METHODS: Seventy-seven medical doctors and eighty nurses answered a self-administered questionnaire designed to capture demographic data and information regarding abbreviation use in medical practice. Comparisons were made between doctors and nurses with regards to frequency and reasons for using abbreviations; from where abbreviations were learned; frequency of encountering abbreviations in medical practice; prevalence of medical errors due to misinterpretation of abbreviations; and their ability to correctly interpret commonly used abbreviations.
RESULTS: The use of abbreviations was highly prevalent among doctors and nurses. Time saving, avoidance of writing sentences in full and convenience, were the main reasons for using abbreviations. Doctors learned abbreviations from fellow doctors while nurses learned from fellow nurses and doctors. More doctors than nurses reported encountering abbreviations. Both groups reported no difficulties in interpreting abbreviations although nurses reported often resorting to guesswork. Both groups felt abbreviations were necessary and an acceptable part of work. Doctors outperformed nurses in correctly interpreting commonly used standard and non-standard abbreviations.
CONCLUSION: The use of standard and non-standard abbreviation in clinical practice by doctors and nurses was highly prevalent. Significant variability in interpretation of abbreviations exists between doctors and nurses.
METHODS: Fifty overweight/obese individuals aged 22-29 years were assigned to either no-exercise control (n=25) or HIIT (n=25) group. The HIIT group underwent a 12-week intervention, three days/week, with intensity of 65-80% of age-based maximum heart rate. Anthropometric measurements, homeostatic model of insulin resistance (HOMA-IR) and gene expression analysis were conducted at baseline and post intervention.
RESULTS: Significant time-by-group interactions (p<0.001) were found for body weight, BMI, waist circumference and body fat percentage. The HIIT group had lower body weight (2.3%, p<0.001), BMI (2.7%, p<0.001), waist circumference (2.4%, p<0.001) and body fat percentage (4.3%, p<0.001) post intervention. Compared to baseline, expressions of PGC-1∝ and AdipoR1 were increased by approximately three-fold (p=0.019) and two-fold (p=0.003) respectively, along with improved insulin sensitivity (33%, p=0.019) in the HIIT group.
CONCLUSION: Findings suggest that HIIT possibly improved insulin sensitivity through modulation of PGC-1∝ and AdipoR1. This study also showed that improved metabolic responses can occur despite modest reduction in body weight in overweight/obese individuals undergoing HIIT intervention.