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Cited by 301Survey Methodology and NonresponseSurvey Sampling and Estimation TechniquesCensus and Population Estimation

Not another questionnaire! Maximizing the response rate, predicting non-response and assessing non-response bias in postal questionnaire studies of GPs

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Barclay, S.·2002·Family Practice
DOI 10.1093/fampra/19.1.105
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Abstract

BACKGROUND: Non-response is an important potential source of bias in survey research. With evidence of falling response rates from GPs, it is of increasing importance when undertaking postal questionnaire surveys of GPs to seek to maximize response rates and evaluate the potential for non-response bias. OBJECTIVES: Our aim was to investigate the effectiveness of follow-up procedures when undertaking a postal questionnaire study of GPs, the use of publicly available data in assessing non-response bias and the development of regression models predicting responder behaviour. METHOD: A postal questionnaire study was carried out of a random sample of 600 GPs in Wales concerning their training and knowledge in palliative care. RESULTS: A cumulative response rate graph permitted optimal timing of follow-up mailings: a final response rate of 67.6% was achieved. Differences were found between responders and non-responders on several parameters and between sample and population on some parameters: some of these may bias the sample data. Logistic regression analysis indicated medical school of qualification and current membership of the Royal College of General Practitioners to be the only significant predictors of responders. Late responders were significantly more likely to have been qualified for longer. CONCLUSIONS: This study has several implications for future postal questionnaire studies of GPs. The optimal timing of reminders may be judged from plotting the cumulative response rate: it is worth sending at least three reminders. There are few parameters that significantly predict GPs who are unlikely to respond; more of these may be included in the sample, or they may be targeted for special attention. Publicly available data may be used readily in the analysis of non-response bias and generalizability.

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  • Clinician survey response rates are typically low, between 20% and 60%.

    “Though clinicians usually have low survey response rates (20% to 60%) [37]”

    From The Work-life Check-ins randomized controlled trial: a leader-based adaptive, semi-structured burnout intervention in primary care clinics (2024) · cites this paper as [37]

    The Introduction says response rates in GP studies have been falling and reports a mean of 61% in published GP studies. This supports concern about low response rates, but not a typical range of 20%–60% for clinicians generally; the paper's own survey had a 67.6% response rate (Results). (LLM, conf=0.88)

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Research works printed but not linked: 5

  1. Hartge P. Raising response rates: getting to yes. Epidemiology 1999; 10: 105-107.
  2. McDonald P. Response rates in general practice studies. Br J Gen Pract 1993; 43: 484.
  3. O'Neill T, Marsden D, Silman A. Differences in the character- istics of responders and non-responders in a prevalence study of vertebral osteoporosis. Osteoporosis Int 1995; 5: 327-334.
  4. Barclay S, Todd C, Grande G, Lipscombe J. How common is medical training in palliative care? Br J Gen Pract 1997; 47: 800-805.
  5. Sloan M, Kreiger N, James B. Improving response rates among doctors: randomised trial. Br Med J 1997; 315: 1136.

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Authors
Barclay, S.
Affiliations
University of Cambridge (GB)
Corresponding author
Barclay, S.
ORCID
Barclay, S.
Venue
Family Practice
Publisher
Oxford University Press (OUP)
Published
2002-02-01
Volume
19
Issue
1
Pages
105-111
ISSN
  • 0263-2136 (ISSN-L)
  • 1460-2229
DOI
10.1093/fampra/19.1.105
OpenAlex
W2134361987
Cited by
301
References
37
Citations by year
2026: 8 · 2025: 7 · 2024: 10 · 2023: 13 · 2022: 10 · 2021: 11 · 2020: 12 · 2019: 2 · 2018: 7 · 2017: 14 · 2016: 14 · 2015: 22 · 2014: 22 · 2013: 18 · 2012: 21
FWCI
34.91
Type
journal article
Language
en
Open access
Locations
  • Family Practice (publishedVersion)
  • PubMed (publishedVersion)
  • Research Explorer (The University of Manchester) (submittedVersion, other-oa)
Topics
  • Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
  • Physical Sciences › Mathematics › Statistics and Probability › Survey Sampling and Estimation Techniques
  • Physical Sciences › Mathematics › Statistics and Probability › Census and Population Estimation
Keywords
nonresponse bias, response rate, postal questionnaires, general practitioners, follow-up reminders, predictors of non-response, generalizability, palliative care education
MeSH terms
Adult, Family Practice, Female, Health Services Research, Humans, Male, Middle Aged, Surveys and Questionnaires, Bias, Logistic Models

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