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Better to ask online when it concerns intimate relationships? Survey mode differences in the assessment of relationship quality

Author

Listed:
  • Almut Schumann

    (Bundesinstitut für Bevölkerungsforschung (BiB))

  • Detlev Lück

    (Bundesinstitut für Bevölkerungsforschung (BiB))

Abstract

Background: The assessment of relationship quality is a key construct in family research and relies on several indicators. As answer behavior for sensitive and subjective questions can be biased by the interview situation, the emerging switch from face-to-face mode to web or mixed mode in surveys challenges the comparability of measurements. Objective: This study investigates the impact of two modes of data collection – face-to-face mode and web mode – on central measurements of relationship quality in quantitative family research. Methods: In a German experimental pilot study (2018) within the Generations and Gender Programme, target persons were randomly assigned to face-to-face or online interviews. Mode differences are assessed by comparing distributions for various indicators of relationship quality. To adjust for confounders, post-stratification weighting and multivariate regression analysis are applied. Results: Findings reveal consistent mode effects for almost all indicators of relationship quality even after adjusting for confounders. Respondents in web mode assess their relationship quality substantially lower than respondents in face-to-face mode, thinking more often about breaking up and reporting lower satisfaction and more conflicts. Conclusions: Web mode seems to support less socially desirable reflections on respondents’ relationships compared to face-to-face mode. Family researchers should consider survey design decisions when evaluating intimate relationships, particularly in longitudinal and cross-national studies. Contribution: Findings on the assessment of relationships in family research based on self-administered modes, such as web mode, can be considered more reliable than those based on interviewer-administered modes.

Suggested Citation

  • Almut Schumann & Detlev Lück, 2023. "Better to ask online when it concerns intimate relationships? Survey mode differences in the assessment of relationship quality," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 48(22), pages 609-640.
    • Handle: RePEc:dem:demres:v:48:y:2023:i:22
    DOI: 10.4054/DemRes.2023.48.22
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    References listed on IDEAS

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    1. Atkeson, Lonna Rae & Adams, Alex N. & Alvarez, R. Michael, 2014. "Nonresponse and Mode Effects in Self- and Interviewer-Administered Surveys," Political Analysis, Cambridge University Press, vol. 22(3), pages 304-320, July.
    2. Ivar Krumpal, 2013. "Determinants of social desirability bias in sensitive surveys: a literature review," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 2025-2047, June.
    3. Matthias Schonlau & Arthur van Soest & Arie Kapteyn & Mick Couper, 2009. "Selection Bias in Web Surveys and the Use of Propensity Scores," Sociological Methods & Research, , vol. 37(3), pages 291-318, February.
    4. Lugtig, Peter & Toepoel, Vera & Emery, Tom & Cabaço, Susana Laia Farinha & Bujard, Martin & Naderi, Robert & Schumann, Almut & Lück, Detlev, 2022. "Can we Successfully Move a Cross-national Survey online? Results from a Large Three-country Experiment in the Gender and Generations Programme survey," SocArXiv mu8jy, Center for Open Science.
    5. Arieke J. Rijken & Aart C. Liefbroer, 2009. "The Influence of Partner Relationship Quality on Fertility," European Journal of Population, Springer;European Association for Population Studies, vol. 25(1), pages 27-44, February.
    6. Elise Braekman & Rana Charafeddine & Stefaan Demarest & Sabine Drieskens & Finaba Berete & Lydia Gisle & Johan Van der Heyden & Guido Van Hal, 2020. "Comparing web-based versus face-to-face and paper-and-pencil questionnaire data collected through two Belgian health surveys," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 65(1), pages 5-16, January.
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    Cited by:

    1. Tomova, Georgia D & Silverwood, Richard J. & Wright, Liam, 2026. "Mode effects on survey item measurement: A systematic review of the experimental evidence," SocArXiv bc7qn_v1, Center for Open Science.

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    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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