BackgroundPsychological factors, such as self-efficacy, are important in understanding the progress and management of coronary heart disease (CHD), and how patients make lifestyle modifications to compensate for the disease. The main objectives of this research are to assess patterns of cardiac self-efficacy (CSE) and quality of life (QoL) among CHD patients, and to determine the factors that affect their QoL.MethodsA cross-sectional descriptive correlational study was carried out between August 2016 and December 2016. We used a structured questionnaire completed by interviewers during face-to-face interviews with patients. Cardiac self-efficacy was evaluated using three scales: 1) the 5-item perceived efficacy in patient- physician interaction scale (PEPPI-5); 2) the self-efficacy for managing chronic diseases 6-item scale (SEMCD-6) and 3) Sullivan’s cardiac self-efficacy scale 13-items (SCSES). The 5-level version of the EuroQoL 5-dimensions questionnaire (EQ-5D-5 L), and Euroqol Visual Analogue Scale (EQ VAS) were used to evaluate health-related QoL (HRQoL) among CHD patients. Multiple binary logistic regression was carried out to evaluate the influence on the QoL score of demographic and medical characteristics, and self-efficacy factors.ResultsA total of 275 patients participated in our study. The patients’ mean age was 59.51 ± 1.005 years. The HRQoL was measured by the EQ-5D-5 L index score and EQ-VAS score; their means were 0.62 ± 0.16 and 57.44 ± 1.61, respectively. The QoL showed moderate positive correlations with the PEPPI-5 (r = 0.419; p-value < 0.001), SEMCD-6 (r = 0.419; p-value < 0.001), and SCSES score (r = 0.273; p-value < 0.001). Multiple binary logistic regression showed that only patients with higher PEPPI-5 score (odds ratio (OR) = 1.11; 95% confidence interval (CI) =1.01–1.22; p = 0.036), and higher SCSES score (OR = 1.10; 95% CI = 1.03–1.17; p = 0.004) were significantly associated with a high QoL score. Moreover, multiple binary logistic regression model showed that patients with higher numbers of medications (OR = 0.23; 95% CI = 0.07–0.78); p = 0.018) remained significantly associated with impaired QoL.ConclusionsLower levels of self-efficacy and poorer patient-physician interactions predicted poor HRQoL. Thus, health providers should be aware of these factors in CHD patients when trying to improve their QoL.

Background: Neonates frequently experience pain as a result of diagnostic or therapeutic interventions or as a result of a disease process. Neonates cannot verbalize their pain experience and depend on others to recognize, assess and manage their pain. Neonates may suffer immediate or long-term consequences of unrelieved pain. Accurate assessment of pain is essential to provide adequate management. Observational scales, which include physiological and behavioral responses to pain, are available to aid consistent pain management. Pain assessment is considered as the fifth vital sign. Objectives: Aims of the present study were (1) to compare two commonly cited neonatal pain assessment tools, Neonatal Pain, Agitation and Sedation Scale (N-PASS) and modified Pain Assessment Tool (mPAT), with regard to their psychometric qualities, (2) to explore intuitive clinicians' ratings by relating them to the tools' items and (3) to ensure that neonates receive adequate pain control. Methods: Two coders applied both pain assessment tools to 850 neonates while undergoing a painful or a stressful procedure. Each neonate was assessed before, during and after the procedure. The evaluation before and after the procedure was done using NPASS, while pain score during the procedure was assessed by mPAT. Analyses of variances and regression analyses were used to investigate whether tools could discriminate between the procedures and whether tools' items were predictors of pain severity. Results: Internal consistency, reliability and validity were high for both assessment tools. N-PASS tool discriminated between painful and stressful situations better than mPAT. There was no relation between the age of neonate and the pain score. Moreover, P-value was statistically significant between mPAT score and post procedural assessment score as well as between pre and post procedural assessment scores. Conclusion: Both assessment tools performed equally well regarding physiologic parameters. However, N-PASS makes it possible to assess pain during sedation. It was noticed that gaps exist between practitioner knowledge and attitude regarding neonatal pain.