This paper is in the following e-collection/theme issue:

Recruitment of Research Participants (277) Registered Report (516) Smoking Cessation (514) Web-based and Mobile Health Interventions (3092) mHealth for Wellness, Behavior Change and Prevention (2728)

Published on in Vol 24, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34863, first published .
Effectiveness of Recruitment Strategies of Latino Smokers: Secondary Analysis of a Mobile Health Smoking Cessation Randomized Clinical Trial

Effectiveness of Recruitment Strategies of Latino Smokers: Secondary Analysis of a Mobile Health Smoking Cessation Randomized Clinical Trial

Effectiveness of Recruitment Strategies of Latino Smokers: Secondary Analysis of a Mobile Health Smoking Cessation Randomized Clinical Trial

Authors of this article:

Evelyn Arana-Chicas1 Author Orcid Image ;   Francisco Cartujano-Barrera2 Author Orcid Image ;   Katherine K Rieth3 Author Orcid Image ;   Kimber K Richter4 Author Orcid Image ;   Edward F Ellerbeck4 Author Orcid Image ;   Lisa Sanderson Cox4 Author Orcid Image ;   Kristi D Graves5 Author Orcid Image ;   Francisco J Diaz6 Author Orcid Image ;   Delwyn Catley7 Author Orcid Image ;   Ana Paula Cupertino2 Author Orcid Image
Article Authors Cited by (4) Tweetations (11) Metrics

    Original Paper

    1Department of Surgery, University of Rochester School of Medicine & Dentistry, Rochester, NY, United States

    2Department of Public Health Sciences, University of Rochester School of Medicine & Dentistry, Rochester, NY, United States

    3Department of Otolaryngology, University of Rochester School of Medicine & Dentistry, Rochester, NY, United States

    4Department of Population Health, The University of Kansas Medical Center, Kansas City, KS, United States

    5Department of Oncology, Georgetown University Medical Center, Washington DC, DC, United States

    6Department of Biostatistics & Data Science, The University of Kansas Medical Center, Kansas City, KS, United States

    7Center for Children’s Healthy Lifestyle and Nutrition, Children's Mercy Kansas City, Kansas City, MO, United States

    *all authors contributed equally

    Corresponding Author:

    Evelyn Arana-Chicas, DrPH

    Department of Surgery

    University of Rochester School of Medicine & Dentistry

    265 Crittenden Blvd

    Rochester, NY, 14642

    United States

    Phone: 1 585 287 4217

    Email: Evelyn_Arana@urmc.rochester.edu


    Background: Latinos remain disproportionately underrepresented in clinical trials, comprising only 2%-3% of research participants. In order to address health disparities, it is critically important to increase enrollment of Latino smokers in smoking cessation trials. There is limited research examining effective recruitment strategies for this population.

    Objective: The purpose of this study was to compare the effectiveness of direct versus mass and high- versus low-effort recruitment strategies on recruitment and retention of Latino smokers to a randomized smoking cessation trial. We also examine how the type of recruitment might have influenced the characteristics of enrolled participants.

    Methods: Latino smokers were enrolled into Decídetexto from 4 states—New Jersey, Kansas, Missouri, and New York. Participants were recruited from August 2018 until March 2021. Mass recruitment strategies included English and Spanish advertisements to the Latino community via flyers, Facebook ads, newspapers, television, radio, church bulletins, and our Decídetexto website. Direct, high-effort strategies included referrals from clinics or community-based organizations with whom we partnered, in-person community outreach, and patient registry calls. Direct, low-effort strategies included texting or emailing pre-existing lists of patients who smoked. A team of trained bilingual (English and Spanish) recruiters from 9 different Spanish-speaking countries of origin conducted recruitment, assessed eligibility, and enrolled participants into the trial.

    Results: Of 1112 individuals who were screened, 895 (80.5%) met eligibility criteria, and 457 (457/895, 51.1%) enrolled in the trial. Within the pool of screened individuals, those recruited by low-effort recruitment strategies (both mass and direct) were significantly more likely to be eligible (odds ratio [OR] 1.67, 95% CI 1.01-2.76 and OR 1.70, 95% CI 0.98-2.96, respectively) and enrolled in the trial (OR 2.60, 95% CI 1.81-3.73 and OR 3.02, 95% CI 2.03-4.51, respectively) compared with those enrolled by direct, high-effort strategies. Among participants enrolled, the retention rates at 3 months and 6 months among participants recruited via low-effort strategies (both mass and direct) were similar to participants recruited via direct, high-effort methods. Compared with enrolled participants recruited via direct (high- and low-effort) strategies, participants recruited via mass strategies were less likely to have health insurance (44.0% vs 71.2% and 71.7%, respectively; P<.001), lived fewer years in the United States (22.4 years vs 32.4 years and 30.3 years, respectively; P<.001), more likely to be 1st generation (92.7% vs 76.5% and 77.5%, respectively; P=.007), more likely to primarily speak Spanish (89.3% vs 65.8% and 66.3%, respectively), and more likely to be at high risk for alcohol abuse (5.8 mean score vs 3.8 mean score and 3.9 mean score, respectively; P<.001).

    Conclusions: Although most participants were recruited via direct, high-effort strategies, direct low-effort recruitment strategies yielded a screening pool more likely to be eligible for the trial. Mass recruitment strategies were associated with fewer acculturated enrollees with lower access to health services—groups who might benefit a great deal from the intervention.

    Trial Registration: ClinicalTrials.gov identifier: NCT03586596; https://clinicaltrials.gov/ct2/show/NCT03586596

    International Registered Report Identifier (IRRID): RR2-10.1016/j.cct.2020.106188

    J Med Internet Res 2022;24(6):e34863

    doi:10.2196/34863

    Keywords

    smoking cessation; Latino health, Latino recruitment; health disparities; participant recruitment 


    Latinos constitute the largest minority group in the United States, representing 18.5%, or 55 million, of the current US population [1], and this group is projected to grow to 30% by 2060 [2]. An estimated 6 million Latinos (9.8%) in the United States are current cigarette smokers [3,4]. Although the National Institutes of Health (NIH) Revitalization Act of 1993 [5,6] called for the inclusion of minorities in clinical research, Latinos remain disproportionately underrepresented in clinical trials, comprising only 2%-3% of research participants [7-9].

    Increasing enrollment of Latino smokers in smoking cessation trials is critical for addressing health disparities; however, there is limited research examining effective strategies for recruiting this population [10,11]. Common obstacles to recruitment may include language barriers and health literacy [12,13], and some Latinos may have concerns or mistrust of government-funded research related to privacy or deportation concerns [7,13-15]. Increased burden from social conditions such as poverty [16], low education levels [16,17], and immigration issues [18] also contribute to low participation in clinical trials. These reported barriers may lead to the perception that recruitment of Latinos into clinical trials is difficult. However, despite these barriers, when invited to participate in research, enrollment rates of Latinos are comparable to those of non-Latino Whites [7,14]. Indeed, Latinos are interested in enrolling in research when recruitment strategies are culturally and linguistically tailored to them.

    Literature on the recruitment of Latinos into clinical trials has described the use of different recruitment strategies [19-23]. Some studies have recruited Latinos through proactive recruitment in which study staff directly contact individual potential participants [20,24] and reactive recruitment in which studies disseminate information via mass media and potential participants must contact the study themselves [19,21,25]. Often, recruitment studies emphasize including Latino researchers, fostering community connections to build trust, and using culturally and linguistically tailored recruitment materials delivered through culturally appropriate outlets such as Latino newspapers [19,22,23].

    Traditional categorizations of recruitment approaches (eg, into proactive versus reactive) do not capture the complexity of current recruitment strategies. Although proactive recruitment strategies involving personal outreach to individuals have historically necessitated relatively high effort compared with reactive outreach efforts such as mass advertising, the advent of electronic communications such as text messages and emails now allows direct, personalized outreach with relatively low effort. To date, there has been a lack of research distinguishing the effects of direct versus mass outreach and level of effort on recruitment success. Furthermore, there are limited data available on the retention of Latinos who were recruited via different strategies in clinical trials. One study compared ethnic-specific retention rates in various clinical trials and found that Latino adults have a retention rate of ~54% in clinical trials, and this did not significantly differ compared with other ethnic groups [26]. Only one study has analyzed the effects of recruitment type on retention; however, the recruitment strategies used in that study were limited to newspapers, posters on buses and subways, study flyers at community organizations, and in-person recruitment and community organizations [24].

    It is also possible that different recruitment strategies will yield participants with different characteristics. For example, compared with direct recruitment, mass media recruitment (eg, radio, flyers) may yield more inherently motivated participants since little outreach or encouragement is provided; those who reactively join the study following mass media exposure may have higher commitment to behavior change [27]. This study, therefore, calculated the associations of mass versus direct recruitment strategies, involving high and low study staff effort, with characteristics of Latino smokers who were screened, enrolled, and retained in a randomized smoking cessation trial—Decídetexto [28].


    Study Design

    This study is a secondary data analysis of Decidetexto, a mobile health (mHealth) smoking cessation randomized clinical trial. It compares the efficiency ratios for eligibility, enrollment, and retention (at 3 months and 6 months) of Latino smokers recruited via direct versus mass and high- versus low-effort recruitment strategies.

    Ethical Approval

    The details of the study intervention and protocol are described elsewhere [28]. Study procedures were approved and monitored by Hackensack University Medical Center (#Pro2017-0528), the University of Rochester Medical Center (IRB #STUDY00005080), and the University of Kansas Medical Center Institutional Review Boards (IRB # KUMC IRB #STUDY00004475).

    Recruitment

    Latino smokers were enrolled into Decídetexto from multiple communities (both urban and rural) in 4 states—New Jersey, Kansas, Missouri, and New York. Participants were recruited from August 2018 until March 2021. Direct recruitment strategies involved one-on-one communication with identified Latino smokers and were dichotomized as either “direct, high-effort” or “direct, low-effort” strategies. Recruitment and eligibility were conducted by a team of trained bilingual (English and Spanish) recruiters from different countries of origin (eg, Cuba, Dominican Republic, Ecuador, El Salvador, Mexico, Nicaragua, Peru, Puerto Rico, Venezuela).

    In this study, “recruitment method” refers broadly to either mass, direct high-effort, or direct low-effort recruitment methods. “Recruitment strategies” refer to the specific recruitment strategy implemented. Mass recruitment strategies did not rely on interpersonal communication but instead included bilingual (English and Spanish) advertisements of the study to the larger Latino community via flyers, Facebook ads, newspapers, television, radio, church bulletins, and the Decídetexto website. Direct, high-effort strategies required more staff resources to connect with potential participants and included personal calls based on referrals from clinics or community-based organizations (CBOs), in-person community outreach, and personal calls made to patients on patient registries. Furthermore, as reported in previous research [23], research staff adhered to important cultural values in their interactions with potential participants by communicating with personalismo (initiating warm conversations that conveyed care and understanding of the patient’s circumstances), simpatía (not criticizing the patient), and confianza (establishing trust). Direct, low-effort strategies demanded less time and effort from the research team. Direct, low-effort strategies included sending emails and texts to patients on patient registries and referrals from family and friends. Direct, low-effort and mass strategies were similar in that interested participants had to take the step of contacting the study for screening and follow-up. In this sense, they are both “reactive” recruitment strategies. However, in this study, they are differentiated by whether the recruitment strategy used mass communication to the Latino community or was directly sent to an identified Latino smoker.

    Measures

    Research staff administered all study assessments either in person or via telephone. Prior to completing the eligibility questionnaire, participants were asked the open-ended question “How did you learn about the study?” The baseline assessment collected data on demographics (eg, gender, education, age, income, health insurance status, marital status), smoking characteristics (eg, cigarettes smoked per day; the number of past quit attempts), and biopsychosocial variables: eg, depressive symptoms via the Patient Health Questionnaire-2 (PHQ-2) scale [29], alcohol use via the Alcohol Use Disorders Identification Test-2 (AUDIT-2) [30], anxiety via the Generalized Anxiety Disorder-2 (GAD-2) [31], self-efficacy [32], and acculturation measures including years lived in the United States, primary language, generation, and region of origin.

    Analyses

    Logistic regression analyses were used to calculate odds ratios (ORs; efficiency ratios) and 95% CIs for associations (1) between recruitment method and obtaining eligible individuals among screened individuals, (2) between recruitment method and enrolling the screened participants, and (3) between recruitment method and retaining the enrolled participants at the 3-month and 6-month follow-up visits. Rates of eligibility, enrollment, and retention across the 3 recruitment methods and recruitment strategies were compared using chi-square tests. For each recruitment method, characteristics of enrolled participants were summarized with percentages for categorical variables and with means and SDs for continuous variables. Differences in categorical variables were exploratorily compared using Pearson chi-square tests while differences in continuous variables were compared using 1-way ANOVA tests. Reasons for ineligibility were compared between participants who were recruited via direct, high-effort; direct, low-effort; and mass recruitment methods using Pearson chi-square tests or Fisher exact tests. Data were analyzed using SPSS version 25.


    Overview

    Of 1112 individuals who completed screening, 895 (80.5%) met eligibility criteria, and 457 (457/895, 51.1%) enrolled in the trial. The majority of participants were enrolled via direct, high-effort strategies (300/457, 65.6%). Table 1 lists the numbers screened, eligible, enrolled, and retained at 3 months and 6 months by recruitment method and includes efficiency ratios for eligibility, enrollment, and retention at 3 months and 6 months.

    Table 2 shows the efficiency of specific recruitment strategies. Overall, eligibility efficiency ratios were lowest for Facebook ads (66.7%), followed by in-person community outreach (74.7%), our Decidetexto website (75.0%), and patient registry calls (79.1%). Enrollment efficiency ratios were lowest for Facebook ads (33.3%), followed by television (41.9%), in-person community outreach (31.9%), and patient registry calls (35.4%). The 3-month retention efficiency ratios were lowest for the Decidetexto website (66.7%), television (69.2%), and patient registry text (70.6%). The 6-month retention efficiency ratios were lowest for television (76.9%) and patient registry text (76.5%).

    Compared with the direct, high-effort recruitment method, individuals screened in both the mass and direct, low-effort recruitment methods were significantly more likely to be eligible (OR 1.67, 95% CI 1.01-2.76 and OR 1.70, 95% CI 0.98-2.96, respectively) and enrolled (OR 2.60, 95% CI 1.81-3.73 and OR 3.02, 95% CI 2.03-4.51, respectively; Table 3). Of participants enrolled, those recruited via mass and direct, low-effort methods were just as likely to be retained at 3 months and 6 months compared with participants recruited via the direct, high-effort method. Furthermore, given that 45.5% (208/457) of all enrolled participants were recruited via patient registry calls and that 69.3% (208/300) of all participants who were recruited via direct, high-effort strategies were recruited via patient registry calls, a logistic regression model was run to identify any differences in efficiency ratios between patient registry calls and other direct, high-effort strategies. No differences were found between the 2 (data not shown).

    Table 1. Efficiency ratios for personalized and nonpersonalized recruitment methods.
    Recruitment methodNumber
    screeneda    		Number
    eligibleb    		Number
    enrolled    		Number retained at 3 monthsNumber retained at 6 monthsEligibility efficiency ratioc, %Enrollment efficiency ratiod, %3-month retention efficiency ratioe, %6-month retention efficiency ratiof, %
    Mass14412784697388.258.382.186.9
    Direct, low effort11710173606186.362.482.283.6
    Direct, high effort84766630026126178.635.487.0 87.0

    aThe total is not 1112 because of missing data on the recruitment strategy.

    bThe total is not 895 because of missing data on the recruitment strategy.

    cRatio of number eligible to number screened.

    dRatio of number enrolled to number screened.

    eRatio of number retained at 3 months to number enrolled.

    fRatio of number retained at 6 months to number enrolled.

    Table 2. Recruitment efficiency of specific recruitment strategies.
    Recruitment methodProportion for the recruitment strategies, n (%)Number screenedNumber eligibleNumber enrolledNumber retained at 3 monthsNumber retained at 6 monthsEligibility efficiency ratio, %Enrollment efficiency ratio, %3-month retention efficiency ratio, %6-month retention efficiency ratio, %
    Mass (n=144)

    		Church bulletin4 (2.8)4444310010010075.0

    		Newspaper22 (15.3)222216141410072.787.587.5

    		Radio32 (22.2)322818141587.556.377.883.3

    		Flyer48 (33.3)484029252783.360.486.293.1

    		Decídetexto website4 (2.8)4332375.075.066.7100

    		Television31 (21.5)31241391077.441.969.276.9

    		Facebook ads3 (2.1)3211166.733.3100100
    Direct, low effort (n=117)

    		Clinic or CBOa email10 (8.5)1097769010010085.7

    		Patient registry text35 (29.9)352817121380.048.670.676.5

    		Friend or family referral72 (61.6)726449414288.968.183.785.7
    Direct, high effort (n=847)

    		Clinic or CBO referral81 (9.6)816835302983.943.285.782.3

    		In-person community outreach182 (21.5)18213658485274.731.982.389.7

    		Patient registry call584 (68.9)58446220718318079.135.488.4 86.9

    aCBO: community-based organization.

    Table 3. Results of the logistic regression analysis using recruitment method to predict eligibility, enrollment, and retention.
    Recruitment methodEligiblea (n=895)Enrolleda (n=459)Retained at 3 monthsb (n=390)Retained at 6 monthsb (n=395)

    		Odds ratio (95% CI)P valueOdds ratio (95% CI)P valueOdds ratio (95% CI)P valueOdds ratio (95% CI)P value
    Mass recruitment1.67 (1.01-2.76).042.60 (1.81-3.73)<.0011.4 (0.76-2.80).261.01 (0.49-2.1).98
    Direct, low effort1.70 (0.98-2.96).063.02 (2.03-4.51)<.0011.4 (0.73-2.9).291.32 (0.65-2.66).44
    Direct, high effort1.0N/Ac1.0N/A1.0N/A1.0 N/A

    aDenominator for recruitment method is number screened.

    bDenominator for recruitment method is number enrolled.

    cN/A: not applicable.

    Differences in Participant Characteristics

    The characteristics of enrolled participants (Table 4) were compared across recruitment methods. Participants recruited via mass recruitment strategies were significantly less likely to have health insurance (44.0% vs 71.2% and 71.7%, respectively; P<.001), lived significantly fewer years in the United States (22.4 years vs 32.4 years and 30.3 years, respectively; P<.001), significantly more likely to be 1st generation (92.7% vs 76.5% and 77.5%, respectively; P=.007), significantly more likely to primarily speak Spanish (89.3% vs 65.8% and 66.3%, respectively), and significantly more likely to be at high risk for alcohol abuse (5.8 mean score vs 3.8 mean score and 3.9 mean score, respectively; P<.001) compared with those recruited via direct, low-effort and direct, high-effort strategies. Participants recruited via mass recruitment strategies were significantly more likely to come from Mexico (45.2% vs 20.5% and 8.3%, respectively; P<.001), while participants from Central America were more likely to be recruited via direct, low-effort strategies and direct, high-effort strategies (13.1% vs 32.9% and 35.0%, respectively; P<.001) compared with mass recruitment strategies. Participants born in the United States were significantly more likely to be recruited via both direct low-effort strategies and direct high-effort strategies (9.5% vs 28.8% and 25.8%, respectively; P<.001) compared with mass recruitment strategies. Moreover, Latino smokers recruited via direct, high-effort strategies were more likely to have depressive symptoms (1.7 mean score vs 1.1 mean score and 1.4 mean score, respectively; P=.02) and anxiety (1.8 mean score vs 1.1 mean score and 1.6 mean score, respectively; P=.004).

    With respect to the 3-month retention rate, participants were significantly more likely to primarily speak English (68.7% vs 80.6%; P=.06) and to be a second or higher generation American (75.8% vs 89.6%; P=.02) compared with participants who did not complete their 3-month follow-up assessment. With respect to 6-month retention, particpants were significantly older (49.7 years vs 46.5 years; P=.02) and reported less self-efficacy (1.9 mean score vs 2.2 mean score; P=.008) compared with participants who did not complete their 6-month follow-up assessment (Table 4).

    Of participants who were ineligible (n=217), the most frequent reasons for ineligibility were planning to move in the next 6 months, not willing to come to all study visits, smoking on average less than 3 cigarettes per day, and not knowing how to send or read text messages (Table 5). Ineligible participants identified via direct, high-effort strategies were significantly more likely to plan to move in the next 6 months (69.4% vs 13.9% and 16.7%, respectively; P=.04) compared with mass and direct, low-effort strategies.

    Table 4. Baseline characteristics of enrolled participants who were recruited using proactive and reactive strategies and who were retained at 3 months and 6 months.
    CharacteristicRecruitment methodRetained at 3 months (n=391)Retained at 6 months (n=395)

    		Mass (n=144), n (%)Direct, low effort (n=117), n (%)Direct, high effort (n=847), n (%)P
    value    		Yes, n (%)No, n (%)P
    value    		Yes, n (%)No, n (%)P
    value
    Female54 (64.3)39 (53.4)157 (52.3).15211 (54.1)39 (58.2).60212 (53.7)38 (61.3).28
    Greater than a high school education25 (29.8)29 (39.7)117 (39.0).28152 (39.0)19 (28.4).10153 (38.7)18 (29.0).16
    Has health insurance37 (44.0)52 (71.2)215 (71.7)<.001264 (68.2)40 (59.7).21266 (67.9)38 (61.3).31
    Married52 (61.9)35 (47.9)157 (52.3).22207 (53.4)37 (56.1).69206 (52.4)38 (62.3).17
    Employed full time55 (65.5)36 (49.3)151 (50.3).04212 (54.4)30 (44.8).19209 (52.9)33 (53.2).99
    Annual income (US $)

    		0-29,00033 (39.3)29 (39.7)125 (41.7).34159 (42.0)29 (46.8).53165 (43.8)22 (36.1).45

    		30,000-59,00033 (39.3)22 (30.1)86 (28.7)125 (33.2)16 (25.8)120 (31.8)21 (34.4)

    		≥60,00013 (15.5)20 (27.4)77 (25.7)93 (24.7)17 (27.4)92 (24.4)18 (29.5)
    Age (years)a46.6 (11.1)50.1 (12.5)48.9 (10.7).1148.9 (11.1)47.5 (11.2).3549.7 (11.1)45.6 (10.9).02
    Number of cigarettes per daya10.3 (7.6)12.8 (9.3)11.7 (7.8).1711.5 (7.9)12.0 (8.0).6811.5 (7.9)12.4 (8.5).37
    Number of prior quit attemptsa5.0 (9.4)2.7 (5.6)3.5 (7.8).163.8 (8.2)2.7 (4.8).303.9 (8.3)2.4 (3.4).17
    Alcohol scoreb5.8 (2.6)3.8 (2.4)3.9 (2.5)<.0014.2 (2.6)4.5 (2.7).444.2 (2.6)4.5 (2.8).38
    Depressive symptomsb1.1 (1.6)1.4 (1.5)1.7 (1.8).021.5 (1.7)1.4 (1.8).651.6 (1.7)1.3 (1.6).29
    Anxietyb1.1 (1.4)1.6 (1.7)1.8 (1.7).0041.7 (1.7)1.6 (1.7).601.7 (1.7)1.6 (1.6).60
    Self-efficacya2.1 (0.82)2.0 (0.87)1.9 (0.71).131.9 (0.7)2.0 (1.7).721.9 (0.7)2.2 (0.9).008
    Years in the United Statesa22.4 (14.3)32.4 (16.9)30.3 (16.7)<.00129.4 (17.0)27.8 (13.7).4329.2 (16.9)29.1 (14.7).96
    Language, Spanish77 (89.3)48 (65.8)199 (66.3)<.001268 (68.7)54 (80.6).06275 (69.6)47 (75.8).37
    1st generation76 (92.7)52 (76.5)224 (77.5).007292 (75.8)60 (89.6).02305 (78.0)47 (77.0).87
    Region of birth

    		Mexico38 (45.2)15 (20.5)25 (8.3)<.00164 (16.5)14 (20.9).0767 (17.0)11 (17.7).04

    		Caribbean11 (13.1)24 (32.9)105 (35.0)120 (30.9)20 (29.9)126 (31.9)14 (22.6)

    		South America18 (21.4)11 (15.1)84 (28.0)91 (23.5)22 (32.8)98 (24.8)15 (24.2)

    		Central America9 (10.7)2 (2.7)8 (2.7)15 (3.9)4 (6.0)12 (3.0)7 (11.3)

    		United States8 (9.5)21 (28.8)76 (25.8)98 (25.3)7 (10.4)90 (22.8)15 (24.2)

    aMean (SD).

    bScore (sum score).

    Table 5. Major reasons for ineligibility by recruitment method (only ineligibility criteria that included a total of ≥10 individuals are reported).
    ReasonsMassa (n=20), n (%)Direct, low efforta (n=16), n (%)Direct, high efforta (n=180), n (%)P value
    Not willing to come to all study visits6 (30.0)1 (6.7)b41 (25.6)c.22
    Does not know how to send or read text messages4 (20.0)1 (6.7)b36 (21.4)d.51
    Smokes cigarettes less than 3 days/week4 (20.0)3 (18.8)36 (20.2)e.20
    Planning to move in the next 6 months5 (25.0)6 (37.5)25 (14.7)f.04
    Uses other tobacco products more than 1 day/week5 (25.0)4 (25.0)24 (13.9)g.23
    Not interested in quitting in 30 days2 (10.0)1 (6.7)9 (5.3)h.41
    Has not smoked cigarettes for at least 6 months2 (10.0)1 (6.7)7 (4.0)i.29

    aThe denominator is the difference across ineligibility criteria because of missing data.

    bn=15.

    cn=160.

    dn=168.

    en=178.

    fn=170.

    gn=172.

    hn=82.6.

    in=174.


    Principal Findings

    This paper compared mass; direct, low-effort; and direct, high-effort recruitment methods on Latino eligibility, enrollment, and retention at 3 months and 6 months for a smoking cessation clinical trial, Decídetexto. Results showed that, although direct, high-effort methods yielded the highest total number of enrollees, eligibility and enrollment were significantly lower when compared with the mass and direct, low-effort methods. However, when considering retention at 3 months and 6 months, there is no evidence that method of recruitment impacted retention once participants were enrolled in the study. Thus, although the eligibility and enrollment rates were low for direct, high-effort strategies, participants are just as likely to be retained after they are enrolled when compared with mass and direct low-effort strategies.

    It is important to note that, although mass and direct, low-effort strategies are efficient methods and do not demand much staff time, they are unlikely to reach the recruitment goal for a randomized clinical trial without contribution from direct, high-effort strategies. Future studies should include cost-effectiveness to determine whether highly funded mass and direct, low-effort strategies can recruit equal numbers in a cost-effective manner. This is especially important to consider as mass recruitment strategies seemed to yield fewer acculturated enrollees with lower access to health services—groups that might benefit a great deal from the intervention.

    Our research corroborates a study that tested the efficiency of strategies to recruit Latino male smokers. That study found that reactive recruitment was more efficient than proactive recruitment but yielded significantly fewer participants and was costlier per participant enrolled [11]. As noted by Harris et al [27], reactive recruitment may be more effective at identifying eligible individuals because it reaches a wider audience and individuals who take the trouble to respond are likely to be more ready and motivated to quit. Furthermore, individuals who learn about research via mass media may have more time to collect information about the study and consider the pros and cons of enrolling before calling the study phone number to complete eligibility. This, in turn, might prevent less motivated individuals from contacting the study for screening. It should be noted that this study’s advertisements did not include all of our eligibility criteria. Potential participants were able to self-screen for some criteria using the Latino identity and current smoker criteria that were noted in the advertisments. There were a number of additional criteria they had to meet (Table 5). Future research should consider enhancing advertisements (eg, flyers, posters) to yield higher response rates using theoretical constructs such as self-efficacy, social norms, and rewards. Moreover, additional research should consider assessing which method of recruitment yielded a higher rate of participants who quit smoking.

    Of the individual mass recruitment strategies, Facebook ads yielded the lowest efficiency ratios for eligibility and enrollment. This contradicts previous research that found Facebook was a useful recruitment tool for smokers [33,34]. Of direct low-effort strategies, patient registry texts yielded the lowest efficiency ratios for eligibility and enrollment and yielded among the lowest ratios for retention at 3 months and 6 months. This is consistent with previous research reporting an ~34% enrollment rate for patients recruited via text messages [35]. It is interesting to note that referring friends and family members were either (1) Latino smokers on a patient registry who received a call from us but no longer smoked or were ineligible or (2) study participants who had completed the study. Of direct, high-effort strategies, in-person community outreach yielded the lowest efficiency ratios for eligibility and enrollment. This is important to note, as this is the recruitment strategy that demanded the most staff resources. Although patient registry calls yielded the highest number of participants, it was among the lowest efficiency ratio for eligibility and enrollment. This is in contrast to previous research that has reported the feasibility and cost-effectiveness of recruiting participants via calls from patient registries via a research associate program [20,33].

    With respect to the characteristics of participants recruited via the different recruitment methods, mass recruitment yielded less acculturated participants (eg, more likely to speak Spanish, to be 1st generation, fewer years lived in the United States) who were more likely to be at risk for alcohol abuse than participants recruited via direct, low-risk and direct, high-risk methods. It is possible that low-acculturation Latino smokers face unique barriers that limit the effectiveness of direct recruitment strategies.

    We also found that Latinos from different Latin American regions appear to respond differently to different recruitment methods. Mexicans were more likely to be recruited via mass recruitment strategies compared with all other Latin American regions, while Latinos from the Caribbean were more likely to be recruited using direct strategies. Thus, recruitment approaches that researchers choose to employ should be determined by their population of interest and the desired participant characteristics. Furthermore, Latino smokers experiencing depression or anxiety were less likely to respond to mass recruitment. This may be because they are less motivated to quit smoking or they have less energy to reach out to inquire about the study [36]. The psychosocial finding corroborates findings from a study that compared reactive versus proactive recruitment strategies in recruiting African American smokers [27], in which it was found that participants recruited proactively were more likely to report indicators of depression. Taken together, these findings suggest that both mass and direct recruitment strategies should be implemented for studies interested in recruiting Latino participants across the socioeconomic, acculturation, and country of origin spectra. Additional research is also needed to examine differences in clinical outcomes based on recruitment method.

    Limitations

    The Decídetexto clinical trial was not designed to test the efficiency of recruitment strategies; therefore, this study has several limitations. Given the broad reach of our advertisements, it is possible that participants were exposed to multiple advertisement strategies. It is possible that individuals responding to a mass strategy may have been exposed to a direct strategy. Therefore, some cross-contamination effect is likely to have occurred. However, no participants in this study mentioned that they learned about the study through more than one strategy. Moreover, we were unable to conduct a cost analysis in this study given that (1) most of our mass recruitment strategies were free of cost or paid in an unusual way (eg, paid a graphic artist in Mexico) and (2) we had volunteers aid in personalized recruitment for this study. We did not collect data on barriers to participant retention. Despite these limitations, this study has high representation of a heterogeneous group of Latino smokers representing different Latin American regions of origin, making it generalizable to Latinos nationwide. The study team consisted of Latino researchers and interns from different Latin American countries of origin, several of whom were native Spanish speakers. Our recruitment efforts involved working collaboratively with a community advisory board, collaborating closely with local CBOs, and culturally and linguistically tailoring all materials to Latino smokers. Furthermore, the bulk of our recruitment occurred prior to the onset of the COVID-19 pandemic. No recruitment activities occurred from March 2020 through July 2020. From August 2020 to March 2021 we recruited 21 additional participants, 62% of whom were recruited via mass recruitment strategies. It is possible that the effect of recruitment strategies will be different during and after the COVID-19 pandemic. Moreover, although this study is specific to a tobacco treatment trial, the findings are relevant to health research and clinical trials broadly.

    Conclusion

    This study compared the eligibility, enrollment, and retention efficiency ratios of recruiting Latino smokers via mass; direct, low-effort; and direct, high-effort strategies utilized in Decídetexto, a mobile smoking cessation randomized clinical trial. A heterogeneous sample of Latino smokers was enrolled in the trial. Results show that, although direct, high-effort recruitment strategies yielded the highest total number of enrollees, eligibility and enrollment were significantly lower when compared with mass and direct, low-effort recruitment strategies. Yet, when considering retention at 3 months and 6 months, there is no evidence that method of recruitment impacted retention once participants were enrolled in the study. Participants recruited via mass recruitment strategies were less acculturated, of lower socioeconomic status, and more likely to be Mexican than those recruited via other strategies. These findings suggest that these 3 recruitment methods should be implemented for studies interested in recruiting Latino participants across the socioeconomic, acculturation, and country of origin spectra. These findings provide further insight into effective recruitment strategies for Latino smokers.

    Acknowledgments

    The authors would like to thank the recruitment research staff and volunteers. This includes Ileana Cepeda, Arlette Chavez, Carlos Coronado, Katia Gallegos-Carillo, Stephanie Horton, Rudy Lara, Denise Maldonado, Joanna Mansfield, Maria Mansfield, Arturo Ponce, Dora Ponce, Rosibel Rodriguez Bolaños, Lizbeth Sandoval, Ciara Torres, Yamilet Torres, and Victoria Uceda.

    Special acknowledgment goes to Marco Polo Ramírez Bonilla at In Touch Productions for the development of the graphic materials for recruitment. Finally, we thank the people and organizations that facilitated the recruitment of this study: (1) Angel Vazquez, Bill Tipacti, Charles Neugebauer, Marlon Mazo, Roberto Yanez, Contigo en la Comunidad New York, and Noticiero Univisión Edición Digital at Univision Local Media, New York; (2) Aidè Almeida and Ricardo Salinas at El Gallito Radio; (3) Ida Pérez at Radio Poder 97.1 FM, part of Ibero American Action League; (4) Enrique Rodriguez Franz at KSMM-FM La Mexicana radio in Liberal, Kansas; and (5) Anthony Ibarria and Johnny Torres at El Especialito Hispanic Weekly in New York and New Jersey.

    This work was supported by the National Cancer Institute (NCI) under grant R01CA212189 (principal investigator: APC) and T32CA102618 for author EAC. The content is the sole responsibility of the authors and does not necessarily represent the official views of the NCI.

    Authors' Contributions

    EAC, FCB, KK Rieth, EFE, LSC, KDG, FJD, DC, and APC conceptualized the study. EAC curated the data, performed the formal analysis, supervised the study, performed project administration, and drafted the original manuscript. APC acquired the funding. EAC, FCB, and APC designed the methodology. EAC, FCB, KK Rieth, KK Richter, EFE, LSC, KDG, FJD, DC, and APC reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

    Conflicts of Interest

    None declared.

    1. Quick Facts: United States. United States Census Bureau.   URL: https://www.census.gov/quickfacts/fact/table/US/PST045219 [accessed 2021-03-23]
    2. Colby SL, Ortman JM. Projections of the size and composition of the U.S. Population: 2014 to 2060. United States Census Bureau. 2015 Mar 03.   URL: https://www.census.gov/library/publications/2015/demo/p25-1143.html [accessed 2022-06-12]
    3. Creamer MR, Wang TW, Babb S, Cullen KA, Day H, Willis G, et al. Tobacco Product Use and Cessation Indicators Among Adults - United States, 2018. MMWR Morb Mortal Wkly Rep 2019 Nov 15;68(45):1013-1019 [FREE Full text] [CrossRef] [Medline]
    4. Bethel J, Schenker M. Acculturation and smoking patterns among Hispanics: a review. Am J Prev Med 2005 Aug;29(2):143-148. [CrossRef] [Medline]
    5. Chen MS, Lara PN, Dang JHT, Paterniti DA, Kelly K. Twenty years post-NIH Revitalization Act: enhancing minority participation in clinical trials (EMPaCT): laying the groundwork for improving minority clinical trial accrual: renewing the case for enhancing minority participation in cancer clinical trials. Cancer 2014 Apr 01;120 Suppl 7:1091-1096 [FREE Full text] [CrossRef] [Medline]
    6. Freedman LS, Simon R, Foulkes MA, Friedman L, Geller NL, Gordon DJ, et al. Inclusion of women and minorities in clinical trials and the NIH Revitalization Act of 1993--the perspective of NIH clinical trialists. Control Clin Trials 1995 Oct;16(5):277-85; discussion 286. [CrossRef] [Medline]
    7. Ellington L, Wahab S, Sahami Martin S, Field R, Mooney KH. Factors that influence Spanish- and English-speaking participants' decision to enroll in cancer randomized clinical trials. Psychooncology 2006 Apr;15(4):273-284. [CrossRef] [Medline]
    8. Wallington SF, Luta G, Noone A, Caicedo L, Lopez-Class M, Sheppard V, et al. Assessing the awareness of and willingness to participate in cancer clinical trials among immigrant Latinos. J Community Health 2012 Apr 31;37(2):335-343 [FREE Full text] [CrossRef] [Medline]
    9. Vickers S, Fouad M. An overview of EMPaCT and fundamental issues affecting minority participation in cancer clinical trials: enhancing minority participation in clinical trials (EMPaCT): laying the groundwork for improving minority clinical trial accrual. Cancer 2014 Apr 01;120 Suppl 7:1087-1090 [FREE Full text] [CrossRef] [Medline]
    10. Thompson TP, Greaves CJ, Ayres R, Aveyard P, Warren FC, Byng R, et al. Lessons learned from recruiting socioeconomically disadvantaged smokers into a pilot randomized controlled trial to explore the role of Exercise Assisted Reduction then Stop (EARS) smoking. Trials 2015 Feb 12;16:1 [FREE Full text] [CrossRef] [Medline]
    11. Graham AL, Lopez-Class M, Mueller NT, Mota G, Mandelblatt J. Efficiency and cost-effectiveness of recruitment methods for male Latino smokers. Health Educ Behav 2011 Jun 01;38(3):293-300 [FREE Full text] [CrossRef] [Medline]
    12. George S, Duran N, Norris K. A Systematic Review of Barriers and Facilitators to Minority Research Participation Among African Americans, Latinos, Asian Americans, and Pacific Islanders. Am J Public Health 2014 Feb;104(2):e16-e31. [CrossRef]
    13. London L, Hurtado-de-Mendoza A, Song M, Nagirimadugu A, Luta G, Sheppard VB. Motivators and barriers to Latinas' participation in clinical trials: the role of contextual factors. Contemp Clin Trials 2015 Jan;40:74-80 [FREE Full text] [CrossRef] [Medline]
    14. Larkey L, Ogden S, Tenorio S, Ewell T. Latino recruitment to cancer prevention/screening trials in the Southwest: setting a research agenda. Appl Nurs Res 2008 Feb;21(1):30-39. [CrossRef] [Medline]
    15. Hildebrand J, Billimek J, Olshansky E, Sorkin DH, Lee JA, Evangelista LS. Facilitators and barriers to research participation: perspectives of Latinos with type 2 diabetes. Eur J Cardiovasc Nurs 2018 Dec;17(8):737-741 [FREE Full text] [CrossRef] [Medline]
    16. Flores A, Lopes G, Radford J. Hispanic Population in the United States Statistical Portrait. Pew Research Center. 2017 Sep 18.   URL: https:/​/www.​pewresearch.org/​hispanic/​2017/​09/​18/​2015-statistical-information-on-hispanics-in-united-states-trend-data/​ [accessed 2022-06-12]
    17. Krogstad JM. 5 facts about Latinos and education. Pew Research Center. 2016 Jul 28.   URL: https://www.pewresearch.org/fact-tank/2016/07/28/5-facts-about-latinos-and-education/ [accessed 2022-06-12]
    18. Arbona C, Olvera N, Rodriguez N, Hagan J, Linares A, Wiesner M. Acculturative Stress Among Documented and Undocumented Latino Immigrants in the United States. Hisp J Behav Sci 2010 Aug 19;32(3):362-384 [FREE Full text] [CrossRef] [Medline]
    19. Sheppard V, Cox L, Kanamori M, Cañar J, Rodríguez Y, Goodman M, Latin American Cancer Research Coalition. Brief report: if you build it, they will come: methods for recruiting Latinos into cancer research. J Gen Intern Med 2005 May;20(5):444-447 [FREE Full text] [CrossRef] [Medline]
    20. Arana-Chicas E, Cartujano-Barrera F, Ogedegbe C, Ellerbeck EF, Cox LS, Graves KD, et al. Feasibility and Effectiveness of Recruiting Latinos in -A Smoking Cessation Clinical Trial from an Emergency Department Patient Registry. Int J Environ Res Public Health 2021 Oct 15;18(20):10859 [FREE Full text] [CrossRef] [Medline]
    21. Kiernan M, Phillips K, Fair J, King AC. Using direct mail to recruit hispanic adults into a dietary intervention: An experimental study. Ann Behav Med 2000 Mar;22(1):89-93. [CrossRef]
    22. Rhodes S, Alonzo J, Mann-Jackson L, Tanner AE, Vissman AT, Martinez O, et al. Selling the product: Strategies to increase recruitment and retention of Spanish-speaking Latinos in biomedical research. J Clin Transl Sci 2018 Jun;2(3):147-155 [FREE Full text] [CrossRef] [Medline]
    23. García AA, Zuñiga JA, Lagon C. A Personal Touch: The Most Important Strategy for Recruiting Latino Research Participants. J Transcult Nurs 2017 Jul;28(4):342-347 [FREE Full text] [CrossRef] [Medline]
    24. Collins BN, Wileyto EP, Hovell MF, Nair US, Jaffe K, Tolley NM, et al. Proactive recruitment predicts participant retention to end of treatment in a secondhand smoke reduction trial with low-income maternal smokers. Transl Behav Med 2011 Sep 6;1(3):394-399 [FREE Full text] [CrossRef] [Medline]
    25. Topolovec-Vranic J, Natarajan K. The Use of Social Media in Recruitment for Medical Research Studies: A Scoping Review. J Med Internet Res 2016 Nov 07;18(11):e286 [FREE Full text] [CrossRef] [Medline]
    26. Sangi-Haghpeykar H, Meddaugh HM, Liu H, Grino P. Attrition and retention in clinical trials by ethnic origin. Contemp Clin Trials 2009 Nov;30(6):499-503. [CrossRef] [Medline]
    27. Harris K, Ahluwalia J, Catley D, Okuyemi KS, Mayo MS, Resnicow K. Successful recruitment of minorities into clinical trials: The Kick It at Swope project. Nicotine Tob Res 2003 Aug;5(4):575-584. [CrossRef] [Medline]
    28. Cartujano-Barrera F, Arana-Chicas E, Catley D, Cox LS, Diaz FJ, Ellerbeck EF, et al. Decídetexto: Mobile cessation support for Latino smokers. Study protocol for a randomized clinical trial. Contemp Clin Trials 2020 Dec;99:106188 [FREE Full text] [CrossRef] [Medline]
    29. Löwe B, Kroenke K, Gräfe K. Detecting and monitoring depression with a two-item questionnaire (PHQ-2). J Psychosom Res 2005 Feb;58(2):163-171. [CrossRef] [Medline]
    30. Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Arch Intern Med 1998 Sep 14;158(16):1789-1795. [CrossRef] [Medline]
    31. Donker T, van Straten A, Marks I, Cuijpers P. Quick and easy self-rating of Generalized Anxiety Disorder: validity of the Dutch web-based GAD-7, GAD-2 and GAD-SI. Psychiatry Res 2011 Jun 30;188(1):58-64. [CrossRef] [Medline]
    32. Cartujano-Barrera F, McIntosh S, Cox LS, Arana-Chicas E, Catley D, Ellerbeck EF, et al. Translation and Examination of the Reliability and Validity of the Spanish Version of the Smoking Self-Efficacy Questionnaire Among Latino Smokers. Tob Use Insights 2021 Jul 29;14:1179173X2110353 [FREE Full text] [CrossRef]
    33. Abar B, Ogedegbe C, Dalawari P, Freeman K, Boudreaux ED, Illuzzi F, et al. Promoting tobacco cessation utilizing pre-health professional students as research associates in the emergency department. Addict Behav 2015 Jan;40:73-76 [FREE Full text] [CrossRef] [Medline]
    34. Cook S, Jerome R, Dunagan J, Kennedy N, Edwards T, Minnix JA, et al. Engaging smokers in research: Utility of Facebook in facilitating recruitment to a smoking cessation study. Contemp Clin Trials 2021 Aug;107:106461 [FREE Full text] [CrossRef] [Medline]
    35. Alsumidaie M. Text Messagingnhancing Clinical Trial Patient Recruitment and Enrollment. Applied Clinical Trials. 2014 Nov 3.   URL: https:/​/www.​appliedclinicaltrialsonline.com/​view/​text-messaging-enhancing-clinical-trial-patient-recruitment-and-enrollment [accessed 2022-06-12]
    36. Haukkala A, Uutela A, Vartiainen E, Mcalister A, Knekt P. Depression and smoking cessation. Addictive Behaviors 2000 Mar;25(2):311-316. [CrossRef]

    ‎
    AUDIT-2: Alcohol Use Disorders Identification Test-2
    CBO: community-based organization
    GAD-2: Generalized Anxiety Disorder-2
    mHealth: mobile health
    NCI: National Cancer Institute
    PHQ-2: Patient Health Questionnaire-2

    Edited by A Mavragani; submitted 12.11.21; peer-reviewed by S Morgan, C Bullen; comments to author 12.12.21; revised version received 30.03.22; accepted 18.04.22; published 27.06.22

    Copyright

    ©Evelyn Arana-Chicas, Francisco Cartujano-Barrera, Katherine K Rieth, Kimber K Richter, Edward F Ellerbeck, Lisa Sanderson Cox, Kristi D Graves, Francisco J Diaz, Delwyn Catley, Ana Paula Cupertino. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.06.2022.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.