Factors associated with male recruitment in a multi-site randomized behavioral clinical trial targeting the metabolic syndrome: analysis of screening and recruitment data from the ELM trial

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Crane, Bryce Daniels, Barbara Lohse, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4656235/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Dec, 2024 Read the published version in Trials → Version 1 posted 5 You are reading this latest preprint version Abstract Background Males are underrepresented in behavioral clinical trials of lifestyle change or weight loss. Little is known about factors that facilitate or deter males from participating in such trials. The aim of this exploratory study was to describe the sample of males recruited into a multi-site behavioral trial targeting lifestyle change and remission of the metabolic syndrome and to investigate factors associated with trial interest at different stages of recruitment and overall. Similar analyses were performed for female participation to investigate the uniqueness or consistency with the findings for males. Methods Data collected at various stages of recruitment in an ongoing multi-site behavioral clinical trial were used. A series of logistic regressions compared respondents who moved forward to the next step of the screening process versus those who did not. These analyses were stratified by sex. A chi-squared test was used to directly compare proportions of men and women who chose to advance to the next step. Results Males who showed interest in the trial were more likely to be self-aware of their current health risk. Comparison of males and females showed that men tended to lose interest earlier in the recruitment process (58.3% of men vs. 66.5% of women attended an in-person information session, p < 0.001), but the proportion that moved forward among those who demonstrated initial interest was similar in men and women. Conclusion Efforts to increase male enrollment in behavioral clinical trials will benefit from a focus on early stages of recruitment, aiming to increase potential participants’ initial levels of interest and awareness of their health risk. As men and women differ in the reasons they choose to participate in a behavioral trial, recruitment should be tailored to sex to maximize trial participation. Trial registration ClinicalTrials.gov number, NCT04036006, https//clinicaltrials.gov/study/NCT04036006 Behavioral clinical trials metabolic syndrome male recruitment Figures Figure 1 Figure 2 Introduction The goal of primary and secondary prevention of many diseases is combatting overweight and obesity. 1 It is well-documented that obesity is a major risk factor for chronic conditions such as diabetes, high blood pressure, and cardiovascular diseases including stroke and coronary artery disease. 2 – 4 Small to moderate weight loss (5–10% of starting weight) has been linked to clinically significant benefits, including significantly improving triglyceride levels, cholesterol, blood pressure, and blood glucose. 5 , 6 These improvements lead to reduced risk for the aforementioned chronic diseases associated to obesity, with some of the reductions in risk being sustained for periods of 10 to 15 years or longer. 7 , 8 For these reasons, clinical trials in preventive medicine, especially ones promoting cardiovascular health, often involve a behavioral intervention targeting weight loss consisting of diet and exercise. Such interventions have been associated to greater weight-loss and less weight-gain. 9 However, like other trials in preventive medicine, participants in trials that specifically target weight-loss through behavioral changes, are likely to be female as opposed to male. Pagoto and colleagues reviewed 244 studies (total n = 95,207 participants) published between 1999 to 2009 that included weight loss as an outcome and tested a behavioral intervention. The results showed that men accounted for only 27% of all participants. 10 In a review of 22 randomized controlled trials with a weight management intervention of at least 12 months, only 36% (4,771 out of 13,305) were men. 11 Another study that analyzed a total of 20,020 clinical trials conducted in the United States (US) between 2000–2020, showed that participants of trials with preventive interventions tend to be female (median 53.6%, interquartile range 41.7–76.2%). 12 Yet, risks for obesity and cardiovascular diseases in the US either tend to be similar between males and females or tend to be higher for males. In 2017–2018, the prevalence of obesity was 43% for men and 42.1% for women, a statistically insignificant difference. 13 An analysis of the National Health and Nutrition Examination Survey (NHANES) showed that, the prevalence of the metabolic syndrome has increased significantly from 1988 to 2012, but differences between sexes have remained stagnant (35.1% in men vs. 34.3% in women as of 2016). 14 Prevalence of diabetes in 2018 was 14% in men and 12% in women. 15 Age-adjusted hypertension prevalence was higher in men (51.0%) compared to women (39.7%). 16 Thus, to find effective treatment and prevention strategies, male representation in clinical trials targeting these conditions is imperative. Studies on underrepresentation of males in behavioral trials is sparse. Studying only the cohort of participants who enrolled in the trial does not elucidate the reasons why they were more likely to enroll, or whether they were systematically different from those who chose not to enroll. The recruitment process in most clinical trials involves several stages (e.g., phone calls, orientation sessions, screening visits, etc.) until a participant is ultimately enrolled in the trial. During this process, a potential participant may show interest but end up declining or being deemed ineligible, and little is known about such potential participants. There may be discernible differences between males who show interest in the trial at different stages of the recruitment process. Few studies have investigated the differences between participants and non-participants at various stages of recruitment. You et al., prior to conducting a worksite-clustered randomized trial for weight loss, sent out a brief survey to potential employee participants to determine their eligibility and predictors for trial participation. 17 Nineteen out of the 33 worksites agreed to participate, resulting in 2,055 participants completing the survey. Their data collection methods allowed for information to be collected from potential participants who were eligible but did not enroll in the study. Their findings were similar to what has already been established. Employees with higher income, higher education, and higher health literacy were more likely to participate. Their study was limited in that the survey was short and only asked basic demographic, behavioral, and health questions. The availability of more in-depth information from potential participants prior to randomization of a trial may provide a more accurate picture of a person likely to participate in a behavioral trial. The Enhanced Lifestyles for the Metabolic Syndrome multi-site trial (ELM trial) completed recruitment in February 2022, and 150 (24.3%) of 618 total randomized participants were male. The metabolic syndrome (MetS) is a cluster of cardiometabolic risk conditions (elevated blood pressure, abdominal obesity, elevated triglycerides, elevated glucose, and low HDL cholesterol), when present, significantly increases the risk of cardiovascular diseases 18 , cardiovascular mortality, and type 2 diabetes, among others. Causes of MetS are complex and multifactorial, but the fundamental causes at the individual level are in a lifestyle characterized by an unhealthy diet and physical inactivity. These are the major components of the intervention for the ELM trial. A vast amount of information is collected from initial screening to information session to baseline exam in this trial. Describing this sample and comparing characteristics among males who show interest versus those who decline elucidates the attributes of males who are more likely to participate in a behavioral trial. Thus, the aim of this exploratory study was to describe the sample of males recruited into the ELM trial and compare factors associated to trial participation at different stages of recruitment and overall. Similar analyses were performed for female participation in the ELM trial to contrast with the findings for males. Methods The design and baseline characteristics of the ongoing ELM trial are described extensively elsewhere. 19 Briefly, the purpose of the trial is to determine the efficacy of a lifestyle program on the remission of the MetS after 24 months. It is an individually randomized, partially clustered group treatment trial where participants with the MetS are randomized into either a group-based lifestyle treatment or a self-directed, enhanced standard of care comparator. The ELM recruitment process is shown in Fig. 1 . Participants were recruited mainly from three sources: electronic health records (EHR), self-referrals, and other referrals (e.g., physician referral). Advertisements that led to self-referrals were placed on social media sites, radio, television, and local newspapers. Prospective participants identified through EHR were sent an introductory letter with an option of opting out or receiving a subsequent recruiting call within two weeks. Others were called or emailed and directed to complete an online pre-screening survey. Screening was conducted in two steps. A telephone screen obtained self-reported information on MetS components, medical, and safety eligibility. Anyone who passed this initial phone screen was deemed tentatively eligible. Those tentatively eligible were referred to an in-person information session aimed at providing potential participants with a better understanding of what lifestyle change entails and requirements for participation in the trial. The session featured a presentation with visual aids that included information on the treatment arms, the clinical trial process, and the meaning of informed consent. Discussions included considerations for current life priorities, time needed for lifestyle change, confidence in making changes at the current time, and expected barriers. Attendees were asked to consider participation in the upcoming week, and if interested, to call the site research staff. Attendees who were sure about wanting to participate were given the option to sign up immediately following the session. Those showing interest were invited for baseline examinations conducted in three steps. First was an in-person visit for obtaining informed consent, demographic information, physical measurements, a 12-hour fasting blood draw, and instructions for a run-in period. Second was a one-week run-in that included completion of the accelerometer protocol (7 consecutive days, 10 hours/day), food and beverage logs (all food and beverage intake over an entire day for 3 weekdays and 1 weekend day), and a logistical plan for accessing vegetables and engaging in physical activity. The third step, for only those confirmed to have the MetS, was a second in-person visit that included completion of questionnaire data and confirmation of successful completion of the run-in. After baseline examinations, those who successfully completed the run-in, were confirmed to have the MetS, were still interested, and had clearance from their respective primary care physicians, if needed, entered a waiting protocol until approximately 30 participants at the site were ready to be randomized. The waiting protocol was necessary because the group treatment arm required approximately 15 participants. All participants signed informed consent, and the trial was approved by the appropriate Institutional Review Boards (IRBs) of the participating sites and a central IRB at Rush University Medical Center. The study sample included all potential participants who were tentatively eligible after the initial phone screening (N = 14,817). Corresponding to various stages of the recruitment process, each person was categorized to reflect their willingness to participate in the trial. Subsequently these categories served as outcomes for the four sets of analyses conducted. After screening eligible, potential participants were coded as either “attended information session” or “did not attend information session” (outcome for Analysis 1). Those that attended the information session were further coded as either “attended baseline examination” (irrespective of completion of all baseline components) or “did not attend baseline examination” (outcome for Analysis 2). Those who attended baseline examination were further coded as either “eligible and enrolled”, “eligible but not interested”, or “ineligible” (outcome for Analysis 3, excluding “ineligible”). Analyses 4 was meant to capture potential differences between those who were randomized versus anyone who did not make it to randomization for any reason (e.g., “no longer interested”, “ineligible”). As such, participants were coded as either “engaged in the any part of the screening process but not randomized” or “eligible and enrolled” (outcome for Analysis 4). The “ineligible” group of people who indicated they were not interested midway through baseline were not included in Analysis 3 because their eligibility for randomization was unknown, but they were included in Analysis 4 because it was meant to be inclusive of all persons who were not interested in the trial at any point in the process. As this was an exploratory study, all measures collected at screening were considered as individual predictors to investigate whether they were associated with moving forward in the trial (i.e., attend info session, attend baseline, or enroll in the trial). Lists of all predictors used for the study and ones excluded are shown in Supplementary Tables 1 and 2, respectively. Missing responses were deleted pairwise. Responses such as “don’t know” or “refused to answer” were also deleted pairwise. Predictors with no variation, i.e., everyone provided the same response, were removed from the analyses (e.g., a question as to ever having bariatric surgery had only “no” or missing responses from male subjects). Similarly, categorical variables with very little representation in one or some categories were removed (e.g., only 22 out of 2,674 or 0.8% of respondents said they were ever diagnosed with cancer). A few variables were excluded due to their lack of relevance for increasing male enrollment in future behavioral trials. These included a self-reported previous diagnosis of bipolar disorder and chronic obstructive pulmonary disease. These exclusions led to a total of 19 predictors. Unadjusted analyses involved a series of logistic regression models, each with a single unique predictor. Adjusted analyses involved similar logistic regression models but with all significant predictors from the unadjusted analyses. All analyses were stratified by sex to investigate whether significant findings were consistent across both sexes. Subsequently, males and females were directly compared at similar stages of recruitment, e.g., male versus female attendance of an info session. Statistical analyses were performed in SAS (version 9.4; SAS Institute, Cary, NC). Despite some concerns of multiplicity due to many simultaneous statistical tests, a conventional p-value threshold of 0.05 was used. All significant results were interpreted with caution. Results A full depiction of the sample, overall and stratified by sex, is shown on Fig. 2 . Tentative eligibility was examined in 14,817 people. Among them, 2,796 (18.9% of 14,817) were eligible to attend an info session. However, the sex of 118 of them was unknown, and hence excluded from all analyses. Of 1,717 (61.4% of 2,796) people (with known sex) who attended an info session, 1,142 (66.5% of 1,717) attended a baseline examination. From this, 653 (57.2% of 1,142) were deemed eligible for the trial, and 618 (94.6% of 653) were randomized. Significant results discussed below are summarized in Tables 1 and 2 for males and females, respectively. Information session attendance (Analysis 1) Among 769 males eligible to attend the information session, there were 448 (58.3%) who attended and 321 (41.7%) who did not. Among 1,909 females, there were 1,269 (66.5%) who attended and 640 (33.5%) who did not. In the unadjusted models, three factors were positively associated with attendance in only male respondents: (i) self-reported fasting glucose between 100 and 125 mg/dL, which is the state of prediabetes, compared to below 100 mg/dL (OR = 1.69, p = 0.005), (ii) 10-point self-efficacy Likert scale item asking, “How confident are you that you can be or can work up to be physically active for at least 30 minutes on most days?” (OR = 1.24, p = 0.002), and (iii) presence of a major food allergy or dietary preference (OR = 1.97, p = 0.03). In the adjusted model controlling for all significant predictors from the unadjusted analyses, other chronic illness (OR = 1.74, p = 0.04), confidence in being active (OR = 1.40, p = 0.0006), and Black race compared to White (OR = 0.43, p = 0.0032) remained significant independent predictors of attendance for males. Common to both sexes, race (coded as White, Black, or other) and self-reported presence of other chronic illness or health problems (coded as yes or no) were significantly associated with attending an info session. Unique to female respondents, a 10-point Likert scale asking, “How willing and able are you to make changes to your current diet?” was significant (OR = 1.11, p = 0.03). In the adjusted model, willingness to change diet (OR = 1.12, p = 0.02) and Black race compared to White (OR = 0.68, p = 0.0006) remained significant. Baseline examination attendance (Analysis 2) Among 448 males who attended the information session and were invited to complete the baseline examination, 293 (65.4%) attended and 155 (34.6%) did not. Among 1,269 females, 849 (66.9%) attended and 420 (33.1%) did not. Hispanic ethnicity was significantly associated with lower odds (OR = 0.51, p = 0.04) of attendance for males. Self-reported diagnosis of asthma was positively associated with female attendance (OR = 1.55, p = 0.01). No other factor was statistically significant for either sex. As there was only one significant predictor, no adjusted analyses were conducted. Trial enrollment compared to respondents eligible for randomization but not interested (Analysis 3) Of the 1,142 who attended a baseline examination, 489 were ineligible for the trial (due to incomplete baseline, no MetS, etc.), 618 (94.6%; 150 males, 468 females) were randomized, and 35 (5.4%; 9 males, 26 females) were eligible to be randomized but not interested in the trial. The purpose of Analysis 3 was to compare the latter two categories. However, due to the very small number of people who were eligible but not interested (N = 35), no analyses were conducted as any evidence from it would likely not be robust. Trial enrollment compared to respondent not interested at any point in the recruitment process (Analysis 4) The 618 randomized participants were compared to the combined group consisting of those who did not attend an info session, did not attend baseline examination, were eligible to be randomized but were not interested, and indicated they were not interested in the middle of baseline examination (n = 1,630, 499 males, 1,131 females). Unique to male respondents, self-reported A1c between 5.7 and 6.4 percent (OR = 1.57, p = 0.03), current order of fibrates medication (OR = 2.34, p = 0.01), fasting glucose between 100 and 125 mg/dL (OR = 1.68, p = 0.03), and triglycerides over 150 mg/dL (OR = 1.95, p = 0.003) were all positively associated with trial enrollment. However, none of the predictors remained significant in the adjusted analyses. Only race was significant in both sexes, with Black respondents less likely to enroll compared to White respondents (OR = 0.41, p = 0.0032 for males; OR = 0.55, p < 0.0001 for females). For females, willingness to make changes to their current diet (OR = 1.15, p = 0.01) and presence of other chronic illnesses (OR = 1.30, p = 0.03) were uniquely associated to trial enrollment. Willingness to change diet (OR = 1.17, p = 0.008) and Black race (OR = 0.55, p < 0.0001) remained significant in the adjusted model. The proportion of males and females who chose to move forward to the subsequent step in the recruitment process were compared using chi-squared tests. No significant differences were found in proportions of males and females for baseline attendance or trial enrollment, meaning qualifying males and females were equally likely to attend baseline assessments and enroll in the trial. However, there was a significant difference in proportions (58.3% in males vs. 66.5% females; p < 0.001) attending an info session after being tentatively eligible. Discussion The purpose of this exploratory study was to determine factors associated to male participation in a behavioral clinical trial targeting remission of the MetS. Using data collected in the trial screening process, various factors were compared during successive stages of the recruitment process, where a potential participant had the choice of either moving forward to the next stage or indicating no interest. The same set of analyses were conducted for potential female participants to determine the uniqueness of the findings to males. Black respondents were consistently less likely to move forward in the screening process compared to White respondents, irrespective of sex. There were also distinct factors associated to male trial participation, not observed in females. Results indicated that males who show initial interest in the trial were more likely to lose interest quickly. Those who continued were more aware of their current health risk. A direct comparison of males and females showed that men tended to lose interest earlier in the recruitment process. Several factors were uniquely associated to trial participation for men. The presence of other chronic illnesses and confidence in ability to be physically active were significantly associated with attending an information session in the adjusted analyses. Self-reported HbA1c between 5.7 and 6.4 percent, current order of fibrates medication, fasting glucose between 100 and 125 mg/dL, and triglycerides over 150 mg/dL were associated with trial enrollment, albeit only in the unadjusted analyses. All these factors point toward self-awareness of an already existing condition and a likely patient-provider relationship. For both sexes, a 2020 Cochrane review (of 29 studies) identified potential personal benefit as a reason to facilitate participation. 20 Similarly, a 2016 narrative review of 61 studies related to clinical trial participation from the patient or caregiver perspective, reported that top facilitating factors were improved personal health, personal benefit 21 , and perception of better care. Moreover, a 2023 mixed studies review (i.e., review of studies with diverse designs) of 37 studies found that the existence of a strong patient-provider relationship can improve recruitment. 22 Thus, male participants who were aware of their health, likely through their providers (having a primary care provider was an inclusion for the trial), and thought it necessary to receive more care may have been more inclined and motivated to participate. Males, in general, underutilize primary and preventive care. 23 As such, male participation in behavioral trials may see an increase by raising awareness toward preventive care for males in general. In addition to differences in factors influencing moving forward between men and women, more men tended to lose interest earlier in the screening process compared to women. Of the 2,796 total respondents invited to an info session, only 58.3% of men attended compared to 66.5% for women (p < 0.001). No such differences were observed for subsequent steps in the process, meaning that for men who show initial interest and initiative, the rate of enrollment is not significantly different than for women. As such, efforts to increase male enrollment in behavioral clinical trials will benefit with a focus on earlier stages of recruitment, aiming to increase potential participants’ initial levels of interest by leveraging factors mentioned above associated to moving forward. The Recruitment Innovation Center, part of the Trial Innovation Network 24 , recommends that recruitment be viewed as a continuum in research rather than a one-time event, which starts with awareness of potential participants. 25 This is consistent with a 2010 systematic review of 37 studies that compared methods of recruitment into an actual or a mock trial. 26 The authors found that increasing awareness of the health problem and impact on health increased recruitment. Thus, earlier stages of recruitment may benefit from efforts to increase potential participant awareness. Throughout the enrollment process, for both males and females, Black race was consistently associated with lower participation compared to White race. The US government has long mandated the inclusion of women and racial/ethnic minorities in federally funded research. 27 The findings from this study shed light on sample diversity beyond final numbers. Of the 618 randomized participants, 106 (17.2%) identified as Black race. Given that the percent of the US population who identify as only Black or African American race is 13.4% 28 , and that unlike many other chronic illnesses, the disease burden of MetS in the US is higher in White adults compared to Black adults 14 , at face value, the randomized cohort of ELM does not seem to suffer from a lack of diversity. In fact, the numbers from ELM are comparable with other trials focused on lifestyle interventions for weight loss. A review of 94 such trials in the US between 2009 and 2015 showed that the proportion of Black participants was 18.2%, compared to 58.9% for White participants. 29 However, there is a noticeable difference in the enrollment rate between the two racial groups. Of the 688 Black adults who were invited to an info session, only 106 were randomized, a 15.4% enrollment rate. By comparison, there were 1,567 White adults who were invited to an info session leading to 456 being randomized, a 29.1% enrollment rate. This means that the recruitment effort to enroll Black adults into similar trials should be roughly 1.9 times higher than that of recruiting White adults. A breakdown by sex provides an even more concerning outlook. Of the 152 Black men invited to an info session, only 17 were randomized, an enrollment rate of 11.2%, compared to 16.6% for Black women, 23.5% for White men, and 31.5% for White women. Additionally, although not as robust as findings for Black race, Hispanic ethnicity was significantly associated with lower male baseline attendance. Similar trends were seen in that of the 75 Hispanic men invited to an info session, only 12 were randomized (16%). A major contribution of the current study is the availability of data from a large number of potential participants at various stages of recruitment in a multi-site behavioral trial allowed elucidation of the factors associated with moving toward enrollment. The robustness of the findings is supported by factors such as race and ethnicity being associated with participation, a trend seen in other studies. At the same time, factors that were unique to males and females were also discovered. These findings support the idea that reasons for participating in a behavioral trial are different for men and women. Moreover, it suggests that tailored strategies may be needed to recruit the desired number of male participants. Despite the contributions, this study is not without its limitations. First, as the data are cross-sectional, no causality can be drawn. Second, many of the measures are self-reported. This was unavoidable as most of the screening process was done through surveys. However, the large sample size from five sites across the US does bolster the level of confidence in the study findings. Third, the self-reported HbA1c and glucose questions were yes/no format that asked whether the respondent was within the pre-diabetes range. Thus, a “no” response could indicate lower or upper ranges. However, as respondents with a diagnosis of diabetes were not invited to the information session, it would be reasonable to assume that most, if not all, of the ”no” responses fall below the pre-diabetes range. In conclusion, recruiting male participants into a behavioral clinical trial remains a challenge. Reasons why men may choose not to participate are distinct from women. Future efforts and strategies to increase male recruitment must be cognizant of these barriers. Declarations Acknowledgement and Declarations All participants signed informed consent, and the trial was approved by the appropriate Institutional Review Boards (IRBs) of the participating sites and a central IRB at Rush University Medical Center. The authors declare no conflict of interest. All authors contributed equally to this manuscript. The ELM trial was supported by a grant from the William G. McGowan Charitable Fund (The Fund). The Fund had no role in the design or conduct of the trial, the decision to publish trial results, the analysis of data, or the preparation of this manuscript. Data used in this study may be available by request. References Franz MJ, VanWormer JJ, Crain AL, Boucher JL, Histon T, Caplan W, Bowman JD, Pronk NP. Weight-loss outcomes: a systematic review and meta-analysis of weight-loss clinical trials with a minimum 1-year follow-up. Journal of the American Dietetic association. 2007 Oct 1;107(10):1755-67. 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Moffat KR, Shi W, Cannon P, Sullivan F. Factors associated with recruitment to randomised controlled trials in general practice: a systematic mixed studies review. Trials. 2023 Dec;24(1):1-9. Mursa R, Patterson C, Halcomb E. Men’s help-seeking and engagement with general practice: An integrative review. Journal of Advanced Nursing. 2022 78(7): 1938-53. Trial Innovation Network, https://trialinnovationnetwork.org/ (accessed 27 October 2023). Wilkins CH, Edwards TL, Stroud M, Kennedy N, Jerome RN, Lawrence CE, Kusnoor SV, Nelson S, Byrne LM, Boone LR, Dunagan J. The Recruitment Innovation Center: developing novel, person-centered strategies for clinical trial recruitment and retention. Journal of Clinical and Translational Science. 2021;5(1):e194. Caldwell PH, Hamilton S, Tan A, Craig JC. Strategies for increasing recruitment to randomised controlled trials: systematic review. PLoS medicine. 2010 Nov 9;7(11):e1000368. National Institutes of Health. 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Supplementary Tables Table 1: Significant predictors of male participation Unadjusted OR (95% CI) Adjusted a OR (95% CI) Analysis 1 – Info session attendance vs. not Other chronic illnesses or health problems 1.81 (1.22, 2.69) 1.74(1.02,2.97) Major food allergies or dietary preferences 1.97 (1.05, 3.72) n/s b Fasting glucose between 100 and 125 mg/dL 1.69 (1.17, 2.45) n/s Self-Efficacy: Confidence of being physically active for at least 30 minutes on most days 1.24 (1.08, 1.42) 1.40(1.15,1.70) Black race (reference White) 0.52 (0.36, 0.75) 0.43 (0.24, 0.75) Analysis 2 – Baseline attendance vs. not Hispanic, Latinx, or Spanish origin 0.51 (0.27, 0.98) n/a Analysis 4 – Randomized vs. not at any point prior A1c between 5.7 and 6.4 1.57 (1.03, 2.40) n/s Current order for Fibrates medications 2.34 (1.20, 4.55) n/s Fasting glucose between 100 and125 mg/dL 1.68 (1.06, 2.67) n/s Self-Efficacy: Confidence of being physically active for at least 30 minutes on most days 1.22 (1.02, 1.46) n/s Black race (reference white race) 0.41 (0.23, 0.74) n/s Triglycerides = 150 mg/d> 1.95 (1.24, 3.04) n/s a Adjusted models include all significant predictors from unadjusted models. b n/s indicates p-value ≥ 0.05. Table 2: Significant predictors of female participation Unadjusted OR (95% CI) Adjusted a OR (95% CI) Analysis 1 – Info session attendance vs. not Willing and able are to make changes to current diet 1.11 (1.01, 1.22) 1.12 (1.02,1.23) Other chronic illnesses or health problems 1.28 (1.02, 1.60) n/s b Black race (reference white race) 0.68 (0.55, 0.84) 0.68 (0.55, 0.85) Black race (reference any other race) 0.61 (0.39, 0.94) 0.63 (0.41, 0.98) Analysis 2 – Baseline attendance vs. not Asthma 1.55 (1.08, 2.24) n/a Analysis 4 – Randomized vs. not at any point prior Willing and able are to make changes to current diet 1.15 (1.03, 1.28) 1.17 (1.04, 1.31) Other chronic illnesses or health problems 1.30 (1.02, 1.66) n/s Black race (reference white race) 0.55 (0.42, 0.72) 0.55 (0.42, 0.72) a Adjusted models include all significant predictors from unadjusted models. b n/s indicates p-value ≥ 0.05. Cite Share Download PDF Status: Published Journal Publication published 21 Dec, 2024 Read the published version in Trials → Version 1 posted Editorial decision: Major revision 18 Oct, 2024 Reviewers agreed at journal 10 Sep, 2024 Reviewers invited by journal 09 Aug, 2024 Editor assigned by journal 31 Jul, 2024 First submitted to journal 16 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4656235","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":338250159,"identity":"1c946534-7f7e-437e-8dd2-4e50ab4380d8","order_by":0,"name":"Sumihiro Suzuki","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYJCCwwwGMOYBCTkgyQbEzMRrMSZKC5LsAYbEBkJa5GdkJx4uKLgnx8B/xvgzzxmL9O0z0p89YKiwBunFCgxu5G44PMOg2JhBIsfAmOeGRO6cGznmBgxn0nFrkQBq4TFISGyQ4DFI5vkgkTtDIodNgrHtME4t8jNgWvjPGBwGakmXkEh/JsH4D7cWhhswLQw5hs1AhyVISCSYSTA24NZicOYtWAvQL2nFjHPOSBjO4HljJpFwLN0Yp8Paczd/5vmTAAyxw5s/vDlWJy/BDnTYhxprWZwOgwH7A8i8BELKR8EoGAWjYBTgBQAjI1TzzPBFYwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-6408-9580","institution":"Rush University Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Sumihiro","middleName":"","lastName":"Suzuki","suffix":""},{"id":338250160,"identity":"a2d59f4a-3b40-4421-b2e7-77a01a2bbdee","order_by":1,"name":"Chen Yeh","email":"","orcid":"","institution":"Rush University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Chen","middleName":"","lastName":"Yeh","suffix":""},{"id":338250161,"identity":"b4ad8685-646e-46ad-87dc-1abea2fc7767","order_by":2,"name":"Melissa M. Crane","email":"","orcid":"","institution":"Rush University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Melissa","middleName":"M.","lastName":"Crane","suffix":""},{"id":338250162,"identity":"10a82d67-1952-403b-ab3f-3e8be13927e1","order_by":3,"name":"Bryce Daniels","email":"","orcid":"","institution":"Rush University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Bryce","middleName":"","lastName":"Daniels","suffix":""},{"id":338250163,"identity":"92aecfec-62fd-4f60-9de4-f0b8260b51a0","order_by":4,"name":"Barbara Lohse","email":"","orcid":"","institution":"Rochester Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Barbara","middleName":"","lastName":"Lohse","suffix":""},{"id":338250164,"identity":"29c38fcc-63e5-43f4-9c7d-8fc029efad7e","order_by":5,"name":"Kelly Karavolos","email":"","orcid":"","institution":"Rush University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Kelly","middleName":"","lastName":"Karavolos","suffix":""},{"id":338250165,"identity":"b6ed0294-4ba3-4b83-b895-5c35a0ac4185","order_by":6,"name":"Tami Olinger","email":"","orcid":"","institution":"Rush University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Tami","middleName":"","lastName":"Olinger","suffix":""},{"id":338250166,"identity":"3773d62c-4946-404c-8b07-947a7ae0c9f4","order_by":7,"name":"Jacinda Nicklas","email":"","orcid":"","institution":"University of Colorado School of Medicine: University of Colorado Anschutz Medical Campus School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jacinda","middleName":"","lastName":"Nicklas","suffix":""},{"id":338250167,"identity":"7c342f27-f606-4630-9c44-c74b996498d9","order_by":8,"name":"Lynda H. Powell","email":"","orcid":"","institution":"Rush University Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Lynda","middleName":"H.","lastName":"Powell","suffix":""}],"badges":[],"createdAt":"2024-06-28 17:37:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4656235/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4656235/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13063-024-08703-8","type":"published","date":"2024-12-21T15:58:20+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":64713871,"identity":"79531edf-3676-4e17-ae87-bb0dbf5cb2b2","added_by":"auto","created_at":"2024-09-18 02:17:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":222397,"visible":true,"origin":"","legend":"\u003cp\u003eScreening process in ELM\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4656235/v1/4b1e75a3c05989895a2994ff.png"},{"id":64713872,"identity":"245bc186-fd26-4046-82a3-3a845d477f2a","added_by":"auto","created_at":"2024-09-18 02:17:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":323952,"visible":true,"origin":"","legend":"\u003cp\u003eResults of the ELM screening process and samples used for each analysis\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4656235/v1/b9552e563295307ecfe63816.png"},{"id":72202884,"identity":"65e5dba0-fab2-4ee1-8c67-a10ee6ce9593","added_by":"auto","created_at":"2024-12-23 16:16:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":933046,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4656235/v1/2b7f815f-9a7a-4006-8f9e-9287a122f4ac.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eFactors associated with male recruitment in a multi-site randomized behavioral clinical trial targeting the metabolic syndrome: analysis of screening and recruitment data from the ELM trial\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe goal of primary and secondary prevention of many diseases is combatting overweight and obesity.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e It is well-documented that obesity is a major risk factor for chronic conditions such as diabetes, high blood pressure, and cardiovascular diseases including stroke and coronary artery disease.\u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Small to moderate weight loss (5\u0026ndash;10% of starting weight) has been linked to clinically significant benefits, including significantly improving triglyceride levels, cholesterol, blood pressure, and blood glucose.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e These improvements lead to reduced risk for the aforementioned chronic diseases associated to obesity, with some of the reductions in risk being sustained for periods of 10 to 15 years or longer.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFor these reasons, clinical trials in preventive medicine, especially ones promoting cardiovascular health, often involve a behavioral intervention targeting weight loss consisting of diet and exercise. Such interventions have been associated to greater weight-loss and less weight-gain.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e However, like other trials in preventive medicine, participants in trials that specifically target weight-loss through behavioral changes, are likely to be female as opposed to male. Pagoto and colleagues reviewed 244 studies (total n\u0026thinsp;=\u0026thinsp;95,207 participants) published between 1999 to 2009 that included weight loss as an outcome and tested a behavioral intervention. The results showed that men accounted for only 27% of all participants.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e In a review of 22 randomized controlled trials with a weight management intervention of at least 12 months, only 36% (4,771 out of 13,305) were men.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Another study that analyzed a total of 20,020 clinical trials conducted in the United States (US) between 2000\u0026ndash;2020, showed that participants of trials with preventive interventions tend to be female (median 53.6%, interquartile range 41.7\u0026ndash;76.2%).\u003csup\u003e12\u003c/sup\u003e Yet, risks for obesity and cardiovascular diseases in the US either tend to be similar between males and females or tend to be higher for males. In 2017\u0026ndash;2018, the prevalence of obesity was 43% for men and 42.1% for women, a statistically insignificant difference.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e An analysis of the National Health and Nutrition Examination Survey (NHANES) showed that, the prevalence of the metabolic syndrome has increased significantly from 1988 to 2012, but differences between sexes have remained stagnant (35.1% in men vs. 34.3% in women as of 2016).\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Prevalence of diabetes in 2018 was 14% in men and 12% in women.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Age-adjusted hypertension prevalence was higher in men (51.0%) compared to women (39.7%).\u003csup\u003e16\u003c/sup\u003e Thus, to find effective treatment and prevention strategies, male representation in clinical trials targeting these conditions is imperative.\u003c/p\u003e \u003cp\u003eStudies on underrepresentation of males in behavioral trials is sparse. Studying only the cohort of participants who enrolled in the trial does not elucidate the reasons why they were more likely to enroll, or whether they were systematically different from those who chose not to enroll. The recruitment process in most clinical trials involves several stages (e.g., phone calls, orientation sessions, screening visits, etc.) until a participant is ultimately enrolled in the trial. During this process, a potential participant may show interest but end up declining or being deemed ineligible, and little is known about such potential participants. There may be discernible differences between males who show interest in the trial at different stages of the recruitment process. Few studies have investigated the differences between participants and non-participants at various stages of recruitment. You et al., prior to conducting a worksite-clustered randomized trial for weight loss, sent out a brief survey to potential employee participants to determine their eligibility and predictors for trial participation.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Nineteen out of the 33 worksites agreed to participate, resulting in 2,055 participants completing the survey. Their data collection methods allowed for information to be collected from potential participants who were eligible but did not enroll in the study. Their findings were similar to what has already been established. Employees with higher income, higher education, and higher health literacy were more likely to participate. Their study was limited in that the survey was short and only asked basic demographic, behavioral, and health questions. The availability of more in-depth information from potential participants prior to randomization of a trial may provide a more accurate picture of a person likely to participate in a behavioral trial.\u003c/p\u003e \u003cp\u003eThe Enhanced Lifestyles for the Metabolic Syndrome multi-site trial (ELM trial) completed recruitment in February 2022, and 150 (24.3%) of 618 total randomized participants were male. The metabolic syndrome (MetS) is a cluster of cardiometabolic risk conditions (elevated blood pressure, abdominal obesity, elevated triglycerides, elevated glucose, and low HDL cholesterol), when present, significantly increases the risk of cardiovascular diseases\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, cardiovascular mortality, and type 2 diabetes, among others. Causes of MetS are complex and multifactorial, but the fundamental causes at the individual level are in a lifestyle characterized by an unhealthy diet and physical inactivity. These are the major components of the intervention for the ELM trial. A vast amount of information is collected from initial screening to information session to baseline exam in this trial. Describing this sample and comparing characteristics among males who show interest versus those who decline elucidates the attributes of males who are more likely to participate in a behavioral trial. Thus, the aim of this exploratory study was to describe the sample of males recruited into the ELM trial and compare factors associated to trial participation at different stages of recruitment and overall. Similar analyses were performed for female participation in the ELM trial to contrast with the findings for males.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe design and baseline characteristics of the ongoing ELM trial are described extensively elsewhere.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e Briefly, the purpose of the trial is to determine the efficacy of a lifestyle program on the remission of the MetS after 24 months. It is an individually randomized, partially clustered group treatment trial where participants with the MetS are randomized into either a group-based lifestyle treatment or a self-directed, enhanced standard of care comparator.\u003c/p\u003e \u003cp\u003eThe ELM recruitment process is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Participants were recruited mainly from three sources: electronic health records (EHR), self-referrals, and other referrals (e.g., physician referral). Advertisements that led to self-referrals were placed on social media sites, radio, television, and local newspapers. Prospective participants identified through EHR were sent an introductory letter with an option of opting out or receiving a subsequent recruiting call within two weeks. Others were called or emailed and directed to complete an online pre-screening survey. Screening was conducted in two steps. A telephone screen obtained self-reported information on MetS components, medical, and safety eligibility. Anyone who passed this initial phone screen was deemed tentatively eligible. Those tentatively eligible were referred to an in-person information session aimed at providing potential participants with a better understanding of what lifestyle change entails and requirements for participation in the trial. The session featured a presentation with visual aids that included information on the treatment arms, the clinical trial process, and the meaning of informed consent. Discussions included considerations for current life priorities, time needed for lifestyle change, confidence in making changes at the current time, and expected barriers. Attendees were asked to consider participation in the upcoming week, and if interested, to call the site research staff. Attendees who were sure about wanting to participate were given the option to sign up immediately following the session. Those showing interest were invited for baseline examinations conducted in three steps. First was an in-person visit for obtaining informed consent, demographic information, physical measurements, a 12-hour fasting blood draw, and instructions for a run-in period. Second was a one-week run-in that included completion of the accelerometer protocol (7 consecutive days, 10 hours/day), food and beverage logs (all food and beverage intake over an entire day for 3 weekdays and 1 weekend day), and a logistical plan for accessing vegetables and engaging in physical activity. The third step, for only those confirmed to have the MetS, was a second in-person visit that included completion of questionnaire data and confirmation of successful completion of the run-in. After baseline examinations, those who successfully completed the run-in, were confirmed to have the MetS, were still interested, and had clearance from their respective primary care physicians, if needed, entered a waiting protocol until approximately 30 participants at the site were ready to be randomized. The waiting protocol was necessary because the group treatment arm required approximately 15 participants. All participants signed informed consent, and the trial was approved by the appropriate Institutional Review Boards (IRBs) of the participating sites and a central IRB at Rush University Medical Center.\u003c/p\u003e \u003cp\u003eThe study sample included all potential participants who were tentatively eligible after the initial phone screening (N\u0026thinsp;=\u0026thinsp;14,817). Corresponding to various stages of the recruitment process, each person was categorized to reflect their willingness to participate in the trial. Subsequently these categories served as outcomes for the four sets of analyses conducted. After screening eligible, potential participants were coded as either \u0026ldquo;attended information session\u0026rdquo; or \u0026ldquo;did not attend information session\u0026rdquo; (outcome for Analysis 1). Those that attended the information session were further coded as either \u0026ldquo;attended baseline examination\u0026rdquo; (irrespective of completion of all baseline components) or \u0026ldquo;did not attend baseline examination\u0026rdquo; (outcome for Analysis 2). Those who attended baseline examination were further coded as either \u0026ldquo;eligible and enrolled\u0026rdquo;, \u0026ldquo;eligible but not interested\u0026rdquo;, or \u0026ldquo;ineligible\u0026rdquo; (outcome for Analysis 3, excluding \u0026ldquo;ineligible\u0026rdquo;). Analyses 4 was meant to capture potential differences between those who were randomized versus anyone who did not make it to randomization for any reason (e.g., \u0026ldquo;no longer interested\u0026rdquo;, \u0026ldquo;ineligible\u0026rdquo;). As such, participants were coded as either \u0026ldquo;engaged in the any part of the screening process but not randomized\u0026rdquo; or \u0026ldquo;eligible and enrolled\u0026rdquo; (outcome for Analysis 4). The \u0026ldquo;ineligible\u0026rdquo; group of people who indicated they were not interested midway through baseline were not included in Analysis 3 because their eligibility for randomization was unknown, but they were included in Analysis 4 because it was meant to be inclusive of all persons who were not interested in the trial at any point in the process.\u003c/p\u003e \u003cp\u003eAs this was an exploratory study, all measures collected at screening were considered as individual predictors to investigate whether they were associated with moving forward in the trial (i.e., attend info session, attend baseline, or enroll in the trial). Lists of all predictors used for the study and ones excluded are shown in Supplementary Tables\u0026nbsp;1 and 2, respectively. Missing responses were deleted pairwise. Responses such as \u0026ldquo;don\u0026rsquo;t know\u0026rdquo; or \u0026ldquo;refused to answer\u0026rdquo; were also deleted pairwise. Predictors with no variation, i.e., everyone provided the same response, were removed from the analyses (e.g., a question as to ever having bariatric surgery had only \u0026ldquo;no\u0026rdquo; or missing responses from male subjects). Similarly, categorical variables with very little representation in one or some categories were removed (e.g., only 22 out of 2,674 or 0.8% of respondents said they were ever diagnosed with cancer). A few variables were excluded due to their lack of relevance for increasing male enrollment in future behavioral trials. These included a self-reported previous diagnosis of bipolar disorder and chronic obstructive pulmonary disease. These exclusions led to a total of 19 predictors. Unadjusted analyses involved a series of logistic regression models, each with a single unique predictor. Adjusted analyses involved similar logistic regression models but with all significant predictors from the unadjusted analyses. All analyses were stratified by sex to investigate whether significant findings were consistent across both sexes. Subsequently, males and females were directly compared at similar stages of recruitment, e.g., male versus female attendance of an info session. Statistical analyses were performed in SAS (version 9.4; SAS Institute, Cary, NC). Despite some concerns of multiplicity due to many simultaneous statistical tests, a conventional p-value threshold of 0.05 was used. All significant results were interpreted with caution.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA full depiction of the sample, overall and stratified by sex, is shown on Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Tentative eligibility was examined in 14,817 people. Among them, 2,796 (18.9% of 14,817) were eligible to attend an info session. However, the sex of 118 of them was unknown, and hence excluded from all analyses. Of 1,717 (61.4% of 2,796) people (with known sex) who attended an info session, 1,142 (66.5% of 1,717) attended a baseline examination. From this, 653 (57.2% of 1,142) were deemed eligible for the trial, and 618 (94.6% of 653) were randomized. Significant results discussed below are summarized in Tables \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e for males and females, respectively.\u003c/p\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003eInformation session attendance (Analysis 1)\u003c/h2\u003e\n \u003cp\u003eAmong 769 males eligible to attend the information session, there were 448 (58.3%) who attended and 321 (41.7%) who did not. Among 1,909 females, there were 1,269 (66.5%) who attended and 640 (33.5%) who did not. In the unadjusted models, three factors were positively associated with attendance in only male respondents: (i) self-reported fasting glucose between 100 and 125 mg/dL, which is the state of prediabetes, compared to below 100 mg/dL (OR\u0026thinsp;=\u0026thinsp;1.69, p\u0026thinsp;=\u0026thinsp;0.005), (ii) 10-point self-efficacy Likert scale item asking, \u0026ldquo;How confident are you that you can be or can work up to be physically active for at least 30 minutes on most days?\u0026rdquo; (OR\u0026thinsp;=\u0026thinsp;1.24, p\u0026thinsp;=\u0026thinsp;0.002), and (iii) presence of a major food allergy or dietary preference (OR\u0026thinsp;=\u0026thinsp;1.97, p\u0026thinsp;=\u0026thinsp;0.03). In the adjusted model controlling for all significant predictors from the unadjusted analyses, other chronic illness (OR\u0026thinsp;=\u0026thinsp;1.74, p\u0026thinsp;=\u0026thinsp;0.04), confidence in being active (OR\u0026thinsp;=\u0026thinsp;1.40, p\u0026thinsp;=\u0026thinsp;0.0006), and Black race compared to White (OR\u0026thinsp;=\u0026thinsp;0.43, p\u0026thinsp;=\u0026thinsp;0.0032) remained significant independent predictors of attendance for males.\u003c/p\u003e\n \u003cp\u003eCommon to both sexes, race (coded as White, Black, or other) and self-reported presence of other chronic illness or health problems (coded as yes or no) were significantly associated with attending an info session. Unique to female respondents, a 10-point Likert scale asking, \u0026ldquo;How willing and able are you to make changes to your current diet?\u0026rdquo; was significant (OR\u0026thinsp;=\u0026thinsp;1.11, p\u0026thinsp;=\u0026thinsp;0.03). In the adjusted model, willingness to change diet (OR\u0026thinsp;=\u0026thinsp;1.12, p\u0026thinsp;=\u0026thinsp;0.02) and Black race compared to White (OR\u0026thinsp;=\u0026thinsp;0.68, p\u0026thinsp;=\u0026thinsp;0.0006) remained significant.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003eBaseline examination attendance (Analysis 2)\u003c/h2\u003e\n \u003cp\u003eAmong 448 males who attended the information session and were invited to complete the baseline examination, 293 (65.4%) attended and 155 (34.6%) did not. Among 1,269 females, 849 (66.9%) attended and 420 (33.1%) did not. Hispanic ethnicity was significantly associated with lower odds (OR\u0026thinsp;=\u0026thinsp;0.51, p\u0026thinsp;=\u0026thinsp;0.04) of attendance for males. Self-reported diagnosis of asthma was positively associated with female attendance (OR\u0026thinsp;=\u0026thinsp;1.55, p\u0026thinsp;=\u0026thinsp;0.01). No other factor was statistically significant for either sex. As there was only one significant predictor, no adjusted analyses were conducted.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003eTrial enrollment compared to respondents eligible for randomization but not interested (Analysis 3)\u003c/h2\u003e\n \u003cp\u003eOf the 1,142 who attended a baseline examination, 489 were ineligible for the trial (due to incomplete baseline, no MetS, etc.), 618 (94.6%; 150 males, 468 females) were randomized, and 35 (5.4%; 9 males, 26 females) were eligible to be randomized but not interested in the trial. The purpose of Analysis 3 was to compare the latter two categories. However, due to the very small number of people who were eligible but not interested (N\u0026thinsp;=\u0026thinsp;35), no analyses were conducted as any evidence from it would likely not be robust.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eTrial enrollment compared to respondent not interested at any point in the recruitment process (Analysis 4)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThe 618 randomized participants were compared to the combined group consisting of those who did not attend an info session, did not attend baseline examination, were eligible to be randomized but were not interested, and indicated they were not interested in the middle of baseline examination (n\u0026thinsp;=\u0026thinsp;1,630, 499 males, 1,131 females). Unique to male respondents, self-reported A1c between 5.7 and 6.4 percent (OR\u0026thinsp;=\u0026thinsp;1.57, p\u0026thinsp;=\u0026thinsp;0.03), current order of fibrates medication (OR\u0026thinsp;=\u0026thinsp;2.34, p\u0026thinsp;=\u0026thinsp;0.01), fasting glucose between 100 and 125 mg/dL (OR\u0026thinsp;=\u0026thinsp;1.68, p\u0026thinsp;=\u0026thinsp;0.03), and triglycerides over 150 mg/dL (OR\u0026thinsp;=\u0026thinsp;1.95, p\u0026thinsp;=\u0026thinsp;0.003) were all positively associated with trial enrollment. However, none of the predictors remained significant in the adjusted analyses.\u003c/p\u003e\n \u003cp\u003eOnly race was significant in both sexes, with Black respondents less likely to enroll compared to White respondents (OR\u0026thinsp;=\u0026thinsp;0.41, p\u0026thinsp;=\u0026thinsp;0.0032 for males; OR\u0026thinsp;=\u0026thinsp;0.55, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 for females). For females, willingness to make changes to their current diet (OR\u0026thinsp;=\u0026thinsp;1.15, p\u0026thinsp;=\u0026thinsp;0.01) and presence of other chronic illnesses (OR\u0026thinsp;=\u0026thinsp;1.30, p\u0026thinsp;=\u0026thinsp;0.03) were uniquely associated to trial enrollment. Willingness to change diet (OR\u0026thinsp;=\u0026thinsp;1.17, p\u0026thinsp;=\u0026thinsp;0.008) and Black race (OR\u0026thinsp;=\u0026thinsp;0.55, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) remained significant in the adjusted model.\u003c/p\u003e\n \u003cp\u003eThe proportion of males and females who chose to move forward to the subsequent step in the recruitment process were compared using chi-squared tests. No significant differences were found in proportions of males and females for baseline attendance or trial enrollment, meaning qualifying males and females were equally likely to attend baseline assessments and enroll in the trial. However, there was a significant difference in proportions (58.3% in males vs. 66.5% females; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) attending an info session after being tentatively eligible.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe purpose of this exploratory study was to determine factors associated to male participation in a behavioral clinical trial targeting remission of the MetS. Using data collected in the trial screening process, various factors were compared during successive stages of the recruitment process, where a potential participant had the choice of either moving forward to the next stage or indicating no interest. The same set of analyses were conducted for potential female participants to determine the uniqueness of the findings to males. Black respondents were consistently less likely to move forward in the screening process compared to White respondents, irrespective of sex. There were also distinct factors associated to male trial participation, not observed in females. Results indicated that males who show initial interest in the trial were more likely to lose interest quickly. Those who continued were more aware of their current health risk. A direct comparison of males and females showed that men tended to lose interest earlier in the recruitment process.\u003c/p\u003e \u003cp\u003eSeveral factors were uniquely associated to trial participation for men. The presence of other chronic illnesses and confidence in ability to be physically active were significantly associated with attending an information session in the adjusted analyses. Self-reported HbA1c between 5.7 and 6.4 percent, current order of fibrates medication, fasting glucose between 100 and 125 mg/dL, and triglycerides over 150 mg/dL were associated with trial enrollment, albeit only in the unadjusted analyses. All these factors point toward self-awareness of an already existing condition and a likely patient-provider relationship. For both sexes, a 2020 Cochrane review (of 29 studies) identified potential personal benefit as a reason to facilitate participation.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e Similarly, a 2016 narrative review of 61 studies related to clinical trial participation from the patient or caregiver perspective, reported that top facilitating factors were improved personal health, personal benefit\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, and perception of better care. Moreover, a 2023 mixed studies review (i.e., review of studies with diverse designs) of 37 studies found that the existence of a strong patient-provider relationship can improve recruitment.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Thus, male participants who were aware of their health, likely through their providers (having a primary care provider was an inclusion for the trial), and thought it necessary to receive more care may have been more inclined and motivated to participate. Males, in general, underutilize primary and preventive care.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e As such, male participation in behavioral trials may see an increase by raising awareness toward preventive care for males in general.\u003c/p\u003e \u003cp\u003eIn addition to differences in factors influencing moving forward between men and women, more men tended to lose interest earlier in the screening process compared to women. Of the 2,796 total respondents invited to an info session, only 58.3% of men attended compared to 66.5% for women (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No such differences were observed for subsequent steps in the process, meaning that for men who show initial interest and initiative, the rate of enrollment is not significantly different than for women. As such, efforts to increase male enrollment in behavioral clinical trials will benefit with a focus on earlier stages of recruitment, aiming to increase potential participants\u0026rsquo; initial levels of interest by leveraging factors mentioned above associated to moving forward. The Recruitment Innovation Center, part of the Trial Innovation Network\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, recommends that recruitment be viewed as a continuum in research rather than a one-time event, which starts with awareness of potential participants.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e This is consistent with a 2010 systematic review of 37 studies that compared methods of recruitment into an actual or a mock trial.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e The authors found that increasing awareness of the health problem and impact on health increased recruitment. Thus, earlier stages of recruitment may benefit from efforts to increase potential participant awareness.\u003c/p\u003e \u003cp\u003eThroughout the enrollment process, for both males and females, Black race was consistently associated with lower participation compared to White race. The US government has long mandated the inclusion of women and racial/ethnic minorities in federally funded research.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e The findings from this study shed light on sample diversity beyond final numbers. Of the 618 randomized participants, 106 (17.2%) identified as Black race. Given that the percent of the US population who identify as only Black or African American race is 13.4%\u003csup\u003e28\u003c/sup\u003e, and that unlike many other chronic illnesses, the disease burden of MetS in the US is higher in White adults compared to Black adults\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, at face value, the randomized cohort of ELM does not seem to suffer from a lack of diversity. In fact, the numbers from ELM are comparable with other trials focused on lifestyle interventions for weight loss. A review of 94 such trials in the US between 2009 and 2015 showed that the proportion of Black participants was 18.2%, compared to 58.9% for White participants.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e However, there is a noticeable difference in the enrollment rate between the two racial groups. Of the 688 Black adults who were invited to an info session, only 106 were randomized, a 15.4% enrollment rate. By comparison, there were 1,567 White adults who were invited to an info session leading to 456 being randomized, a 29.1% enrollment rate. This means that the recruitment effort to enroll Black adults into similar trials should be roughly 1.9 times higher than that of recruiting White adults. A breakdown by sex provides an even more concerning outlook. Of the 152 Black men invited to an info session, only 17 were randomized, an enrollment rate of 11.2%, compared to 16.6% for Black women, 23.5% for White men, and 31.5% for White women. Additionally, although not as robust as findings for Black race, Hispanic ethnicity was significantly associated with lower male baseline attendance. Similar trends were seen in that of the 75 Hispanic men invited to an info session, only 12 were randomized (16%).\u003c/p\u003e \u003cp\u003eA major contribution of the current study is the availability of data from a large number of potential participants at various stages of recruitment in a multi-site behavioral trial allowed elucidation of the factors associated with moving toward enrollment. The robustness of the findings is supported by factors such as race and ethnicity being associated with participation, a trend seen in other studies. At the same time, factors that were unique to males and females were also discovered. These findings support the idea that reasons for participating in a behavioral trial are different for men and women. Moreover, it suggests that tailored strategies may be needed to recruit the desired number of male participants.\u003c/p\u003e \u003cp\u003eDespite the contributions, this study is not without its limitations. First, as the data are cross-sectional, no causality can be drawn. Second, many of the measures are self-reported. This was unavoidable as most of the screening process was done through surveys. However, the large sample size from five sites across the US does bolster the level of confidence in the study findings. Third, the self-reported HbA1c and glucose questions were yes/no format that asked whether the respondent was within the pre-diabetes range. Thus, a \u0026ldquo;no\u0026rdquo; response could indicate lower or upper ranges. However, as respondents with a diagnosis of diabetes were not invited to the information session, it would be reasonable to assume that most, if not all, of the \u0026rdquo;no\u0026rdquo; responses fall below the pre-diabetes range.\u003c/p\u003e \u003cp\u003eIn conclusion, recruiting male participants into a behavioral clinical trial remains a challenge. Reasons why men may choose not to participate are distinct from women. Future efforts and strategies to increase male recruitment must be cognizant of these barriers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement and Declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants signed informed consent, and the trial was approved by the appropriate Institutional Review Boards (IRBs) of the participating sites and a central IRB at Rush University Medical Center. The authors declare no conflict of interest. All authors contributed equally to this manuscript. The ELM trial was supported by a grant from the William G. McGowan Charitable Fund (The Fund). The Fund had no role in the design or conduct of the trial, the decision to publish trial results, the analysis of data, or the preparation of this manuscript. Data used in this study may be available by request.\u003c/p\u003e\n\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFranz MJ, VanWormer JJ, Crain AL, Boucher JL, Histon T, Caplan W, Bowman JD, Pronk NP. Weight-loss outcomes: a systematic review and meta-analysis of weight-loss clinical trials with a minimum 1-year follow-up. Journal of the American Dietetic association. 2007 Oct 1;107(10):1755-67.\u003c/li\u003e\n\u003cli\u003eConsequences of Obesity, https://www.cdc.gov/obesity/basics/consequences.html (2022, accessed 27 October 2023).\u003c/li\u003e\n\u003cli\u003ePhilip W, James T. What are the health risks? The medical consequences of obesity and its health risks. Experimental and clinical endocrinology \u0026amp; diabetes. 1998;106(S 02):1-6.\u003c/li\u003e\n\u003cli\u003eNational Institutes of Health. Clinical guidelines for the identification, evaluation, and treatment of overweight and obesity in adults-the evidence report. 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Factors affecting patient participation in clinical trials in Ireland: a narrative review. Contemporary Clinical Trials Communications. 2016 Aug 15;3:23-31.\u003c/li\u003e\n\u003cli\u003eMoffat KR, Shi W, Cannon P, Sullivan F. Factors associated with recruitment to randomised controlled trials in general practice: a systematic mixed studies review. Trials. 2023 Dec;24(1):1-9.\u003c/li\u003e\n\u003cli\u003eMursa R, Patterson C, Halcomb E. Men\u0026rsquo;s help-seeking and engagement with general practice: An integrative review. Journal of Advanced Nursing. 2022 78(7): 1938-53. \u003c/li\u003e\n\u003cli\u003eTrial Innovation Network, https://trialinnovationnetwork.org/ (accessed 27 October 2023).\u003c/li\u003e\n\u003cli\u003eWilkins CH, Edwards TL, Stroud M, Kennedy N, Jerome RN, Lawrence CE, Kusnoor SV, Nelson S, Byrne LM, Boone LR, Dunagan J. The Recruitment Innovation Center: developing novel, person-centered strategies for clinical trial recruitment and retention. Journal of Clinical and Translational Science. 2021;5(1):e194.\u003c/li\u003e\n\u003cli\u003eCaldwell PH, Hamilton S, Tan A, Craig JC. Strategies for increasing recruitment to randomised controlled trials: systematic review. PLoS medicine. 2010 Nov 9;7(11):e1000368.\u003c/li\u003e\n\u003cli\u003eNational Institutes of Health. Inclusion of Women and Minorities as Participants in Research Involving Human Subjects, https://grants.nih.gov/policy/inclusion/women-and-minorities.htm (accessed 27 October 2023).\u003c/li\u003e\n\u003cli\u003eUS Census Bureau. https://www.census.gov/quickfacts/fact/table/US/PST045222 (accessed 2023).\u003c/li\u003e\n\u003cli\u003eHaughton CF, Silfee VJ, Wang ML, Lopez-Cepero AC, Estabrook DP, Frisard C, Rosal MC, Pagoto SL, Lemon SC. Racial/ethnic representation in lifestyle weight loss intervention studies in the United States: a systematic review. Preventive medicine reports. 2018 Mar 1;9:131-7.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Supplementary Tables","content":"\u003cp\u003eTable 1: Significant predictors of male participation\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eUnadjusted\u003c/p\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eOR (95% CI)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnalysis 1 \u0026ndash; Info session attendance vs. not\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eOther chronic illnesses or health problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.81 (1.22, 2.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.74(1.02,2.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eMajor food allergies or dietary preferences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.97 (1.05, 3.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003en/s\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eFasting glucose between 100 and 125 mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.69 (1.17, 2.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003en/s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eSelf-Efficacy: Confidence of being physically active for at least 30 minutes on most days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.24 (1.08, 1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.40(1.15,1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eBlack race (reference White)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e0.52 (0.36, 0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e0.43 (0.24, 0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnalysis 2 \u0026ndash; Baseline attendance vs. not\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eHispanic, Latinx, or Spanish origin\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e0.51 (0.27, 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003en/a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnalysis 4 \u0026ndash; Randomized vs. not at any point prior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eA1c between 5.7 and 6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.57 (1.03, 2.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003en/s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eCurrent order for Fibrates medications\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e2.34 (1.20, 4.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003en/s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eFasting glucose between 100 and125 mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.68 (1.06, 2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003en/s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eSelf-Efficacy: Confidence of being physically active for at least 30 minutes on most days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.22 (1.02, 1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003en/s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eBlack race (reference white race)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e0.41 (0.23, 0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003en/s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eTriglycerides = 150 mg/d\u0026gt;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.95 (1.24, 3.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003en/s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eAdjusted models include all significant predictors from unadjusted models.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003en/s indicates p-value \u0026ge; 0.05.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2: Significant predictors of female participation\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eUnadjusted\u003c/p\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eOR (95% CI)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnalysis 1 \u0026ndash; Info session attendance vs. not\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eWilling and able are to make changes to current diet\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.11 (1.01, 1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.12 (1.02,1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eOther chronic illnesses or health problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.28 (1.02, 1.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003en/s\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eBlack race (reference white race)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e0.68 (0.55, 0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e0.68 (0.55, 0.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eBlack race (reference any other race)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e0.61 (0.39, 0.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e0.63 (0.41, 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnalysis 2 \u0026ndash; Baseline attendance vs. not\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eAsthma\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.55 (1.08, 2.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003en/a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnalysis 4 \u0026ndash; Randomized vs. not at any point prior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eWilling and able are to make changes to current diet\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.15 (1.03, 1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.17 (1.04, 1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eOther chronic illnesses or health problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e1.30 (1.02, 1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003en/s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55.833333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eBlack race (reference white race)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e0.55 (0.42, 0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.083333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e0.55 (0.42, 0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eAdjusted models include all significant predictors from unadjusted models.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003en/s indicates p-value \u0026ge; 0.05.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"trials","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trls","sideBox":"Learn more about [Trials](http://trialsjournal.biomedcentral.com/)","snPcode":"13063","submissionUrl":"https://www.editorialmanager.com/trls","title":"Trials","twitterHandle":"MedicalEvidence","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Behavioral clinical trials, metabolic syndrome, male recruitment","lastPublishedDoi":"10.21203/rs.3.rs-4656235/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4656235/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMales are underrepresented in behavioral clinical trials of lifestyle change or weight loss. Little is known about factors that facilitate or deter males from participating in such trials. The aim of this exploratory study was to describe the sample of males recruited into a multi-site behavioral trial targeting lifestyle change and remission of the metabolic syndrome and to investigate factors associated with trial interest at different stages of recruitment and overall. Similar analyses were performed for female participation to investigate the uniqueness or consistency with the findings for males.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData collected at various stages of recruitment in an ongoing multi-site behavioral clinical trial were used. A series of logistic regressions compared respondents who moved forward to the next step of the screening process versus those who did not. These analyses were stratified by sex. A chi-squared test was used to directly compare proportions of men and women who chose to advance to the next step.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMales who showed interest in the trial were more likely to be self-aware of their current health risk. Comparison of males and females showed that men tended to lose interest earlier in the recruitment process (58.3% of men vs. 66.5% of women attended an in-person information session, p \u0026lt; 0.001), but the proportion that moved forward among those who demonstrated initial interest was similar in men and women.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEfforts to increase male enrollment in behavioral clinical trials will benefit from a focus on early stages of recruitment, aiming to increase potential participants’ initial levels of interest and awareness of their health risk. As men and women differ in the reasons they choose to participate in a behavioral trial, recruitment should be tailored to sex to maximize trial participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinicalTrials.gov number, NCT04036006, https//clinicaltrials.gov/study/NCT04036006\u003c/p\u003e","manuscriptTitle":"Factors associated with male recruitment in a multi-site randomized behavioral clinical trial targeting the metabolic syndrome: analysis of screening and recruitment data from the ELM trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-18 02:17:16","doi":"10.21203/rs.3.rs-4656235/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2024-10-18T13:13:13+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-09-10T12:42:52+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-09T15:46:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-31T08:29:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Trials","date":"2024-07-16T11:52:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"trials","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trls","sideBox":"Learn more about [Trials](http://trialsjournal.biomedcentral.com/)","snPcode":"13063","submissionUrl":"https://www.editorialmanager.com/trls","title":"Trials","twitterHandle":"MedicalEvidence","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3bb1174e-c6a2-49c8-8f7a-edba4a453148","owner":[],"postedDate":"September 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-23T16:12:58+00:00","versionOfRecord":{"articleIdentity":"rs-4656235","link":"https://doi.org/10.1186/s13063-024-08703-8","journal":{"identity":"trials","isVorOnly":false,"title":"Trials"},"publishedOn":"2024-12-21 15:58:20","publishedOnDateReadable":"December 21st, 2024"},"versionCreatedAt":"2024-09-18 02:17:16","video":"","vorDoi":"10.1186/s13063-024-08703-8","vorDoiUrl":"https://doi.org/10.1186/s13063-024-08703-8","workflowStages":[]},"version":"v1","identity":"rs-4656235","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4656235","identity":"rs-4656235","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}