Utility of telephone survey methods in population-based health studies of older adults: an example from the Alberta Older Adult Health Behavior (ALERT) study
نویسندگان
چکیده
BACKGROUND Random digit dialing is often used in public health research initiatives to accrue and establish a study sample; however few studies have fully described the utility of this approach. The primary objective of this paper was to describe the implementation and utility of using random digit dialing and Computer Assisted Telephone Interviewing (CATI) for sampling, recruitment and data collection in a large population-based study of older adults [Alberta Older Adult Health Behavior (ALERT) study]. METHODS Using random digit dialing, older adults (> = 55 years) completed health behavior and outcome and demographic measures via CATI. After completing the CATI, participants were invited to receive a step pedometer and waist circumference tape measure via mail to gather objectively derived ambulatory activity and waist circumference assessments. RESULTS Overall, 36,000 telephone numbers were called of which 7,013 were deemed eligible for the study. Of those, 4,913 (70.1%) refused to participate in the study and 804 (11.4%) participants were not included due to a variety of call dispositions (e.g., difficult to reach, full quota for region). A total of 1,296 participants completed telephone interviews (18.5% of those eligible and 3.6% of all individuals approached). Overall, 22.8% of households did not have an age 55+ resident and 13.6% of individuals refused to participate, Average age was 66.5 years, and 43% were male. A total of 1,081 participants (83.4%) also submitted self-measured ambulatory activity (i.e., via step pedometer) and anthropometric data (i.e., waist circumference). With the exception of income (18.7%), the rate of missing data for demographics, health behaviors, and health measures was minimal (<1%). CONCLUSIONS Older adults are willing to participate in telephone-based health surveys when randomly contacted. Researchers can use this information to evaluate the feasibility and the logistics of planned studies using a similar population and study design.
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