METHODS: A randomized controlled trial was conducted from December 2014 to April 2015. The home blood pressure monitoring group used an automatic blood pressure device along with standard hypertension outpatient care. Patients were seen at baseline and after 2 months. Medication adherence was measured using a novel validated Medication Adherence Scale (MAS) questionnaire. Office blood pressure and MAS were recorded at both visits. The primary outcomes included evaluation of mean office blood pressure and MAS within groups and between groups at baseline and after 2 months.
RESULTS: Mean changes in systolic blood pressure (SBP) and diastolic blood pressure (DBP) and MAS differed significantly within groups. The home blood pressure monitoring group showed greater mean changes (SBP 17.6 mm Hg, DBP 9.5 mm Hg, MAS 1.5 vs. SBP 14.3 mm Hg, DBP 6.4 mm Hg, MAS 1.3), while between group comparisons showed no significant differences across all variables. The adjusted mean difference for mean SBP was 4.74 (95% confidence interval [CI], -0.65 to 10.13 mm Hg; P=0.084), mean DBP was 1.41 (95% CI, -2.01 to 4.82 mm Hg; P=0.415), and mean MAS was 0.05 (95% CI, -0.29 to 0.40 mm Hg; P=0.768).
CONCLUSION: Short-term home blood pressure monitoring significantly reduced office blood pressure and improved medication adherence, albeit similarly to standard care.
OBJECTIVE: This study aims to evaluate the effectiveness of carbon monoxide measurement feedback and the standard brief motivation adopted to encourage the smoker to quit.
METHODS: A single-blind, cluster randomised controlled trial was conducted at ten tertiary colleges in Selangor. The study recruited young adult smokers at the precontemplation and contemplation stages. The subjects in the control group received a standard brief motivational strategy. On the other hand, the intervention group received additional carbon monoxide measurement and a motivational feedback module. A follow up was conducted at the first, third and sixth month to measure changes in smoking cessation stage. Subsequently, the secondary outcomes of a mean number of cigarette consumption and quit smoking attempt were analysed. A total of 160 subjects were required to detect the expected difference of 17% in primary outcomes between the groups. This study utilised Generalised Estimating Equations (GEE) to handle the clustering effects.
CONCLUSION: Biomedical risk assessment feedback mechanism by using carbon monoxide is a promising aid to motivate the smoker to quit. This mechanism is a relatively easy, quick and non-invasive technique. Thus, it can be utilised as a reinforcement relating to the harmful effect of smoking. Besides, it can also increase the smokers' selfefficacy and decisional balance to adopt behavioural changes.
METHODS: A cross-sectional study was conducted among 295 medical doctors and staff nurses from June to December 2015. Simple random sampling was applied. The data were collected using a self-administered questionnaire and analyzed using IBM SPSS ver. 22.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics and logistic regression analysis were performed.
RESULTS: The prevalence of unsuccessful exclusive breastfeeding among the study participants was 58.3%. Mothers who preferred formula milk (odds ratio [OR], 4.40; 95% confidence interval [CI], 1.45-13.31) delivered via lower segment cesarean section (OR, 2.31; 95% CI, 1.07-4.98) and produced inadequate breast milk (OR, 4.06; 95% CI, 2.40- 6.89) were significantly associated with unsuccessful exclusive breastfeeding.
CONCLUSION: The prevalence of unsuccessful exclusive breastfeeding among the study participants was high. Maternal characteristics such as preference towards formula milk, mode of delivery and adequacy of breast milk must be assessed to prevent unsuccessful exclusive breastfeeding among healthcare providers.
DESIGN AND METHODS: The model is an improvement of the susceptible, infected, recovery, and death (SIRD) compartmental model. The epidemiological parameters of the infection, recovery, and death rates were formulated as time dependent piecewise functions by incorporating the control measures of lockdown, social distancing, quarantine, lockdown lifting time and the percentage of people who abide by the rules. An improved SIRD model was solved via the 4th order Runge-Kutta (RK4) method and 14 unknown parameters were estimated by using Nelder-Mead algorithm and pattern-search technique. The publicly available data for COVID-19 outbreak in Malaysia was used to validate the performance of the model. The GUI-based SIRD model was developed to simulate the number of active cases of COVID-19 over time by considering movement control order (MCO) lifted date and the percentage of people who abide the rules.
RESULTS: The simulator showed that the improved SIRD model adequately fitted Malaysia COVID-19 data indicated by low values of root mean square error (RMSE) as compared to other existing models. The higher the percentage of people following the SOP, the lower the spread of disease. Another key point is that the later the lifting time after the lockdown, the lower the spread of disease.
CONCLUSIONS: These findings highlight the importance of the society to obey the intervention measures in preventing the spread of the COVID-19 disease.