Department of Public Health & Mortality Studies, International Institute for Population Sciences, Mumbai, 400 088, India.
Demographic and Health Surveys Program, ICF, Calverton, Maryland, USA.
Stud Fam Plann. 2022 Jun;53(2):259-279. doi: 10.1111/sifp.12193. Epub 2022 Mar 16.
Despite a general understanding that interviewers might cause measurement errors on sensitive questions in sample surveys, there is relatively little research on interviewer effects on responses to questions on women justifying a woman's refusal to have sex with her husband, women justifying wife beating, women's experience of physical and sexual violence, and whether the woman's father ever beat her mother. This study examines interviewer effects on these indicators that were collected in two large-scale National Family Health Surveys (NFHS) in India (2005-2006 and 2015-2016). We use cross-classified random intercept multivariable multilevel logit models to examine interviewer effects. In both surveys, we find large interviewer effects on questions about the justification of a woman refusing to have sex with her husband (32-33% in NFHS-3 and 45-46% in NFHS-4) and the justification of wife beating (27-28% in NFHS-3 and 33-34% in NFHS-4). The interviewer effects were much larger in the 2015-2016 survey than in the 2005-2006 survey. Such large interviewer effects should be considered when interpreting trends and patterns on these topics, especially since the interviewer effects might have changed between survey rounds. Understanding interviewer effects is important given the wide use of these surveys in policy formulation and monitoring in India.
尽管人们普遍认为,在抽样调查中,采访者可能会对敏感问题的测量造成误差,但对于采访者对以下问题的回应的影响,即女性拒绝与丈夫发生性关系的正当性、女性对丈夫殴打妻子的正当性、女性遭受身体和性暴力的经历以及女性的父亲是否曾经殴打过她的母亲,研究相对较少。本研究考察了在印度两次大型国家家庭健康调查(NFHS)中收集的这些指标的采访者效应(2005-2006 年和 2015-2016 年)。我们使用交叉分类随机截距多变量多水平逻辑回归模型来检验采访者的影响。在两次调查中,我们发现采访者对女性拒绝与丈夫发生性关系的正当性(NFHS-3 中的 32-33%和 NFHS-4 中的 45-46%)和妻子殴打丈夫的正当性(NFHS-3 中的 27-28%和 NFHS-4 中的 33-34%)问题的影响较大。在 2015-2016 年的调查中,这种采访者的影响比 2005-2006 年的调查要大得多。在解释这些主题的趋势和模式时,应该考虑到这种较大的采访者影响,特别是因为在调查轮次之间,采访者的影响可能已经发生了变化。考虑到这些调查在印度的政策制定和监测中被广泛使用,了解采访者的影响非常重要。