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Nursing Research and Practice
Volume 2012, Article ID 303816, 8 pages
Research Article

A Data Quality Control Program for Computer-Assisted Personal Interviews

1Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada K1H 8L6
2School of Nursing, University of Ottawa, Ottawa, ON, Canada K1H 8M5
3Cabrini-Deakin Centre for Nursing Research, School of Nursing and Midwifery, Deakin University and Cabrini Health, Melbourne, VIC 3KM, Australia
4Division of Nursing, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, 14183 Huddinge, Sweden
5Department of Geriatric Medicine, Danderyd Hospital, 18287 Danderyd, Sweden
6Faculty of Nursing, University of Alberta, Edmonton, AB, Canada T6G 1C9
7Department of Family Medicine, University of Calgary, Calgary, AB, Canada T2M 0H5

Received 24 July 2012; Revised 24 October 2012; Accepted 29 October 2012

Academic Editor: M. H. F. Grypdonck

Copyright © 2012 Janet E. Squires et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Researchers strive to optimize data quality in order to ensure that study findings are valid and reliable. In this paper, we describe a data quality control program designed to maximize quality of survey data collected using computer-assisted personal interviews. The quality control program comprised three phases: (1) software development, (2) an interviewer quality control protocol, and (3) a data cleaning and processing protocol. To illustrate the value of the program, we assess its use in the Translating Research in Elder Care Study. We utilize data collected annually for two years from computer-assisted personal interviews with 3004 healthcare aides. Data quality was assessed using both survey and process data. Missing data and data errors were minimal. Mean and median values and standard deviations were within acceptable limits. Process data indicated that in only 3.4% and 4.0% of cases was the interviewer unable to conduct interviews in accordance with the details of the program. Interviewers’ perceptions of interview quality also significantly improved between Years 1 and 2. While this data quality control program was demanding in terms of time and resources, we found that the benefits clearly outweighed the effort required to achieve high-quality data.