OBJECTIVES: Little is known about the effect of noncompletion on telephone surveys of health issues. This paper identifies a little-studied source of noncompletion, passive refusal, and evaluates its contribution to noncompletion bias along with two other sources: noncooperation and noncontact. Passive refusals include respondents who repeatedly request callbacks and households where interviewers repeatedly encounter an answering machine. METHODS: Measures of noncompletion (noncooperation, passive refusal, and noncontact), demographic and socioeconomic characteristics, health risk factors, and indicators of health care access and health status were collected through the Orange County Health Surveys on 4893 respondents. The surveys sampled by random-digit dialing and interviewed by computer-assisted telephone. RESULTS: Passive refusals have a substantial impact on completion rates and bias due to noncompletion. Commonly used definitions for completion rates may underestimate the bias due to noncompletion because they omit passive refusals. After we controlled for demographic and socioeconomic factors, few noncompletion biases appeared on selected health indicators. CONCLUSIONS: These results suggest improved reporting of completion rates and support a multivariate framework for studying noncompletion in telephone health surveys.
OBJECTIVES: Little is known about the effect of noncompletion on telephone surveys of health issues. This paper identifies a little-studied source of noncompletion, passive refusal, and evaluates its contribution to noncompletion bias along with two other sources: noncooperation and noncontact. Passive refusals include respondents who repeatedly request callbacks and households where interviewers repeatedly encounter an answering machine. METHODS: Measures of noncompletion (noncooperation, passive refusal, and noncontact), demographic and socioeconomic characteristics, health risk factors, and indicators of health care access and health status were collected through the Orange County Health Surveys on 4893 respondents. The surveys sampled by random-digit dialing and interviewed by computer-assisted telephone. RESULTS: Passive refusals have a substantial impact on completion rates and bias due to noncompletion. Commonly used definitions for completion rates may underestimate the bias due to noncompletion because they omit passive refusals. After we controlled for demographic and socioeconomic factors, few noncompletion biases appeared on selected health indicators. CONCLUSIONS: These results suggest improved reporting of completion rates and support a multivariate framework for studying noncompletion in telephone health surveys.
Authors: Kennet Harald; Veikko Salomaa; Pekka Jousilahti; Seppo Koskinen; Erkki Vartiainen Journal: J Epidemiol Community Health Date: 2007-05 Impact factor: 3.710
Authors: M K Campbell; B M DeVellis; V J Strecher; A S Ammerman; R F DeVellis; R S Sandler Journal: Am J Public Health Date: 1994-05 Impact factor: 9.308