Relationships between perceptions of barriers and self-management adherence, and differences in learning preferences of patients with chronic conditions

Research on the barriers to self-management adherence in chronic care rarely addresses the learning and performance support patients need to improve their adherence to treatment and key activities. This correlational study investigated the relationships between patients\u27 perceptions of barriers and adherence to key self-management activities, and the connection between patient demographics and barriers and adherence. A survey containing questions of research interest was administered through Qualtrics to a sample of adults being diagnosed or at risk of chronic diseases draw from a local health care institution. Valid responses (n=420) entered into the data analyses. Fourteen items selected from chronic care and performance support were utilized as measures of barriers, and most of them were found significantly correlated with adherence. A factor analysis was employed to thoroughly examine the dimensions of barriers and yielded three sub-scales of barriers: (1) Lack of performance support and poor communications, (2) Lack of capabilities, or physical and psychological obstacles accompanied by chronic conditions, and (3) Lack of time, motivation, and support from family. Regression models incorporated Factor (1) and (2), which accounted for a significant portion of variances in adherence to two key self-management activities. No significant correlation was observed between demographics and adherence, while some demographic items were associated with perceptions of barriers. Gender was the only demographic that showed significant difference in adherence to exercise. However, age, gender, education and income all played a role in the group differences in learning preferences. Findings from this study could further the understanding of barriers to adherence, help inform the design of chronic care education, align patients\u27 needs and preferences with the selection of technologies and interventions, and eventually improve the design of learning and performance support interventions to self-management