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BMC Medical Research Methodology
Published in: BMC Medical Research Methodology 1/2018

Open Access 01-12-2018 | Research article

Retention strategies in longitudinal cohort studies: a systematic review and meta-analysis

Authors: Samantha Teague, George J. Youssef, Jacqui A. Macdonald, Emma Sciberras, Adrian Shatte, Matthew Fuller-Tyszkiewicz, Chris Greenwood, Jennifer McIntosh, Craig A. Olsson, Delyse Hutchinson, the SEED Lifecourse Sciences Theme

Published in: BMC Medical Research Methodology | Issue 1/2018

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Abstract

Background

Participant retention strategies that minimise attrition in longitudinal cohort studies have evolved considerably in recent years. This study aimed to assess, via systematic review and meta-analysis, the effectiveness of both traditional strategies and contemporary innovations for retention adopted by longitudinal cohort studies in the past decade.

Methods

Health research databases were searched for retention strategies used within longitudinal cohort studies published in the 10-years prior, with 143 eligible longitudinal cohort studies identified (141 articles; sample size range: 30 to 61,895). Details on retention strategies and rates, research designs, and participant demographics were extracted. Meta-analyses of retained proportions were performed to examine the association between cohort retention rate and individual and thematically grouped retention strategies.

Results

Results identified 95 retention strategies, broadly classed as either: barrier-reduction, community-building, follow-up/reminder, or tracing strategies. Forty-four of these strategies had not been identified in previous reviews. Meta-regressions indicated that studies using barrier-reduction strategies retained 10% more of their sample (95%CI [0.13 to 1.08]; p = .01); however, studies using follow-up/reminder strategies lost an additional 10% of their sample (95%CI [− 1.19 to − 0.21]; p = .02). The overall number of strategies employed was not associated with retention.

Conclusions

Employing a larger number of retention strategies may not be associated with improved retention in longitudinal cohort studies, contrary to earlier narrative reviews. Results suggest that strategies that aim to reduce participant burden (e.g., flexibility in data collection methods) might be most effective in maximising cohort retention.
Appendix
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Literature
1.
Rothman KJ, Greenland S. Cohort studies. In: Rothman KJ, Greenland S, Lash TL, editors. Modern epidemiology. Philadelphia: Lippincott Williams & Wilkins; 2008.
2.
Rothman KJ, Greenland S, Lash TL. Modern epidemiology. 3rd ed. Philadelphia: Lippincott Williams & Wilkins; 2008.
3.
Gustavson K, von Soest T, Karevold E, Røysamb E. Attrition and generalizability in longitudinal studies: findings from a 15-year population-based study and a Monte Carlo simulation study. BMC Public Health. 2012;12:918.PubMedPubMedCentralCrossRef
4.
Davis L, Broome ME, Cox RP. Maximizing retention in community-based clinical trials. J Nurs Scholarsh. 2002;1:47–53.CrossRef
5.
6.
Booker CL, Harding S, Benzeval M. A systematic review of the effect of retention methods in population-based cohort studies. BMC Public Health. 2011;11:249.PubMedPubMedCentralCrossRef
7.
Anderson CL, Agarwal R, Anderson CL. The digitization of healthcare: boundary risks, emotion, and consumer willingness to disclose personal health information. Inf Syst Res. 2011;22:469–90.CrossRef
8.
Ward S, Bridges K, Chitty B. Do incentives matter? An examination of on-line privacy concerns and willingness to provide personal and financial information. J Mark Commun. 2005;11:21–40.CrossRef
9.
Sepah SC, Jiang L, Peters AL. Long-term outcomes of a web-based diabetes prevention program: 2-year results of a single-arm longitudinal study. J Med Internet Res. 2015;17:e92.PubMedPubMedCentralCrossRef
10.
Dobkin BH, Dorsch A. The promise of mHealth: daily activity monitoring and outcome assessments by wearable sensors. Neurorehabil Neural Repair. 2011;25:788–98.PubMedPubMedCentralCrossRef
11.
Fuller-Tyszkiewicz M, Skouteris H, Richardson B, Blore J, Holmes M, Mills J. Does the burden of the experience sampling method undermine data quality in state body image research? Body Image. 2013;10:607–13.PubMedCrossRef
12.
Rostosky SS, Riggle EDB, Rothblum ED, Balsam KF. Same-sex couples’ decisions and experiences of marriage in the context of minority stress: interviews from a population-based longitudinal study. J Homosex. 2016;63:1019–40.PubMedCrossRef
13.
Loxton D, Powers J, Anderson AE, Townsend N, Harris ML, Tuckerman R, et al. Online and offline recruitment of young women for a longitudinal health survey: findings from the australian longitudinal study on women’s health 1989-95 cohort. J Med Internet Res. 2015;17:1–14.CrossRef
14.
Mychasiuk R, Benzies K. Facebook: an effective tool for participant retention in longitudinal research. Child Care Health Dev. 2012;38:753–6.PubMedCrossRef
15.
Man MS, Tilbrook HE, Jayakody S, Hewitt CE, Cox H, Cross B, et al. Electronic reminders did not improve postal questionnaire response rates or response times: a randomized controlled trial. J Clin Epidemiol. 2011;64:1001–4.PubMedCrossRef
16.
Brueton VC, Tierney JF, Stenning S, Meredith S, Harding S, Nazareth I, et al. Strategies to improve retention in randomised trials: a Cochrane systematic review and meta-analysis. BMJ Open. 2014;4:e003821.PubMedPubMedCentralCrossRef
17.
Robinson KA, Dennison CR, Wayman DM, Pronovost PJ, Needham DM. Systematic review identifies number of strategies important for retaining study participants. J Clin Epidemiol. 2007;60:757–65.PubMedPubMedCentralCrossRef
18.
Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta analyses: the PRISMA statement. Ann Intern Med. 2009;151:264–9.PubMedCrossRef
19.
Viechtbauer W. Conducting Meta-analyses in R with the metafor package. J Stat Softw. 2010;36:1–48.CrossRef
20.
R Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2015.
21.
Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ Br Med J. 2003;327:557–60.CrossRef
22.
United Nations Development Programme (UNDP). Human development report. New York: United Nations Development Programme; 2016.
23.
Victora CG, Huttly SR, Fuchs SC, Olinto MT. The role of conceptual frameworks in epidemiological analysis: a hierarchical approach. Int J Epidemiol. 1997;26:224–7.PubMedCrossRef
24.
Hosmer J, Lemeshow S, Sturdivant R. Model-building strategies and methods for logistic regression. In: Applied logistic regression. 3rd ed. Hoboken: Wiley; 2013. p. 89–151.CrossRef
25.
Pattanasin S, Wimonsate W, Chonwattana W, Tongtoyai J, Chaikummao S, Sriporn A, et al. Loss to follow-up and bias assessment among a cohort of Thai men who have sex with men in Bangkok. Thailand Int J STD AIDS. 2016;27:196–206.PubMedCrossRef
26.
van Lieshout M, Luman M, Twisk JWR, van Ewijk H, Groenman AP, Thissen AJAM, et al. A 6-year follow-up of a large European cohort of children with attention-deficit/hyperactivity disorder-combined subtype: outcomes in late adolescence and young adulthood. Eur Child Adolesc Psychiatry. 2016;25:1007–17.PubMedPubMedCentralCrossRef
27.
Von Hippel PT. The heterogeneity statistic I2 can be biased in small meta-analyses. BMC Med Res Methodol. 2015;15:1–8.CrossRef
28.
Enders CK. Applied missing data analysis. New York: Guilford Press; 2010.
29.
Graham JW. Missing data analysis: making it work in the real world. Annu Rev Psychol. 2009;60:549–76.PubMedCrossRef
30.
Vehovar V. Field substitution and unit nonresponse. J Off Stat. 1999;15:335–50.
31.
David MC, Bensink M, Higashi H, Donald M, Alati R, Ware RS. Monte Carlo simulation of the cost-effectiveness of sample size maintenance programs revealed the need to consider substitution sampling. J Clin Epidemiol. 2012;65:1200–11.PubMedCrossRef
32.
Cepeda A, Valdez A. Ethnographic strategies in the tracking and retention of street-recruited community-based samples of substance using hidden populations in longitudinal studies. Subst Use Misuse. 2010;45:700–16.PubMedPubMedCentralCrossRef
33.
Rosenberg AR, Bona K, Wharton CM, Bradford M, Shaffer ML, Wolfe J, et al. Adolescent and young adult patient engagement and participation in survey-based research: a report from the “resilience in adolescents and young adults with cancer” study. Pediatr Blood Cancer. 2016;63:734–6.PubMedCrossRef
34.
Lankenau SE, Sanders B, Hathazi D, Bloom JJ. Recruiting and retaining mobile young injection drug users in a longitudinal study. Subst Use Misuse. 2010;45:684–99.PubMedPubMedCentralCrossRef
35.
36.
Crawford JA, Hargrave TM, Hunt A, Liu CC, Anbar RD, Hall GE, et al. Issues in design and implementation in an urban birth cohort study: the Syracuse AUDIT project. J Urban Heal. 2006;83:741–59.CrossRef
37.
Hughes JR, Naud S, Budney AJ, Fingar JR, Callas PW. Attempts to stop or reduce daily cannabis use: an intensive natural history study. Psychol Addict Behav. 2016;30:389–97.PubMedPubMedCentralCrossRef
38.
Langley JD, Lilley R, Wilson S, Derrett S, Samaranayaka A, Davie G, et al. Factors associated with non-participation in one or two follow-up phases in a cohort study of injured adults. Inj Prev. 2013;19:428–33.PubMedCrossRef
39.
Gabbe BJ, Cameron PA, Hannaford AP, Sutherland AM, McNeil JJ. Routine follow up of major trauma patients from trauma registries: what are the outcomes? J Trauma. 2006;61:1393–9.PubMedCrossRef
40.
Dorn JM, Genco RJ, Grossi SG, Falkner KL, Hovey KM, Iacoviello L, et al. Periodontal disease and recurrent cardiovascular events in survivors of myocardial infarction (MI): the Western New York acute MI study. J Periodontol. 2010;81:502–11.PubMedCrossRef
41.
Pescud M, Pettigrew S, Wood L, Henley N. Insights and recommendations for recruitment and retention of low socio-economic parents with overweight children. Int J Soc Res Methodol. 2015;18:617–33.CrossRef
42.
Loue S, Sajatovic M. Research with severely mentally ill Latinas: successful recruitment and retention strategies. J Immigr Minor Health. 2008;10:145–53.PubMedCrossRef
43.
Wu C, Thompson ME, Fong GT, Jiang Y, Yang Y, Feng G, et al. Methods of the International Tobacco Control (ITC) China survey: waves 1, 2 and 3. Tob Control. 2015;24:iv1–5.PubMedCrossRef
44.
Højmark K, Støttrup C, Carreon L, Andersen MO. Patient-reported outcome measures unbiased by loss of follow-up. Single-center study based on DaneSpine, the Danish spine surgery registry. Eur Spine J. 2016;25:282–6.PubMedCrossRef
45.
Tansey CM, Matté AL, Needham D, Herridge MS. Review of retention strategies in longitudinal studies and application to follow-up of ICU survivors. Intensive Care Med. 2007;33:2051–7.PubMedCrossRef
46.
Donald M, Dower J, Ware R, Mukandi B, Parekh S, Bain C. Living with diabetes: rationale, study design and baseline characteristics for an Australian prospective cohort study. BMC Public Health. 2012;12:8.PubMedPubMedCentralCrossRef
47.
McSweeney JC, Pettey CM, Fischer EP, Spellman A. Going the distance. Res Gerontol Nurs. 2009;2:256–64.PubMedCrossRef
48.
Dubé K, Zango A, Van De Wijgert J, Meque I, Ferro JJ, Cumbe F, et al. HIV incidence in a cohort of women at higher risk in Beira, Mozambique: prospective study 2009-2012. PLoS One. 2014;9:1–6.CrossRef
49.
Heppner PP, Armer JM, Mallinckrodt B. Problem-solving style and adaptation in breast cancer survivors: a prospective analysis. J Cancer Surviv. 2009;3:128–36.PubMedPubMedCentralCrossRef
50.
Friedman R, Bastos F, Leite I, Veloso V, Moreira R, Cardoso S, et al. Pregnancy rates and predictors in women with HIV/AIDS in Rio de Janeiro, Southeastern Brazil. Rev Saude Publica. 2011;45:373–81.PubMedCrossRef
51.
Albus M, Hubmann W, Mohr F, Hecht S, Hinterberger-Weber P, Seitz NN, et al. Neurocognitive functioning in patients with first-episode schizophrenia: results of a prospective 5-year follow-up study. Eur Arch Psychiatry Clin Neurosci. 2006;256:442–51.PubMedCrossRef
52.
Kiwanuka N, Mpendo J, Nalutaaya A, Wambuzi M, Nanvubya A, Kitandwe PK, et al. An assessment of fishing communities around Lake Victoria, Uganda, as potential populations for future HIV vaccine efficacy studies: an observational cohort study. BMC Public Health. 2014;14:986.PubMedPubMedCentralCrossRef
53.
Thege BK, Woodin EM, Hodgins DC, Williams RJ. Natural course of behavioral addictions: a 5-year longitudinal study. BMC Psychiatry. 2015;15:4.CrossRef
54.
Sinclair JMA, Hawton K, Gray A. Six year follow-up of a clinical sample of self-harm patients. J Affect Disord. 2010;121:247–52.PubMedCrossRef
55.
Smith JA, Wilde MH, Brasch J. Internet recruitment and retention for a 6 months’ longitudinal study. J Nurs Scholarsh. 2012;44:165–70.PubMedCrossRef
56.
Pendlebury ST, Chen PJ, Bull L, Silver L, Mehta Z, Rothwell PM. Methodological factors in determining rates of dementia in transient ischemic attack and stroke: (i) impact of baseline selection bias. Stroke. 2015;46:641–6.PubMedPubMedCentralCrossRef
57.
Coley N, Gardette V, Toulza O, Gillette-Guyonnet S, Cantet C, Nourhashemi F, et al. Predictive factors of attrition in a cohort of Alzheimer disease patients: the REAL.FR study. Neuroepidemiology. 2008;31:69–79.PubMedCrossRef
58.
Shatenstein B, Kergoat M-J, Reid I. Issues in recruitment, retention, and data collection in a longitudinal nutrition study of community-dwelling older adults with early-stage Alzheimer’s dementia. J Appl Gerontol. 2008;27:267–85.CrossRef
59.
Ellis KA, Szoeke C, Bush AI, Darby D, Graham PL, Lautenschlager NT, et al. Rates of diagnostic transition and cognitive change at 18-month follow-up among 1,112 participants in the Australian imaging, biomarkers and lifestyle flagship study of ageing (AIBL). Int Psychogeriatr. 2014;26:543–54.PubMedCrossRef
60.
Newberry A, Sherwood P, Hricik A, Bradley S, Kuo J, Crago E, et al. Understanding recruitment and retention in neurological research. J Neurosci Nurs. 2010;42:47–57.PubMedPubMedCentralCrossRef
61.
62.
Novljan MP, Rotar Z, Ambrozic A, Vidmar G, Tomsic M. Comparison of the performance of the different classification criteria for primary Sjogren’s syndrome: a prospective cohort study. Clin Rheumatol. 2014;33:1657–64.CrossRef
63.
Torgalsbøen AK, Mohn C, Czajkowski N, Rund BR. Relationship between neurocognition and functional recovery in first-episode schizophrenia: results from the second year of the Oslo multi-follow-up study. Psychiatry Res. 2015;227:185–91.PubMedCrossRef
64.
Jourdan C, Bayen E, Bahrami S, Ghout I, Darnoux E, Azerad S, et al. Loss to follow-up and social background in an inception cohort of patients with severe traumatic brain injury. J Head Trauma Rehabil. 2016;31:E42–8.PubMedCrossRef
65.
Bair E, Brownstein NC, Ohrbach R, Greenspan JD, Dubner R, Fillingim RB, et al. Study protocol, sample characteristics, and loss to follow-up: the OPPERA prospective cohort study. J Pain. 2013;14:T2–19.PubMedCrossRef
66.
Langley J, Johnson S, Slatyer M, Skilbeck CE, Thomas M. Issues of loss to follow-up in a population study of traumatic brain injury (TBI) followed to 3 years post-trauma. Brain Inj. 2010;24:939–47.PubMedCrossRef
67.
Rapoport MJ, Kiss A, Feinstein A. The impact of major depression on outcome following mild-to-moderate traumatic brain injury in older adults. J Affect Disord. 2006;92:273–6.PubMedCrossRef
68.
Gabbe BJ, Cleland H, Watterson DM, Schrale R, McRae S, Parker C, et al. Long term outcomes data for the burns registry of Australia and New Zealand: is it feasible? Burns. 2015;41:1732–40.PubMedCrossRef
69.
Fenix JB, Cherlin EJ, Prigerson HG, Johnson-Hurzeler R, Kasl SV, Bradley EH. Religiousness and major depression among bereaved family caregivers: a 13-month follow-up study. J Palliat Care. 2006;22:286–92.PubMed
70.
Bennett KS, Hay DA, Piek J, Pearsall-Jones J, Levy F, Martin N. The Australian twin ADHD project: current status and future directions. Twin Res Hum Genet. 2006;9:718–26.PubMedCrossRef
71.
Meinck F, Cluver LD, Boyes ME. Household illness, poverty and physical and emotional child abuse victimisation: findings from South Africa’s first prospective cohort study. BMC Public Health. 2015;15:444.PubMedPubMedCentralCrossRef
72.
Guey LT, Bromet EJ, Gluzman SF, Zakhozha V, Paniotto V. Determinants of participation in a longitudinal two-stage study of the health consequences of the Chornobyl nuclear power plant accident. BMC Med Res Methodol. 2008;8:27.PubMedPubMedCentralCrossRef
73.
Graziotti AL, Hammond J, Messinger DS, Bann CM, Miller-Loncar C, Twomey JE, et al. Maintaining participation and momentum in longitudinal research involving high-risk families. J Nurs Scholarsh. 2012;44:120–6.PubMedPubMedCentralCrossRef
74.
Williams P, Chernoff M, Angelidou K, Brouwers P, Kacanek D, Deygoo N, et al. Participation and retention of youth with perinatal HIV infection in mental health research studies. J Acquir Immune Defic Syndr. 2013;63:401–9.PubMedPubMedCentralCrossRef
75.
Betancourt TS, Brennan RT, Rubin-Smith JE, Fritzmaurice GM, Gilman SE. Sierra Leone’s former child soldiers: a longitudinal study of risk, protective factors, and mental health. J Am Acad Child Adolesc Psychiatry. 2011;49:606–15.
76.
Hinshaw SP, Owens EB, Zalecki C, Huggins SP, Montenegro-Nevado AJ, Schrodek E, et al. Prospective follow-up of girls with attention-deficit/hyperactivity disorder into early adulthood: continuing impairment includes elevated risk for suicide attempts and self-injury. J Consult Clin Psychol. 2012;80:1041–51.PubMedPubMedCentralCrossRef
77.
Boykin DM, London MJ, Orcutt HK. Examining minority attrition among women in longitudinal trauma research. J Trauma Stress. 2016;29:26–32.PubMedCrossRef
78.
Johnson SB, Lynch KF, Baxter J, Lernmark B, Roth R, Simell T, et al. Predicting later study withdrawal in participants active in a longitudinal birth cohort study for 1 year: the TEDDY study. J Pediatr Psychol. 2016;41:373–83.PubMedCrossRef
79.
Baral S, Kizub D, Masenior NF, Peryskina A, Stachowiak J, Stibich M, et al. Male sex workers in Moscow, Russia: a pilot study of demographics, substance use patterns, and prevalence of HIV-1 and sexually transmitted infections. AIDS Care. 2010;22:112–8.PubMedPubMedCentralCrossRef
80.
Khosropour CM, Sullivan PS. Predictors of retention in an online follow-up study of men who have sex with men. J Med Internet Res. 2011;13:1–14.CrossRef
81.
Khosropour CM, Johnson BA, Ricca AV, Sullivan PS. Enhancing retention of an internet-based cohort study of men who have sex with men (MSM) via text messaging: randomized controlled trial. J Med Internet Res. 2013;15:1–11.CrossRef
82.
Liu G, Lu H, Wang J, Xia D, Sun Y, Mi G, et al. Incidence of HIV and syphilis among men who have sex with men (MSM) in Beijing: an open cohort study. PLoS One. 2015;10:1–13.
83.
Mao H, Ma W, Lu H, Wang L, Zheng H, Zhu Y, et al. High incidence of HIV and syphilis among migrant men who have sex with men in Beijing, China: a prospective cohort study. BMJ Open. 2014;4:e005351.PubMedPubMedCentralCrossRef
84.
Peng Z, Yang H, Norris J, Chen X, Huan X, Yu R, et al. HIV incidence and predictors associated with retention in a cohort of men who have sex with men in Yangzhou, Jiangsu Province. China PLoS One. 2012;7:4–9.
85.
Segura M, Estani SS, Marone R, Bautista CT, Pando MA, Eyzaguirre L, et al. Buenos Aires cohort of men who have sex with men: prevalence, incidence, risk factors, and molecular genotyping of HIV type 1. AIDS Res Hum Retrovir. 2007;23:1322–9.PubMedCrossRef
86.
Abaasa A, Asiki G, Mpendo J, Levin J, Seeley J, Nielsen L, et al. Factors associated with dropout in a long term observational cohort of fishing communities around Lake Victoria. Uganda BMC Res Notes. 2015;8:815.PubMedCrossRef
87.
Seed M, Juarez M, Alnatour R. Improving recruitment and retention rates in preventive longitudinal research with adolescent mother. J Child Adolesc Psychiatr Nurs. 2009;22:150–3.PubMedCrossRef
88.
Vinther-Larsen M, Riegels M, Rod MH, Schiotz M, Curtis T, Gronbaek M. The Danish youth cohort: characteristics of participants and non-participants and determinants of attrition. Scand J Public Health. 2010;38:648–56.PubMedCrossRef
89.
90.
Orpinas P, Lacy B, Nahapetyan L, Dube SR, Song X. Cigarette smoking trajectories from sixth to twelfth grade: associated substance use and high school dropout. Nicotine Tob Res. 2016;18:156–62.PubMedCrossRef
91.
Hemphill SA, Heerde JA, Scholes-Balog KE, Herrenkohl TI, Toumbourou JW, Catalano RF. Effects of early adolescent alcohol use on mid-adolescent school performance and connection: a longitudinal study of students in Victoria, Australia and Washington state, United States. J Sch Health. 2014;84:706–15.PubMedPubMedCentralCrossRef
92.
Oldehinkel AJ, Rosmalen JGM, Buitelaar JK, Hoek HW, Ormel J, Raven D, et al. Cohort profile update: the tracking adolescents’ individual lives survey (TRAILS). Int J Epidemiol. 2015;44:76.PubMedCrossRef
93.
Oman RF, Vesely SK, Aspy CB, Fluhr J, Marshall L, Calhoun G, et al. Methodological considerations in a community-based longitudinal study. Am J Health Behav. 2009;33:58–68.PubMedCrossRef
94.
Pluddemann A, Flisher AJ, McKetin R, Parry CD, Lombard CJ. A prospective study of methamphetamine use as a predictor of high school non-attendance in Cape Town, South Africa. Subst Abuse Treat Prev Policy. 2010;5:1–7.CrossRef
95.
Van Lissa CJ, Hawk ST, Branje S, Koot HM, Meeus WHJ. Common and unique associations of adolescents’ affective and cognitive empathy development with conflict behavior towards parents. J Adolesc. 2016;47:60–70.PubMedCrossRef
96.
Hamdi NR, Iacono WG. Lifetime prevalence and co-morbidity of externalizing disorders and depression in prospective assessment. Psychol Med. 2014;44:315–24.PubMedCrossRef
97.
Holt CL, Le D, Calvanelli J, Huang J, Eddie M, Roth DL, et al. Participant retention in a longitudinal national telephone survey of African American men and women. Ethn Dis. 2015;25:187–92.PubMed
98.
Baird DD, Harmon QE, Upson K, Moore KR, Barker-Cummings C, Baker S, et al. A prospective, ultrasound-based study to evaluate risk factors for uterine fibroid incidence and growth: methods and results of recruitment. J Women’s Heal. 2015;24:907–15.CrossRef
99.
Redwood D, Leston J, Asay E, Ferucci E, Etzel R, Lanier AP. Strategies for successful retention of Alaska native and American Indian study participants. J Prim Prev. 2011;32:43–52.PubMedCrossRef
100.
101.
Martin SA, Haren MT, Middleton SM, Wittert GA. The Florey Adelaide male ageing study (FAMAS): design, procedures & participants. BMC Public Health. 2007;7:126.PubMedPubMedCentralCrossRef
102.
Anders KL, Nguyen NM, Van Thuy NT, Hieu NT, Nguyen HL, Hong Tham NT, et al. A birth cohort study of viral infections in Vietnamese infants and children: study design, methods and characteristics of the cohort. BMC Public Health. 2013;13:937.PubMedPubMedCentralCrossRef
103.
Panter-Brick C, Goodman A, Tol W, Eggerman M. Mental health and childhood adversities: a longitudinal study in Kabul, Afghanistan. J Am Acad Child Adolesc Psychiatry. 2011;50:349–63.PubMedPubMedCentralCrossRef
104.
Hush JM, Michaleff Z, Maher CG, Refshauge K. Individual, physical and psychological risk factors for neck pain in Australian office workers: a 1-year longitudinal study. Eur Spine J. 2009;18:1532–40.PubMedPubMedCentralCrossRef
105.
West R, Gilsenan A, Coste F, Zhou X, Brouard R, Nonnemaker J, et al. The ATTEMPT cohort: a multi-national longitudinal study of predictors, patterns and consequences of smoking cessation; introduction and evaluation of internet recruitment and data collection methods. Addiction. 2006;101:1352–61.PubMedCrossRef
106.
Göritz AS, Wolff H-G, Goldstein DG. Individual payments as a longer-term incentive in online panels. Behav Res Methods. 2008;40:1144–9.PubMedCrossRef
107.
Eaton WW, Kalaydjian A, Scharfstein DO, Mezuk B, Ding Y. Prevalence and incidence of depressive disorder: the Baltimore ECA follow-up, 1981-2004. Acta Psychiatr Scand. 2007;116:182–8.PubMedPubMedCentralCrossRef
108.
Ejiogu N, Norbeck JH, Mason MA, Cromwell BC, Zonderman AB, Evans MK. Recruitment and retention strategies for minority or poor clinical research participants: lessons from the healthy aging in neighborhoods of diversity across the life span study. Gerontologist. 2011;51 SI:S33–45.CrossRef
109.
Bambs CE, Kip KE, Mulukutla SR, Aiyer AN, Johnson C, McDowell LA, et al. Sociodemographic, clinical, and psychological factors associated with attrition in a prospective study of cardiovascular prevention: the heart strategies concentrating on risk evaluation (heart SCORE) study. Ann Epidemiol. 2013;23:328–33.PubMedPubMedCentralCrossRef
110.
Siukosaari P, Ajwani S, Ainamo A, Wolf J, Närhi T. Periodontal health status in the elderly with different levels of education: a 5-year follow-up study. Gerodontology. 2012;29:170–8.CrossRef
111.
Peat G, Thomas E, Handy J, Wood L, Dziedzic K, Myers H, et al. The knee clinical assessment study – CAS(K). a prospective study of knee pain and knee osteoarthritis in the general population: baseline recruitment and retention at 18 months. BMC Musculoskelet Disord. 2006;7:30.PubMedPubMedCentralCrossRef
112.
Khoo SK, O’Neill S, Travers C, Oldenburg B. Age-related changes relevant to health in women: design, recruitment, and retention strategies for the longitudinal assessment of women (LAW) study. J Womens Health (Larchmt). 2008;17:135–46.CrossRef
113.
Radler BT, Ryff CD. Who participates? Accounting for longitudinal retention in the MIDUS national study of health and well-being. J Aging Health. 2010;22:307–31.PubMedPubMedCentralCrossRef
114.
Stafford M, Black S, Shah I, Hardy R, Pierce M, Richards M, et al. Using a birth cohort to study ageing: representativeness and response rates in the National Survey of health and development. Eur J Ageing. 2013;10:145–57.PubMedPubMedCentralCrossRef
115.
De Graaf R, Van Dorsselaer S, Tuithof M, Ten Have M. Sociodemographic and psychiatric predictors of attrition in a prospective psychiatric epidemiological study among the general population. Result of the Netherlands mental health survey and incidence Study-2. Compr Psychiatry. 2013;54:1131–9.PubMedCrossRef
116.
Lamers F, Hoogendoorn AW, Smit JH, Van Dyck R, Zitman FG, Nolen WA, et al. Sociodemographic and psychiatric determinants of attrition in the Netherlands study of depression and anxiety (NESDA). Compr Psychiatry. 2012;53:63–70.PubMedCrossRef
117.
Satherley N, Milojev P, Greaves LM, Huang Y, Osborne D, Bulbulia J, et al. Demographic and psychological predictors of panel attrition: evidence from the New Zealand attitudes and values study. PLoS One. 2015;10:1–22.CrossRef
118.
Méjean C, Szabo De Edelenyi F, Touvier M, Kesse-Guyot E, Julia C, Andreeva VA, et al. Motives for participating in a web-based nutrition cohort according to sociodemographic, lifestyle, and health characteristics: the nutrinet-santé cohort study. J Med Internet Res. 2014;16:e189.PubMedPubMedCentralCrossRef
119.
Xie G, Laskowitz DT, Turner EL, Egger JR, Shi P, Ren F, et al. Baseline health-related quality of life and 10-year all-cause mortality among 1739 Chinese adults. PLoS One. 2014;9:1–9.
120.
Leonard CA, Williams RJ. The relationship between gambling fallacies and problem gambling. Psychol Addict Behav. 2016;30:694–704.PubMedCrossRef
121.
Haring R, Alte D, Völzke H, Sauer S, Wallaschofski H, John U, et al. Extended recruitment efforts minimize attrition but not necessarily bias. J Clin Epidemiol. 2009;62:252–60.PubMedCrossRef
122.
Wu XM, Bennett DH, Ritz B, Tancredi DJ, Hertz-Picciotto I. Temporal variation of residential pesticide use and comparison of two survey platforms: a longitudinal study among households with young children in Northern California. Environ Health. 2013;12:65.PubMedCrossRef
123.
Dishman RK, Vandenberg RJ, Motl RW, Nigg CR. Using constructs of the transtheoretical model to predict classes of change in regular physical activity: a multi-ethnic longitudinal cohort study. Ann Behav Med. 2010;40:150–63.PubMedCrossRef
124.
Barnett W, Brittain K, Sorsdahl K, Zar HJ, Stein DJ. Maternal participant experience in a South African birth cohort study enrolling healthy pregnant women and their infants. Philos Ethics Humanit Med. 2016;11:3.PubMedPubMedCentralCrossRef
125.
Loubet P, Guerrisi C, Turbelin C, Blondel B, Launay O, Bardou M, et al. First nationwide web-based surveillance system for influenza-like illness in pregnant women: participation and representativeness of the French G-GrippeNet cohort. BMC Public Health. 2016;16:253.PubMedPubMedCentralCrossRef
126.
Martini J, Wittich J, Petzoldt J, Winkel S, Einsle F, Siegert J, et al. Maternal anxiety disorders prior to conception, psychopathology during pregnancy and early infants’ development: a prospective-longitudinal study. Arch Womens Ment Health. 2013;16:549–60.PubMedCrossRef
127.
Saiepour N, Ware R, Najman J, Baker P, Clavarino A, Williams G. Do participants with different patterns of loss to follow-up have different characteristics? A multi-wave longitudinal study. J Epidemiol. 2016;26:45–9.PubMedPubMedCentralCrossRef
128.
Daniels JL, Savitz DA, Bradley C, Dole N, Evenson KR, Eucker B, et al. Attitudes toward participation in a pregnancy and child cohort study. Paediatr Perinat Epidemiol. 2006;20:260–6.PubMedCrossRef
129.
Althuizen E, van Poppel MN, de Vries JH, Seidell JC, van Mechelen W. Postpartum behaviour as predictor of weight change from before pregnancy to one year postpartum. BMC Public Health. 2011;11:165.PubMedPubMedCentralCrossRef
130.
Milgrom J, Gemmill AW, Bilszta JL, Hayes B, Barnett B, Brooks J, et al. Antenatal risk factors for postnatal depression: a large prospective study. J Affect Disord. 2008;108:147–57.PubMedCrossRef
131.
Saadeh FB, Clark MA, Rogers ML, Linkletter CD, Phipps MG, Padbury JF, et al. Pregnant and moving: understanding residential mobility during pregnancy and in the first year of life using a prospective birth cohort. Matern Child Health J. 2013;17:330–43.PubMedCrossRef
132.
Baird DD, Saldana TM, Shore DL, Hill MC, Schectman JM. A single baseline ultrasound assessment of fibroid presence and size is strongly predictive of future uterine procedure: 8-year follow-up of randomly sampled premenopausal women aged 35-49 years. Hum Reprod. 2015;30:2936–44.PubMedPubMedCentral
133.
Kandula NR, Puri-Taneja A, Victorson DE, Dave SS, Kanaya AM, Huffman MD. Mediators of atherosclerosis in south Asians living in America: use of web-based methods for follow-up and collection of patient-reported outcome measures. JMIR Res Protoc. 2016;5:e95.PubMedPubMedCentralCrossRef
134.
Elbogen EB, Johnson SC, Newton VM, Timko C, Vasterling JJ, Van Male LM, et al. Protective mechanisms and prevention of violence and aggression in veterans. Psychol Serv. 2014;11:220–8.PubMedPubMedCentralCrossRef
135.
Powers J, Tavener M, Graves A, Loxton D. Loss to follow-up was used to estimate bias in a longitudinal study: a new approach. J Clin Epidemiol. 2015;68:870–6.PubMedCrossRef
136.
Young AF, Powers JR, Bell SL. Attrition in longitudinal studies: who do you lose? Aust N Z J Public Health. 2006;30:353–61.PubMedCrossRef
137.
Decker KM. Retention of screened women in program. Can J Public Heal. 2008;99:216–20.
138.
Boucher S, Gray A, Leong SL, Sharples H, Horwath C. Token monetary incentives improve mail survey response rates and participant retention: results from a large randomised prospective study of mid-age New Zealand women. N Z Med J. 2015;128:1175–8716.
139.
Ekman A, Klint Å, Dickman PW, Adami HO, Litton JE. Optimizing the design of web-based questionnaires - experience from a population-based study among 50,000 women. Eur J Epidemiol. 2007;22:293–300.PubMedCrossRef
140.
Zielinski R, Ackerson K, Misiunas RB, Miller JM. Feasibility of a longitudinal study of women anticipating first pregnancy and assessed by multiple pelvic exams: recruitment and retention challenges. Contemp Clin Trials. 2010;31:544–8.PubMedPubMedCentralCrossRef
141.
Farrall S, Hunter B, Sharpe G, Calverley A. What ‘works’ when retracing sample members in a qualitative longitudinal study? Int J Soc Res Methodol. 2016;19:287–300.CrossRef
142.
Lawrance M, Sayers SM, Singh GR. Challenges and strategies for cohort retention and data collection in an indigenous population: Australian aboriginal birth cohort. BMC Med Res Methodol. 2014;14:31.PubMedPubMedCentralCrossRef
143.
Richter LM, Panday S, Norris SA. Factors influencing enrolment: a case study from birth to twenty, the 1990 birth cohort in Soweto-Johannesburg. Eval Program Plann. 2009;32:197–203.PubMedPubMedCentralCrossRef
144.
Greene N, Greenland S, Olsen J, Nohr EA. Estimating bias from loss to follow-up in the Danish National Birth Cohort. Epidemiology. 2011;22:815–22.PubMed
145.
Nunes MA, Ferri CP, Manzolli P, Soares RM, Drehmer M, Buss C, et al. Nutrition, mental health and violence: from pregnancy to postpartum cohort of women attending primary care units in southern Brazil - ECCAGE study. BMC Psychiatry. 2010;10:66.PubMedPubMedCentralCrossRef
146.
Ng SK, Scott R, Scuffham PA. Contactable non-responders show different characteristics compared to lost to follow-up participants: insights from an Australian longitudinal birth cohort study. Matern Child Health J. 2016;20:1472–84.PubMedCrossRef
147.
148.
Morton SMB, Grant CC, Carr PEA, Robinson EM, Kinloch JM, Fleming CJ, et al. How do you recruit and retain a prebirth cohort? Lessons learnt from growing up in New Zealand. Eval Health Prof. 2014;37:411–33.PubMedCrossRef
149.
Yamakawa N, Koike H, Ohtani N, Bonno M, Tanaka S, Ido M, et al. Mission in Sukusuku cohort, Mie: focusing on the feasibility and validity of methods for enrolling and retaining participants. J Epidemiol. 2010;20(Suppl 2):S407–12.PubMedPubMedCentralCrossRef
150.
Firestone R, Cheng S, Pearce N, Douwes J, Merletti F, Pizzi C, et al. Internet-based birth-cohort studies: is this the future for epidemiology? JMIR Res Protoc. 2015;4:e71.PubMedPubMedCentralCrossRef
151.
Dubé E, Bettinger JA, Halperin B, Bradet R, Lavoie F, Sauvageau C, et al. Determinants of parents’ decision to vaccinate their children against rotavirus: results of a longitudinal study. Health Educ Res. 2012;27:1069–80.PubMedCrossRef
152.
Launes J, Hokkanen L, Laasonen M, Tuulio-Henriksson A, Virta M, Lipsanen J, et al. Attrition in a 30-year follow-up of a perinatal birth risk cohort: factors change with age. PeerJ. 2014;2:e480.PubMedPubMedCentralCrossRef
153.
Gartrell N, Bos H. US national longitudinal lesbian family study: psychological adjustment of 17-year-old adolescents. Pediatrics. 2010;126:28–36.PubMedCrossRef
154.
Brannon EE, Kuhl ES, Boles RE, Aylward BS, Benoit Ratcliff M, Valenzuela JM, et al. Strategies for recruitment and retention of families from low-income, ethnic minority backgrounds in a longitudinal study of caregiver feeding and child weight. Child Heal Care. 2013;42:198–213.CrossRef
155.
Baker LA, Tuvblad C, Wang P, Gomez K, Bezdjian S, Niv S, et al. The Southern California twin register at the University of Southern California: III. Twin Res Hum Genet. 2013;16:336–43.PubMedPubMedCentralCrossRef
156.
Winding TN, Andersen JH, Labriola M, Nohr EA. Initial non-participation and loss to follow-up in a Danish youth cohort: implications for relative risk estimates. J Epidemiol Community Health. 2014;68:137–44.PubMedCrossRef
157.
Trang NHHD, Hong TK, Dibley MJ. Cohort profile: Ho Chi Minh City youth cohort--changes in diet, physical activity, sedentary behaviour and relationship with overweight/obesity in adolescents. BMJ Open. 2012;2:e000362.PubMedPubMedCentralCrossRef
158.
Strycker LA, Duncan SC, Duncan TE, He H, Desai N. Retention of African-American and white youth in a longitudinal substance use study. J Ethn Subst Abus. 2006;5:119–31.CrossRef
159.
Whitbeck LB, Sittner Hartshorn KJ, Crawford DM, Walls ML, Gentzler KC, Hoyt DR. Mental and substance use disorders from early adolescence to young adulthood among indigenous young people: final diagnostic results from an 8-year panel study. Soc Psychiatry Psychiatr Epidemiol. 2014;49:961–73.PubMedPubMedCentralCrossRef
160.
Neiswanger K, McNeil DW, Foxman B, Govil M, Cooper ME, Weyant RJ, et al. Oral health in a sample of pregnant women from northern Appalachia (2011–2015). Int J Dent. 2015;2015:1–12.CrossRef
161.
Strotmeyer ES, Arnold AM, Boudreau RM, Ives DG, Cushman M, Robbins JA, et al. Long-term retention of older adults in the cardiovascular health study: implications for studies of the oldest old. J Am Geriatr Soc. 2010;58:696–701.PubMedPubMedCentralCrossRef
162.
Gu D. General Data Quality Assessment of the CLHLS. In: Zeng Y, Poston Jr DL, Ashbaugh Vlosky D, Gu D, editors. Healthy Longevity in China: Demographic, Socioeconomic, and Psychological Dimensions. Dordrecht: Springer Science+Business Media B.V.; 2008. p. 39–60.
163.
Stevens NL, Van Tilburg TG. Cohort differences in having and retaining friends in personal networks in later life. J Soc Pers Relat. 2011;28:24–43.CrossRef
164.
165.
Davies K, Kingston A, Robinson L, Hughes J, Hunt JM, Barker SAH, et al. Improving retention of very old participants in longitudinal research: experiences from the Newcastle 85+ study. PLoS One. 2014;9:1–10.
166.
Carlson BW, Carlson JR, Neelon VJ, Hartman M. Tailoring protocols to successfully recruit and retain older adults in a longitudinal study of sleep and cognition. Res Gerontol Nurs. 2008;1:232–7.PubMedPubMedCentralCrossRef
167.
Allman RM, Sawyer P, Crowther M, Strothers HS, Turner T, Fouad MN. Predictors of 4-year retention among African American and white community-dwelling participants in the UAB study of aging. Gerontologist. 2011;51:S46–58.PubMedPubMedCentralCrossRef
168.
Gerhart JI, Hall BJ, Russ EU, Canetti D, Hobfoll SE. Sleep disturbances predict later trauma-related distress: cross-panel investigation amidst violent turmoil. Health Psychol. 2014;33:365–72.PubMedCrossRef
169.
Tay A, Rees S, Steel Z, Tam N, Soares Z, Soares C, et al. Six-year trajectories of post-traumatic stress and severe psychological distress symptoms and associations with timing of trauma exposure, ongoing adversity and sense of injustice: a latent transition analysis of a community cohort in conflict-affected Ti. BMJ Open. 2016;6:e010205.PubMedPubMedCentralCrossRef
170.
Walker J, Fairley CK, Urban E, Chen MY, Bradshaw C, Walker SM, et al. Maximising retention in a longitudinal study of genital chlamydia trachomatis among young women in Australia. BMC Public Health. 2011;11:156.PubMedPubMedCentralCrossRef
Metadata
Title
Retention strategies in longitudinal cohort studies: a systematic review and meta-analysis
Authors
Samantha Teague
George J. Youssef
Jacqui A. Macdonald
Emma Sciberras
Adrian Shatte
Matthew Fuller-Tyszkiewicz
Chris Greenwood
Jennifer McIntosh
Craig A. Olsson
Delyse Hutchinson
the SEED Lifecourse Sciences Theme
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Medical Research Methodology / Issue 1/2018
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/s12874-018-0586-7

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