In large national surveys like the Health and Retirement Study that include in-person data collection, the interviewers collecting the survey data are often also asked to record observations of household and neighborhood characteristics. Interviewers are trained to use all available cues in an effort to record accurate observations.
Did you know that the HRS records these types of contextual interviewer observations and makes them available for HRS data users in public-use data files? The observation variables can be downloaded and merged with HRS survey data files.
Respondent level data includes interviewer ratings of their perceptions of the interview. Household level data includes information on the interviewer's rating of the home and surrounding area. The module is labelled IO for interviewer observations. Data are available for all waves and are part of the distribution set for each core wave of HRS data.
Respondent level file hwIO_r
Household level hwIO_h
where w represents the wave year
While these observations are useful to survey methodologists, researchers using HRS data have found these data to be quite useful in substantive applications. Here are some example publications that have used these data in substantive models:
Wilkinson, L. R., Ferraro, K. F., & Kemp, B. R. (2017). Contextualization of Survey Data: What Do We Gain and Does It Matter?. Research in human development, 14(3), 234–252. https://doi.org/10.1080/15427609.2017.1340049
Freedman, V. A., Grafova, I. B., Schoeni, R. F., & Rogowski, J. (2008). Neighborhoods and disability in later life. Social science & medicine, 66(11), 2253–2267. https://doi.org/10.1016/j.socscimed.2008.01.013
Velasquez, A. J., Douglas, J. A., Guo, F., & Robinette, J. W. (2021). What predicts how safe people feel in their neighborhoods and does it depend on functional status?. SSM - population health, 16, 100927. https://doi.org/10.1016/j.ssmph.2021.100927