting effects of concern about trial methods and the practical implications of research, the perception of a trial as low burden or convenient tended to facilitate participation [29, 37, 40].
Whilst knowledge could facilitate research participation, a lack of knowledge and understanding of clinical research could have a negative effect [24, 29, 30, 40], and participants identified a need for more information [38]. This lack of knowledge was sometimes linked to limitations of the informed consent process [30].
Finally, the patient’s health state at the time of invitation to participate was important in some reviews. Some patients felt too ill to participate [27, 28, 42]; others who were happy with their current health were less likely to participate for fear of disrupting this [27]. However, adverse health could favour research participation. One review of trials in acute conditions found that patients in pain said they were willing to agree to anything [30].
The thematic pattern of barriers and facilitators
It is notable that the identified barriers and facilitators include cognitive, emotional, social, practical and instrumental factors.
We identified a smaller number of facilitators than barriers, and three facilitating factors were dominant: the potential for personal benefit; altruism; and trust. Each of these was identified in a majority of the 26 included systematic reviews. These three factors were evidenced across different health settings and different research designs: they appear to be generic factors in being potentially important influences on individuals’ decisions about research participation whatever the context.
Barriers to participation were larger in number and more disparate. Their influence also appears to relate to the research design and to individual circumstances. For example, patients had stated treatment preferences or a current stable state of health, both of which might be disrupted by research involving a change to treatment. In patients with HIV or mental illness, research participation could be seen as threatening to self-identity or other’s perception of them. Distrust of research was reported and was often culturally specific, being reported most often in minority and ‘low power’ population groups. Practical difficulties associated with research were related to individuals’ circumstances, such as the impact of research on transport costs, childcare or paid work: the impact of these factors on participation will vary considerably across the population. Many stated barriers were specific to trial-based research, with expressed dislike of randomisation, uncertainty and possible treatment change.
Determinants and their links to the Theoretical Domains Framework
The identified barriers and facilitators from the 26 systematic reviews each link to at least one TDF domain, although there is a clustering on knowledge, social influences, optimism (or pessimism), goals and beliefs about consequences (see Table 2). Each of these domains was then mapped to the overarching constructs outlined in the COM-B model. Amongst the inductively identified facilitators of research participation, the three most commonly included were personal benefit; altruism; and trust. All the facilitators including the three most common ones map to different facets of the Motivation component of the COM-B model.
Amongst the 11 inductively identified barriers, all are linked to Motivation facets (both reflective and automatic), with two also linked to Opportunities. One barrier was linked to Physical Capabilities. The two factors that could operate either as facilitators or barriers (other people’s influence; information quality and participant knowledge) were mapped to Motivation and Opportunity components, respectively.
Reported reasons for/against research participation and links to empirical recruitment research
There is a lack of overlap between the barriers and facilitators we identified and the interventions tested, both in terms of the distribution of studied strategies and their impact. Whilst treatment preference was an important barrier to participation, only one study tested a strategy (patient preference trial design) which could be mapped to this theme. For a number of identified barriers, including condition stigma and distrust, we identified no related interventions. Similarly, no identified studies appeared to analyse strategies which may improve recruitment by impacting on altruistic motives. Additionally, there were no tested interventions linked to the patient’s confidence in the physician and the influence of family and/or friends, although the influence of recruitment via the Church or endorsements by previous participants has been studied.
Three tested recruitment strategies (phone reminders, recruitment primer letters, increased contact during recruitment in person or by phone) were not linked to any identified psychosocial determinants. Phone reminders act as a prompt to memory, whilst primer letters act by raising awareness, with neither cited as a barrier to participation. Increased contact during recruitment could potentially act on knowledge, although its intended action is not made clear. A fifth strategy not linked to the identified psychosocial determinants (strategies aimed at recruiters or recruitment sites) is intended to change the behaviour of recruiters, not participants. Also of note is that our overview identified three systematic reviews that investigated barriers or facilitators in relation to recruitment to paediatric research, and yet only one of the intervention studies included in the Treweek review [8] assessed recruitment to paediatric trials.