Comparison of early-, late-, and non-participants in a school-based asthma management program for urban high school students

Christine L M Joseph, Jacquelyn Saltzgaber, Suzanne L Havstad, Christine C Johnson, Dayna Johnson, Edward L Peterson, Gwen Alexander, Mick P Couper, Dennis R Ownby, Christine L M Joseph, Jacquelyn Saltzgaber, Suzanne L Havstad, Christine C Johnson, Dayna Johnson, Edward L Peterson, Gwen Alexander, Mick P Couper, Dennis R Ownby

Abstract

Background: To assess bias and generalizability of results in randomized controlled trials (RCT), investigators compare participants to non-participants or early- to late-participants. Comparisons can also inform the recruitment approach, especially when working with challenging populations, such as urban adolescents. In this paper, we describe characteristics by participant status of urban teens eligible to participate in a RCT of a school-based, web-based asthma management program.

Methods: The denominator for this analysis was all students found to be eligible to participate in the RCT. Data were analyzed for participants and non-participants of the RCT, as well as for students that enrolled during the initially scheduled recruitment period (early-participants) and persons that delayed enrollment until the following fall when recruitment was re-opened to increase sample size (late-participants). Full Time Equivalents (FTEs) of staff associated with recruitment were estimated.

Results: Of 1668 teens eligible for the RCT, 386 enrolled early, and 36 enrolled late, leaving 1246 non-participants. Participants were younger (p < 0.01), more likely to be diagnosed, use asthma medication, and have moderate-to-severe disease than non-participants, odds ratios (95% Confidence Intervals) = 2.1(1.7-2.8), 1.7(1.3-2.1), 1.4(1.0-1.8), respectively. ORs were elevated for the association of late-participation with Medicaid enrollment, 1.9(0.7-5.1) and extrinsic motivation to enroll, 1.7(0.6-5.0). Late-participation was inversely related to study compliance for teens and caregivers, ORs ranging from 0.1 to 0.3 (all p-values < 0.01). Early- and late-participants required 0.45 FTEs/100 and 3.3 FTEs/100, respectively.

Conclusions: Recruitment messages attracted youth with moderate-to-severe asthma, but extending enrollment was costly, resulting in potentially less motivated, and certainly less compliant, participants. Investigators must balance internal versus external validity in the decision to extend recruitment. Gains in sample size and external validity may be offset by the cost of additional staff time and the threat to internal validity caused by lower participant follow-up.

Trial registration: ClinicalTrials.gov: NCT00201058.

References

    1. Stang A. Nonresponse research--an underdeveloped field in epidemiology. European Journal of Epidemiology. 2003;18(10):929–31.
    1. Paganini-Hill A, Hsu G, Chao A, Ross RK. Comparison of early and late respondents to a postal health survey questionnaire. Epidemiology. 1993;4(4):375–9. doi: 10.1097/00001648-199307000-00014.
    1. Holle R, Hochadel M, Reitmeir P, Meisinger C, Wichmann HE. KORA Group. Prolonged recruitment efforts in health surveys: effects on response, costs, and potential bias. Epidemiology. 2006;17(6):639–43. doi: 10.1097/01.ede.0000239731.86975.7f.
    1. Harrington KF, Binkley D, Reynolds KD. et al.Recruitment issues in school-based research: lessons learned from the High 5 Alabama Project. J Sch Health. 1997;67(10):415–421. doi: 10.1111/j.1746-1561.1997.tb01287.x.
    1. McCormick LK, Crawford M, Anderson RH, Gittelsohn J, Kingsley B, Upson D. Recruiting adolescents into qualitative tobacco research studies: experiences and lessons learned. J Sch Health. 1999;69(3):95–99. doi: 10.1111/j.1746-1561.1999.tb07215.x.
    1. Herring P, Montgomery S, Yancey AK, Williams D, Fraser G. Understanding the challenges in recruiting blacks to a longitudinal cohort study: the Adventist health study. Ethn Dis. 2004;14(3):423–430.
    1. Durant LE, Carey MP. Self-administered questionnaires versus face-to-face interviews in assessing sexual behavior in young women. Arch Sex Behav. 2000;29(4):309–322. doi: 10.1023/A:1001930202526.
    1. Julion W, Gross D, Barclay-McLaughlin G. Recruiting families of color from the inner city: insights from the recruiters. Nurs Outlook. 2000;48(5):230–237. doi: 10.1067/mno.2000.102992.
    1. Kearney KA, Hopkins RH, Mauss AL, Weisheit RA. Sampling bias resulting from a requirement for written parental consent. Public Opinion Quarterly. 1983;47:96–102. doi: 10.1086/268769.
    1. Geluda K, Bisaglia JB, Moreira V, Maldonado BM, Cunha AJ, Trajman A. Third-party informed consent in research with adolescents: the good, the bad and the ugly. Social Science & Medicine. 2005;61(5):985–8. doi: 10.1016/j.socscimed.2004.11.061.
    1. Ross JG, Sundberg EC, Flint KH. Informed consent in school health research: why, how, and making it easy. Review. 14 refs] Journal of School Health. 1999;69(5):171–6, 1999. doi: 10.1111/j.1746-1561.1999.tb06378.x.
    1. Severson HH, Ary DV. Sampling bias due to consent procedures with adolescents. Addict Behav. 1983;8(4):433–437. doi: 10.1016/0306-4603(83)90046-1.
    1. Williams MM, Meisel MM, Williams J, Morris JC. An Interdisciplinary Outreach Model of African American Recruitment for Alzheimer's Disease Research. The Gerontologist.
    1. Cottler LB, Zipp JF, Robins LN, Spitznagel EL. Difficult-to-recruit respondents and their effect on prevalence estimates in an epidemiologic survey. American Journal of Epidemiology. 1987;125(2):329–39.
    1. Cottler LB, Comstock GW, Keating S. What incentives are effective rewards for 'Hidden Populations' interviewed as a part of research projects? Public Health Reports. 1995;110(2):178.
    1. Durant RW, Davis RB, St George DM, Williams IC, Blumenthal C, Corbie-Smith GM. Participation in research studies: factors associated with failing to meet minority recruitment goals. Ann Epidemiol. 2007;17(8):634–642. doi: 10.1016/j.annepidem.2007.02.003.
    1. Joseph CLM, Baptist AP, Stringer S. et al.Identifying students with self-report of asthma and respiratory symptoms in an urban, high school setting. J Urban Health. 2007;84(1):60–69. doi: 10.1007/s11524-006-9121-y.
    1. Joseph CLM, Peterson EL, Havstad SL. et al.A web-based, tailored asthma management program for urban African-American high school students. Am J Respir Crit Care Med. 2007;175(9):888–895. doi: 10.1164/rccm.200608-1244OC.
    1. Fleiss JL, Levin B, Paik M. Statistical methods for rates and proportions. Third. New York, New York: Wiley and Sons; 2003.
    1. Hosmer DW, Lemeshow S. Applied Logistic Regression. Second. New York, N.Y.: Wiley & Sons; 2000.
    1. McKenna H. Adolescents managed their asthma or diabetes in gendered ways with the aim of projecting different gendered identities. Evid Based Ment Health. 2000;3:125. doi: 10.1136/ebmh.3.4.125.
    1. Rhee H, Belyea MJ, Ciurzynski S, Brasch J. Barriers to asthma self-management in adolescents: Relationships to psychosocial factors. Pediatr Pulmonology. 2009;44:183–191. doi: 10.1002/ppul.20972.
    1. Woods VD, Montgomery SB, Herring RP. Recruiting Black/African American men for research on prostate cancer prevention. Cancer. 2004;100(5):1017–1025. doi: 10.1002/cncr.20029.
    1. Spoth R, Goldberg C, Redmond C. Engaging families in longitudinal preventive intervention research: discrete-time survival analysis of socioeconomic and social-emotional risk factors. Journal of Consulting & Clinical Psychology. 1999;67(1):157–63.
    1. Geraghty AWA, Wood AM, Hyland ME. Attrition from self-directed interventions: Investigating the relationship between psychological predictors, intervention content and dropout from a body dissatisfaction intervention. Social Science & Medicine. 2010;71:30–37. doi: 10.1016/j.socscimed.2010.03.007.
    1. Mattila V, Parkkari J, Rimpela A. Adolescent survey non-response and later risk of death. A prospective cohort study of 78 609 persons with 11-year follow-up. BMC Public Health. 2007;7:87. doi: 10.1186/1471-2458-7-87.
    1. Vinther-Larsen M, Riegels M, Rod MH, Schiøtz M, Curtis T, Grønbæk M. The Danish Youth Cohort: Characteristics of participants and non-participants and determinants of attrition. Scandinavian Journal of Public Health. 2010;38:648–656. doi: 10.1177/1403494810374222.
    1. Hille ETM, Elbertse L, Gravenhorst JB, Brand R, Verloove-Vanhorick SP. The Dutch POPS. Nonresponse Bias in a Follow-up Study of 19-Year-Old Adolescents Born as Preterm Infants. Pediatr. 2005;116:e662–e666. doi: 10.1542/peds.2005-0682.
    1. Ronmark EP, Ekerljung L, Lotvall J, Toren K, Ronmark E, Lundback B. Large scale questionnaire survey on respiratory health in Sweden: effects of late- and non-response. Respiratory Medicine. 2009;103(12):1807–15. doi: 10.1016/j.rmed.2009.07.014.
    1. Stang A, Jockel KH. Studies with low response proportions may be less biased than studies with high response proportions. American Journal of Epidemiology. 2004;159(2):204–10. doi: 10.1093/aje/kwh009.
    1. Expert Panel Report 3: Guidelines for the diagnosis and management of asthma. NIH publication no. 07-4051. 2007. Bethesda, MD: U.S. Department of Health and Human Services; National Institutes of Health; National Heart, Lung, and Blood Institute; National Asthma Education and Prevention Program; 2007.
    1. Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am Psychol. 2000;55(1):68–78.

Source: PubMed

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