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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Main Authors: Nicole Rübsamen, Manas K. Akmatov, Stefanie Castell, André Karch, Rafael T. Mikolajczyk
Format: Article
Language:English
Published: BMC 2017-08-01
Series:BMC Medical Research Methodology
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12874-017-0408-3
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spelling 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
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