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Interventions for increasing colorectal cancer screening uptake among African-American men: A systematic review and meta-analysis

  • Charles R. Rogers ,

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing

    Affiliation Department of Family & Preventive Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America

  • Phung Matthews,

    Roles Formal analysis, Methodology, Validation, Writing – review & editing

    Affiliation Department of Family & Preventive Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America

  • Lei Xu,

    Roles Writing – original draft, Writing – review & editing

    Affiliation Department of Health Education and Promotion, East Carolina University, Greenville, NC, United States of America

  • Kenneth Boucher,

    Roles Conceptualization, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

    Affiliation Cancer Biostatistics Shared Resource, Huntsman Cancer Institute, Salt Lake City, UT, United States of America

  • Colin Riley,

    Roles Formal analysis, Writing – original draft, Writing – review & editing

    Affiliation Department of Family & Preventive Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America

  • Matthew Huntington,

    Roles Formal analysis, Writing – original draft, Writing – review & editing

    Affiliation Department of Family & Preventive Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America

  • Nathan Le Duc,

    Roles Writing – original draft, Writing – review & editing

    Affiliation Department of Family & Preventive Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America

  • Kola S. Okuyemi,

    Roles Conceptualization, Writing – original draft, Writing – review & editing

    Affiliation Department of Family & Preventive Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America

  • Margaret J. Foster

    Roles Conceptualization, Data curation, Methodology, Supervision, Writing – original draft, Writing – review & editing

    Affiliation Medical Sciences Library, Texas A&M University, College Station, TX, United States of America



African-American men have the lowest 5-year survival rate in the U.S. for colorectal cancer (CRC) of any racial group, which may partly stem from low screening adherence. It is imperative to synthesize the literature evaluating the effectiveness of interventions on CRC screening uptake in this population.

Materials and methods

In this systematic review and meta-analysis, Medline, CINAHL, Embase, and Cochrane CENTRAL were searched for U.S.-based interventions that: were published after 1998–January 2020; included African-American men; and evaluated CRC screening uptake explicitly. Checklist by Cochrane Collaboration and Joanna Brigg were utilized to assess risk of bias, and meta-regression and sensitivity analyses were employed to identify the most effective interventions.


Our final sample comprised 41 studies with 2 focused exclusively on African-American men. The most frequently adopted interventions were educational materials (39%), stool-based screening kits (14%), and patient navigation (11%). Most randomized controlled trials failed to provide details about the blinding of the participant recruitment method, allocation concealment method, and/or the outcome assessment. Due to high heterogeneity, meta-analysis was conducted among 17 eligible studies. Interventions utilizing stool-based kits or patient navigation were most effective at increasing CRC screening completion, with odds ratios of 9.60 (95% CI 2.89–31.82, p = 0.0002) and 2.84 (95% CI 1.23–6.49, p = 0.01). No evidence of publication bias was present for this study registered with the International Prospective Registry of Systematic Reviews (PROSPERO 2019 CRD42019119510).


Additional research is warranted to uncover effective, affordable interventions focused on increasing CRC screening completion among African-American men. When designing and implementing future multicomponent interventions, employing 4 or fewer interventions types may reduce bias risk. Since only 5% of the interventions solely focused on African-American men, future theory-driven interventions should consider recruiting samples comprised solely of this population.


African-American men and women in the United States (U.S.) have the highest rates of most cancers in terms of both mortality and morbidity [1]. Despite being highly treatable when detected early, colorectal cancer (CRC) remains the second leading cause of death in the U.S. from cancers affecting both men and women, and the third deadliest among African Americans [2]. African-American men are disproportionately affected by CRC, experiencing the lowest 5-year survival rate of all racial and gender groups. Furthermore, African-American men are 24% more likely to have CRC than white men [3]. Contributing factors to these CRC incidence and mortality inequities among African-American men include a lack of health insurance and limited access to early detection screening, in addition to socioeconomic disadvantages such as lower education levels and higher poverty rates [1, 2, 4, 5]. Other contributing factors noted in the literature include lifestyle factors, existing chronic conditions, family history, tumor characteristics, a lack of social support, mistrust of medical systems, and perceptions of both racial discrimination and the African-American masculine role [314].

In June 2016, the U.S. Preventive Services Task Force (USPSTF), a panel of independent national experts who provide recommendations about clinical preventive services, recommended that all people, unless at heightened risk, should begin obtaining regular CRC screening at age 50 [15, 16]. In May 2018, the American Cancer Society (ACS) recommended that, due to increasing rates of CRC in younger individuals, routine screening should begin at age 45 [17]. Evidence-based screening for CRC exists in the form of either stool-based laboratory tests or camera-aided visual exams of the colon and rectum [17]. These options for asymptomatic individuals who are at average risk include the fecal immunochemical test (FIT) and guaiac-based fecal occult blood test (FOBT), recommended yearly; the multi-targeted stool DNA test every 3 years; a computed-tomography colonography or flexible sigmoidoscopy every 5 years, or a colonoscopy every 10 years [17]. An estimated 50% reduction in CRC mortality among the total U.S. population has been attributed to adherence to these guidelines [18].

Although CRC screening rates have been improving since 2005, evidence suggests that uptake remains low among African-American men and that screening is poorly understood in this population [19, 20]. African Americans “in general” have lower screening rates than whites (55.5% versus 61.5%) [1]. Recent research has identified several key factors associated with lower CRC screening uptake in African-American men, including fear and anxiety, especially in regard to colonoscopy, and a lack of knowledge about the curability of early-stage CRC [13, 21]. African-American men may also overestimate the risks associated with CRC screening procedures [13]. In addition, the FOBT—that requires patients to avoid eating certain kinds of meat and vegetables before the collection of stool, has a lengthy testing time, and necessitates patients handling their own fecal matter—has been associated with negative attitudes among African Americans [22].

Understanding and implementing evidence-based interventions that increase screening uptake among African-American men is a challenge. Intervention studies have reported mixed results about determining the most efficacious methods of increasing CRC screening uptake overall, and few studies of this nature specific to African-American men have been conducted. Furthermore, many of these trials are of low quality. Gee, Walsemann, and Brondolo argue that such interventions should be grounded in a theoretical approach that includes cultural and social factors as agents of change, as all too often healthcare interventions neglect the importance of these aspects in patients’ healthcare decisions [23]. Accordingly, our research team advocated for an assessment and evaluation of current evidence-based interventions that target increasing CRC screening uptake in African-American men. To meet this goal, we conducted a systematic review of the literature and a quantitative meta-analysis, with 2 aims: (1) synthesize the evidence from published studies evaluating interventions to increase CRC screening uptake among African-American men; and (2) quantitatively assess the evidence from these published studies through meta-analysis to determine the most effective screening uptake interventions for African-American men.

Rationale for systematic literature reviews

In recent decades, the amount of research on interventions to increase the uptake of CRC screening among African-American men has increased exponentially [24]. Consequently, it is more difficult for some researchers and medical professionals to digest current findings and directions in the literature [24]. Systematic reviews thus fill an important role by providing an overview of the current state of research on a particular topic, pointing out weaknesses and gaps in the literature, and clarifying where disagreement or contradictions are reported, as findings from individual studies may be inconsistent [25, 26]. Systematic methods must be used to conduct literature reviews because nonsystematic or narrative reviews are difficult to properly assess [27]. The use of a systematic approach also permits the researcher to create a set of parameters that allows for the elimination of bias by excluding flawed studies from the ultimate analysis [27].

Rationale for meta-analyses

Single studies are informative for building the literature on a particular topic, especially when evaluating treatments and interventions, but are prone to false positives and negatives [25]. A meta-analysis provides a systematic approach for evaluating a series of studies in which those with larger sample sizes carry more weight [25]. The strength of this technique also includes 1) enabling researchers to provide a quantitative estimate for the effect of a treatment or intervention, 2) helping researchers identify more precise estimates of intervention effectiveness or other outcomes than any individual study in a pooled analysis [28]. Thus, by aggregating the findings of many studies and correcting for potential error or bias, a meta-analysis helps to identify the potential pitfalls within any single study as well as to identify studies with consistent results [24]. Additionally, this technique enables researchers to identify the overall effect of a particular treatment or intervention [25].

Materials and methods

Study selection

To be included in the review, studies had to be: (1) inclusive of African-American/Black adult men 18 years of age or older; (2) focused on interventions for CRC screening uptake; (3) published after 1998, 2 years before the initial publication of the American College of Gastroenterology’s CRC screening guidelines [29]; (4) written in English and conducted in the U.S.; and (5) published, peer-reviewed, full-text journal articles. The (colorectal) cancer profile of African-born Blacks differs from that of U.S. States-born Blacks and also varies by region of birth [30], thus, our research team solely focused on U.S.-born African-American men. Studies based on secondary analyses of data were excluded. Although potential for publication bias remains, only peer-reviewed articles were considered as review for quality, relevancy, and accuracy by multiple experts in the field provides a higher level of validity [31]. In addition, because the research team was interested in interventions that proved to be effective in achieving increased screening completion, included studies had to report on actual CRC screening uptake, as opposed to changes in CRC screening beliefs or intent to screen.

To determine an article’s eligibility, a team consisting of 3 systematic review screening-trained co-investigators (authors CR, MH, and PM) performed 2 rounds of assessment. In the first round, they reviewed potentially eligible studies by article title and abstract from the results obtained in Rayyan QCRI, a web-based systematic-review platform that was created to expedite the initial screening of abstracts and titles, and uses a process of semi-automation while incorporating a high level of usability [32]. The databases Medline (Ovid), CINAHL (EBSCO), Embase (Ovid), and Cochrane CENTRAL (Wiley) were individually searched, and Rayyan QCRI was used to sort the retrieved manuscripts.

Last ran on January 14, 2020, the literature search combined 4 concepts: colorectal cancer, screening, African American, and men. Each concept was searched using database thesaurus terms and keywords as appropriate (see S1 Appendix). This method was based on the principles discussed in the Cochrane Handbook, including the combination of keywords and subject headings [33]. Discrepancies between the 2 team members were adjudicated by the study Principal Investigator (PI; first author CRR).

After this initial screening process, articles that potentially met all criteria, or the eligibility of which was unclear, underwent a second round of screening in which the same 2 authors again independently screened each article, and conflicts were resolved through face-to-face meetings with the PI. The screening team also reviewed the references of included articles. As a systematic review, this study did not require informed consent or institutional review board approval as human subjects were not involved. Yet, the protocol was registered with the International Prospective Registry of Systematic Reviews (PROSPERO 2019 CRD42019119510).

Data abstraction, risk of bias assessment, synthesis, and analysis

After articles had been accepted for the systematic review, the same 3 members of the research team (CR, MH, PM) coded each paper individually by entering information into a standardized Google form. Extracted data covered study characteristics such as sample size, demographics, and eligibility criteria. Other data gathered from the accepted articles included statistical analyses used, intervention type, theoretical background used, and limitations cited by the study authors. CR, MH, and PM also abstracted data and met weekly to resolve any coding conflicts. Tables were constructed to qualitatively describe the study design and report the results of each included study.

In order to determine the potential risk of bias, each study was randomly assigned to 2 of 3 study members (CRR, PM, MF) who assessed the studies by applying the appropriate critical appraisal criteria based on each study’s type independently. During this quality assessment process, the two authors followed the blind review protocol [34]. In detail, Cochrane Collaboration’s checklist was used to assess risk of bias for randomized control trials [35], as well as Joanna Brigg’s checklist for quasi-experimental [36] and cohort [37] studies. All disagreements were settled through discussions with a third member until consensus was reached.

For the meta-analysis, we first defined the values of I2 statistics; our results showed that I2 >75%, indicating that considerable heterogeneity was present [38, 39]. Next, substantial heterogeneity was investigated using meta-regression for intervention type (control intervention, FIT or other stool-based screening test, printed education materials, or patient navigation) as recommended by Sharp [40] and Newton [41]. Control intervention denoted the control group in the studies. For example, some studies reported usual care as a control group while others mailed letters recommending CRC screening. Then, we conducted sensitivity analyses to evaluate the effect of removing any 1 study from each meta-regression. To evaluate for bias resulting from the absence of studies with negative or insignificant results (often termed “publication bias”), we examined funnel plots visually for asymmetry and used the method of Egger and colleagues to formally test for funnel-plot asymmetry [25]. The “metaprop” and "metareg” functions in R package “meta” and “metafor” were employed for statistical analysis, using a random intercept logistic regression model that was fitted using restricted maximum likelihood (REML). We also used Clopper-Pearson exact binomial confidence intervals to report, respectively, for individual studies on the funnel plots. These analyses were conducted using R, and figures were produced using the meta package [4244].



A total of 1,465 articles were initially identified from the 4 databases searched, 41 (2.79%) were included in the final sample for the systematic review [4585]. As recommended by the PRISMA group [86], Fig 1 provides details regarding the identification, screening, eligibility, and inclusion processes. S2 Appendix details the research team’s adherence to PRISMA’s checklist—which helped improve the reporting quality for the current study.

Fig 1. Selection of studies for inclusion in review and meta-analysis.

Characteristics of included studies

Most interventions (73%) were performed in clinical or medical facilities. The remaining 11 (27%) studies that were not conducted in a clinical setting took place in a church (12%), business (3%), or did not report their intervention setting (12%). Studies were published between 2000 and 2019, with most (n = 12) appearing between 2010 and 2012. Two authors published more than 1 study on the topic (11%), namely, Blumenthal (n = 2), and Leone (n = 2) [50, 54, 68, 77]. Slightly more than half (56%; n = 23) of the studies included only participants aged 50 years and older, while five (12%) included participants starting at age 45 years, three (7%) included participants younger than 45. Twelve of the studies (29.27%) reported demographics specific to African-American men [50, 52, 56, 57, 59, 60, 63, 66, 71, 74, 82, 84]. In the studies aimed at increasing CRC screening uptake among African-American men, the intervention components most frequently employed (among 135 interventions types utilized) were telephone encounters or education (18%; n = 25), mailed or electronically sent educational materials (13%; n = 18), FIT or other CRC stool-based screening kits (mailed or administered in person) (13%; n = 17), patient navigation (10%; n = 13), and printed materials given to individuals in person (12%; n = 16). A matrix of the included studies, sorted according to their theoretical design and methodological features, is found in Table 1; these features are detailed below.

Table 1. Matrix of 41 reviewed studies, according to theoretical design and methodological features.


Nearly half of the studies (39%; n = 16) did not report a theoretical framework, while the remaining studies (61%; n = 25) used 1 to 3 frameworks. A theoretical foundation built on 1 conceptual model was most common (56%; n = 14), with the Health Belief Model the most utilized (28%; n = 7), followed by the Preventive Health Model (16%; n = 4) and the Transtheoretical Model (also referred to as Stages of Change) (16%; n = 4). For example, in a study grounded by the Preventive Health Model and input from a community advisory board, Christy and colleagues tested the effectiveness of their self-created CRC photonovella booklet plus a fecal immunochemical test (FIT) kit and the CDC’s standard “Screen for Life” brochure (not targeted to African-Americans plus a FIT kit among 330 Black participants (308 African Americans, 22 Caribbean/Haitians/Other) in Florida who were not current with CRC screening [5]. Fifty-two percent of this sample was male. The educational messages developed for the CRC photonovella were based on the following theoretical constructs: barriers, self-efficacy, CRC screening coherence and salience, response efficacy, and susceptibility of focus. Also, noteworthy, a randomized control trial (RCT) by DeGroff and colleagues was the only study driven by 3 frameworks: the Health Belief Model, Theory of Reasoned Action, and social learning theories [73]. This patient-navigation intervention aimed to address multilevel patient-defined barriers to CRC screening completion among 840 patients who were referred for a colonoscopy by primary care providers in Massachusetts. Eighty percent of participants were either non-Hispanic Black (40%) or Hispanic (40%). Two bilingual lay navigators (1 male, 1 female) delivered the intervention primarily via telephone, while some activities were conducted by mail or in person, with an average time of 44 minutes per patient. Both navigators received additional training in motivational interviewing.


Interventions were evaluated by geographic location, with 4 regions considered during coding: West, Midwest, South, and Northeast [87]. Interventions were conducted in all 4 geographic regions: South (44%), Northeast (32%), Midwest (12%), and West (12%). Most studies (90%; n = 37) reported that intervention delivery occurred in a single geographic region, 2 articles reported delivery in 2 regions, and 2 articles did not report the location of their interventions. For example, Leone and colleagues performed their intervention in both Michigan and North Carolina, stating that the 2-state approach was as an effort to increase the generalizability of their results [54].


Setting—where studies take place—is a highly influential factor for intervention outcomes due to its potential impact on sample representation, intervention uptake, and sustainability. Approximately 81% of studies implemented interventions in 1 primary setting, 7% used multiple settings, and 12% did not report the intervention setting. For example, Blumenthal and colleagues delivered CRC education messages via radio, newsletters, public transportation, health fairs, festivals, television programs, etc [68]. Blumenthal and colleagues used community-based participatory research, which places the responsibility for intervention design and delivery, including setting, in the hands of community partners [50, 68]. DeGroff et al., Fiscella and colleagues, and Gupta et al. are examples of studies that used local resources (i.e. established medical networks and safety clinics) to meet the disproportionate health needs of largely minority areas [46, 58, 73]. Two studies used clinical/medical settings due to the presence of an open-access endoscopy system, which was defined by Chen and colleagues as providing direct referrals for CRC screening and thus bypassing additional gastroenterology exams and decreasing the number of appointments that study participants needed to attend [47, 49].

Interventions that took place outside of clinical or medical settings were conducted in churches (12%), local businesses (5%), and other communal spaces (e.g., community centers, social organizations) (~5%). Several studies justified using church-based settings because religion and faith are central themes of African-American culture; church settings are a natural venue to introduce faith-based intervention materials; previous church-based interventions have proven effective for addressing other health disparities in African-American populations; and church settings may be able to reach those with limited access to healthcare [54, 60, 78]. Cole and colleagues, who conducted their intervention in New York City barbershops, emphasized the community-based approach, stating that––as is commonly seen among African-American men––those with the greatest need are not accessing the healthcare system [57]. Setting selection in our sample was likely also influenced by available resources, funding sources, and population need. The effectiveness of interventions conducted in clinical versus community-based settings should be further evaluated.

Post-intervention screening uptake.

Reported screening uptake percentages among study participants ranged from 8% to 90% [45, 76]. The intervention with the highest overall screening uptake (81.9%) involved sending participants a culturally sensitive photonovella and a free FIT kit [45]. Interestingly, however, this same study reported that 90% of their controls––subjects who received a standard CRC screening brochure developed by the CDC, along with the free FIT kit––also reported screening uptake [45]. Most, but not all, studies reported higher screening uptake rates in the intervention group than in the control group.

Intervention types.

Many of the studies evaluated used more than 1 intervention to increase CRC screening (see Table 2). Often, 2 or more intervention arms were used, along with a control arm. Intervention arms often included more than 1 component or type of intervention. For example, 1 study compared patient navigation alone with patient navigation plus motivational interviewing or a control group [57]. Another study combined a screening decision aid with patient navigation [62]. One intervention was a citywide messaging campaign that included educational sessions at local community centers, yard signs, and messages in newspapers [68]. Because of this heterogeneity, it was difficult to succinctly categorize studies by the type of intervention used. However, we found that 43% (n = 16) of studies used some form of tailored educational material; 32% (n = 12) included patient navigation; 22% (n = 9) included some form of group or 1-on-1 education; 22% (n = 9) gave subjects free FIT or immunochemical fecal occult blood test (iFOBT) kits; 9% (n = 4) employed telephone outreach; and 3% (n = 1) intervened at the physician level.

Table 2. Number of CRC interventions used in a sample of (41) reviewed studies.

The intervention that performed best compared with controls was in a study by Reuland and colleagues that incorporated a screening decision aid along with patient navigation; 68% of participants in the intervention arm reported screening uptake compared with 27% of controls [62]. Unfortunately, this study did not break out its screening-uptake results by race; thus, it cannot be determined how much this intervention affected African Americans specifically. Among African Americans specifically, the intervention that resulted in the highest screening uptake compared with controls mailed a free FIT kit to participants, 43% of whom returned the kit, compared with 15% of controls who engaged in some other form of screening [58].

The 2 interventions that most commonly reported significant differences in screening uptake among African-American participants compared with controls were patient navigation and free FIT or iFOBT kits. Tailored materials, such as culturally sensitive brochures or videos, and education, whether in person or in a group setting, also had positive outcomes, but not to the extent of patient navigation or free screening kits. Interestingly, Mehta and colleagues approached CRC screening uptake by providing financial incentives via 3 arms: unconditional, conditional, and lottery [81]. The unconditional arm was given a $10 gift card along with the FIT kit, while those in the conditional arm received the $10 gift card after completion of the FIT testing if within 2 months. Participants randomized to the lottery arm were afforded the opportunity to win a $100 gift card–with a 1 in 10 chance of winning—if the FIT test were completed and returned within the 2 months mark [81].

Intervention delivery.

Interventions were most commonly implemented by the study researchers themselves, medical personnel, or public health workers (as was the case among patient navigation interventions). Some studies enlisted the help of local community members, including churches, barbershops, and other local businesses [57, 68, 78, 82]. Besides the use of patient navigators in general, there was no observed trend in CRC screening uptake related to who implemented the intervention. For example, standard patient navigation resulted in higher CRC screening uptake (80%) compared with peer–patient navigators (African-American community members who were specially trained to be patient navigators) (74%) or pro–patient navigators (healthcare professionals who were trained to deliver culturally sensitive patient navigation) (76%) [60].

Limitations of interventions.

Most studies recognized a lack of generalizability in their results due to the subject population or the geographic region in which the study was conducted. For example, 1 study reported that “participants were recruited from healthcare providers in large urban settings, consisted of 75% females and had regular contact with a healthcare provider, and thus are not representative of the African American community in its entirety [67].” Another reported issue regarding generalizability relates to the potential for selection bias, especially in studies in which the main intervention was a free FIT/iFOBT kit. These studies first contacted the individuals to see if they were willing to participate in the study, and then the subjects received the free kits. Because the participants were already willing to participate in research, they may have been more likely than other members of the general public to use and send back the FIT kits.

In many studies, especially those that used patient navigation or provided free FIT/iFOBT kits, cost was often cited as problematic for wide-scale implementation of the intervention. A study of 2 citywide interventions that implemented various intervention strategies reported that radio and TV were the most effective media used, but recognized these are expensive options that may not be financially feasible for others [68]. However, if granted financial incentives, Mehta et al. found the incentive amount of $10 might have been too small to promote any increase in FIT kit completion [81].

Another commonly reported limitation was the nature of the intervention follow-up. In general, follow-up to check CRC screening status ranged from 3 to 12 months. However, it is possible that participants obtained screening after these follow-up points and thus their data were missed. Along with follow-up time, the ability to contact participants at follow-up was also reported to be problematic. This was especially true in low-income populations. In 1 study, patient navigators were unable to follow up with 23% of participants [55]. This problem was avoided in studies that had access to electronic health records where screening status could easily be verified. However, not all studies had such capability.

Study design was also commonly mentioned as a potential limitation. Though most studies were RCTs, few incorporated any kind of blinding because of the nature of the interventions used (patient navigation, free FIT kits, culturally tailored brochures).

Risk of bias

Studies were allocated into 3 categories to assess for biases: Randomized Controlled Trials ([RCTs], Fig 2), Cohort (Fig 3), and Quasi-Experimental (Fig 4). Twenty-nine studies [45, 46, 48, 5052, 5466, 69, 71, 7375, 77, 7981, 83, 84] in the RCT category were largely rated as unclear risk, yet 20 of the studies had low risk on random sequence generation (i.e., description of randomization procedure) [5052, 5663, 69, 74, 75, 7981]. The majority of the studies (n = 13) did not explain or detail if any blinding of the participants and/or personnel in group allocation occurred, which included 18 studies with an unclear risk on allocation concealment [48, 50, 52, 54, 55, 57, 6366, 71, 74, 77, 79, 80, 83]. Either listed as a supplement in the manuscript or published elsewhere, only 5 studies [50, 57, 58, 61, 80] reported their study protocol. Overall, 26 RCTs did not account for blinding of outcomes while 6 RCTs [45, 48, 50, 56, 57, 63] received a high bias rating due to their report of additional biases. Moreover, studies with the highest numbers of interventions (n = 9, Leone et al. 2016 [54], n = 7, Martin et al. 2017 [72], and n = 6, Reuland et al. 2017 [62]) demonstrated risk of bias scores ranging from unclear to high risks. Multicomponent studies with the lowest risk bias utilized 4 or fewer types of interventions.

Fig 4. Risk of bias graph for Quasi-experimental studies.

Next, 9 of the studies were classified as quasi-experimental [49, 53, 67, 68, 70, 72, 76, 78, 82]. Although only 2 of these studies contained a control group [68, 76], a high bias risk was yielded for the remaining 7 studies. All 9 studies revealed low bias risk for outcome measurement appropriate statistical analysis use. Lastly, 2 studies were considered for the cohort design [47, 85], with both having similar ratings for low bias risk.


Meta-regression was used to compare the 4 intervention types (Table 3). The endpoint for the meta-analysis was intervention effectiveness, defined as the proportion of participants that obtained CRC screening during or after the intervention. Interventions that used a FIT kit or patient navigation were significantly better than the print and control intervention at increasing CRC screening uptake among African-American men, with odds ratios (ORs) of 9.60 (95% CI 2.89–31.82, p = 0.0002) and 2.84 (95% CI 1.23–6.49, p = 0.01), respectively. Meta-analysis results were reported for each intervention type separately (see Figs 57). Interventions that used print materials were not significantly better than control interventions. To directly compare pairs of interventions, additional models were fitted restricting the studies to a pair of interventions. In these models, FIT interventions were not superior to patient-navigation (PN) interventions (OR = 3.42, 95% CI 0.75–15.62, p = 0.11), FIT interventions were superior to print interventions (OR = 5.01, 95% CI 1.87–13.67, p = 0.001), and PN interventions were not significantly different from print interventions (OR = 1.52, 95% CI 0.59–3.90, p = 0.38). There was evidence of substantial statistical heterogeneity (range of I2 between 93% and 98% for the 4 interventions, all p < 0.01) for combined ORs across categories. No single study significantly influenced the meta-regression results.

Fig 5. Meta-analysis for control and FIT (fecal immunochemical test) interventions.

Events: number of participants with screening outcomes in the arm of the study; Total: number of participants in the arm of the study; Proportion: the ratio between Events and Total.

Fig 6. Meta-analysis for PN (patient navigation) interventions.

Events: number of participants with screening outcomes in the arm of the study; Total: number of participants in the arm of the study; Proportion: the ratio between Events and Total.

Fig 7. Meta-analysis for print interventions.

Events: number of participants with screening outcomes in the arm of the study; Total: number of participants in the arm of the study; Proportion: the ratio between Events and Total.

Publication bias analysis

As depicted in a symmetric funnel plot (see S1 Fig), no publication bias was found in this study [88]. Moreover, no evidence of bias was detected by Egger and colleagues’ test (bias = –1.17, SE = 3.18, P = .72) [89].


Findings overview

The purpose of this systematic review and meta-analysis was to ascertain which interventions were most effective in increasing CRC screening uptake among African-American men. In our qualitative analysis of the extant literature examining the various types of interventions, patient navigation and the distribution of free stool-based test kits, including FIT and iFOBT kits, emerged as the most consistently effective interventions. Print and other educational materials were the most common interventions, but their results were mixed, with some studies reporting increased screening rates compared with controls, while others reported similar or lower screening rates compared with control groups. Through using the Cochrane risk of bias tools to assess the eligible studies in our review, we found that most RCTs failed to provide any details about the blinding of the participants recruitment method, the allocation concealment method, and/or the outcome assessment. Future RCT research should focus on enhancing the research design quality in these specific areas, particularly in the implementation and evaluation stages. In addition, most of the quasi-experimental studies lacked control groups in their study design. Therefore, the ability to make group comparisons among participants was challenging and it was nearly impossible to compare the interventions’ effectiveness. Statistical evidence with both clearly defined controls are needed in future studies.

Heterogeneity of the findings made it challenging to determine which intervention was most effective and should be considered for future studies focused on African-American men as recommended by Kwaan and Jones-Webb [90]. Due to the diversity of settings, geographic regions, interventions employed, and outcomes measured, factors other than the intervention may have influenced CRC screening uptake. For example, most studies were conducted within a medical clinical or hospital. This setting in and of itself may have increased CRC screening uptake by increasing access to other resources (e.g., electronic health records, scheduling services, screening materials).

Further, it should be noted that most of the interventions were implemented by healthcare professionals, including physicians, public health workers (e.g., patient navigators), and the researchers themselves. This may have influenced screening uptake rates as participants may have had an implicit bias toward obtaining CRC screening to please researchers or doctors. Conversely, medical mistrust—a common factor that significantly contributes to delays in healthcare system utilization by African-American men—may have discouraged African American study participants specifically from obtaining CRC screening [3].

Future directions

Only 2 of 41 studies reviewed (5%) focused exclusively on African-American males [57, 66]. Though each study included some African-American males, researchers rarely examined barriers and enablers specific to this group, which continues to suffer the most from CRC incidence and mortality [1]. The lack of understanding of CRC screening-completion barriers and enablers among African-American men was exacerbated in our study by the lack of distinction in the data reported for race and gender. Studies that segmented data by race or gender did one or the other but not both, leaving the African-American male experience with CRC screening further underrepresented in intervention studies. To achieve the goal of reducing CRC-related inequities among African-American men, health promotion and prevention interventions that centralize cultural identity and cultural empowerment should be developed in order to better capture African-American men’s CRC screening experiences within a culture-specific context and their understanding of those experiences [91, 92].

Our inclusion criteria for the review required a study population that included African-American men, and this specification may have been the cause of the geographic dispersion among the interventions evaluated. The U.S. Census Bureau reports that a majority of the African-American population of the U.S. is concentrated in the Southern and Northeastern regions [93]. Additionally, African Americans experience greater CRC incidence, higher mortality, and lower survival at all stages, when compared to their white counterparts, and several articles mentioned that the geographical locations where interventions were implemented had large populations of African Americans experiencing CRC disparities [3, 19, 49, 59, 78]. However, the majority of the studies (76%) is this review occurred in Eastern and Southern states, with only 25% in Western and Midwestern states. The preponderance of data from the East and South––while helpful for providing insight into regional barriers and enablers to CRC screening uptake––is not equally applicable to all African-American populations. Given geographical variability in diet, culture, and intergenerational attitudes along with the effect of these variables on CRC screening outcomes, more-specific regional information is required to develop effective interventions in understudied areas. Western states, though included in only 12% of the studies evaluated, are home to the nation’s most ethnically diverse populations and currently represent what is projected to be a nationwide shift in the ratio of ethnic-to-nonethnic residents [94, 95]. Specifically, the West encompasses 13 of the 25 most ethnically diverse cities in the nation and the most ethnically diverse state, California, with a census-reported population that is 39% Hispanic-white and 36% non-Hispanic white [94, 96]. As more regions transform to resemble California’s demographic distribution, it is critical that future research includes and emphasizes the barriers and enablers of CRC screening completion in minority-majority areas. More geographically dispersed studies occurring outside of the Southern and Northeastern regions of the U.S. are needed. Moreover, with the unscreened populations in these regions, subgroup differences for those experiencing CRC disparities are yet to be identified.

It is noteworthy that slightly over 75% of the interventions aimed at increasing CRC screening uptake occurred in medical or clinical settings. Although many of these studies did not provide a justification for choosing to provide the intervention in a clinical setting, this decision may have been due to ease of data access, convenience sampling, or community needs. While many of the initiatives to promote CRC screening described in this review took place in healthcare settings and have proved successful, it is likely that individuals who did not seek routine medical care, did not have a regular healthcare provider, or lived with lower socioeconomic status were excluded from the interventions [19]. In particular, the aforementioned scenarios have been demonstrated as potential barriers that prevent African-American men from seeking or obtaining CRC screening [97100]. Therefore, to reduce the pervasive CRC screening disparities faced by African-American men, it is important for future public health workers, healthcare organizations, patient navigators, researchers, and physicians to consider collaborating to design, evaluate, and implement interventions in non-healthcare settings.

In this review, 24% of the included studies formulated and conducted their CRC intervention programs in churches, local businesses (e.g., barbershops), and other community settings [47, 57, 68, 78, 101]. For example, Holt and colleagues discussed using church-based approaches to promote CRC prevention behaviors through a series of community health advisor–led educational modules [78]. However, results from the educational series suggested that adding spiritual themes did not result in significant behavioral changes among attendees. This might further validate the role of other contributing factors, such as lack of health insurance, lack of access to early-detection screening, medical system mistrust, and socioeconomic disadvantages as mediators influencing early detection screening behavior changes among African-American men, and thus, should be considered alongside the other well-documented barriers to CRC screening [101, 102].

Furthermore, as highlighted in a previous systematic review by Rogers and colleagues, there is a need to better understand the influence of sociocultural determinants that may influence African-American men’s negative responses, reluctance, and apprehension associated with CRC screening [103]. Culturally sensitive community-based interventions among African-American men should be further developed and implemented. However, a few other cautions should be considered by future researchers while designing Federally Qualified Health Center (FQHC) non-clinically–based programs. Maxwell and colleagues noted that it remained challenging to implement and sustain their community-based programs to increase CRC screening among Filipino Americans primarily due to (1) the need for program participants to seek screening through their healthcare providers, (2) lack of funds to sustain the program, and (3) lack of an adequately trained workforce to maintain program activities [104]. Similarly, it is imperative to test the effectiveness of community-based interventions in an environment that supports the sustainable growth of CRC screening promotion programs for African-American men. Moreover, to ensure that African-American men receive the optimal benefits of early detection screening for CRC, researchers must move beyond traditional practice-based settings into community-based locations.

Lastly, from the research team’s observations, cost was a dominant concern or barrier in implementing large-scale CRC screening interventions across the selected studies. Cost-effectiveness strategies require an overall assessment of patient and provider barriers, the navigation system, and other potential inhibitors of CRC screening [105]. Because a significant burden of CRC and observed disparities in CRC screening uptake still exists among African-American men, programs tailored to this population should consider how to effectively enhance knowledge of the benefits of CRC screening, improve access to health care, and elevate the related insurance services [15, 103105]. In clinical settings, strategies to better utilize patient navigation systems to emphasize the importance of screening and enhance educational outreach for healthcare providers who provide routine care for African-American men could conceivably aid in lowering the cost of promoting CRC screening, particularly among low-income patients [105]. In community settings, interventions that could efficaciously dispel the mistrust and ease the anxiety associated with screening are vital to promoting screening among African-American men [19, 102]. According to Adams and colleagues in a recent systematic review, African-American men often face unique challenges and express substantial fears about medical procedures associated with CRC [106108]. Adams and colleagues reported that higher mistrust scores correlated with lower CRC screening rates among African-American men in most of the quantitative studies included in their review [96, 106, 109]. In addition, several dominant recurring themes such as “mistrust as a barrier to screening,” “skepticism of provider motives,” and “mistrust of competence and quality of providers/systems” were identified in qualitative studies [74, 106, 110].

Future studies should thoroughly evaluate the effectiveness of different modes of intervention—e.g., patient navigators, telephone outreach, and text messaging. For example, in an effort to explore CRC screening among African-American church members using both qualitative and quantitative methods, the quality of patient-provider communication proved to be the most influential factor in participants’ completion of CRC screening [111]. From the articles included in this review, we can conclude that it is debatable which CRC promotion modes work best for African-American men. However, our meta-analysis results revealed that future interventions utilizing FIT or enhancing patient navigation suited better than traditional methods in increasing CRC screening uptake among this group. Traditional methods included usual care as seen in the control groups of the study, and was significantly inferior to the FIT (p = 0.0002) and patient navigation interventions (p = 0.01). Print interventions were also secondary juxtaposed to FIT (p = 0.001). As recommended in the 2019 CRC screening messaging guidebook, promoting CRC screening via text messaging could be a cost-effective strategy to improve interventions compared with traditional methods (e.g., mailings, printed materials, telephone reminders) [112]. More research and evidence are warranted to identify more cost-beneficial interventions focused on motivating unscreened African-American men to seek recommended CRC screening.


Our study is not without limitations. First, although our publication bias analysis found no such bias, it cannot be ruled out, as studies with negative findings were less likely to be published. Secondly, a significant challenge with our meta-analysis was the heterogeneity of the published data. Most of the studies we reviewed could not be included in the meta-analysis because they did not provide sample or study-outcome data specific to African Americans, especially African-American men, or because the interventions were too dissimilar to combine with other studies. Moreover, since most studies had different inclusion criteria, it was impossible to adjust for a confounder or covariate unless all levels of the covariate were available in all studies. Since this resulted in difficulty teasing out which intervention components were most effective, the meta-analysis results must be interpreted with caution. Next, due to the small sample, aforementioned heterogeneity, and the notion that ‘the best CRC screening test is the one that gets done’, the data captured for the meta-analysis focused on the proportion of participants who completed CRC screening juxtaposed to specific types of screening. On account of the significant difference in the nature of CRC screening modalities, such as colonoscopy vs. FIT, separate analyses (both in future systematic review and meta-analyses) may reveal different results regarding strengthening future interventions for increasing CRC screening completion. Furthermore, since most clinical trials require 2–4 phases—potentially causing minor to major percentage differences for CRC screening uptake based on the effects of different intervention approaches, a more thorough systematic approach that compares these differences as well as conduciveness of different CRC screening modalities in clinical versus community settings may be useful to detect the intervention outcomes. Nevertheless, our findings highlight the lack of consensus in the literature regarding interventions for increasing CRC screening uptake, especially among African-American males. Lastly, although our research team made every effort to ensure our search yielded all applicable data and no publication bias was found in this study, it is possible that some articles were missed and the ability of bias to distort results of future meta-analyses and systematic reviews should be considered.


In summary, this systematic review and meta-analysis examined the existing evidence for interventions aimed at increasing CRC screening uptake among African-American men. Most of the included studies used approaches such as patient navigation, telephone outreach, targeted brochures, and other multicomponent promotion packages to enhance CRC screening rates. Yet, our findings reflected a dearth of studies unambiguously focused on African-American men. Only 2 of the 41 studies in our review (5%) specifically explored the efficacy of CRC screening-promoting initiatives among African-American men. Since half of the reviewed studies were guided by 1 or multiple conceptual frameworks, a greater number of theory-driven CRC screening interventions are needed. Since studies with the lowest risk of bias employed 4 or fewer interventions, future multicomponent interventions should consider this evidence when designing and implementing CRC screening completion-focused studies among African-American men and other underserved populations. To achieve the National Colorectal Cancer Roundtable’s challenge to attain screening rates of 80% or higher in every community, further study is warranted that considers employing evidence-based, cost-effective, and culture-specific techniques targeting CRC screening completion among African-American men outside of traditional clinic settings.

Supporting information

S1 Fig. Begg’s funnel plot with 95% confidence limits.



The research team extends appreciation to Eleanor Mayfield for editorial support. This study was supported by Huntsman Cancer Institute’s Cancer Biostatistics Shared Resource at the University of Utah and the National Cancer Institute of the National Institutes of Health (NIH) [grant numbers K01CA234319 and P30CA042014]. All relevant materials discussed in this study—registered with the International Prospective Registry of Systematic Reviews (PROSPERO 2019 CRD42019119510)—may be requested from the corresponding author free of charge. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, Huntsman Cancer Institute, or the University of Utah.


  1. 1. DeSantis C, Siegel R, Jemal A. Cancer Facts & Figures for African Americans 2016–2018. Atlanta: American Cancer Society; 2018,40p Report No.:861416.
  2. 2. American Cancer Society. Cancer Facts & Figures 2018. Atlanta: American Cancer Society; 2018:76p.
  3. 3. American Cancer Society. Colorectal Cancer Facts & Figures 2017-2019.Atlanta; American Cancer Society 2018:40p.
  4. 4. Griffith KA, McGuire DB, Royak‐Schaler R, Plowden KO, Steinberger EK. Influence of family history and preventive health behaviors on colorectal cancer screening in African Americans. Cancer. 2008;113(2):276–285. pmid:18543276
  5. 5. Holden DJ. Systematic Review: Enhancing the Use and Quality of Colorectal Cancer Screening. Ann Intern Med. 2010;152(10):668. pmid:20388703
  6. 6. Hammond WP, Matthews D, Mohottige D, Agyemang A, Corbie-Smith G. Masculinity, Medical Mistrust, and Preventive Health Services Delays Among Community-Dwelling African-American Men. J Gen Intern Med. 2010;25(12):1300–1308. pmid:20714819
  7. 7. Rogers CR, Mitchell JA, Franta GJ, Foster MJ, Shires D. Masculinity, Racism, Social Support, and Colorectal Cancer Screening Uptake Among African American Men: A Systematic Review. Am J Mens Health. 2017;11(5):1486–1500. pmid:26483293
  8. 8. Sineshaw MH, Ng K, Flanders WD, Brawley OW, Jemal A. Factors that Contribute to Differences in Survival of Blacks vs White Patients with Colorectal Cancer. Gastroenterology. 2018;154(4):906–915.e7 pmid:29146523
  9. 9. Rodriguez EA, Tamariz L, Palacio A, Li H, Sussman D. Racial Disparities in the Presentation and Treatment of Colorectal Cancer: A Statewide Cross-sectional Study. J Clin Gastroent. 2018;52(9):817–820 pmid:29095418
  10. 10. Silber JH, Rosenbaum PR, Ross RN, Nikman BA, Ludwig JM, Wang W, et al. Racial Disparities in Colon Cancer Survival: A Matched Cohort Study. Ann Intern Med. 2014;161(12):845–854 pmid:25506853
  11. 11. Ellis L, Canchola AJ, Spiegel D, Ladabaum U, Haile R, Gomez SL. Racial and Ethnic Disparities in Cancer Survival: The Contribution of Tumor, Sociodemographic, Institutional, and Neighborhood Characteristics. J Clin Oncol. 2018:36(1):25–33 pmid:29035642
  12. 12. Augustus GJ and Ellis NA. Colorectal Cancer Disparity in African Americans Risk Factors and Carcinogenic Mechanisms. Am J Pathol. 2018:188(2):291–303 pmid:29128568
  13. 13. Williams R, White P, Nieto J, Vieira D, Francois F, Hamilton F. Colorectal Cancer in African Americans: An Update. Clin Transl Gastroenterol. 2016;7(7):e185. pmid:27467183
  14. 14. Henrikson NB, Webber EM, Goddard KA, Scrol A, Piper M, Williams MS, et al. Family History and the Natural History of Colorectal Cancer: Systematic Review. Genet Med. 2015:17(9):702–712 pmid:25590981
  15. 15. Agency for Healthcare Research and Quality. U.S. Preventive Services Task Force (USPSTF): An Introduction[Internet]. Rockville(MD); Agency for Healthcare Research and Quality; 2012 Sep- [last reviewed 2019 June, cited 2018 Nov 7]. Available from:
  16. 16. U.S. Preventive Services Task Force. USPSTF A and B Recommendations—US Preventive Services Task Force [Internet]. Rockville (MD); 2016 - [updated 2019 Aug, cited 2018 Nov 7]. Available from:
  17. 17. American Cancer Society. American Cancer Society Guideline for Colorectal Cancer Screening [Internet]. Atlanta(GA); 2018 [last revised 2018 May 30, cited 2018 Oct 26]. Available from:
  18. 18. Zauber AG. The Impact of Screening on Colorectal Cancer Mortality and Incidence–Has It Really Made a Difference? Dig Dis Sci. 2015;60(3):681–691. pmid:25740556
  19. 19. Brittain K, Loveland-Cherry C, Northouse L, Caldwell CH, Taylor JY. Sociocultural differences and colorectal cancer screening among African American men and women. Oncol Nurs Forum. 2012;39(1):100–107. pmid:22201660
  20. 20. Harewood GC, Wiersema MJ, Nelson H, Maccarty RL, Olson JE, Clain JE, et al. A prospective, blinded assessment of the impact of preoperative staging on the management of rectal cancer. Gastroenterology. 2002;123(1):24–32. pmid:12105829
  21. 21. Sly JR, Edwards T, Shelton RC, Jandorf L. Identifying Barriers to Colonoscopy Screening for Nonadherent African American Participants in a Patient Navigation Intervention. Health Educ Behav. 2013;40(4):449–457. pmid:23086556
  22. 22. Bass SB, Gordon TF, Ruzek SB, Wolak C, Ward S, Paranjape A, et al. Perceptions of Colorectal Cancer Screening in Urban African American Clinic Patients: Differences by Gender and Screening Status. J Cancer Educ Off J Am Assoc Cancer Educ. 2011;26(1):121–128. pmid:20443096
  23. 23. Gee GC, Walsemann KM, Brondolo E. A Life Course Perspective on How Racism May Be Related to Health Inequities. Am J Public Health. 2012;102(5):967–974. pmid:22420802
  24. 24. Littell JH, Corcoran J, Pillai VK. Systematic Reviews and Meta-Analysis. Oxford; New York: Oxford University Press; 2008.
  25. 25. Egger M, Smith GD, O’Rourke K. Introduction: Rationale, Potentials, and Promise of Systematic Reviews. In: Systematic Reviews in Health Care. John Wiley & Sons, Ltd; 2008:1–19.
  26. 26. Garrard J. Health Sciences Literature Review Made Easy: The Matrix Method. 5th ed. Burlington: Jones & Bartlett Learning; 2017.
  27. 27. Oxman AD, Guyatt GH. Guidelines for reading literature reviews. CMAJ Can Med Assoc J. 1988;138(8):697–703.
  28. 28. Russo MW. How to Review a Meta-Analysis. Gastroenterology & Hepatology. 2007;3(8):637–642
  29. 29. Rex DK, Johnson DA, Anderson JC, Schoenfeld PS, Burke CA, Inadomi JM. American College of Gastroenterology Guidelines for Colorectal Cancer Screening 2008. Am J Gastroenterol. 2009;104:12.
  30. 30. Medhanie GA, Fedewa SA, Adissu H, DeSantis CE, Siegel RL, Jemal A. Cancer Incidence Profile in Sub-Saharan African-born Blacks in the United States: Similarities and Differences with US-born Non-Hispanic Blacks. Cancer. 2017:123(16):3116–3124 pmid:28407201
  31. 31. Kelly J, Sadeghieh T, Adeli K. Peer Review in Scientific Publications: Benefits, Critiques, & A Survival Guide. EJIFCC. 2014;25(3):227–243. pmid:27683470
  32. 32. Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan—a web and mobile app for systematic reviews. Syst Rev. 2016;5(1). pmid:27919275
  33. 33. Higgins JPT, Green S. Cochrane Handbook of Systematic Reviews of Interventions. Chichester: Wiley; 2008.
  34. 34. Drucker AM, Fleming P, Chan AW. Research Techniques Made Simple: Assessing Risk of Bias in Systematic Reviews. J Invest Dermatolo. 2016;136(11):e109–e114 pmid:27772550
  35. 35. Higgins JPT, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials BMJ 2011; 343: d5928 pmid:22008217
  36. 36. Tufanaru C, Munn Z, Aromataris E, Campbell J, Hopp L. Chapter 3: Systematic reviews of effectiveness. In: Aromataris E, Munn Z (Editors). Joanna Briggs Institute Reviewer's Manual. The Joanna Briggs Institute, 2017. Available from
  37. 37. Moola S, Munn Z, Tufanaru C, Aromataris E, Sears K, Sfetcu R, Currie M, Qureshi R, Mattis P, Lisy K, Mu P-F. Chapter 7: Systematic reviews of etiology and risk. In: Aromataris E, Munn Z(Editors). Joanna Briggs Institute Reviewer's Manual. The Joanna Briggs Institute, 2017. Available from
  38. 38. Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Statist Med. 2002;21(11):1539–1558. pmid:12111919
  39. 39. Higgins JPT. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–560. pmid:12958120
  40. 40. Sharp S. Meta-analysis regression. Stata Technical Bulletin. 1998;7(42).
  41. 41. Newton, HJ., editor. [cited 2019 Dec 17] Meta-analysis regression. Stata Technical Bulletin [Internet]. 1998. 42(March). Available from:
  42. 42. R Core Team. R: A Language and Environment for Statistical Computing. [Internet] Vienna, Austria: R Foundation for Statistical Computing; 2018 [cited 2019 Dec 17]. Available from:
  43. 43. Schwarzer G. meta: An R Package for Meta-Analysis. R News. 2007;7:7.
  44. 44. Viechtbauer W. Conducting Meta-Analyses in R with the metafor Package. J Stat Softw, Articles. 2010;36(3):1–48.
  45. 45. Christy SM, Davis SN, Williams KR, Zhao X, Govindaraju SK, Quinn GP, et al. A community-based trial of educational interventions with fecal immunochemical tests for colorectal cancer screening uptake among blacks in community settings: Community CRC Screening Trial. Cancer. 2016;122(21):3288–3296. pmid:27420119
  46. 46. Fiscella K, Humiston S, Hendren S, Winters P, Idris A, Li SXL, et al. A Multimodal Intervention to Promote Mammography and Colorectal Cancer Screening in a Safety-Net Practice. J Natl Med Assoc. 2011;103(8):762–768. pmid:22046855
  47. 47. Chen LA, Santos S, Jandorf L, Christie J, Castillo A, Winkel G, et al. A Program to Enhance Completion of Screening Colonoscopy Among Urban Minorities. Clin Gastroenterol Hepatol 2008;6(4):443–450. pmid:18304882
  48. 48. Davis SN, Christy SM, Chavarria EA, Abdulla R, Sutton SK, Schmidt AR, et al. A randomized controlled trial of a multicomponent, targeted, low-literacy educational intervention compared with a nontargeted intervention to boost colorectal cancer screening with fecal immunochemical testing in community clinics: Screening With FIT Among Underserved. Cancer. 2017;123(8):1390–1400. pmid:27906448
  49. 49. Eberth JM, Thibault A, Caldwell R, Josey MJ, Qiang B, Peña E, et al. A statewide program providing colorectal cancer screening to the uninsured of South Carolina: CRC Screening Program for the Uninsured. Cancer. 2018;124(9):1912–1920. pmid:29415338
  50. 50. Blumenthal DS, Smith SA, Majett CD, Alema-Mensah E. A trial of 3 interventions to promote colorectal cancer screening in African Americans. Cancer. 2010;116(4):922–929. pmid:20052732
  51. 51. Inadomi JM, Vijan S., Janz NK, Fagerlin A, Thomas JP, Lin YV, et al. Adherence to Colorectal Cancer Screening: A Randomized Clinical Trial of Competing Strategies. Arch Intern Med. 2012;172(7):575. pmid:22493463
  52. 52. Hoffman AS, Lowenstein LM, Kamath GR, Housten AJ, Leal VB, Linder SK, et al. An entertainment-education colorectal cancer screening decision aid for African American patients: A randomized controlled trial: Colorectal Cancer Screening Decision Ai. Cancer. 2017;123(8):1401–1408. pmid:28001305
  53. 53. Kempe KL, Shetterly SM, France EK, Levin TR. Automated Phone and Mail Population Outreach to Promote Colorectal Cancer Screening. Am J Manag Care. 2012;18(7): 370–378. pmid:22823531
  54. 54. Leone LA, Allicock M, Pignone MP, Walsh JF, Johnson L, Armstrong-Brown J, et al. Cluster Randomized Trial of a Church-Based Peer Counselor and Tailored Newsletter Intervention to Promote Colorectal Cancer Screening and Physical Activity Among Older African Americans. Health Educ Behav. 2016;43(5):568–576. pmid:26515276
  55. 55. Lasser KE, Murillo J, Lisboa S, Casimir AN, Valley-Shah L, Emmons KM, et al. Colorectal Cancer Screening Among Ethnically Diverse, Low-Income Patients: A Randomized Controlled Trial. Arch Intern Med. 2011;171(10). pmid:21606094
  56. 56. Resnicow K, Zhou Y, Hawley S, Jimbo M, Ruffin MT, Davis RE, et al. Communication preference moderates the effect of a tailored intervention to increase colorectal cancer screening among African Americans. Patient Educ Couns. 2014;97(3):370–375. pmid:25224317
  57. 57. Cole H, Thompson HS, White M, Browne R, Trin-Shevrin C, Braithwaite S, et al. Community-Based, Preclinical Patient Navigation for Colorectal Cancer Screening Among Older Black Men Recruited From Barbershops: The MISTER B Trial. Am J Public Health. 2017;107(9):1433–1440. pmid:28727540
  58. 58. Gupta S, Halm EA, Rockey DC, Hammons M, Koch M, Carter E, et al. Comparative Effectiveness of Fecal Immunochemical Test Outreach, Colonoscopy Outreach, and Usual Care for Boosting Colorectal Cancer Screening Among the Underserved: A Randomized Clinical Trial. JAMA Intern Med. August 2013. pmid:23921906
  59. 59. Morgan PD, Fogel J, Tyler ID, Jones JR. Culturally Targeted Educational Intervention to Increase Colorectal Health Awareness among African Americans. J Health Care Poor Underserved. 2010; 21(3): 132–147.
  60. 60. Jandorf L, Braschi C, Ernstoff E, Wong CR, Thelemaque LD, Winkel G, et al. Culturally Targeted Patient Navigation for Increasing African Americans’ Adherence to Screening Colonoscopy: A Randomized Clinical Trial. Cancer Epidemiol Biomarkers Prev. 2013;22(9):1577–1587. pmid:23753039
  61. 61. Singal AG, Gupta S, Skinner CS, Ahn C, Santini N, Agrawal D, et al. Effect of Colonoscopy Outreach vs Fecal Immunochemical Test Outreach on Colorectal Cancer Screening Completion: A Randomized Clinical Trial. JAMA. 2017;318(9):806. pmid:28873161
  62. 62. Reuland DS, Brenner AT, Hoffman R, McWilliams A, Rhyne RL, Getrich C, et al. Effect of Combined Patient Decision Aid and Patient Navigation vs Usual Care for Colorectal Cancer Screening in a Vulnerable Patient Population: A Randomized Clinical Trial. JAMA Intern Med. 2017;177(7):967–974. pmid:28505217
  63. 63. Horne HN, Phelan-Emrick DF, Pollack CE, Markakis D, Wenzel J, Ahmed S, et al. Effect of patient navigation on colorectal cancer screening in a community-based randomized controlled trial of urban African American adults. Cancer Causes Control. 2015;26(2):239–246. pmid:25516073
  64. 64. Pignone M, Winquist A, Schild LA, Lewis C, Scott T, Hawley J, et al. Effectiveness of a patient and practice-level colorectal cancer screening intervention in health plan members: The CHOICE trial. Cancer. 2011;117(15):3352–3362. pmid:21319147
  65. 65. Miller DP, Spangler JG, Case LD, Goff DC, Singh S, Pignone MP. Effectiveness of a Web-Based Colorectal Cancer Screening Patient Decision Aid. Am J Prev Med. 2011;40(6):608–615. pmid:21565651
  66. 66. Ford ME, Havstad S, Vernon SW, Davis SD, Kroll D, Lamerato L, et al. Enhancing Adherence Among Older African American Men Enrolled in a Longitudinal Cancer Screening Trial. Gerontologist. 2006;46(4):545–550. pmid:16921009
  67. 67. Philip EJ, DuHamel K, Jandorf L. Evaluating the impact of an educational intervention to increase CRC screening rates in the African American community: a preliminary study. Cancer Causes Control. 2010;21(10):1685–1691. pmid:20535541
  68. 68. Blumenthal DS, Fort JG, Ahmed NU, Semenya KA, Schreiber GB, Perry S et al. Impact of a Two-City Community Cancer Prevention Intervention on African Americans. J Natl Med Assoc. 2005 Nov;97(11):1479–1488. pmid:16334495
  69. 69. Greiner KA, Daley CM, Epp A, James A, Yeh HW, Geana M, et al. Implementation Intentions and Colorectal Screening. Am J Prev Med. 2014;47(6):703–714. pmid:25455115
  70. 70. Khankari K, Eder M, Osborn CY, Makoul G, Clayman M, Skripkauskas S, et al. Improving Colorectal Cancer Screening Among the Medically Underserved: A Pilot Study within a Federally Qualified Health Center. J GEN INTERN MED. 2007;22(10):1410–1414. pmid:17653808
  71. 71. Myers RE, Sifri R, Daskalakis C, DiCarlo M, Geethakumari PR, Cocroft J, et al. Increasing Colon Cancer Screening in Primary Care Among African Americans. JNCI J Nat Cancer Inst. 2014;106(12):dju344–dju344. pmid:25481829
  72. 72. Martin RL, Tully M, Kos A, Frazer D, Williamson A, Conlon A, et al. Increasing Colorectal Cancer Screening at an Urban FQHC Using iFOBT and Patient Navigation. Health Promot Pract. 2017;18(5):741–750. pmid:28812930
  73. 73. DeGroff A, Schroy PC, Morrissey KG, Slotman B, Rohan EA, Bethel J, et al. Patient Navigation for Colonoscopy Completion: Results of an RCT. Am J Prev Med. 2017;53(3):363–372. pmid:28676254
  74. 74. Bastani R, Glenn BA, Maxwell AE, Ganz PA, Mojica CM, Alber S, et al. Randomized trial to increase colorectal cancer screening in an ethnically diverse sample of first-degree relatives: CRC Screening in First-Degree Relatives. Cancer. 2015;121(17):2951–2959. pmid:25946376
  75. 75. Hendren S, Winters P, Humiston S, Idris A, Li SX, Ford P, et al. Randomized, Controlled Trial of a Multimodal Intervention to Improve Cancer Screening Rates in a Safety-Net Primary Care Practice. J Gen Intern Med. 2014;29(1):41–49. pmid:23818159
  76. 76. Leone LA, Reuland DS, Lewis CL, Ingle M, Erman B, Summers TJ, et al. Reach, Usage, and Effectiveness of a Medicaid Patient Navigator Intervention to Increase Colorectal Cancer Screening, Cape Fear, North Carolina, 2011. Prev Chronic Dis. 2013;10:120221. pmid:23701719
  77. 77. Basch CE, Wolf RL, Brouse CH, Shmukler C, Neugut A, DeCarlo LT, et al. Telephone Outreach to Increase Colorectal Cancer Screening in an Urban Minority Population. Am J Public Health. 2006;96(12):2246–2253. pmid:17077394
  78. 78. Holt CL, Shipp M, Eloubeidi M, Fouad MN, Britt K, Norena M. Your Body Is the Temple: Impact of a Spiritually Based Colorectal Cancer Educational Intervention Delivered Through Community Health Advisors. Health Promot Pract. 2011;12(4):577–588. pmid:21525419
  79. 79. Arnold CL, Rademaker AW, Morris JD, Ferguson LA, Wiltz G, Davis TC. Follow-Up Approaches to a Health Literacy Intervention to Increase Colorectal Cancer Screening in Rural Community Clinics: A Randomized Controlled Trial. Cancer, 2019; 125(20): 3615–3622 pmid:31355924
  80. 80. Davis TC, Rademaker A, Morris J, Ferguson LA, Wiltz G, Arnold CL. Repeat Annual Colorectal Cancer Screening in Rural Community Clinics: A Randomized Clinical Trial to Evaluate Outreach Strategies to Sustain Screening. J Rural Health. 2019 pmid:31523848
  81. 81. Mehta SJ, Pepe RS, Gabler NB, Kanneganti M, Reitz C, Saia C et al. Effect of Financial Incentives on Patient Use of Mailed Colorectal Cancer Screening Tests A Randomized Clinical Trial. JAMA Network Open. 2019;2(3):e191156 pmid:30901053
  82. 82. Maxwell AE, Lucas-Wright A, Santifer RE, Vargas C, Gatson J, Chang C. Promoting Cancer Screening in Partnership with Health Minitries in 9 African American Churches in South Los Angeles: an Implementation Pilot Study. Prev Chronic Dis 2019;16:190135
  83. 83. Schroy PC, Emmons KM, Peters E, Glick JT, Robinson PA, Lydotes MA et al. Aid-Assisted Decision-Making and Colorectal Cancer Screening: A randomized controlled trial. AM J Prev Med. 2012;43(6):573–583 pmid:23159252
  84. 84. Siddiqui AA, Sifri R, Hyslop T, Andrel J, Rosenthal M, Vernon SW et al. Race and Response to colon cancer screening interventions. Prev Med. 2011;52:262–264 pmid:21256149
  85. 85. Zubarik R, Eisen G, Zubarik J, Teal C, Benjamin S, Glaser M. Education Improves Colorectal Cancer Screening by Flexible Sigmoisdoscopy in an Inner City Population. Am J Gast 2000;95(2):509–512
  86. 86. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med. 2009;6(7):6.
  87. 87. U.S. Census Bureau [Internet]. Washington DC; US Census Bureau; 2015.[cited 2019 Dec 17]. Available from;
  88. 88. Sterne JAC, Egger M. Funnel plots for detecting bias in meta-analysis: Guidelines on choice of axis. J Clin Epidemiol. 2001:10.
  89. 89. Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–634. pmid:9310563
  90. 90. Kwaan MR and Jones-Webb R. Colorectal Cancer Screening in Black Men: Recommendations for Best Practices. Am J Prev Med. 2018:55(5):S95–102
  91. 91. Nastasi BK, Varjas K, Bernstein R, Jayasena A. Conducting participatory culture-specific consultation: A global perspective on multicultural consultation. School Psych Rev. 2000;29(3):401–413.
  92. 92. Iwelunmor J, Newsome V, Airhihenbuwa CO. Framing the Impact of Culture on Health: A Systematic Review of the PEN-3 Cultural Model and Its Application in Public Health Research and Interventions. Ethn Health. 2014;19(1):20–46. pmid:24266638
  93. 93. Ratogi S, Johnosn TD, Hoeffel EM, Drewery MP Jr. The Black Population: 2010. Washington DC; U.S. Census Bureau. 2011 Sept. 20p Report No.: C2010BR-06.
  94. 94. Colby S, Ortman S. Projections of the Size and Composition of the U.S. Population: 2014 to 2060. Washington DC: US Census Bureau; 2015 March.13p. Report No.: P25-1143
  95. 95. Raajpoot, U. A. Chapter 5—Multicultural Demographic Developments: Current and Future Trends. In Handbook of Multicultural Mental Health. 2000:79–94. Amsterdam: Elsevier Inc.
  96. 96. U.S. Census Bureau QuickFacts: California [Internet]. Washington DC: U.S Census Bureau. c2018 [cited 2018 Jul 1]. Available from:
  97. 97. Greiner KA, James AS, Born W, Hall S, Engelman KK, Okuyemi KS, et al. Predictors of fecal occult blood test (FOBT) completion among low-income adults. Prev Med. 2005;41(2):676–684. pmid:15917068
  98. 98. James AS, Daley CM, Greiner KA. Knowledge and attitudes about colon cancer screening among African Americans. Am J Health Behav. 2011;35(4):393–401. pmid:22040586
  99. 99. Jepson C, Kessler LG, Portnoy B, Gibbs T. Black-White differences in cancer prevention knowledge and behavior. Am JPublic Health. 1991;81(4):501–504. pmid:2003635
  100. 100. Pfister DG, Benson AB, Somerfield MR. Surveillance Strategies after Curative Treatment of Colorectal Cancer. N Engl J Med. 2004;350(23):2375–2382. pmid:15175439
  101. 101. Dougherty MK, Brenner AT, Crockett SD, Gupta S, Wheeler SB, Coker-Schwimmer M, et al. Evaluation of Interventions Intended to Increase Colorectal Cancer Screening Rates in the United States: A Systematic Review and Meta-analysis. JAMA Intern Med. 2018;178(12):1645–1658. pmid:30326005
  102. 102. Rogers CR, Goodson P, Dietz LR, Okuyemi KS. Predictors of Intention to Obtain Colorectal Cancer Screening Among African American Men in a State Fair Setting. Am J Men Health. 2018;12(4):851–862. pmid:27161985
  103. 103. Rogers CR, Goodson P, Foster MJ. Factors Associated with Colorectal Cancer Screening among Younger African American Men: A Systematic Review. J Health Dispar Res Pract. 2015;8(3):133–156. pmid:26435888
  104. 104. Maxwell AE, Bastani R, Danao LL, Antonio C, Garcia GM, Crespi CM. Results of a community-based randomized trial to increase colorectal cancer screening among Filipino Americans. Am J Public Health. 2010;100(11):2228–2234. pmid:20864724
  105. 105. Misra S, Lairson DR, Chan W, Chang Y, Bartholomew LK, Greisinger A, et al. Cost effectiveness of interventions to promote screening for colorectal cancer: a randomized trial. J Prev Med Public Health. 2011;44(3):101–110. pmid:21617335
  106. 106. Adams LB, Richmond J, Corbie-Smith G, Powell W. Medical Mistrust and Colorectal Cancer Screening Among African Americans. J Community Health. 2017;42(5):1044–1061. pmid:28439739
  107. 107. Powe BD, Faulkenberry R, Harmond L. A Review of Intervention Studies That Seek to Increase Colorectal Cancer Screening among African-Americans. Am J Health Promot. 2010;25(2):92–99. pmid:21039289
  108. 108. Fitzpatrick-Lewis D, Ali MU, Warren R, Kenny M, Sherifali D, Raina P. Screening for Colorectal Cancer: A Systematic Review and Meta-Analysis. Clin Colorectal Cancer. 2016;15(4):298–313. pmid:27133893
  109. 109. BeLue R, Menon U, Kinney AY, Szalacha LA. Psychosocial risk profiles among Black male Veterans Administration patients non-adherent with colorectal cancer screening. Psychooncology. 2011;20(11):1151–1160. pmid:20928929
  110. 110. Griffith KA, Passmore SR, Smith D, Wenzel J. African Americans with a family history of colorectal cancer: barriers and facilitators to screening. Oncol Nurs Forum. 2012;39(3):299–306. pmid:22543388
  111. 111. Katz ML, James AS, Pignone MP, Hudson MA, Jackson E, Oates V, et al. Colorectal cancer screening among African American church members: a qualitative and quantitative study of patient-provider communication. BMC Public Health. 2004;4:62. pmid:15601463
  112. 112. NCCRT and ACS. 2019 Colorectal Cancer Screening Messaging Guidebook: Recommended Messages to Reach the Unscreened.[Internet]: American Cancer Society; 2019 [cited 2019 Aug 9]. Available from: