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INTRODUCTION: Face-to-face surveys are applied frequently when conducting research in older populations. Interviewers play a decisive role in data quality, may affect measurement and influence results. This study uses survey data about pain in nursing home residents and analyses, whether affiliation-of-interviewer (internal vs. external to nursing home) and gender-of-interviewer affect residents' responses in terms of interviewer variance and systematically varying pain reports. METHODS: Overall, 258 nursing home residents with up to moderate cognitive impairment were examined by 61 interviewers about pain intensity and interference applying the Brief Pain Inventory. Interviewer variance was measured using intra-interviewer correlation coefficients (ρ). Two-factorial covariance analysis was applied to analyse whether pain intensity and interference scores differ by interviewer characteristics. RESULTS: Interviewer heterogeneity accounts for almost one quarter of total variance on average. Interviewer variance is higher for internal and male interviewers than for external and female interviewers. Covariance analyses show significant effects of interviewer characteristics on pain reports. Average pain intensity and interference scores vary considerably by interviewer gender and affiliation. Highest pain intensity was reported towards female internal and male external interviewers; highest pain interference was reported towards male external interviewers. CONCLUSION: Residents' answers substantially differ in relation to who is assessing pain. There is a risk of imprecise and biased survey estimates on sensitive topics like pain in nursing homes. Interviewer gender and affiliation seem to evoke gender-specific and status-related expectations and attributions which influence residents' response process. Interviewer effects pose a considerable threat to survey data quality in institutionalised older populations.

Effets synchrones et longitudinaux sur la qualité des panels CATI des intervieweurs et des répondants : C’est en particulier dans les enquête par panel que les effets de la perte de répondants, de l’apprentissage par les répondants, et de l’expérience des intervieweurs jouent un rôle crucial en ce qui concerne la qualité des données. Nous examinons de manière synchrone et longitudinale pour la même enquête trois indicateurs de qualité. Dans l’analyse synchrone, nous comparons la qualité des données dans l’échantillon d’origine non-renouvellé avec celle d’un échantillon qui l’a été, les deux étant sondé dans la même vague. Pour la même vague, une enquête des intervieweurs a été faite, fournissant des données sur leur démographie sociale, leurs attitudes envers des enquêtes, et leur estimation de la charge de travail, nous permettant ainsi d’estimer l’effet des intervieweurs. L’analyse longitudinale permet l’analyse des effets de l’apprentissage par les répondants par rapport aux indicateurs de qualité en considérant les mêmes répondants dans plusieurs vagues. Le Panel Suisse des Ménages – une enquête CATI représentative de la population résidentielle suisse – fournit une base de données idéale pour modéliser puisque l’affectation des intervieweurs est au hasard pour toutes les vagues et dans chacune. Ce plan évite la confusion possible avec d’autres effets dus aux affectations non aléatoire telles que les affectations par quartiers où les meilleurs enquêteurs traitant les cas les plus difficiles. Pour séparer les effets des intervieweurs, des répondants et des vagues, nous utilisons des models multi-niveaux croisés. Especially in panel surveys, respondent attrition, respondent learning, and interviewer experience effects play a crucial role with respect to data quality. We examine three interview survey quality indicators in the same survey in a cross sectional as well as in a longitudinal way. In the cross sectional analysis we compare data quality in the mature original sample with that in a refreshment sample, surveyed in the same wave. Because in the same wave an interviewer survey was conducted, collecting attitudes on their socio demography, survey attitudes and burden measures, we are able to consider interviewer fixed effects as well. The longitudinal analysis gives more insight in the respondent learning effects with respect to the quality indicators considered by considering the very same respondents across waves. The Swiss Household Panel, a CATI survey representative of the Swiss residential population, forms an ideal modelling database: the interviewer – respondent assignment is random, both within and across waves. This design avoids possible confusion with other effects stemming from a non-random assignment of interviewers, e.g. area effects or effects from assigning the best interviewers to the hard cases. In order to separate interviewer, respondent and wave effects, we build cross-classified multilevel models.