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A Note on How Prior Survey Experience With Self-Administered Panel Surveys Affects Attrition in Different Modes

[journal article]

Gummer, Tobias
Daikeler, Jessica

Abstract

Attrition poses an important challenge for panel surveys. With respect to these surveys, respondents’ decisions about whether to participate in reinterviews are affected by their participation in prior waves of the panel. However, in self-administered mixed-mode panels, the way of experiencing a sur... view more

Attrition poses an important challenge for panel surveys. With respect to these surveys, respondents’ decisions about whether to participate in reinterviews are affected by their participation in prior waves of the panel. However, in self-administered mixed-mode panels, the way of experiencing a survey differs between the mail mode and the web mode. Consequently, this study investigated how respondents' prior experience with the characteristics of a survey - such as length, difficulty, interestingness, sensitivity, and the diversity of the questionnaire - affects their informed decision about whether to participate again or not. We found that the length of a questionnaire seems to be of such importance to respondents that they base their participation on this characteristic, regardless of the mode. Our findings also suggest that the difficulty and diversity of questionnaires are readily accessible information that respondents use in the mail mode when making a decision about whether to participate again, whereas these characteristics have no effect in the web mode. In addition, privacy concerns have an impact in the web mode but not in the mail mode.... view less

Keywords
survey research; mail survey; online survey; panel; participant; motivation; questionnaire; data protection

Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods

Free Keywords
mixed-mode; panel attrition; self-administered survey; survey experience; web survey; GESIS panel, release v19.0.0 of study number ZA5665

Document language
English

Publication Year
2020

Page/Pages
p. 490-498

Journal
Social Science Computer Review, 38 (2020) 4

DOI
https://doi.org/10.1177/0894439318816986

ISSN
1552-8286

Status
Published Version; peer reviewed

Licence
Deposit Licence - No Redistribution, No Modifications


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© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.