Comparison of alternative falls data collection methods in the Prevention of Falls Injury Trial (PreFIT)

James Griffin*, Ranjit Lall, Julie Bruce, Emma Withers, Susanne Finnegan, Sarah E. Lamb, PreFIT Study Group

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Background and Objectives: Prospective, monthly diaries are recommended for collecting falls data but are burdensome and expensive. The aim of the article was to compare characteristics of fallers and estimates of fall rates by method of data collection.

Study Design and Setting: A methodology study nested within a large cluster randomized controlled trial. We randomized 9,803 older adults from 63 general practices across England to receive one of three fall prevention interventions. Participants provided a retrospective report of falls in postal questionnaires mailed every 4 months. A separate randomization allocated participants to receive prospective monthly falls diaries for one simultaneous 4-month period. 

Results: Falls diaries were returned by 7,762 of 9,375 (83%); of which 6,306 (67%) participants reported the same number of falls on both data sources. Diary non responders were older and had poorer levels of physical and mental health. Analysis of time points where both data sources were available showed the falls rate on diaries was consistently higher than on the questionnaire (mean rate: 0.16 vs. 0.12 falls per person-month observation). Diary allocation was associated with a higher rate of withdrawal from the main trial. 

Conclusion: Diary completion was associated with sample attrition. We found on average a 32% difference in falls rates between the two data sources. Retrospective and prospective falls data are not consistently reported when collected simultaneously.

Original languageEnglish
Pages (from-to)32-40
Number of pages9
JournalJournal of Clinical Epidemiology
Volume106
Early online date2 Nov 2018
DOIs
Publication statusPublished - 1 Feb 2019

Keywords

  • clinical trials
  • data quality
  • falls
  • older adults
  • statistical analysis
  • SWAT

ASJC Scopus subject areas

  • Epidemiology

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