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Correlates of Obtaining Informed Consent to Data Linkage


  • Emanuela Sala

    (Department of sociology and social research, Università di Milano-Bicocca, Milan, Italy)

  • Jonathan Burton

    (University of Essex, UK)

  • Gundi Knies

    (University of Essex, UK)


In the United Kingdom, in order to link individual-level administrative records to survey responses, respondents need to give their consent. Using an unprecedented set of respondent, interview, and interviewer characteristics derived from the British Household Panel Survey (BHPS) matched with an interviewer survey, this research investigates which characteristics influence consent to adding health and social security records to the survey responses. We find that consent is related to respondents’ attitudes to privacy, community mindedness and data linkage salience as well as to some interview features such as the “household contagion effect†and the survey “fidelity.†Interviewer characteristics, including their personality, attitudes to persuading respondents, and job experience, are not associated with consent. Interviewers’ survey experience in the current wave and their task-specific experience, however, do influence consent. Implications of the findings are discussed and areas for future research are identified.

Suggested Citation

  • Emanuela Sala & Jonathan Burton & Gundi Knies, 2012. "Correlates of Obtaining Informed Consent to Data Linkage," Sociological Methods & Research, , vol. 41(3), pages 414-439, August.
  • Handle: RePEc:sae:somere:v:41:y:2012:i:3:p:414-439

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    Cited by:

    1. Knies, Gundi & Sala, Emanuela & Burton, Jonathan, 2011. "Consenting to health record linkage: evidence from the British Household Panel Study," ISER Working Paper Series 2011-27, Institute for Social and Economic Research.
    2. Fertig, Michael & Görlitz, Katja, 2013. "Missing wages: How to test for biased estimates in wage functions?," EconStor Open Access Articles, ZBW - German National Library of Economics, pages 269-271.
    3. Das Marcel & Couper Mick P., 2014. "Optimizing Opt-Out Consent for Record Linkage," Journal of Official Statistics, De Gruyter Open, vol. 30(3), pages 1-19, September.


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