Factors associated with attrition in a longitudinal online study: results from the HaBIDS panel
Abstract Background Knowing 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. Methods We used data...
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doaj-2b50218af5484a83845c1ae2bfd7dea02020-11-24T20:59:04ZengBMCBMC Medical Research Methodology1471-22882017-08-0117111110.1186/s12874-017-0408-3Factors associated with attrition in a longitudinal online study: results from the HaBIDS panelNicole Rübsamen0Manas K. Akmatov1Stefanie Castell2André Karch3Rafael T. Mikolajczyk4Department of Epidemiology, Helmholtz Centre for Infection Research (HZI)Department of Epidemiology, Helmholtz Centre for Infection Research (HZI)Department of Epidemiology, Helmholtz Centre for Infection Research (HZI)Department of Epidemiology, Helmholtz Centre for Infection Research (HZI)Department of Epidemiology, Helmholtz Centre for Infection Research (HZI)Abstract Background Knowing 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. Methods We 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. Results In 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. Conclusions Predictors 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.http://link.springer.com/article/10.1186/s12874-017-0408-3AttritionHealth surveyInternetLongitudinal studyMixed-modeOnline |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nicole Rübsamen Manas K. Akmatov Stefanie Castell André Karch Rafael T. Mikolajczyk |
spellingShingle |
Nicole Rübsamen Manas K. Akmatov Stefanie Castell André Karch Rafael T. Mikolajczyk Factors associated with attrition in a longitudinal online study: results from the HaBIDS panel BMC Medical Research Methodology Attrition Health survey Internet Longitudinal study Mixed-mode Online |
author_facet |
Nicole Rübsamen Manas K. Akmatov Stefanie Castell André Karch Rafael T. Mikolajczyk |
author_sort |
Nicole Rübsamen |
title |
Factors associated with attrition in a longitudinal online study: results from the HaBIDS panel |
title_short |
Factors associated with attrition in a longitudinal online study: results from the HaBIDS panel |
title_full |
Factors associated with attrition in a longitudinal online study: results from the HaBIDS panel |
title_fullStr |
Factors associated with attrition in a longitudinal online study: results from the HaBIDS panel |
title_full_unstemmed |
Factors associated with attrition in a longitudinal online study: results from the HaBIDS panel |
title_sort |
factors associated with attrition in a longitudinal online study: results from the habids panel |
publisher |
BMC |
series |
BMC Medical Research Methodology |
issn |
1471-2288 |
publishDate |
2017-08-01 |
description |
Abstract Background Knowing 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. Methods We 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. Results In 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. Conclusions Predictors 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. |
topic |
Attrition Health survey Internet Longitudinal study Mixed-mode Online |
url |
http://link.springer.com/article/10.1186/s12874-017-0408-3 |
work_keys_str_mv |
AT nicolerubsamen factorsassociatedwithattritioninalongitudinalonlinestudyresultsfromthehabidspanel AT manaskakmatov factorsassociatedwithattritioninalongitudinalonlinestudyresultsfromthehabidspanel AT stefaniecastell factorsassociatedwithattritioninalongitudinalonlinestudyresultsfromthehabidspanel AT andrekarch factorsassociatedwithattritioninalongitudinalonlinestudyresultsfromthehabidspanel AT rafaeltmikolajczyk factorsassociatedwithattritioninalongitudinalonlinestudyresultsfromthehabidspanel |
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