Recruitment and Retention of Adolescents in a Smoking Trajectory Study: Who Participates and Lessons Learned

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1 Substance Use & Misuse, 41: Copyright 2006 Taylor & Francis Inc. ISSN: (print); (online) DOI: / Recruitment and Retention of Adolescents in a Smoking Trajectory Study: Who Participates and Lessons Learned KATHLEEN R. DIVIAK, SARAH K. WAHL, JOHN J. O KEEFE, ROBIN J. MERMELSTEIN, AND BRIAN R. FLAY University of Illinois at Chicago, Chicago, Illinois, USA Recruitment of adolescents into tobacco use research is often challenging. This study reports on the predictors of recruitment and retention in a longitudinal study of adolescent smoking behavior. In 2000, 8th and 10th grade students at 18 schools (N = 5,298) in the Chicago metropolitan area completed brief screening surveys; 1457 students (ranging from susceptible nonsmokers to regular smokers) were invited to participate in a longitudinal study, and 48.9% agreed. Chi-square analyses revealed that female and white students were more likely to participate than male and nonwhite students. Recruitment rates did not vary by parental smoking status, students experience with smoking, or student grade. Multivariate analyses revealed that overall, gender and race were significant predictors of participation. Chi-square and multivariate analyses revealed no significant differences in retention on the demographic, smoking experience, or psychosocial variables measured. Implications of the results and study limitations are discussed. Keywords adolescents; smoking; recruitment; retention Introduction Recruiting adolescents into tobacco use research can be a challenge (USDHHS, 1994). Unfortunately, literature on the recruitment of adolescents into smoking research and the factors associated with participation or nonparticipation is scarce (McCormick et al., 1999). In many studies, it is difficult to determine the actual rates of participation because researchers seldom report data on the size of the potential pool of participants or on the number willing to participate, although there are some notable exceptions (e.g., Peterson et al., 2000). Some researchers have reported greater difficulty recruiting teens with higher levels of smoking than those with less smoking experience (McCormick et al., 1999). Other studies have found it easier to recruit female participants than males (Bauman et al., 2001; Martinson et al., 2000). Data on the recruitment of ethnic/minority youth into tobacco studies are extremely limited. Some suggest that minorities are more difficult to enroll in health research generally (Swanson and Ward, 1995), although others challenge this as an assumption based on little data (Cauce et al., 1998). Address correspondence to Kathleen R. Diviak, Ph.D., University of Illinois at Chicago, Institute for Health Research and Policy, 1747 W. Roosevelt Road, Room 558 M/C 275, Chicago, IL kdiviak@uic.edu 175

2 176 Diviak et al. Recruitment of adolescents can be complicated by Institutional Review Boards (IRB) requirement of written parental permission for involvement in research. Adolescents often report being uninterested in participating in tobacco use research, particularly cessation studies, once they are informed that their parents must provide their permission prior to enrollment (Backinger et al., 2003). Requiring written parental consent can result in a study sample with fewer minorities, fewer cigarette smokers, and fewer high-risk adolescents than other consent procedures (Anderman et al., 1995; Dent et al., 1993; Frissell et al., 2004). A reasonable alternative for minimal-risk studies involving adolescents is an implied consent procedure. In this case, an IRB waives the requirement of written parental permission. Parents are provided with information about the study and have the opportunity to decline their child s participation; if parents do not respond, their permission is implied. There is a growing consensus that waivers of parental permission can be appropriate under certain circumstances (Diviak et al., 2004; Ellickson and Hawes, 1989; Field and Berman, 2004; Peterson et al., 2000; Streissguth and Giunta, 1992). Rates of attrition in longitudinal studies of adolescent smoking behavior vary greatly. Peterson and colleagues (2000) had tremendous success retaining a sample from a smoking prevention project over a 12-year study period with follow-up rates at 94%. In general, tobacco use researchers have had more difficulty retaining ethnic minority than nonminority participants as well as adolescent participants with higher levels of cigarette smoking, drug use, alcohol consumption, and psychopathology (Morrison et al., 1997; Siddiqui et al., 1996). The current study reports individual-level predictors of recruitment and retention in a natural history study of adolescent smoking behavior over a 12-month period. In addition, we highlight lessons learned in our recruitment and retention efforts. Method Research Design All procedures were approved by the University of Illinois at Chicago IRB. Middle and high schools served as study recruitment sites and were selected on the basis of broad racial/ethnic and socioeconomic diversity, large student populations, and close proximity to our research office. Participating schools were willing to allow students to carry and respond to palmtop computers during school days, a crucial element of the longitudinal study. In 2000, entire classes of 8th and 10th grade students at 11 middle schools (N = 2464) and 7 high schools (N = 2834) in the Chicago suburban metropolitan area completed brief screening surveys about their smoking history, current cigarette use, and the smoking behaviors of family and friends. The screening typically occurred during physical or health education classes. Students were not paid for completing the survey. Staff administering the survey were recent college graduates of diverse race and ethnicity. We were granted a waiver of written parental permission for the screening portion of the study. Several weeks prior to screening we provided parents with information about the study and offered easy ways to contact research staff for questions or to decline their child s participation. Schools with large Hispanic enrollment received parental information forms in English and Spanish. Rates of refusal were extremely low: 1% of adolescents declined and 2% of parents requested that their child not complete the survey. After screening, students eligible for the longitudinal study were mailed invitation packets and called the research office if they were interested in participating. Written parental

3 Recruitment and Retention of Adolescents 177 permission was required prior to enrollment. Staff fluent in Spanish administered consents to Spanish-speaking parents. The longitudinal study included intensive, multimethod assessments accomplished via questionnaires, in-person interviews, and week-long time/event sampling [ecological momentary assessments (EMA)] using palmtop computers at 3 measurement waves over 12-months (Mermelstein et al., in press). Participants were paid at each wave: $50 at baseline and $60 at each follow-up. We used a rolling recruitment procedure where recruitment continued for several weeks after starting data collection within a school. This provided students who had not initially responded to the invitation the opportunity to talk with enrolled students about the study and generate interest in participating. Our retention efforts started with building rapport and making interactions with research staff enjoyable. Each participant received a birthday card signed by project staff and quarterly newsletters that focused on teen life. Cash incentives increased slightly over time to encourage continued participation. Follow-up visits were arranged by phone, reminder postcards mailed prior to the visit, and reminder calls made the night before scheduled visits. We carefully tracked address and phone numbers and also asked parents to provide contact information for someone outside the household who would know how to contact the parent if we could not. Data collection was not limited to participants schools to maintain the involvement of students who were suspended, expelled, or not consistently attending school. Research staff located multiple venues for meeting with students, including local libraries and teen centers. Participants who moved out of the area returned questionnaires by mail and completed interviews by phone but did not complete the EMAs. Participants Recruitment into the longitudinal study focused on adolescents in the early stages of smoking. Students were eligible to participate if they were categorized as susceptible nonsmokers, occasional smokers/experimenters, or regular smokers. Susceptible nonsmokers had never smoked but indicated high susceptibility to smoke based on intentions (Pierce et al., 1996). Experimenters had smoked less than 100 cigarettes in their lifetime and were occasionally smoking but not yet on a daily basis. Regular smokers had smoked within the past week and had smoked more than 100 cigarettes in their lifetime. Based on the screening survey 2153 students (40.6% of those screened) were categorized into these stages. A total of 1457 students (477 susceptible nonsmokers, 894 experimenters, and 86 regular smokers 1 were invited to participate. Table 1 contains a summary of participant characteristics for all students screened, invited, enrolled, and retained through the final follow-up assessment. Measures Demographics. Demographic information included gender, grade, and race/ethnicity. Smoking measures. The screening survey asked adolescents How many cigarettes have you smoked in your lifetime? and In the past 30 days, on how many days did you smoke or try cigarettes (even one puff)? Parental smoking was based on adolescents reports of whether various members of their family currently smoke cigarettes. 1 There were more susceptible nonsmokers than could be enrolled into the study. Equal numbers of susceptible males and females were randomly selected to receive invitations. The sample of regular smokers was designed to be smaller than the other categories and only recruited from 10th graders.

4 178 Diviak et al. Table 1 Participant characteristics by stage of recruitment and retention Retained Enrolled at 12-mo Screened Invited at baseline follow-up Variable (n = 5298) (n = 1457) (n = 562) (n = 507) Gender, % Female Male Grade, % 8th grade th grade Race, % White African American Latino Biracial/other Nicotine dependence. Measures of dependence in the longitudinal study included the modified Fagerstrom Tolerance Questionnaire (Prokhorov et al., 1998) (7-items, α = 0.77) and the Nicotine Dependence Symptom Scale (NDSS) adapted for adolescents (Nichter et al., 2002) (27-items, α =.91). Psychosocial measures. Psychosocial measures were collected at the baseline assessment of the longitudinal study. Symptoms of depression were measured with the Child Depression Inventory (Kovacs, 1985) (27-items, α = 0.87). Stress was measured with the Perceived Stress Scale (4-items, α = 0.72) (Cohen et al., 1983). Psychopathology symptoms were measured with the subscales of the Child Behavior Checklist (Achenbach and Edelbrock, 1983): anxious/depressed; social problems; thought problems; attention problems; delinquent behavior; aggressive behaviors; withdrawn; and somatic complaints. School truancy was measured by students yes or no response to the question do you skip school often? Grade point average was assessed with a single-item with response options from 1 ( A ) to 10 ( F ). Substance use was measured by asking whether adolescents used alcohol or other specified drugs of abuse (e.g., marijuana, methamphetamines, etc.) in the last 3 months. Outcome measures. Willingness to participate was categorized yes if the student and parent verbally agreed to participate and scheduled a baseline study visit and no if the student or parent called to decline (1.8%) or did not respond to the invitation packet (48.8%). Retention was measured by whether the adolescent participated in the final assessment. Results We performed a series of chi-square analyses to examine the relationship between predictor variables and students willingness to participate in the study. Of the 1442 students who

5 Recruitment and Retention of Adolescents 179 Table 2 Results of logistic regression predicting willingness to participate Variable Odds ratio 95% CI P-value Gender Female , 1.87 <0.001 Race Nonwhite , 0.89 <0.01 Grade 10th grade , 1.05 n.s. Smoking history (# days smoked out of last 30; referent none) 1 3 days , 1.30 n.s days , 1.80 n.s days , 2.04 n.s. Smoking history (# cigarettes in lifetime; referent none ) 1 5 cigarettes , 1.26 n.s cigarettes , 1.56 n.s. 100 or more , 1.86 n.s. Parent smoker Yes , 1.04 n.s. Willingness to participate coded at 0 = no, 1 = yes. Model χ 2 = 28.62, df = 10, p < received invitations, (49.4%) were willing to participate. Females were significantly more willing to participate than males (54.0% vs. 44.8%), χ 2 (1, N = 1422) = 12.13, p < White students (51.8%) were significantly more likely than nonwhite students (44.3%) to agree to participate, χ 2 (1, N = 1436) = 6.64, p < There were no differences in participation rates between 8th and 10th graders (50.6% vs. 48.4%), χ 2 (1, N = 1442) = 0.66, n.s. Adolescents with a parent who currently smoked were as likely to participate as their peers with a parent who did not currently smoke (47.8% vs. 50.5%), χ 2 (1, N = 1442) = 1.04, n.s. Neither measure of smoking experience was related to participation: number of days smoked in the last 30, χ 2 (3, N = 1435) = 2.33, n.s. nor lifetime number of cigarettes smoked, χ 2 (3, N = 1420) = 3.90, n.s. The multivariate relationships between the predictor variables and willingness to participate were examined by using logistic regression. The results were consistent with the univariate analyses previously reported. When controlling for the effect of the other predictor variables, only gender and race emerged as significant predictors of participation (Table 2). Of the 713 students who were willing to participate, 562 (78.8%) completed a baseline visit. The students who did not complete the visit were sick/absent and unable to reschedule (n = 25, 3.5%), failed to bring signed parental permission forms (n = 12, 1.7%), or were turned away by research staff 3 because enrollment at the school was complete (n = 114, 2 15 invitation packets were returned to us by the postal system; we were unable to obtain updated addresses for these students. 3 As a result of the EMA portion of the longitudinal study, we had an upper limit on the number of students who could be enrolled at a given school. The upper limit was the total number of palmtop computers available.

6 180 Diviak et al. 16.0%). At the 12-month follow-up, 507 adolescents (90.2%) participated in data collection. The most common reason for dropout was that carrying the palmtop computer and completing EMAs was too much of a hassle (n = 24, 4.3%). Other reasons for dropout included lost interest in participating (n = 13, 2.3%); unable to locate participant (n = 13, 2.3%); and other reasons (n = 5, 0.9%). We performed a series of chi-square or t-test analyses examining demographics, smoking experience, nicotine dependence, depression, perceived stress, psychopathology symptoms, alcohol and drug use, school truancy, and grade point average at baseline as potential predictors of retention at 12 months. All analyses were nonsignificant, indicating no differences between participants who did and did not complete the final visit. The multivariate relationships between the variables and retention were examined by using logistic regression and were consistent with the univariate analyses, χ 2 = 7.23, df = 20, n.s. Thus, attrition was likely the result of random factors. Discussion This demanding study protocol (in particular, the week-long time/event sampling) required significant time and energy from participants. Consistent with previous research, female and white students were more willing to participate than their male and nonwhite counterparts. Contrary to previous studies, response rates were not influenced by adolescents smoking experience. We had excellent retention of our teen participants (90%), and it is encouraging that demographic, smoking history, and psychosocial factors were not associated with attrition. We learned many lessons during the course of this study. First, as others have noted, we echo the importance of using an implied consent procedure with minimal-risk screening measures to assess prevalence, identify potential participants, and reduce research costs. Previous research suggests that most parents who do not return signed permission forms are not opposed to their child s involvement in the research but, rather, forget or are too busy to sign and return the forms in the required time frame (Ellickson and Hawes, 1989). Our results support this with the low number of parents who opted out of the screening (1%) and the fact that there were no complaints from parents of the 5298 students who completed the screening survey. We also learned that it is important to recruit both nonsmokers and smokers, even if the primary emphasis of the project is smoking behavior. To minimize losing smoking teens who were interested in participating but feared parental knowledge of their smoking behavior, we repeatedly stated to both teens and parents that both smoking and nonsmoking teens were being asked to participate in the study. The confidentiality of their smoking status was then maintained at home and at school, and involvement in the study did not mark students as a smoker. There are several study limitations. First, our follow-up period was relatively short (12- months). We also did not follow students past their high school years. Following students into young adulthood would be a challenge to retention efforts, but likely to yield useful information about the course of smoking behavior. Although we had a differential participation rate among males and nonwhites, we were unable to determine the reasons for this difference. The barriers to participation for nonwhites are likely diverse and may include a combination of cultural and socioeconomic factors. Focus groups with ethnic minority teens and their parents may help us learn more about their reasons for nonparticipation and identify ways to increase minority participation in research. Reasons for relatively lower participation by males are less well known and should be addressed in future research.

7 Recruitment and Retention of Adolescents 181 Given differential participation rates for males and nonwhites, tobacco use researchers working to establish a well-balanced sample might overselect potential participants in certain cells to ensure equal distribution of participants on key characteristics. Using a screening measure with an implied consent protocol is likely the most appropriate recruitment strategytoidentify a sample and keep study costs reasonable. Although some issues that affect recruitment are unavoidable, examining the influences on participation and attrition will ultimately improve the quality of our research and help us better understand the generalizability of our findings. Acknowledgments This research was supported by grant CA80266 from NCI and a grant from the Tobacco Etiology Research Network, funded by RWJF. Additional support for the first author was provided by NCI postdoctoral training grant CA References Achenbach, T. M., Edelbrock, C. (1983). Manual for the Child Behavior Checklist and Revised Child Behavior Profile. Burlington, VT University of Vermont Department of Psychiatry. Anderman, C., Cheadle, A., Curry, S., Diehr, P., Shultz, L., Wagner, E. (1995). Selection bias related to parental consent in school-based survey research. Evaluation Review 19: Backinger, C. L., McDonald, P., Ossip-Klein, D. J., Colby, S. M., Maule, C. O., Fagan, P., Husten, C., Colwell, B. (2003). Improving the future of youth smoking cessation. American Journal of Health Behavior 27(Suppl. 2):S170 S184. Bauman, K. E., Ennett, S. T., Foshee, V. A., Pemberton, M., Hicks, K. (2001). Correlates of participation in a family-directed tobacco and alcohol prevention program for adolescents. Health Education and Behavior 28: Cauce, A. M., Ryan, K. D., Grove K. (1998). Children and adolescents of color, where are you? Participation, selection, recruitment, and retention in developmental research. In: McLoyd, V. C., Steinberg, L., Eds., Studying Minority Adolescents: Conceptual, Methodological and Theoretical Issues Mahwah, NJ: Erlbaum, Cohen, S., Kamarck, T., Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior 24: Dent, C. W., Galaif, J., Sussman, S., Stacy, A., Burtun, D., Flay, B. R. (1993). Demographic, psychosocial, and behavioral differences in samples of actively and passively consented adolescents. Addictive Behaviors 18: Diviak, K. R., Curry, S. J., Emery, S. L., Mermelstein, R. J. (2004). Human subjects challenges in youth tobacco cessation research: Researchers perspectives. Ethics & Behavior 14: Ellickson, P. L., Hawes, J. A. (1989). An assessment of active versus passive methods for obtaining parental consent. Evaluation Review 13: Field, M. J., Behrman R. E., Eds. (2004). The Ethical Conduct of Clinical Research Involving Children. Washington, DC: The National Academy Press. Frissell, K. C., McCarthy, D. M., D Amico, E. J., Metrik, J., Ellingstad, T. P., Brown, S. A. (2004). Impact of consent procedures on reported levels of adolescent alcohol use. Psychology of Addictive Behaviors 18: Kovacs, M. (1985). The Children s Depression Inventory (CDI). Psychopharmacology Bulletin 21: Martinson, B. C., Lazovich, D., Lando, H. A., Perry, C. L., McGovern, P. G., Boyle, R. G. (2000). Effectiveness of monetary incentives for recruiting adolescents to an intervention trial to reduce smoking. Preventive Medicine 31:

8 182 Diviak et al. McCormick, L. K., Crawford, M., Anderson, R. H., Gittelsohn, J., Kingsley, B., Upson, D. (1999). Recruiting adolescents into qualitative tobacco research studies: experiences and lessons learned. Journal of School Health 69: Mermelstein, R., Hedeker, D., Flay, B., Shiffman, S. (in press). Real time data capture and adolescent cigarette smoking. In: Stone, A., Shiffman, S., Atienza, A., Eds., The Science of Real-Time Data Capture: Self-Report in Health Research. Cambridge: Oxford University Press. Morrison, T. C., Wahlgren, D. R., Hovell, M. F., Zakarian, J., Burkham-Kreitner, S., Hofstetter, C. R., Slymen, D. J., Keating, K., Russos, S., Jones, J. A. (1997). Tracking and follow-up of 16,915 adolescents: Minimizing attrition bias. Controlled Clinical Trials 18: Nichter, M., Nichter, M., Thompson, P. J., Shiffman, S., Moscicki, A. (2002). Using qualitative research to inform survey development on nicotine dependence among adolescents. Drug & Alcohol Dependence 68(Suppl. 1):S41 S56. Peterson, A. V., Mann, S. L., Kealey, K. A., Marek, P. M. (2000). Experiemental design and methods for school-based randomized trials: experience from the Hutchinson Smoking Prevention Project (HSPP). Controlled Clinical Trials 21: Pierce, J. P., Choi, W. S., Gilpin, E. A., Farkas, A. J., Merritt, R. K. (1996). Validation of susceptibility as a predictor of which adolescents take up smoking in the United States. Health Psychology 15: Prokhorov, A. V., Koehly, L. M., Pallonen, U. E., Hudmon, K. S. (1998). Adolescent nicotine dependence measured by the Modified Fagerstroem Tolerance Questionnaire at two time points. Journal of Child & Adolescent Substance Abuse 7: Siddiqui, O., Flay, B. R., Hu, F. B. (1996). Factors affecting attrition in a longitudinal smoking prevention study. Preventive Medicine 25: Streissguth, A. P., Giunta, C. T. (1992). Subject recruitment and retention for longitudinal research: practical considerations for a nonintervention model. NIDA Research Monographs 117: Swanson, G. M., Ward, A. J. (1995). Recruiting minorities into clinical trials: toward a participantfriendly system. Journal of the National Cancer Institute 87: U.S. Department of Health and Human Services. (1994). Preventing tobacco use among young people: a report of the surgeon general. Atlanta, GA: U.S. Department of Health and Human Services.

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