Who Avoids Going to the Doctor and Why? Audience Segmentation Analysis for Application of Message Development

Abstract

This exploratory study examines the prevalent and detrimental health care phenomenon of patient delay in order to inform formative research leading to the design of communication strategies. Delayed medical care diminishes optimal treatment choices, negatively impacts prognosis, and increases medical costs. Various communication strategies have been employed to combat patient delay, with limited success. This study fills a gap in research informing those interventions by focusing on the portion of patient delay occurring after symptoms have been assessed as a sign of illness and the need for medical care has been determined. We used CHAID segmentation analysis to produce homogeneous segments from the sample according to the propensity to avoid medical care. CHAID is a criterion-based predictive cluster analysis technique. CHAID examines a variety of characteristics to find the one most strongly associated with avoiding doctor visits through a chi-squared test and assessment of statistical significance. The characteristics identified then define the segments. Fourteen segments were produced. Age was the first delineating characteristic, with younger age groups comprising a greater proportion of avoiders. Other segments containing a comparatively larger percent of avoiders were characterized by lower income, lower education, being uninsured, and being male. Each segment was assessed for psychographic properties associated with avoiding care, reasons for avoiding care, and trust in health information sources. While the segments display distinct profiles, having had positive provider experiences, having high health self-efficacy, and having an internal rather than external or chance locus of control were associated with low avoidance among several segments. Several segments were either more or less likely to cite time or money as the reason for avoiding care. And several older aged segments were less likely than the remaining sample to trust the government as a source for health information. Implications for future research are discussed.