Associations Between Sleep and Personality Factors Among Patients Living With Coronary Artery Disease

冠状动脉疾病 人格 疾病 睡眠(系统调用) 内科学 医学 心脏病学 临床心理学 心理学 社会心理学 操作系统 计算机科学
作者
Anna Kjellsdotter,Ulla Edéll‐Gustafsson,Pia Yngman‐Uhlin
出处
期刊:Journal of Cardiovascular Nursing [Lippincott Williams & Wilkins]
卷期号:35 (6): 568-575 被引量:3
标识
DOI:10.1097/jcn.0000000000000691
摘要

Background Insomnia symptoms have become increasingly common in patients with coronary artery disease (CAD). Increasing evidence suggests comorbidity between personality traits and health status. Considering personality traits may act as a predisposition for future illness; this state may influence sleep quality and it appears to precipitate cardiac events in high-risk patients. Objective The aim of this study was to investigate self-reported sleep deficiency in relation to vicious cycle of sleeplessness (VCS) behavior, hyperarousal behavioral trait (H-personality), and type D personality traits in patients with CAD and in a population-based group. Furthermore, our aim was to explore the association of VCS behavior with H-personality trait and type D personality. Finally, we investigated to what extent type D personality can explain self-reported too little sleep in patients with CAD. Methods An observational case-control design was applied comprising 859 patients in cardiac outpatient care and 859 participants from a population-based group. Questionnaires assessing VCS behavior, H-personality, type D personality, and perceptions of too little sleep were used. Results Statistically significant higher scores of a hyperarousal and sleeplessness behavior were revealed for those with too little sleep compared with those with sufficient sleep in both the patient and the population-based group. Age, female gender, or sleeplessness behavior significantly predicted too little sleep ( P < .001). Conclusions The current study highlights the advantage of studying heterogeneity in patients with CAD from a person-centered perspective with focus to identify distressed individuals in order to prevent or treat sleep deficiency. A cluster of factors may be a more accurate predictor of patient-reported outcomes than a single psychosocial factor.
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