Webpage last modified: 2008-Sep-10
Interviewers play a critical role in surveys, as they implement the survey design and are often required to perform multiple tasks at a high level of accuracy. In a face-to-face survey, the interviewer may be required to physically locate the household and to update the sample frame. In both telephone and face-to-face surveys, the interviewer has to contact the household, explain the purpose of the study, gain cooperation, enumerate household members, select the respondent, ask questions in the required manner, put the respondent at ease, and accurately record the respondent's answers and any other required information. Depending upon the survey topic and survey context, the interviewer may be required to perform additional tasks, such as bio-measure collection or oral translation.
Interviewers can influence responses through their personal attributes and their behavior ("interviewer effects"). These guidelines present strategies to minimize the effect interviewer attributes have on the data through appropriate recruitment, selection, and case assignment; they also present strategies to minimize the effect that interviewer behavior has on the data through formal training.
Goal: To improve the overall quality of the survey data by minimizing interviewer effects.
The structure and composition of the interviewing staff must be established during the design and planning phases of the project because these decisions will dictate the number of interviewers required, the training protocol, sample assignment, and optimal methods of supervision.
Interviewer pay is one of the largest expenses in interviewer-administered surveys; at the same time, since field staff quality has a major impact on the quality of the data collected, it is important to attract and retain the most qualified interviewers possible.
The quality of an interviewer-administered survey depends, to a large extent, on the quality of the field staff. It is important, therefore, to recruit and select the best possible people for the job.
Newly hired interviewers and supervisors require general training in techniques for successful interviewing before they receive specific training on the study on which they will be working. Research indicates that interviewer training helps improve the quality of survey data by: (1) reducing item nonresponse [3], (2) increasing the amount of information obtained [3], and (3) increasing survey participation by teaching interviewers how to identify and respond to respondents' concerns [22].
Interviewers and supervisors need to be familiar with the study's protocols in order to carry out their tasks. Depending upon the survey, they may need to learn the instrument's branching structure, the study's requirement for field coding, or the use of a respondent booklet, show cards, or other visual materials. There may be special instructions for implementing all or part of the survey that deviate from the standardized interviewing covered in general interviewer training. Interviewers should also be knowledgeable about the project objectives so that their actions help, not hinder, the overall goals. Both newly hired and experienced interviewers require training specific to the study at hand.
Quality control (QC) is a procedure or set of procedures intended to ensure that a product or service adheres to a defined set of quality criteria or meets the requirements of the client. The implementation of quality control measures enhances the reliability and validity of the survey data and maximizes comparability of these data across cultures. To implement an effective QC program in a cross-cultural survey context, the coordinating center must first decide which specific standards must be met. Then real-world data must be collected and the results reported back to the coordinating center. After this, corrective action must be decided upon and taken. Finally, the QC process must be ongoing to ensure that remedial efforts, if required, have produced satisfactory results.
Including quality control protocols as part of the overall survey design, and implementing them from the start, permits the survey organization and the coordinating center to monitor performance and to take immediate corrective action when required. For example, if many interviewer candidates fail to pass the study-specific certification test, additional training could be provided. Afterward, the candidates would be tested again. Those passing the certification test could then be sent out into the field.
Comprehensive documentation helps analysts correctly interpret the data and serves as a resource for later studies.
Research indicates that the interviewer design effect may be even greater than the design effect attributable to geographic clustering [30].
The intra class coefficient, ρint, is a measure of interviewer variance and is defined as:
| ρint = | (between-interviewer variance) |
| (between-interviewer variance) + (within-interviewer variance) |
The value of ρint is always between 0 and 1. When ρint for a particular variable is 0, the interviewers have no effect on the variance of responses to that variable; the larger the value of ρint, the larger the effect of interviewers on the variance of the particular variable.
The interviewer design effect (deffint) is a measure of the effect of interviewers carrying out multiple interviews, compared to what you would get if there was a different interviewer for each respondent.
deffint = 1 + ρint (m-1)
where m is the average number of interviews per interviewer.
Thus, even a small interviewer variance (ρint,) can have a significant effect on the precision of a survey estimate if m is large.
The following example shows how to calculate the number of interviewers required for a hypothetical study. The example makes the following assumptions:
Make the following calculations:
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