Asking sensitive questions in surveys

Description:

Course Content
Researchers are often interested in investigating sensitive topics as mental health, risky behaviours, drug use, sexuality, personal expenses, tax evasion, etc. Data on these topics often rely on sensitive questions, which are often hard to elicit given privacy concerns, the social desirability of the answer, and/or the fear of disclosure to third parties. The course introduces the concepts of social desirability, misreporting and the cognitive process of asking sensitive questions in surveys. It describes a series of indirect questioning techniques to minimize the embarrassment in answering sensitive questions; these methods include the item count technique, the randomize response technique, and the three card method. Since social desirability may cause missing data, the course describes the basic concepts in non response analysis, including missing data patterns, mechanisms, and imputation methods. Finally, the ethics of asking sensitive questions is discussed, with emphasis on confidentiality and anonymization. The course is mainly applied in nature and includes several examples from empirical research.

Course Objective
The course is addressed to Ph.D. students, academic researchers, survey managers and practitioners that wish to include sensitive questions in their surveys and/or to analyses data produced with sensitive questions. The training may be beneficial in designing data collection instruments for surveying hard-to-reach and elusive populations, in developing countries as well as in the western world. After attending this course participants are expected to be able to design effectively sensitive questions, chose the adequate survey mode, and (when appropriate) adopt indirect questionnaire techniques. Also, students will be familiar with the ethical issues in asking sensitive questions and with the basics of imputation.

Course Prerequisites
This is an introductory course. Basic knowledge in statistics and quantitative research methods would be beneficial.

Background Reading
Tourangeau, R., L. J. Rips, and K. Rasinski. 2000. “Editing of Responses: Reporting about Sensitive Topics” in The Psychology of Survey Response. Cambridge University Press, pp: 255 – 288.

Tourangeau, Roger and Ting Yan. 2007. Sensitive Questions in Surveys. Psychological Bulletin, 133(5): 859–883

Droitcour, J., Caspar, R. A., Hubbard, M. L., and Ezzati, T. M. (1991), “The Item Count Technique as a Method of Indirect Questioning: A Review of Its Development and a Case Study Application,” in Measurement Errors in Surveys, eds. P. P. Biemer, R. M. Groves, L. E. Lyberg, N. A. Mathiowetz, and S. Sudman, New York: Wiley, pp. 185–210.

Other information

This is a 20 hours course, with classes from 10am-12am and from 1pm-3pm. Students are invited to allocate 2 additional hours every course-day for individual study and group exercises. The detailed course outline is available upon request (agaia@essex.ac.uk)

About the instructor

Alessandra Gaia (Ph.D.) is a social researcher working at the Institute for Social and Economic Research of the University of Essex. Her research focuses on non response analysis, attrition, and sensitive questions. She has practical experience in data collection, acquired managing one of the UK cohort studies: Next Steps (previously known as the Longitudinal Study of Young People in England LSYE). Besides academia, she has collaborated as a social researcher in the private sector and in international organizations.

Cost:

Students £200
Academic/non profit £250
Commercial £300

Website and registration:

Region:

East of England

Keywords:

Survey Research, Survey and Questionnaire Design, Questionnaire design, Online Data Collection , Quality in Quantitative Research, Measurement Error, Mode effects, Nonresponse , Missing data, Unit nonresponse, Item nonresponse, Imputation, sensitive questions, hard-to-reach populations

Related publications and presentations from our eprints archive:

Survey Research
Survey and Questionnaire Design
Questionnaire design
Online Data Collection
Quality in Quantitative Research
Measurement Error
Mode effects
Nonresponse
Missing data
Unit nonresponse
Item nonresponse
Imputation

Back to the training database