Literature DB >> 23810078

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.

Ron de Graaf1, Saskia van Dorsselaer, Marlous Tuithof, Margreet ten Have.   

Abstract

BACKGROUND: In prospective psychiatric epidemiological studies, attrition at follow-up can be selective, and can bias the research findings. Therefore, knowledge of predictors of attrition and of its different types (noncontact, refusal, inability to participate) is of importance.
METHODS: By means of (multinomial) logistic regression analyses, predictors of attrition were studied in the first 3-year follow-up of the second Netherlands Mental Health Survey and Incidence Study (NEMESIS-2), a prospective psychiatric epidemiological study among 6646 subjects of the general population aged 18-64 years. Baseline sociodemographic characteristics, physical health, mental disorders and their clinical characteristics, and experience with the previous interview were studied as predictors of attrition and of its different types.
RESULTS: The attrition rate at follow-up was 20.2%. Refusal (14.2%) was more common than noncontact (4.6%) and inability to participate (1.4%). Compared to respondents, nonrespondents were more often younger, lower educated, unemployed and born outside the Netherlands. A less positive experience with the baseline interview and shorter interview duration also predicted attrition. Any 12-month mental disorder, the categories and separate mental disorders, and their clinical characteristics, were not significantly associated with attrition, after controlling for sociodemographics. Sociodemographic predictors and experience with the baseline interview differed between the three types of attrition, but these types were also hardly or not associated with previous mental disorders.
CONCLUSIONS: The authors conclude that bias due to selective attrition was limited to sociodemographics and experience with the baseline interview. Mental health status at baseline was not of influence, possibly due to the large time investment to persuade respondents to re-participate and to find them in case of noncontact or removal to an unknown address. During follow-up waves of future prospective studies it is important to implement an intensive recruitment period with special efforts among young adults and the lower educated.
Copyright © 2013 Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 23810078     DOI: 10.1016/j.comppsych.2013.05.012

Source DB:  PubMed          Journal:  Compr Psychiatry        ISSN: 0010-440X            Impact factor:   3.735


  32 in total

1.  Evidence That Environmental and Familial Risks for Psychosis Additively Impact a Multidimensional Subthreshold Psychosis Syndrome.

Authors:  Lotta-Katrin Pries; Sinan Guloksuz; Margreet Ten Have; Ron de Graaf; Saskia van Dorsselaer; Nicole Gunther; Christian Rauschenberg; Ulrich Reininghaus; Rajiv Radhakrishnan; Maarten Bak; Bart P F Rutten; Jim van Os
Journal:  Schizophr Bull       Date:  2018-06-06       Impact factor: 9.306

2.  'False-positive' self-reported psychotic experiences in the general population: an investigation of outcome, predictive factors and clinical relevance.

Authors:  Y van der Steen; I Myin-Germeys; M van Nierop; M Ten Have; R de Graaf; S van Dorsselaer; J van Os; R van Winkel
Journal:  Epidemiol Psychiatr Sci       Date:  2018-04-16       Impact factor: 6.892

3.  Nonresponse bias in survey estimates of alcohol consumption and its association with harm.

Authors:  Deborah A Dawson; Risë B Goldstein; Roger P Pickering; Bridget F Grant
Journal:  J Stud Alcohol Drugs       Date:  2014-07       Impact factor: 2.582

4.  Predictors of attrition among rural breast cancer survivors.

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Journal:  Res Nurs Health       Date:  2013-12-11       Impact factor: 2.228

5.  Understanding the Disability Dynamics of Youth: Health Condition and Limitation Changes for Youth and Their Influence on Longitudinal Survey Attrition.

Authors:  David R Mann; Todd Honeycutt
Journal:  Demography       Date:  2016-06

6.  The association between type and number of adverse working conditions and mental health during a time of economic crisis (2010-2012).

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Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2015-01-18       Impact factor: 4.328

7.  Age- and sex-specific associations between risk scores for schizophrenia and self-reported health in the general population.

Authors:  Jai L Shah; Sinan Guloksuz; Vincent Paquin; Lotta-Katrin Pries; Margreet Ten Have; Maarten Bak; Nicole Gunther; Ron de Graaf; Saskia van Dorsselaer; Bochao D Lin; Kristel R van Eijk; Gunter Kenis; Alexander Richards; Michael C O'Donovan; Jurjen J Luykx; Bart P F Rutten; Jim van Os
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2022-08-01       Impact factor: 4.519

8.  Association of preceding psychosis risk states and non-psychotic mental disorders with incidence of clinical psychosis in the general population: a prospective study in the NEMESIS-2 cohort.

Authors:  Sinan Guloksuz; Lotta-Katrin Pries; Margreet Ten Have; Ron de Graaf; Saskia van Dorsselaer; Boris Klingenberg; Maarten Bak; Bochao D Lin; Kristel R van Eijk; Philippe Delespaul; Therese van Amelsvoort; Jurjen J Luykx; Bart P F Rutten; Jim van Os
Journal:  World Psychiatry       Date:  2020-06       Impact factor: 49.548

9.  Mental disorders and the risk of adult violent and psychological victimisation: a prospective, population-based study.

Authors:  C Christ; M Ten Have; R de Graaf; D J F van Schaik; M J Kikkert; J J M Dekker; A T F Beekman
Journal:  Epidemiol Psychiatr Sci       Date:  2019-01-17       Impact factor: 6.892

10.  Uncovering survivorship bias in longitudinal mental health surveys during the COVID-19 pandemic.

Authors:  Mark É Czeisler; Joshua F Wiley; Charles A Czeisler; Shantha M W Rajaratnam; Mark E Howard
Journal:  Epidemiol Psychiatr Sci       Date:  2021-05-26       Impact factor: 6.892

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