Literature DB >> 3812439

Difficult-to-recruit respondents and their effect on prevalence estimates in an epidemiologic survey.

L B Cottler, J F Zipp, L N Robins, E L Spitznagel.   

Abstract

Generous contact efforts were used to recruit 3,004 respondents into the first wave of the St. Louis Epidemiologic Catchment Area (ECA) project, a psychiatric epidemiologic study of the general population, conducted from 1981-1982. These efforts were analyzed to establish which sociodemographic characteristics or current psychiatric disorders were determinants of difficulty in recruitment. Being young, male, black, a nonrural resident, educated, and full-time employed were the demographic characteristics associated with increased contact efforts. Persons currently meeting criteria for an alcohol disorder required almost 20% more contact attempts than those without the disorder; this difficulty lay both in their being less available for an initial contact and refusing at a higher rate once contacted. An optimal recruitment effort cutoff point is provided, and a method is suggested for detecting that optimal point in the course of ongoing studies.

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Year:  1987        PMID: 3812439     DOI: 10.1093/oxfordjournals.aje.a114534

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  36 in total

1.  Agency-based tracking of difficult-to-follow populations: runaway and homeless youth programs in St. Louis, Missouri.

Authors:  D E Pollio; S J Thompson; C S North
Journal:  Community Ment Health J       Date:  2000-06

2.  Non-response and related factors in a nation-wide health survey.

Authors:  K Korkeila; S Suominen; J Ahvenainen; A Ojanlatva; P Rautava; H Helenius; M Koskenvuo
Journal:  Eur J Epidemiol       Date:  2001       Impact factor: 8.082

3.  Assessing non-response to a mailed health survey including self-collection of biological material.

Authors:  Anneli Uusküla; Mart Kals; Louise-Anne McNutt
Journal:  Eur J Public Health       Date:  2010-05-10       Impact factor: 3.367

4.  A replicable model for achieving over 90% follow-up rates in longitudinal studies of substance abusers.

Authors:  Christy K Scott
Journal:  Drug Alcohol Depend       Date:  2004-04-09       Impact factor: 4.492

5.  Effect on trend estimates of the difference between survey respondents and non-respondents: results from 27 populations in the WHO MONICA Project.

Authors:  Hanna Tolonen; Annette Dobson; Sangita Kulathinal
Journal:  Eur J Epidemiol       Date:  2005       Impact factor: 8.082

6.  An epidemiologic investigation of potential risk factors for suicide attempts.

Authors:  K R Petronis; J F Samuels; E K Moscicki; J C Anthony
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  1990-07       Impact factor: 4.328

7.  Substance use among nurses: differences between specialties.

Authors:  A M Trinkoff; C L Storr
Journal:  Am J Public Health       Date:  1998-04       Impact factor: 9.308

8.  Lifestyle surveys--the complete answer?

Authors:  R Dengler; H Roberts; L Rushton
Journal:  J Epidemiol Community Health       Date:  1997-02       Impact factor: 3.710

9.  Health and demographic characteristics of respondents in an Australian national sexuality survey: comparison with population norms.

Authors:  D M Purdie; M P Dunne; F M Boyle; M D Cook; J M Najman
Journal:  J Epidemiol Community Health       Date:  2002-10       Impact factor: 3.710

10.  Factors influencing help seeking in mentally distressed young adults: a cross-sectional survey.

Authors:  Lucy Biddle; David Gunnell; Debbie Sharp; Jenny L Donovan
Journal:  Br J Gen Pract       Date:  2004-04       Impact factor: 5.386

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