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

Fam Pract. 2002 Feb;19(1):105-11. doi: 10.1093/fampra/19.1.105.


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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Bias*
  • Family Practice*
  • Female
  • Health Services Research*
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Surveys and Questionnaires*