Sander K R van Zon1, Salome Scholtens2, Sijmen A Reijneveld3, Nynke Smidt4, Ute Bültmann3. 1. Department of Health Sciences, Community & Occupational Medicine, University Medical Center Groningen, University of Groningen, P.O Box 196, FA 10, Antonius Deusinglaan 1, 9700 AD Groningen, The Netherlands. Electronic address: s.k.r.van.zon@umcg.nl. 2. LifeLines Cohort Study and Biobank, Bloemsingel 1, 9713 BZ Groningen, Groningen, The Netherlands. 3. Department of Health Sciences, Community & Occupational Medicine, University Medical Center Groningen, University of Groningen, P.O Box 196, FA 10, Antonius Deusinglaan 1, 9700 AD Groningen, The Netherlands. 4. Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Groningen, The Netherlands.
Abstract
OBJECTIVES: Insight into baseline participation rates and their determinants is crucial for designing future population-based biobank studies. We therefore conducted a systematic review and meta-analysis of baseline participation rates and their determinants in large longitudinal population-based biobank studies. STUDY DESIGN AND SETTING: We screened studies registered within the Public Population Project in Genomics and Society and in the Biobanking and Biomolecular Resources Research Infrastructure catalogues to find potentially eligible studies. We retrieved data with regard to participation rate, biobank design, performed measurements, and specific strategies for improving participation. We calculated weighted pooled proportions for each determinant using random-effects models. RESULTS: We included 25 studies (participation rates 5-96%). Participation rates were highest for studies involving face-to-face recruitment [82.6%; 95% confidence interval (CI): 72.2%, 90.9%], for studies in which participants were visited for an examination (77.5%; 95% CI: 64.0%, 88.6%) and for studies in which at maximum four measurements were performed (78.2%; 95% CI: 69.7%, 85.7%). Specific strategies to improve participation were not found to be associated with higher participation rates. CONCLUSION: Specific choices of recruitment methods and design have consequences for participation rates. These insights may help to increase participation in future studies, thereby enhancing the validity of their findings.
OBJECTIVES: Insight into baseline participation rates and their determinants is crucial for designing future population-based biobank studies. We therefore conducted a systematic review and meta-analysis of baseline participation rates and their determinants in large longitudinal population-based biobank studies. STUDY DESIGN AND SETTING: We screened studies registered within the Public Population Project in Genomics and Society and in the Biobanking and Biomolecular Resources Research Infrastructure catalogues to find potentially eligible studies. We retrieved data with regard to participation rate, biobank design, performed measurements, and specific strategies for improving participation. We calculated weighted pooled proportions for each determinant using random-effects models. RESULTS: We included 25 studies (participation rates 5-96%). Participation rates were highest for studies involving face-to-face recruitment [82.6%; 95% confidence interval (CI): 72.2%, 90.9%], for studies in which participants were visited for an examination (77.5%; 95% CI: 64.0%, 88.6%) and for studies in which at maximum four measurements were performed (78.2%; 95% CI: 69.7%, 85.7%). Specific strategies to improve participation were not found to be associated with higher participation rates. CONCLUSION: Specific choices of recruitment methods and design have consequences for participation rates. These insights may help to increase participation in future studies, thereby enhancing the validity of their findings.
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