BACKGROUND: Many studies have examined barriers to health care utilization, with the majority conducted in the context of specific populations and diseases. Less research has focused on why people avoid seeking medical care, even when they suspect they should go. OBJECTIVE: The purpose of the study was to present a comprehensive description and conceptual categorization of reasons people avoid medical care. DESIGN: Data were collected as part of the 2008 Health Information National Trends Survey, a cross-sectional national survey. PARTICIPANTS: Participant-generated reasons for avoiding medical care were provided by 1,369 participants (40% male; M age =48.9; 75.1% non-Hispanic white, 7.4% non-Hispanic black, 8.5% Hispanic or Latino/ a). MAIN MEASURES: Participants first indicated their level of agreement with three specific reasons for avoiding medical care; these data are reported elsewhere. We report responses to a follow-up question in which participants identified other reasons they avoid seeking medical care. Reasons were coded using a general inductive approach. KEY RESULTS: Three main categories of reasons for avoiding medical care were identified. First, over one-third of participants (33.3% of 1,369) reported unfavorable evaluations of seeking medical care, such as factors related to physicians, health care organizations, and affective concerns. Second, a subset of participants reported low perceived need to seek medical care (12.2%), often because they expected their illness or symptoms to improve over time (4.0%). Third, many participants reported traditional barriers to medical care (58.4%), such as high cost (24.1%), no health insurance (8.3%), and time constraints (15.6%). We developed a conceptual model of medical care avoidance based on these results. CONCLUSIONS: Reasons for avoiding medical care were nuanced and highly varied. Understanding why people do not make it through the clinic door is critical to extending the reach and effectiveness of patient care, and these data point to new directions for research and strategies to reduce avoidance.

The TRIRISK model offers both a novel conceptualization of health-related risk perceptions, and new measures that enhance predictive validity beyond that engendered by unidimensional and bidimensional models. The present findings have implications for the ways in which risk perceptions are targeted in health behavior change interventions, health communications, and decision aids.

This study suggests that e-cigarette use patterns are highly variable over a 1-year period. This analysis provides the first nationally representative estimates of transitions among US adult e-cigarette users. Future research, including additional waves of the PATH Study, can provide further insight into long-term patterns of e-cigarette use critical to understanding the net population health impact of e-cigarettes in USA.