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Associations Between Sleep and Personality Factors Among Patients Living With Coronary Artery Disease
Anna Kjellsdotter1, Ulla Edéll-Gustafsson, Pia Yngman-Uhlin
1Anna Kjellsdotter, PhD, RN Research Manager, Research and Development Centre, Skaraborg Hospital Skövde, Sweden. Research and Development Centre, Skaraborg Hospital, Skövde, Sweden. Ulla Edéll-Gustafsson, PhD, RN, CCRN Professor Emeritus, Department of Medical and Health Sciences, Division of Nursing Sciences, Faculty of Health Sciences, Linköping University, Sweden. Pia Yngman-Uhlin, PhD, RN Associate Professor, Research & Development Unit, and Department of Medicine and Health Sciences, Linköping University, Sweden.
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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