OBJECTIVE: The aim of this study was to explore public sentiments and emotions toward the LSSR and identify issues, fear, and reluctance to observe this restriction among the Indonesian public.
METHODS: This study adopts a sentiment analysis method with a supervised machine learning approach on COVID-19-related posts on selected media platforms (Twitter, Facebook, Instagram, and YouTube). The analysis was also performed on COVID-19-related news contained in more than 500 online news platforms recognized by the Indonesian Press Council. Social media posts and news originating from Indonesian online media between March 31 and May 31, 2020, were analyzed. Emotion analysis on Twitter platform was also performed to identify collective public emotions toward the LSSR.
RESULTS: The study found that positive sentiment surpasses other sentiment categories by 51.84% (n=1,002,947) of the total data (N=1,934,596) collected via the search engine. Negative sentiment was recorded at 35.51% (686,892/1,934,596) and neutral sentiment at 12.65% (244,757/1,934,596). The analysis of Twitter posts also showed that the majority of public have the emotion of "trust" toward the LSSR.
CONCLUSIONS: Public sentiment toward the LSSR appeared to be positive despite doubts on government consistency in executing the LSSR. The emotion analysis also concluded that the majority of people believe in LSSR as the best method to break the chain of COVID-19 transmission. Overall, Indonesians showed trust and expressed hope toward the government's ability to manage this current global health crisis and win against COVID-19.
OBJECTIVES: To assess the prevalence of depression, anxiety, and stress as well as identify predictors among recovered COVID-19 patients after more than six months of being discharged in Dong Thap Province, Vietnam.
MATERIAL AND METHODS: The cross-sectional study was conducted among 549 eligible participants recruited by stratified sampling. Data was collected using the depression, anxiety and stress scale - 21 items had Content Validity Index = 0.9, and Cronbach's alpha for depression, anxiety and stress sub-scales were 0.95, 0.81, and 0.86, respectively. Descriptive statistics were used to measure the prevalence levels and distribution of characteristics of the participant, while factors influencing depression, anxiety, and stress were predicted using binary logistic regression.
RESULTS: The overall prevalence of depression, anxiety, and stress were 24.8% (95% CI: 21.2-28.6), 41.5% (95% CI: 37.4-45.8), and 25.3% (95% CI: 21.7-29.2), respectively. The predictors of depression were living in urban area (OR = 1.97; 95% CI: 1.27-3.08), holding a bachelor's degree (OR:3.51; 95% CI: 1.13-10.8), having a high monthly income (OR: 2.57; 95% CI: 1.03-6.38), diabetes (OR: 2.21; 95% CI: 1.04-4.68), heart disease (OR: 3.83; 95% CI: 1.79-8.17), respiratory disease (OR: 3.49; 95% CI: 1.24-9.84), and diarrhea (OR: 4.07; 95% CI: 1.06-15.6). Living in the urban area (OR: 1.57; 95% CI: 1.07-2.29), having sleep disturbance (OR: 2.32; 95% CI: 1.56-3.46), and fatigue (OR: 1.57; 95% CI: 1.03-2.39) were predictors for anxiety. Having respiratory disease (OR: 3.75; 95% CI: 1.47-9.60) or diarrhea (OR: 4.34; 95% CI: 1.18-15.9) were predictors of stress.
CONCLUSION: People who have recovered from COVID-19 should be assessed for symptoms of depression, anxiety, and stress. Primary healthcare providers should develop interventions to support their recovery.
METHODS: This cross-sectional study took place at the Sarawak Heart Centre's geriatric department from July 1, 2021, to April 30, 2022. Convenient sampling included all TELEG-enrolled patients during this period, to achieve minimum sample size of 148. TELEG's utilization was assessed in terms of medication therapy and treatment plan optimization, as well as enhanced healthcare accessibility. Participants' acceptance of TELEG was measured using the Service User Technology Acceptability Questionnaire (SUTAQ) administered through Google Forms. Descriptive statistics percentages illustrated the proportion of participants who found TELEG moderately to highly acceptable. Associations between baseline characteristics and overall acceptance were explored through bivariate analyses, including Pearson's correlation test, independent t-test, and ANOVA. The influence of six SUTAQ dimensions on overall acceptance, multivariable linear regression using enter method was employed. Statistical significance was determined by p-values less than 0.5.
RESULTS: Among 180 geriatric patients enrolled in TELEG during the study period, 149 agreed to participate. TELEG led to medication therapy optimization for 88.6% of participants, primarily involving dose adjustment (44.7%), de-prescribing (31.8%), and prescribing (15.9%). Additionally, 53.8% received treatment plan optimization, predominantly in the form of self-care education (56.3%), referrals for further treatment (33.8%), additional laboratory investigations (29.6%), and increased monitoring (26.8%). Among those educated in self-care (n = 40), dietary intake (27.5%), lower limb exercise (25.0%), and COVID-19 vaccination (12.5%) were the most common topics. All participants expressed moderate to high acceptance of TELEG (mean = 4.9, SD = 0.65, on a scale of 1 to 6). Notably, care personnel concern (B = 0.256; p
METHODS: Medical records of hospitalized children from January 2020 to June 2021 with acute respiratory illness who received a FilmArray RP for respiratory pathogens were reviewed and compared with data from diagnosis-matched patients without receiving the test.
RESULTS: In total, 283 patients and 150 diagnosis-matched controls were included. Single pathogen was detected in 84.3% (193/229) of the patients. The most common pathogen was human rhinovirus/enterovirus (31.6%, 84/266), followed by respiratory syncytial virus (18.8%, 50/266) and adenovirus (15%, 40/266). Although antimicrobial days of therapy (DOT) was significantly longer in FilmArray group than the control [7.1 ± 4.9 days vs 5.7 ± 2.7 days, P = 0.002], the former showed a higher intensive care unit (ICU) admission rate (3.9% vs 0%; P = 0.010). All ICU admissions were in FilmArray RP-positive group. There was no difference in antimicrobial DOT between FilmArray RP-positive and the negative groups, in all admissions, even after excluding ICU admissions. Antimicrobial DOT was shorter in the positive than negative group in patients with lower respiratory tract infections without admission to ICU [median (IQR): 6 (4-9) days vs 9 (4-12) days, P = 0.047].
CONCLUSIONS: Shorter antimicrobial DOTs were identified in children with lower respiratory tract infection admitted to general pediatric ward and with an identifiable respiratory pathogen, indicating a role of the multiplex PCR in reducing antimicrobial use for children with respiratory tract infection.
CONCLUSIONS: PFA may be useful in helping frontline staff manage stress associated with the increased workload and general anxiety relating to the pandemic.
PRACTICE IMPLICATIONS: It is recommended all staff members, especially those involved in frontline duty, to be provided PFA.
METHODS: This is an open labelled interventional study of a virtual brief psychosocial intervention, called SANUBARI. The program was conducted among COVID-19 patients hospitalized in the COVID-19 wards of two centres from May 2020 until August 2020. Inclusion criteria include patients aged eighteen years and above, diagnosed with COVID-19, medically stable, speaking and reading Bahasa Melayu or English. All study subjects attended two sessions on OHP via telecommunication method and answered questionnaires (General Self-Efficacy (GSE) Scale, Patient Health Questionnaire and Generalized Anxiety Disorder Questionnaire) via computer-assisted self-interview. Data collection was done before the start of the intervention, at the end of the intervention and a month post-intervention.
RESULTS: A total of 37 patients were recruited and more than half of the subjects were males (62.2%), single (75.5%) and from the Malay ethnicity (78.4%). Seventy-three per cent of subjects had received tertiary education, and most of them were students reflecting a higher unemployment status (73%). Most subjects have no comorbid chronic medical illness (89.2%), and none has a comorbid psychiatric illness. Comparison of the GSE score across 3-time points (preintervention, immediate post-intervention and a month postintervention) showed statistically significant improvement in the mean total GSE score immediate and a month postintervention as compared to the pre-intervention; from mean total GSE score of 29.78 pre-intervention to 34.73 (mean difference 4.946, 95% Confidence Interval 95%CI: 3.361, 6.531) immediate post-intervention and 33.08 (mean difference 3.297, 95%CI: 1.211, 5.348) a month post intervention. There was no significant association between the socio-demographic or clinical data, depressive and anxiety symptoms, and changes in GSE scores over three time points.
CONCLUSION: COVID-19 patients improved their self-efficacy levels after the virtual brief OHP intervention, and it maintained a month post-intervention, protecting them from psychological stress and ultimately enhances wellbeing during this coronavirus pandemic.
METHODS: A descriptive cross-sectional study was conducted on hospitalised COVID-19 patients from April 2021 to June 2021 in a tertiary care centre. Ethical approval was taken from the Institutional Review Committee (Reference number: 2078/79/05). The hospital data were collected in the proforma by reviewing the patient's medical records during the study period of 2 months. Convenience sampling was used. Point estimate and 95% Confidence Interval were calculated.
RESULTS: Among 106 hospitalised COVID-19 patients, the prevalence of antibiotic use was 104 (98.11%) (95.52-100, 95% Confidence Interval). About 74 (71.15%) of patients received multiple antibiotics. The most common classes of antibiotics used were cephalosporins, seen in 85 (81.73%) and macrolides, seen in 57 (54.81%) patients.
CONCLUSIONS: The prevalence of antibiotic use among hospitalised COVID-19 patients was found to be higher when compared to other studies conducted in similar settings.
KEYWORDS: antibiotics; bacterial infection; co-infection; COVID-19.