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Published on: January 12, 2018
Increasing questionnaire response: evidence from a nested RCT within a longitudinal birth cohort study
Michaela Goodwin1, Tanya Walsh2, William Whittaker3
1The Dental Health Unit, Division of Dentistry, Williams House, University of Manchester, Manchester Science Park, Manchester, M15 6SE, UK. michaela.goodwin@manchester.ac.uk.
Resending questionnaires significantly boosted response rates in a large epidemiological study. Telephone calls helped address participation imbalances related to participant deprivation levels.
Area of Science:
- Epidemiology
- Public Health Research
Background:
- High questionnaire response rates are crucial for study validity and generalizability in research.
- This study assessed response rates in a large longitudinal epidemiological study.
- The research aimed to improve response rates and address deprivation-related imbalances.
Purpose of the Study:
- To measure questionnaire response rates in a large longitudinal epidemiological study.
- To evaluate the impact of changes in data collection on response rates.
- To determine if interventions addressed response imbalances across different deprivation levels.
Main Methods:
- Analysis of response rates from a prospective, comparative study on water fluoridation's impact on children's oral health.
- Implementation of changes to questionnaire layout and cover letters during data collection.
- A nested randomized controlled trial comparing three reminder methods for questionnaire completion.
Main Results:
- Data were analyzed for 1824 individuals.
- Resending the complete questionnaire to non-responders yielded the highest response rate increase (25%).
- Telephone calls were the only method that showed potential in addressing deprivation-related response imbalances.
Conclusions:
- Low initial response rates raised concerns about non-response bias in the longitudinal study.
- Resending questionnaires proved most effective for increasing participation.
- Targeted efforts and data weighting can help mitigate biases and improve population-level conclusions.
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