Who does not participate in a follow-up postal study? a survey of infertile couples treated by in vitro fertilization

BMC Medical Research Methodology - Tập 12 - Trang 1-8 - 2012
Penelope Troude1,2,3, Estelle Bailly1, Juliette Guibert4, Jean Bouyer1,2,5, Elise de La Rochebrochard1,2,5
1INED, Paris, France
2INSERM, Center for Research in Epidemiology and Population Health, CESP U1018, Le Kremlin-Bicêtre, France
3Univ Paris Diderot, Sorbonne Paris Cité, Service de Santé Publique et Economie de la Santé, Paris, France
4Laboratoire de Procréation Médicalement Assistée, Institut Mutualiste de Montsouris, Paris, France
5Univ Paris-Sud, UMRS 1018, Le Kremlin-Bicêtre, France

Tóm tắt

A good response rate has been considered as a proof of a study’s quality. Decreasing participation and its potential impact on the internal validity of the study are of growing interest. Our objective was to assess factors associated with contact and response to a postal survey in a epidemiological study of the long-term outcome of IVF couples. The DAIFI study is a retrospective cohort including 6,507 couples who began an IVF program in 2000-2002 in one of the eight participating French IVF centers. Medical data on all 6,507 couples were obtained from IVF center databases, and information on long-term outcome was available only for participants in the postal survey (n = 2,321). Logistic regressions were used to assess firstly factors associated with contact and secondly factors associated with response to the postal questionnaire among contacted couples. Sixty-two percent of the 6,507 couples were contacted and 58% of these responded to the postal questionnaire. Contacted couples were more likely to have had a child during IVF treatment than non-contactable couples, and the same was true of respondents compared with non-respondents. Demographic and medical characteristics were both associated with probability of contact and probability of response. After adjustment, having a live birth during IVF treatment remained associated with both probabilities, and more strongly with probability of response. Having a child during IVF treatment was a major factor impacting on participation rate. Non-response as well as non-contact were linked to the outcome of interest, i.e. long-term parenthood success of infertile couples. Our study illustrates that an a priori hypothesis may be too simplistic and may underestimate potential bias. In the context of growing use of analytical methods that take attrition into account (such as multiple imputation), we need to better understand the mechanisms that underlie attrition in order to choose the most appropriate method.

Tài liệu tham khảo

Galea S, Tracy M: Participation rates in epidemiologic studies. Ann Epidemiol. 2007, 17: 643-653. 10.1016/j.annepidem.2007.03.013. Altman DG: Statistics in medical journals: some recent trends. Stat Med. 2000, 19: 3275-3289. 10.1002/1097-0258(20001215)19:23<3275::AID-SIM626>3.0.CO;2-M. Schneider KL, Clark MA, Rakowski W, Lapane KL: Evaluating the impact of non-response bias in the Behavioral Risk Factor Surveillance System (BRFSS). J Epidemiol Community Health. 2012, 66: 290-295. 10.1136/jech.2009.103861. Epub 2010 Oct 19 Brilleman SL, Pachana NA, Dobson AJ: The impact of attrition on the representativeness of cohort studies of older people. BMC Med Res Methodol. 2010, 10: 71-10.1186/1471-2288-10-71. Littman AJ, Boyko EJ, Jacobson IG, Horton J, Gackstetter GD, Smith B, Hooper T, Wells TS, Amoroso PJ, Smith TC: Assessing nonresponse bias at follow-up in a large prospective cohort of relatively young and mobile military service members. BMC Med Res Methodol. 2010, 10: 99-10.1186/1471-2288-10-99. Kristman V, Manno M, Cote P: Loss to follow-up in cohort studies: how much is too much?. Eur J Epidemiol. 2004, 19: 751-760. Fewtrell MS, Kennedy K, Singhal A, Martin RM, Ness A, Hadders-Algra M, Koletzko B, Lucas A: How much loss to follow-up is acceptable in long-term randomised trials and prospective studies?. Arch Dis Child. 2008, 93: 458-461. 10.1136/adc.2007.127316. Young AF, Powers JR, Bell SL: Attrition in longitudinal studies: who do you lose?. Aust N Z J Public Health. 2006, 30: 353-361. 10.1111/j.1467-842X.2006.tb00849.x. Morton LM, Cahill J, Hartge P: Reporting participation in epidemiologic studies: a survey of practice. Am J Epidemiol. 2006, 163: 197-203. Razafindratsima N, Kishimba N, COCON Group: Attrition in the COCON cohort between 2000 and 2002. Popul (English). 2004, 59: 357-385. Plewis I, Ketende S: Millennium Cohort Study: Technical Report on Response. 2006, London: Centre for Longitudinal Studies, Institute of Education Ketende S: Millennium Cohort Study: Technical Report on Response. 2008, London: Centre for Longitudinal Studies, Institute of Education, 2 Nohr EA, Frydenberg M, Henriksen TB, Olsen J: Does low participation in cohort studies induce bias?. Epidemiology. 2006, 17: 413-418. 10.1097/01.ede.0000220549.14177.60. Jacobsen TN, Nohr EA, Frydenberg M: Selection by socioeconomic factors into the Danish National Birth Cohort. Eur J Epidemiol. 2010, 25: 349-355. 10.1007/s10654-010-9448-2. Banks E, Redman S, Jorm L, Armstrong B, Bauman A, Beard J, Beral V, Byles J, Corbett S, Cumming R, et al: Cohort profile: the 45 and up study. Int J Epidemiol. 2008, 37: 941-947. Mealing NM, Banks E, Jorm LR, Steel DG, Clements MS, Rogers KD: Investigation of relative risk estimates from studies of the same population with contrasting response rates and designs. BMC Med Res Methodol. 2010, 10: 26-10.1186/1471-2288-10-26. Lee C, Dobson AJ, Brown WJ, Bryson L, Byles J, Warner-Smith P, Young AF: Cohort Profile: the Australian Longitudinal Study on Women’s Health. Int J Epidemiol. 2005, 34: 987-991. 10.1093/ije/dyi098. Goldberg M, Chastang JF, Leclerc A, Zins M, Bonenfant S, Bugel I, Kaniewski N, Schmaus A, Niedhammer I, Piciotti M, et al: Socioeconomic, demographic, occupational, and health factors associated with participation in a long-term epidemiologic survey: a prospective study of the French GAZEL cohort and its target population. Am J Epidemiol. 2001, 154: 373-384. 10.1093/aje/154.4.373. Goldberg M, Chastang JF, Zins M, Niedhammer I, Leclerc A: Health problems were the strongest predictors of attrition during follow-up of the GAZEL cohort. J Clin Epidemiol. 2006, 59: 1213-1221. 10.1016/j.jclinepi.2006.02.020. Olivius C, Friden B, Borg G, Bergh C: Why do couples discontinue in vitro fertilization treatment? a cohort study. Fertil Steril. 2004, 81: 258-261. 10.1016/j.fertnstert.2003.06.029. Schmidt L: Psychosocial burden of infertility and assisted reproduction. Lancet. 2006, 367 (9508): 379-380. 10.1016/S0140-6736(06)68117-8. Filetto JN, Makuch MY: Long-term follow-up of women and men after unsuccessful IVF. Reprod Biomed Online. 2005, 11: 458-463. 10.1016/S1472-6483(10)61141-8. Hammarberg K, Astbury J, Baker H: Women’s experience of IVF: a follow-up study. Hum Reprod. 2001, 16: 374-383. 10.1093/humrep/16.2.374. Tate AR, Jones M, Hull L, Fear NT, Rona R, Wessely S, Hotopf M: How many mailouts? Could attempts to increase the response rate in the Iraq war cohort study be counterproductive?. BMC Med Res Methodol. 2007, 7: 51-10.1186/1471-2288-7-51. Ludwig AK, Katalinic A, Jendrysik J, Thyen U, Sutcliffe AG, Diedrich K, Ludwig M: Spontaneous pregnancy after successful ICSI treatment: evaluation of risk factors in 899 families in Germany. Reprod Biomed Online. 2008, 17: 403-409. 10.1016/S1472-6483(10)60225-8. Cahill DJ, Meadowcroft J, Akande VA, Corrigan E: Likelihood of natural conception following treatment by IVF. J Assist Reprod Genet. 2005, 22: 401-405. 10.1007/s10815-005-6655-y. de Graaf R, Bijl RV, Smit F, Ravelli A, Vollebergh WA: Psychiatric and sociodemographic predictors of attrition in a longitudinal study: The Netherlands Mental Health Survey and Incidence Study (NEMESIS). Am J Epidemiol. 2000, 152: 1039-1047. 10.1093/aje/152.11.1039. Lee C, Dobson A, Brown W, Adamson L, Goldsworthy J: Tracking participants: lessons from the Women’s Health Australia Project. Aust N Z J Public Health. 2000, 24: 334-336. 10.1111/j.1467-842X.2000.tb01580.x. Ware RS, Williams GM, Aird RL: Participants who left a multiple-wave cohort study had similar baseline characteristics to participants who returned. Ann Epidemiol. 2006, 16: 820-823. 10.1016/j.annepidem.2006.01.008. Pinborg A, Hougaard CO, Nyboe Andersen A, Molbo D, Schmidt L: Prospective longitudinal cohort study on cumulative 5-year delivery and adoption rates among 1338 couples initiating infertility treatment. Hum Reprod. 2009, 24: 991-999. Rajkhowa M, McConnell A, Thomas GE: Reasons for discontinuation of IVF treatment: a questionnaire study. Hum Reprod. 2006, 21: 358-363. Fanarjian N, Drostin C, Garrett J, Montalvo A: Does the provision of free intrauterine contraception reduce pregnancy rates among uninsured low-income women? A cohort study: a two North Carolina clinics. Contraception. 2012, 85: 160-165. 10.1016/j.contraception.2011.06.002. Epub 2011 Jul 14 Templeton A, Morris JK, Parslow W: Factors that affect outcome of in-vitro fertilisation treatment. Lancet. 1996, 348 (9039): 1402-1406. 10.1016/S0140-6736(96)05291-9. Soullier N, Bouyer J, Pouly JL, Guibert J, de La Rochebrochard E: Effect of the woman’s age on discontinuation of IVF treatment. Reprod Biomed Online. 2011, 22: 496-500. 10.1016/j.rbmo.2011.01.013. MacDonald SE, Newburn-Cook CV, Schopflocher D, Richter S: Addressing nonresponse bias in postal surveys. Public Health Nurs. 2009, 26: 95-105. 10.1111/j.1525-1446.2008.00758.x. Graham JW: Missing data analysis: making it work in the real world. Annu Rev Psychol. 2009, 60: 549-576. 10.1146/annurev.psych.58.110405.085530. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2288/12/104/prepub