Strategies to Minimize Selection Bias in Digital Population-Based Studies in Sport and Health Sciences: Methodological and Empirical Insights from the COMO Study

Objectives: Population-based surveys increasingly face challenges of declining response rates and selective participation, particularly since the COVID-19 pandemic. This article presents the COMO study’s design and sampling approach and discusses strategies to minimize selection bias in digital health surveys, focusing on participation enhancement, response rates, and sample composition from the first survey wave of the COMO Study. Methods: The COMO study is a nationwide, prospective panel survey with three annual online waves (2023–2025). In the first wave (COMO1), a probability-based sample of 35,157 families with children aged 4–17 was recruited using a two-stage register-based sampling procedure. Participation was encouraged via a multimodal communication strategy including postal invitations, email reminders, non-monetary incentives, and social media outreach. Weighting procedures were developed based on design weights and calibration to national micro- census benchmarks. Results: A total of 6,097 families submitted at least one complete questionnaire, corresponding to a 17.3% overall participation. The final analytical sample with full parent and child data comprised 5,240 families (15.0%). Response behavior varied by age, gender, and parental education as one proxy of socio economic status (SES), with adolescents, boys, and lower-educational households underrepresented. Re- minder strategies boosted participation, particularly in early stages. A weighting procedures was developed to corrected key demographic imbalances. Qualitative analyses of 50 inquiries revealed technical, communicative, and emotional barriers, including privacy concerns and pandemic-related distress. Conclusions: The COMO study demonstrates that targeted reminders, inclusive materials, and post-survey weighting can reduce—but not fully eliminate—selection bias. Findings underscore the need for participatory, equity-oriented , incentives designs to improve repre- sentativeness in health research, especially in underserved populations.

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Publication Details

Journal
German Journal of Sports Medicine
Published
2025-06-20
DOI
https://doi.org/10.5960/dzsm.2025.631
Citations
5
Primary Topic
Sports Analytics and Performance
Type
article
Field-Weighted Citation Impact
15.66
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article

Strategies to Minimize Selection Bias in Digital Population-Based Studies in Sport and Health Sciences: Methodological and Empirical Insights from the COMO Study

Anne Kaman, Annette Worth, Markus Reichert, Franziska Reiß et al.
5 citations
German Journal of Sports Medicine
Sports Analytics and Performance
15.66
article

Strategies to Minimize Selection Bias in Digital Population-Based Studies in Sport and Health Sciences: Methodological and Empirical Insights from the COMO Study

Anne Kaman, Annette Worth, Markus Reichert, Franziska Reiß, Anke Hanssen‐Doose, Petra Wagner, Alexander Wöll, Matthias Sand, Claudia Niessner, Ulrike Ravens‐Sieberer, Thorsten Klein, Michael Fleps-Dezasse, Carmen Volk, Steven Behn, Robin Olfermann, Birtel von Haaren-Mack, Fredrik Knirsch
article en
5 citations

Abstract

Objectives: Population-based surveys increasingly face challenges of declining response rates and selective participation, particularly since the COVID-19 pandemic. This article presents the COMO study’s design and sampling approach and discusses strategies to minimize selection bias in digital health surveys, focusing on participation enhancement, response rates, and sample composition from the first survey wave of the COMO Study. Methods: The COMO study is a nationwide, prospective panel survey with three annual online waves (2023–2025). In the first wave (COMO1), a probability-based sample of 35,157 families with children aged 4–17 was recruited using a two-stage register-based sampling procedure. Participation was encouraged via a multimodal communication strategy including postal invitations, email reminders, non-monetary incentives, and social media outreach. Weighting procedures were developed based on design weights and calibration to national micro- census benchmarks. Results: A total of 6,097 families submitted at least one complete questionnaire, corresponding to a 17.3% overall participation. The final analytical sample with full parent and child data comprised 5,240 families (15.0%). Response behavior varied by age, gender, and parental education as one proxy of socio economic status (SES), with adolescents, boys, and lower-educational households underrepresented. Re- minder strategies boosted participation, particularly in early stages. A weighting procedures was developed to corrected key demographic imbalances. Qualitative analyses of 50 inquiries revealed technical, communicative, and emotional barriers, including privacy concerns and pandemic-related distress. Conclusions: The COMO study demonstrates that targeted reminders, inclusive materials, and post-survey weighting can reduce—but not fully eliminate—selection bias. Findings underscore the need for participatory, equity-oriented , incentives designs to improve repre- sentativeness in health research, especially in underserved populations.

German Journal of Sports MedicineVol. 76(5)
Openalex Percentile: Top 1%
Sports Analytics and Performance
15.66
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