ABSTRACT
Cancer is one of the leading causes of morbidity and mortality worldwide. There are various detrimental symptoms experienced by a cancer patient due to the disease and the undergoing treatment which adversely affects the Quality of Life (QOL) in these patients. Therefore, QOL and its evaluation have turned out to be progressively vital in the health care system. Hence, the aim of our study was to develop a predictor model to predict the QOL in cancer patients receiving chemotherapy. The study was carried out in the Department of Radiotherapy and Oncology, Kasturba hospital, Manipal, a tertiary care hospital. Predictor model was developed to predict the Quality of Life Scores (QOLS) using multivariate regression analysis. A total of 387 patients participated in the study. Mean age of the patients was 50.85 ± 11.82 years (95% CI, 49.66-52.03). In our study, 16.54% had poor global health status/QOL, 72.35% had average and 11.11% had a high global health status/QOL. A significant difference was found in the QOLS based on the age group, site of cancer, drugs used in treatment of cancer, age as a predisposing factor and organ system affected due to ADRs (respiratory system, sensory system, skin and appendages). In the predictor model, the Coefficient of determination R-square (R2) was found to be 0.3267 indicating that 32.67% of the variation in the ‘quality of life score’ is explained by the independent variables included in the model. The F (45, 341) = 3.67, p < 0.001 indicating the overall significance of the regression model. Thus, the study showed that there are various predictors that can assess the QOL in cancer patients which can further serve as a guide to implement timely interventions to improve patients QOL.
ABSTRACT
Background.The undergraduate curriculum at our institution is divided system-wise into four blocks, each block ending with theory and objective structured practical examination (OSPE). The OSPE in Physiology consists of 12 stations, and a conventional minimum score to qualify is 50%. We aimed to incorporate standard setting using the modified Angoff method in OSPE to differentiate the competent from the non-competent student and to explore the possibility of introducing standard setting in Physiology OSPE at our institution. Methods. Experts rated the OSPE using the modified Angoff method to obtain the standard set cut-off in two of the four blocks. We assessed the OSPE marks of 110 first year medical students. Chi-square test was used to compare the number of students who scored less than standard set cut-off and conventional cut-off; correlation coefficient was used to assess the relation between OSPE and theory marks in both blocks. Feedback was obtained from the experts. Results. The standard set was 62% and 67% for blocks II and III, respectively. The use of standard set cut-off resulted in 16.3% (n=18) and 22.7% (n=25) students being declared unsuccessful in blocks II and III, respectively. Comparison between the number, who scored less than standard set and conventional cut-off was statistically significant (p=0.001). The correlation coefficient was 0.65 (p=0.003) and 0.52 (p<0.001) in blocks II and III, respectively. The experts welcomed the idea of standard setting. Conclusion. Standard setting helped in differentiating the competent from the non-competent student, indicating that standard setting enhances the quality of OSPE as an assessment tool. Natl Med J India 2016;29:160–2