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.
Keywords: Attrition; Health survey; Internet; Longitudinal study; Mixed-mode; Online; Panel; Participation; Response; Withdrawal.