METHODS: A cross sectional study was conducted among 2120 cancer patients in Peninsular Malaysia, between April 2016 to January 2017. All cancer patients aged 18 years old and above, Malaysian citizens and undergoing cancer treatment at government hospitals were approached to participate in this study and requested to complete a set of validated questionnaires. Inferential statistical tests such as t-test and one-way ANOVA were used to determine the differences between demographic variables, physical effects, clinical factors, psychological effects and self-esteem with the quality of life of cancer patients. Predictor(s) of quality of life were determined by using Multivariate linear regression models.

MATERIALS AND METHODS: A cross-sectional study was conducted among three secondary schools located in Kudat district, Sabah, Malaysia during the period from June until September 2012. The protocol of this study was approved by ethics committee of Management and Science University, Malaysia. The aims were explained and a consent form was signed by each participant. Respondents were chosen randomly from each school with the help of the headmasters. Self-administrated questionnaires, covering socio-demographic characteristics and general knowledge of lung cancer, were distributed. Once all 150 respondents completed the questionnaire, they passed it to their head master for collecting and recording. All the data were analyzed using Statistical Package for the Social Sciences (SPSS) version 13. ANOVA and t-test were applied for univariate analysis; and multiple linear regression for multivariate analysis.

RESULTS: A total of 150 male secondary school teachers participated in this study. Their mean age was 35.6 ∓ 6.5 (SD); maximum 50 and minimum 23 years old. More than half of the participants were Malay and married (52%, 79%; respectively). Regarding the knowledge about lung cancer, 57.3% of the participants mentioned that only males are affected by lung cancer. Some 70.7% mentioned that lung cancer can be transmitted from one person to another. More than half (56.7%) reported that lung cancer is not the leading cause of death in Malaysian males. As for risk factors, the majority reported that family history of lung cancer is not involved. However, 91.3% were aware that cigarettes are the main risk factor of lung cancer and more than half (52%) believed that second-hand smoking is one of the risk factor of lung cancer. More than half (51.3%) were not aware that asbestos, ionizing radiation and other cancer causing substances are risk factors for lung cancer. Quitting smoking, avoiding second-hand smoking and avoiding unnecessary x-ray image of the chest (53.3%, 96.0%, 87.3%; respectively) are the main preventive measures mentioned by the participants. For the factors that influence the participants knowledge, univariate and multivariate analysis showed that only race was significant.

METHODS: A quasi-experimental multiple time series was conducted starting in September 2017 and ending in June 2018. 140 nurses were sampled using the proportionate stratified random sampling technique; 132 were completed the study 67 the intervention group, while 65 in the control group.

RESULTS: There were no significant differences in nurses' job performance or commitment between the 2 groups (control and intervention). A repeated measure MANOVA test for both groups revealed that the interaction between group and time was statistically significant (F (4, 127) = 144.841; P = .001; Wilk's Λ = 0.180; η2 = .820), indicating that groups had a significantly different pattern of job performance and commitment over time. A repeated test The MANCOVA test for both groups across time revealed significant differences in nurses' job performance and nurses' commitment at a less than 0.05 significance level (F (2127) = 320.724; P = .001; Wilk's Λ = 0.165; η2 = 0.835), and the overall effect of time was significant for all dependent variables (F (4125) = 36.879; P = .001; Wilk's Λ = 0.459; η2 = 0.541).

METHODS: We analysed plasma and urine samples of 50 stable CAD patients and 50 healthy controls using 1H NMR. Orthogonal partial least square discriminant analysis (OPLS-DA) followed by multivariate logistic regression (MVLR) models were developed to indicate the discriminating metabotypes. Metabolic pathway analysis was performed to identify the implicated pathways.

RESULTS: Both plasma and urine OPLS-DA models had specificity, sensitivity and accuracy of 100%, 96% and 98%, respectively. Plasma MVLR model had specificity, sensitivity, accuracy and AUROC of 92%, 86%, 89% and 0.96, respectively. The MVLR model of urine had specificity, sensitivity, accuracy and AUROC of 90%, 80%, 85% and 0.92, respectively. 35 and 12 metabolites were identified in plasma and urine metabotypes, respectively. Metabolic pathway analysis revealed that urea cycle, aminoacyl-tRNA biosynthesis and synthesis and degradation of ketone bodies pathways were significantly disturbed in plasma, while methylhistidine metabolism and galactose metabolism pathways were significantly disturbed in urine. The enrichment over representation analysis against SNPs-associated-metabolite sets library revealed that 85 SNPs were significantly enriched in plasma metabotype.