ArticleBMC medical research methodology2017
Factors associated with attrition in a longitudinal online study: results from the HaBIDS panel.
Article in BMC medical research methodology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 70 citations in OpenAlex.
- A randomized controlled trial testing a virtual program for Asian American women breast cancer survivors.Nature communications · 2023Trial
- A prospective study of per- and polyfluoroalkyl substances (PFAS), stress, and birth size in a cohort of U.S. Black women.Environmental health : a global access science source · 2026Article
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- Integration of former child and adolescent study participants into a national health online panel for a longitudinal study on young adult mental health.BMC medical research methodology · 2025Article
- Dropout in a Longitudinal Survey of Amazon Mechanical Turk Workers With Low Back Pain: Observational Study.Interactive journal of medical research · 2024Article
- Age-related positivity effect in emotional memory consolidation from middle age to late adulthood.Frontiers in behavioral neuroscience · 2024Article
- Predictors of dropping out from a home tele-exercise programme: A cohort study derived from a randomised controlled trial.Health promotion perspectives · 2024Article
- Article
- To Remind or Not to Remind During Recruitment? An Analysis of an Online Panel in Germany.International journal of public health · 2024Article
- The association of baseline depressive symptoms and stress on withdrawal in a national longitudinal cohort: the REGARDS study.Annals of epidemiology · 2023Article
- Effect of risk status for severe COVID-19 on individual contact behaviour during the SARS-CoV-2 pandemic in 2020/2021-an analysis based on the German COVIMOD study.BMC infectious diseases · 2023Article
- Major depressive disorders increase the susceptibility to self-reported infections in two German cohort studies.Social psychiatry and psychiatric epidemiology · 2023Article
- Adapting the ADVANCE group program for digitally-supported delivery to reduce intimate partner violence by men in substance use treatment: a feasibility study.Frontiers in psychiatry · 2023Article
- Assessing targeted invitation and response modes to improve survey participation in a diverse New York City panel: Healthy NYC.PloS one · 2023Article
- The power of online panel paradata to predict unit nonresponse and voluntary attrition in a longitudinal design.Quality & quantity · 2023Article
- Article
- Providing laypeople with results from dynamic infectious disease modelling studies affects their allocation preference for scarce medical resources-a factorial experiment.BMC public health · 2022Article
- Use of a non-probabilistic online panel as a control group for case-control studies to investigate food and waterborne outbreaks in Lower Saxony, Germany.Epidemiology and infection · 2022Article
- Sexual Contact Patterns in High-Income Countries-A Comparative Analysis Using Data From Germany, the United Kingdom, and the United States.Frontiers in epidemiology · 2022Article
- Changes in social relationships during an initial "stay-at-home" phase of the COVID-19 pandemic: A longitudinal survey study in the U.S.Social science & medicine (1982) · 2021Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundKnowing about predictors of attrition in a panel is important to initiate early measures against loss of participants. We investigated attrition in both early and late phase of an online panel with special focus on preferences regarding mode of participation.
methodsWe used data from the HaBIDS panel that was designed to investigate knowledge, attitudes, and practice regarding infections in the German general population. HaBIDS was divided into two phases: an initial phase when some participants could choose their preferred mode of participation (paper-and-pencil or online) and an extended phase when participants were asked to become members of an online panel that was not limited regarding its duration (i.e. participants initially preferring paper questionnaires switched to online participation). Using competing risks regression, we investigated two types of attrition (formal withdrawal and discontinuation without withdrawal) among online participants, separately for both phases. As potential predictors of attrition, we considered sociodemographic characteristics, physical and mental health as well as auxiliary information describing the survey process, and, in the extended phase, initial mode preference.
resultsIn the initial phase, higher age and less frequent Internet usage predicted withdrawal, while younger age, higher stress levels, delay in returning the consent form, and need for receiving reminder emails predicted discontinuation. In the extended phase, only need for receiving reminder emails predicted discontinuation. Numbers of withdrawal in the extended phase were too small for analysis. Initial mode preference did not predict attrition in the extended phase. Besides age, there was no evidence of differential attrition by sociodemographic factors in any phase.
conclusionsPredictors of attrition were similar in both phases of the panel, but they differed by type of attrition (withdrawal vs. discontinuation). Sociodemographic characteristics only played a minor role for both types of attrition. Need for receiving a reminder was the strongest predictor of discontinuation in any phase, but no predictor of withdrawal. We found predictors of attrition, which can be identified already in the early phase of a panel so that countermeasures (e.g. special incentives) can be taken.
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