Literature DB >> 2945736

Predicting risk among non-respondents in prospective studies.

K Sheikh.   

Abstract

Potential non-response bias was investigated in a follow-up study of 2,011 chronically disabled patients. 82.5% and 73.3% of the study subjects responded to self-administered mail questionnaires respectively at 6-month and 1-year follow-up. Information on employment status, the outcome of interest, of approximately 90% of the non-respondents was obtained from indirect sources. Employment rate was lower among the non-respondents than the respondents. Non-response was associated with age, social class, previous employment record, and the type of disability; but none of these characteristics were associated with the outcome. Out of the five known independent risk factors for unemployment, only one (incompletion of rehabilitation course) was associated with non-response. The employment rate among the respondents was also assessed according to the delay in response, that is the number of reminders sent to achieve response. The outcome among the late respondents was similar to that among the non-respondents. These data suggest that risk estimates may be biased even when the response rate is greater than 80%, the prevalence of risk factors among non-respondents may not indicate the presence or the degree of non-response bias, but reliable estimates can be obtained from extrapolations of the rates among the respondents according to the delay in response.

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Year:  1986        PMID: 2945736     DOI: 10.1007/bf00152716

Source DB:  PubMed          Journal:  Eur J Epidemiol        ISSN: 0393-2990            Impact factor:   8.082


  10 in total

1.  Response and follow-up bias in cohort studies.

Authors:  S Greenland
Journal:  Am J Epidemiol       Date:  1977-09       Impact factor: 4.897

2.  Response bias and risk ratios in epidemiologic studies.

Authors:  M H Criqui
Journal:  Am J Epidemiol       Date:  1979-04       Impact factor: 4.897

3.  Mail survey response by smoking status.

Authors:  C C Seltzer; R Bosse; A J Garvey
Journal:  Am J Epidemiol       Date:  1974-12       Impact factor: 4.897

4.  Importance of a high tracing-rate in long-term medical follow-up studies.

Authors:  A C Sims
Journal:  Lancet       Date:  1973-08-25       Impact factor: 79.321

5.  Employment rehabilitation: outcome and prediction.

Authors:  K Sheikh; S Mattingly
Journal:  Am J Ind Med       Date:  1984       Impact factor: 2.214

6.  Does the type of disabling impairment influence return to work?

Authors:  K Sheikh; S Mattingly
Journal:  Public Health       Date:  1982-07       Impact factor: 2.427

7.  Investigating non-response bias in mail surveys.

Authors:  K Sheikh; S Mattingly
Journal:  J Epidemiol Community Health       Date:  1981-12       Impact factor: 3.710

8.  Stress and smoking in hospital nurses.

Authors:  R Tagliacozzo; S Vaughn
Journal:  Am J Public Health       Date:  1982-05       Impact factor: 9.308

9.  Differences between respondents and non-respondents in a population-based cardiovascular disease study.

Authors:  M H Criqui; E Barrett-Connor; M Austin
Journal:  Am J Epidemiol       Date:  1978-11       Impact factor: 4.897

10.  Characteristics of respondents and non-respondents to a mailed questionnaire.

Authors:  J Barton; C Bain; C H Hennekens; B Rosner; C Belanger; A Roth; F E Speizer
Journal:  Am J Public Health       Date:  1980-08       Impact factor: 9.308

  10 in total
  5 in total

1.  Atherosclerotic risk factor reduction in peripheral arterial diseasea: results of a national physician survey.

Authors:  Mary McGrae McDermott; Elizabeth A Hahn; Philip Greenland; David Cella; Judith K Ockene; Donna Brogan; William H Pearce; Alan T Hirsch; Kendra Hanley; Linda Odom; Shaheen Khan; Michael H Criqui; Martin S Lipsky; Stacie Hudgens
Journal:  J Gen Intern Med       Date:  2002-12       Impact factor: 5.128

2.  Variation in estimates of limited health literacy by assessment instruments and non-response bias.

Authors:  Joan M Griffin; Melissa R Partin; Siamak Noorbaloochi; Joseph P Grill; Somnath Saha; Annamay Snyder; Sean Nugent; Alisha Baines Simon; Ian Gralnek; Dawn Provenzale; Michelle van Ryn
Journal:  J Gen Intern Med       Date:  2010-03-12       Impact factor: 5.128

3.  Strategies for successful retention of Alaska Native and American Indian study participants.

Authors:  Diana Redwood; Jessica Leston; Elvin Asay; Elizabeth Ferucci; Ruth Etzel; Anne P Lanier
Journal:  J Prim Prev       Date:  2011-02

4.  Issues of recruitment and maintaining high response rates in a longitudinal study of older hospital patients in England--pathways through care study.

Authors:  B A Gregson; M Smith; J Lecouturier; N Rousseau; H Rodgers; J Bond
Journal:  J Epidemiol Community Health       Date:  1997-10       Impact factor: 3.710

5.  Baseline characteristics are not sufficient indicators of non-response bias follow up studies.

Authors:  J Vestbo; F V Rasmussen
Journal:  J Epidemiol Community Health       Date:  1992-12       Impact factor: 3.710

  5 in total

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