Abstract
Introduction
Effective recruitment and subsequent enrollment of diverse populations is often a challenge in randomized controlled trials, especially those focused on weight loss. In the civilian literature, individuals identified as racial and ethnic minorities, men, and younger and older adults are poorly represented in weight loss interventions. There are limited weight loss trials within military populations, and to our knowledge, none reported participant characteristics associated with enrollment. There may be unique motives and barriers for active duty personnel for enrollment in weight management trials. Given substantial costs and consequences of overweight and obesity in the U.S. military, identifying predictors and limitations to diverse enrollment can inform future interventions within this population. The study aims to describe the recruitment, screening, and enrollment process of a military weight loss intervention. Demographic and lifestyle characteristics of military personnel lost between screening and randomization are compared to characteristics of personnel randomized in the study and characteristics of the Air Force in general.
Materials and Methods
The Fit Blue study, a randomized controlled behavioral weight loss trial for active duty personnel, was approved by the Institutional Review Board of the Wilford Hall Ambulatory Surgical Center in San Antonio, TX, USA and acknowledged by the Institutional Review Board at the University of Tennessee Health Science Center. Logistic regressions compared participant demographics, anthropometric data, and health behaviors between personnel that attended a screening visit but were not randomized and those randomized. Multivariable models were constructed for the likelihood of being randomized using a liberal entry and stay criteria of 0.10 for the p-values in a stepwise variable selection algorithm. Descriptive statistics compared the randomized Fit Blue cohort demographics to those of the U.S. Air Force
Results
In univariate analyses, older age (p < 0.02), having a college degree or higher (p < 0.007) and higher military rank (p < 0.02) were associated with completing the randomization process. The randomized cohort reported a lower percentage of total daily kilocalories for fat compared to the non-randomized cohort (p = 0.033). The non-randomized cohort reported more total minutes and intensity of physical activity (p = 0.073). In the multivariate model, only those with a college degree or higher were 3.2 times more likely to go onto randomization. (OR = 3.2, 95% CI = 2.0, 5.6, p < 0.0001). The Fit Blue study included a higher representation of personnel who identified as African American (19.4% versus 15.0%) and Hispanic/Latino (22.7% versus 14.3%) compared with the U.S. Air Force in general; however, men were underrepresented (49.4% versus 80.0%).
Conclusions
Accounting for all influencing characteristics, higher educational status was the only independent predictor of randomization. Perhaps, highly educated personnel are more invested in a military career, and thus, more concerned with consequences of failing required fitness tests. Thus, it may be important for future weight loss interventions to focus recruitment on less-educated personnel. Results suggest that weight loss interventions within a military population offer a unique opportunity to recruit a higher prevalence of males and individuals who identify as racial or ethnic minorities which are populations commonly underrepresented in weight loss research.
Keywords: behavioral weight loss intervention, recruitment, enrollment
The overall goal of recruitment into randomized controlled trials (RCTs) is to obtain a sufficiently large and representative sample so results are valid and generalizable to wider target populations. Low and biased enrollment is costly and threatens the interpretation of study findings.1 Unfortunately, effective recruitment and subsequent enrollment is often a challenge.2–6 Barriers to recruiting diverse samples into RCTs have been well documented in the civilian literature.2,3,5,7 Further, studies have reported specific challenges to recruitment in RCTs focused specifically on behavioral weight loss interventions.8–10
In behavioral weight loss trials, eligibility criteria (e.g., medical conditions impacting weight loss) and participant characteristics (e.g., time constraints) can compromise retention of a diverse sample between recruitment and subsequent enrollment.9 Importantly, individuals who identify as racial and ethnic minorities are often poorly represented in weight loss RCTs.8–10 Specifically, studies have found a higher dropout of non-White participants between recruitment and enrollment compared to White participants.8,9 Further, younger participants (i.e., 18–35 years of age)11,12 and individuals over age 6013 have been more difficult to recruit than middle-aged participants. Finally, males, especially those identified in ethnic minority groups, have been largely underrepresented in weight loss interventions.10
Within the military literature, there are few RCTs that reported participant characteristics throughout the process of recruitment, screening, and enrollment.14–16 Of these studies, attrition rates, rather than recruitment data were provided.14,15 Although military and civilian studies achieve recruitment goals at similar rates,14 there might be challenges unique to the U.S. military (e.g., a demanding work schedule, less incentive for participating in research due to free provision of health care).15,16 Importantly, a recent review found less than half (i.e., 44.2%) of military studies successfully enrolled the anticipated number of participants.14 Of RCTs specifically directed at weight management, there are few within military populations.17,18 To our knowledge, there have been no behavioral weight loss interventions in the U.S. military that reported participant characteristics associated with enrollment.
Importantly, documentation of the enrollment process can inform future weight loss interventions by identifying characteristics of military personnel who may not be interested or eligible and thus need interventions better tailored to their needs. Overweight and obesity, affecting approximately 60% of active duty personnel, are critical concerns for the U.S. military.19 Failure to meet fitness standards negatively impacts career trajectories. Repeated failure will lead to discharge and can pose a threat to national security.20 Further, the Department of Defense spends more than $1 billion annually on managing excessive weight and associated co-morbidities.21,22 Given the cost and consequences of overweight and obesity in the military, implementing effective weight loss interventions in this population is a national public health concern. The enrollment of diverse samples in military weight loss studies is especially important given that recent research suggests that obesity disproportionality affects non-Hispanic Black, less educated, older, and male U.S. active duty military personnel .23 Enrollment of populations more affected by obesity is crucial for weight loss programs in the military. Further, even the most effective interventions will not be useful without a willingness among military personnel to enroll.
Thus, the purpose of the current study is to describe the recruitment, screening, and enrollment process of a weight loss RCT in a military population. The primary aim is to compare the demographic and lifestyle characteristics of military personnel lost between screening and randomization to the characteristics of personnel randomized in the final sample. To assess generalizability, the study will compare characteristics of the current sample, of which approximately 94% were affiliated with the Air Force, to the overall Air Force population.
MATERIALS AND METHODS
Design
Data were obtained from the Fit Blue study. The Fit Blue study was a 12-month randomized controlled behavioral weight loss trial at Joint Base San Antonio. The study compared two adapted versions, counselor-initiated and self-paced, of the highly efficacious Look AHEAD Lifestyle Program. Study protocol was primarily ethically approved by the Institutional Review Board of the Wilford Hall Ambulatory Surgical Center in San Antonio, TX, USA and secondarily acknowledged by the Institutional Review Board at the University of Tennessee Health Science Center. Further details on study design have been reported .24
Population
Analyses include individuals who completed a screening visit, regardless of whether they were randomized in the study. Active duty military personnel at Joint Base San Antonio, Texas, ≥18 years old, [body mass index (BMI) ≥ 25], who had phone and computer access were recruited into the Fit Blue study. Participants were required to have at least one more year left in their duty assignment to maximize the likelihood of data collection. Exclusion criteria included major medical or psychiatric conditions, conditions prohibiting exercise, recent substantial weight loss, use of medications known to impact weight, and current or recent pregnancy. Individuals were excluded if they had more than one failed military fitness test in the past 12 months. Failing a fitness test would increase the likelihood of military discharge, thus, decreasing the likelihood of completing data collection. Preliminary power calculations, using the expected percent weight loss between baseline and 12 months for the CI (8%) and SP (4%) conditions, projected an enrollment goal of 204 total.24 Due to greater attrition than expected, the final sample size included 248 participants.
Recruitment Strategies
Individuals were recruited through the use of posters, electronic bulletins, presentations on the base, e-mails, newspaper advertisements, and word-of-mouth. Personnel were able to learn more about the study by phone or a web-based self-screener.
Screening and Enrollment
Study staff conducted a phone screener on individuals who expressed interest in the study (via phone or the web-based self-screener) to determine if initial eligibility criteria were met. If the person met preliminary eligibility criteria and continued to be interested in the study, they were asked to complete an in-person screening visit.
Screening visit times were flexible to make it easier for busy personnel to attend. At the screening visit, informed consent was obtained and BMI eligibility was confirmed. Individuals completed questionnaires and anthropometric assessments. Potential participants were then asked to complete a behavioral run-in consisting of two components – (1) 1 week of dietary and physical activity self-monitoring using the Lose It! website/application and (2) obtain a letter from their Air Force healthcare provider approving participation. They were scheduled for an in-person randomization visit in one to two weeks.
At the randomization visit, it was determined whether the potential participant successfully completed both components of the behavioral run-in (If not, they were given one more opportunity to complete tasks). Failure to eventually complete either task disqualified participation. Participants fully eligible were then randomized at the individual level using computerized block design (six blocks of four) to one of the intervention conditions (1:1 allocation) with allocation concealment to allow for equal assignment of both conditions throughout the intervention.
Enrollment Variables
Self-reported demographics and health behaviors were collected at the screening visit. These included race, ethnicity, gender, education, marital status, number of adults in the home, number of children in the household, military grade [i.e., three Enlisted (E) categories: E1–E4 (i.e., enlisted), E5–E6 (i.e., non-commissioned officers), E7–E9 (i.e., senior non-commissioned officers) and two Officer categories (O): O1–O3 (i.e., Company Grade Officer) and O4–O6 (i.e., Field Grade Officer)], and branch of service. The Global Physical Activity Questionnaire (GPAQ)25 measured self-reported levels of physical activity (i.e., total, moderate, and vigorous physical activity), and the Multifactor Screener provided an approximate intake of fruits and vegetables and energy from fat and fiber.26 Weight was measured without shoes in their physical training clothes or their uniform without their blouse on a calibrated digital scale (Tanita BWB 800S). Height was measured in centimeters using a wall-mounted stadiometer and BMI was calculated {weight (kg)/ [height (m)]2} from these measurements.
Statistical Methods
Participant demographics, anthropometric data, non-exclusionary health conditions, and health behaviors captured at the participants’ screening visit were analyzed. Differences between those who attended a screening visit but not randomized were compared with those randomized using logistic regression. Multivariable models were constructed for the likelihood of being randomized using a liberal entry and stay criteria of 0.10 for the p-values in a stepwise variable selection algorithm. Descriptive statistics compared the randomized cohort demographics to those of the U.S. Air Force.
RESULTS
Recruitment and enrollment
Recruitment and enrollment results for the Fit Blue study are shown in Fig. 1. Telephone pre-screenings (N = 595) were made to individuals who expressed interest in the study via phone or web-based self-screener. Of the 595 personnel initially phone screened, 236 (39.7%) did not complete a screening visit. Specifically, of these 236 individuals, 150 (63.6%) were ineligible, 53 (22.5%) were lost to follow-up, 17 (7.2%) did not attend the screening visit, and 16 (6.8%) refused to participate. Thus, 363 personnel attended a screening visit. Four individuals refused to participate at their screening visit appointment before signing consent. Of the remaining 359 individuals who completed screening visit procedures, 111 (30.9%) were not randomized into the study. Specifically, 17 individuals’ health care professional did not approve medical clearance and 2 refused to participate at the screening visit after signing consent. There were 76 personnel who did not provide a reason and did not attend their baseline visit. At the baseline visit, 6 individuals had high blood pressure, 5 did not obtain a medical clearance letter, 3 failed to complete the self-monitoring task, and 2 refused to participate at the baseline visit. Thus, of 359 individuals who completed the screening visit, there were two cohorts for comparison: (1) 248 (69.0%) completed a screening visit and subsequent randomization visit and (2) 111 (31.0%) completed a screening visit but failed to complete a randomization visit.
FIGURE 1.
Fit Blue recruitment and enrollment.
Characteristics and Comparisons of the Randomized Versus Screened Non-Randomized Fit Blue Cohort
None of the non-exclusionary medical conditions (e.g., controlled hypertension, hypothyroidism, cardiovascular disease) was significantly different between the randomized and non-randomized cohort. The univariate analysis of demographic and anthropometric characteristics showed older age (as a continuous variable) (p < 0.02), having a college degree or higher (p < 0.007) and higher rank (O4-O6 vs. lower ranks) (p < 0.02) were associated with randomization. (Table 1). The randomized cohort reported a lower percentage of total daily kilocalories for fat compared with the non-randomized cohort (p = 0.033) (Table 2). No other dietary differences between cohorts were observed. The non-randomized cohort reported more total minutes (p = 0.027) and vigorous (p = 0.036) minutes of physical activity, as well as in the domains of transportation (p = 0.014) and household physical activity (p = 0.084), but not recreational physical activity (p = 0.29) or work (p = 0.33), compared with the randomized cohort (Table 2).
TABLE I.
Comparisons of Demographic Characteristics of Randomized Fit Blue Cohort to Screened Non-Randomized Cohort
| Fit Blue Randomized Participants (N = 248) | Non-Randomized Cohort (N = 111) | All Screened Participants (N = 359) | p-Value | |
|---|---|---|---|---|
| Sex N (%) | 0.73 | |||
| Male | 122 (49.2) | 52 (46.8) | 174 (48.5) | |
| Female | 126 (50.8) | 59 (53.2) | 183 (51.5) | |
| Age Mean (±SD) years | 34 (±7.5) | 32 (±6.7) | 33 (±7.3) | 0.02 |
| Race N (%) | 0.89 | |||
| African American | 49 (19.8) | 22 (19.8) | 71 (19.8) | |
| Caucasian | 163 (65.7) | 75 (67.6) | 238 (66.3) | |
| Other | 36 (14.5) | 14 (12.2) | 50 (13.9) | |
| Ethnicity N (%) | 0.59 | |||
| Hispanic/Latino | 56 (22.6) | 28 (25.2) | 84 (23.4) | |
| Non-Hispanic/Latino | 192 (77.4) | 83 (74.8) | 275 (76.6) | |
| Education N (%) | <0.0001 | |||
| Less than college degree | 123 (49.6) | 82 (73.9) | 205 (57.1) | |
| College degree or greater | 125 (50.4) | 29 (26.1) | 154 (42.9) | |
| Marital status N (%) | 0.83 | |||
| Single/never married | 40 (16.1) | 20 (18) | 60 (16.7) | |
| Married/living as married | 169 (68.1) | 72 (64.9) | 241 (67.1) | |
| Separated/divorced | 39 (15.7) | 19 (17.1) | 58 (16.2) | |
| Number of additional adults in household N (%) | 0.82 | |||
| 0 | 46 (18.5) | 22 (19.8) | 68 (18.9) | |
| 1 | 162 (65.3) | 73 (65.8) | 235 (65.5) | |
| 2 | 31 (12.5) | 14 (12.6) | 45 (12.5) | |
| 3 or more | 9 (3.6) | 2 (1.8) | 11 (3.1) | |
| Number of children in household N (%) | 0.56 | |||
| 0 | 91 (36.7) | 37 (33.3) | 128 (35.7) | |
| 1 | 59 (23.8) | 23 (20.7) | 82 (22.8) | |
| 2 | 57 (23) | 26 (23.4) | 83 (23.1) | |
| 3 or more | 41 (16.5) | 25 (22.5) | 66 (18.4) | |
| Years in service mean (± SD) | 12 (±6.6) | 11 (±6.1) | 12 (±6.4) | 0.20 |
| Military gradeaN (%) | 0.02 | |||
| E1–E4 | 34 (13.7) | 19 (17.1) | 53 (14.8) | |
| E5–E6 | 105 (42.3) | 58 (52.3) | 163 (45.4) | |
| E7–E9 | 52 (21) | 21 (18.9) | 73 (20.3) | |
| O1–O3 | 17 (6.9) | 9 (8.1) | 26 (7.2) | |
| O4–O6 | 39 (15.7) | 4 (3.6) | 43 (12) | |
| Branch | 0.68 | |||
| Army | 4 (1.6) | 1 (0.9) | 5 (1.4) | |
| Air Force | 234 (94.4) | 105 (94.6) | 339 (94.4) | |
| Navy | 8 (3.2) | 5 (4.5) | 13 (3.6) | |
| Marine Corp | 2 (0.8) | 0 (0.0) | 2 (0.6) | |
| BMI (m2/kg) N (%) | 30.6 (±2.7) | 30.4 (±2.9) | 30.6 (±2.8) | |
| BMI category N (%) | 0.76 | |||
| Overweight | 115 (46.4) | 52 (48.1) | 167 (46.9) | |
| Obese | 133 (53.6) | 56 (51.9) | 189 (53.1) |
aMilitary ranking; Enlisted (E) categories: E1–E4 (enlisted), E5–E6 (non-commissioned officers), E7–E9 (senior non-commissioned officers) and two Officer categories (O): O1–O3 (Company Grade Officer) and O4–O6 (Field Grade Officer); standard deviation (SD).
Table II.
Comparisons of Anthropometric Characteristics of Randomized Fit Blue Cohort to Screened Non-Randomized Cohort
| Fit Blue Randomized Participants (N = 248) | Non-Randomized Cohort (N = 111) | All Screened Participants (N = 359) | p-Value | |
|---|---|---|---|---|
| Physical activity | ||||
| Total physical activity | 2525 (±3218) | 2840 (±2541) | 2621 (±3028) | 0.027 |
| (mean (±SD) minutes per week) | ||||
| Total sedentary physical activity | 5046 (±239) | 472 (±221) | 494 (±234) | 0.35 |
| (mean (±SD) minutes per week) | ||||
| Vigorous physical activity | 34 (±145) | 54 (±152) | 40 (±147) | 0.036 |
| (mean (±SD) minutes per week) | ||||
| Dietary intake | ||||
| Total sweetened beverages (kcal per day) | 165 (±206) | 152.9 (±166) | 160.8 (±194) | 0.80 |
| Fruit and vegetable consumption (cups per day) | 3 (±1) | 3 (±1) | 3 (±1) | 0.52 |
| Dietary fat (% total kcal) | 35 (±4) | 34 (±4) | 35 (±4) | 0.033 |
In the final multivariate model, only education remained a significant predictor. Those with a college degree or higher were 3.2 times more likely to go onto randomization [odds ratio (OR) = 3.2, 95% confidence interval (CI) = 2.0, 5.6, p < 0.0001].
Comparison of Fit Blue to the U.S. Air Force Demographics
The comparison of Fit Blue demographics to available U.S. Air Force demographics at the time of study enrollment is shown in Table 3.27 Although there was some representation of other branches in the study participants, 94.4% of participants were Air Force personnel; thus, the Air Force characteristics are the best comparison to our sample rather than the military as whole. The Fit Blue study included a higher representation of personnel who identified as African American (19.8% versus 14.0%) and Hispanic/Latino (22.6% versus 13.6%) compared with the U.S. Air Force. Compared to the Air Force population, men were underrepresented in the Fit Blue study (49.2% versus 80.6%). Additionally, a higher percentage of married personnel were recruited into the Fit Blue study compared to the entire Air Force (68.1% versus 56.0%).
TABLE III.
Comparison of Fit Blue Study to 2016 US Air Force Demographics
| Fit Blue (%) | Air Force (%) | |
|---|---|---|
| Race | ||
| African American | 19.8 | 14.0 |
| Caucasian | 65.7 | 72.0 |
| Ethnicity | ||
| Hispanic/Latino | 22.6 | 13.6 |
| Gender | ||
| Male | 49.4 | 80.6 |
| Married | 68.1 | 56.0 |
DISCUSSION
This study reached its recruitment goal and successfully enrolled 248 participants. Importantly, the final sample was racially and ethnically representative of the entire Air Force population. Of participants who completed the initial screening visit, the majority (69.0%) were randomized into the final sample. A small percentage (4.7%, n = 17) of individuals who attended the screening visit were not randomized because of failed medical clearance. Thus, the initial phone pre-screening was successful in determining eligibility criteria. Reasons for why 76 eligible participants failed to attend the randomization appointment after their screening visit are unknown. Perhaps, barriers unique to the U.S. military deterred some of these individuals (e.g., access to high-quality health care, and thus, being less incentivized to receive free weight loss services, demanding military lifestyle preventing personnel from committing to a long-term intervention).15
After accounting for covariates, educational status (i.e., college degree or higher) was the only factor independently associated with the likelihood of randomization. Although education was the strongest predictor of enrollment, results from univariate analyses suggest age (range: 19 to 47 years in non-randomized versus 19–60 years in randomized participants) and military rank were related factors also associated with intervention engagement. This difference in education was consistent with previous research that found highly educated individuals were more likely to enroll in health-related studies.15 Further, similarly to the current study, middle-aged adults (i.e., 35–60 years) were more likely to enroll in previous weight loss trials compared with younger individuals.11,12 Perhaps, personnel with college degrees have more motivation to meet fitness standards. If personnel fail a fitness test, they risk losing their career, health insurance, and pension if they have not previously served 20 years.22 More highly educated personnel might be more invested in a military career, and thus, more concerned with consequences of failing fitness tests. Those enlisted (who tend to have less education) rather than officers, as well as younger personnel, might be less motivated for weight loss due to less interest in a long-term military career. In addition, some research suggests poor health literacy is associated with fewer years of education.28 Perhaps, less educated personnel have less understanding about the consequences of overweight and obesity.29
Active duty personnel with less education are more likely to have obesity.23 Thus, it is crucial to address recruitment barriers and tailor intervention marketing strategies to enroll personnel of diverse educational backgrounds, as well as with diverse ages and ranks. During the recruitment process, effectively communicating study services (e.g., free transportation, child-care) could help to engage those who might anticipate barriers to a long-term intervention commitment. Tailoring recruitment materials to particular themes, as well as implementing alternative modalities (e.g., social networks), could help incentivize a more diverse range of personnel. Previous research found self-confidence, quality of life, and physical defense ability were motivators of weight loss more commonly reported by younger and lower ranked personnel.30 Thus, it might be important for recruitment materials to address these weight loss goals, as well as to clearly provide information on the health consequences of overweight and obesity. Further, advertising interventions as additional support for upcoming fitness tests might increase enrollment for behavioral weight loss interventions within the U.S. military.30 Future military weight loss trials should explore alternative components (e.g., briefer interventions, competition between units) and modalities (e.g., smartphone applications) which might engage younger, less educated, and enlisted personnel. There is a need for future qualitative studies to identify the unique barriers to recruiting diversely educated personnel into behavioral weight loss interventions. It is important for future military studies to report data from the recruitment, screening, and enrollment process to determine the replicability of these findings.
Dissimilarly to most behavioral weight loss RCTs, there was an equal distribution of males and females in the current study.10 Thus, findings are likely to be generalizable to both active duty men and women in the Air Force. Previous research found males were predominately underrepresented in weight loss trials compared to females.10 Men might be less likely to seek outside help for weight loss, as well as less socially motivated to lose weight compared with women.10 These potential recruitment barriers are particularly important because there is a higher prevalence of obesity in males among active duty personnel.23 The equal distribution in the current sample might be attributed to the predominance of males in the Air Force (80.6%).27 Although men still remained underrepresented in the current sample compared to the distribution of the entire Air Force, this study’s recruitment process engaged a higher percentage of men compared to civilian weight loss studies. Perhaps, preparation for upcoming fitness tests increased motivation among men to enroll in the Fit Blue intervention. Further, the current study enrolled a higher rate of males identified within racial or ethnic minority groups compared with rates in previous weight loss trials.10 Specifically, this trial enrolled 14% non-White and 11% Hispanic/Latino male participants. In comparison, a previous review found males who identified as a racial or ethnic minority composed only 1.8% of total participants in U.S. weight loss studies.10 Thus, recruitment within the current military population offered a unique opportunity to include more males, particularly those in ethnic minorities, within weight loss research.
There are several limitations in the current study important to consider. The current sample of Air Force personnel might limit generalizability to the entire U.S. military. In addition, the current study did not collect information on the characteristics of participants who expressed interest in the study during the phone screener but did not meet eligibility criteria, since they had not consented to participate in research. Finally, data were obtained from a single site. Thus, future studies should examine recruitment characteristics for interventions from other sites.
CONCLUSION
To our knowledge, no previous study in a military population has reported recruitment and enrollment rates within a behavioral weight loss intervention. Current findings document gender, race, and ethnic diversity of the sample as well as the loss of less educated active duty personnel from initial screening to randomization within a weight loss trial. Thus, increased recruitment outreach of personnel without college educations could improve the generalizability of findings for behavioral weight management studies targeting military populations.
Acknowledgments
The research represents a Collaborative Research and Development Agreement with the United States Air Force (CRADA #13-168-SG-C13001). Finally, we would like to thank the participants and the research team for their dedication to the research. The opinions expressed in this document are solely those of the authors and do not represent an endorsement by or the views of the United States Air Force, the Department of Defense, or the United States Government.
Funding
The study was funded by the National Institute of Diabetes and Digestive and Kidney Diseases (RO1 DK097158) of the National Institutes of Health, with the title of “Dissemination of the Look Ahead Weight Management Treatment in the Military,” Robert Klesges and Rebecca Krukowski, Principal Investigators. The trial is registered on clinicaltrials.gov (NCT 02063178).
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