METHODS AND ANALYSIS: A living systematic review will be conducted which includes an initial systematic review and bimonthly review updates. Searching and screening for the review and subsequent updates will be done in four streams: a systematic search of six databases, grey literature review, preprint review and citizen sourcing. The screening will be done by a minimum of two reviewers at title/abstract and full-text in Covidence, a systematic review management software. Data will be extracted across predefined fields in an excel spreadsheet that includes information about article characteristics, context and population, community engagement approaches, and outcomes. Synthesis will occur using the convergent integrated approach. We will explore the potential to quantitatively synthesise primary outcomes depending on heterogeneity of the studies.
ETHICS AND DISSEMINATION: The initial review and subsequent bimonthly searches and their results will be disseminated transparently via open-access methods. Quarterly briefs will be shared on the reviews' social media platforms and across other interested networks and repositories. A dedicated web link will be created on the Community Health-Community of Practice site for sharing findings and obtaining feedback. A mailing list will be developed and interested parties can subscribe for updates.
PROSPERO REGISTRATION NUMBER: CRD42022301996.
METHODS: A modified and validated Dundee Ready Education Environment Measure (DREEM) questionnaire was used to collect data regarding student perception of their educational environment.
RESULTS: The mean DREEM scores for three time periods were in the accepted positive range of 101 to 150 indicating that most of the students perceived the changes positively. The results indicated that most students preferred blended learning over online learning or face-to-face learning alone. Areas where students were unsatisfied with their learning environment that need improvement were identified by poor item-wise scores.
CONCLUSION: Strategic remedial measures for these concerns need to be developed to improve the quality of education received by the students. However, the results of our study indicated that most of the students were able to adapt positively to the new education environment due to the change in the circumstances during COVID.
CASES: In Malaysia, until end of February 2020, there were four COVID-19 paediatric cases with ages ranging from 20 months to 11 years. All four cases were likely to have contracted the virus in China. The children had no symptoms or mild flu-like illness. The cases were managed symptomatically. None required antiviral therapy.
DISCUSSION: There were 2 major issues regarding the care of infected children. Firstly, the quarantine of an infected child with a parent who tested negative was an ethical dilemma. Secondly, oropharyngeal and nasal swabs in children were at risk of false negative results. These issues have implications for infection control. Consequently, there is a need for clearer guidelines for child quarantine and testing methods in the management of COVID-19 in children.
OBJECTIVE: Therefore, this research aims to create a flexible mental health care architecture that leverages data-driven methodologies and ensemble machine learning models. The objective is to proficiently structure, process, and present data for positive computing. The adaptive data-driven architecture facilitates customized interventions for diverse mental disorders, fostering positive computing. Consequently, improved mental health care outcomes and enhanced accessibility for individuals with varied mental health conditions are anticipated.
METHOD: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, the researchers conducted a systematic literature review in databases indexed in Web of Science to identify the existing strengths and limitations of software architecture relevant to our adaptive design. The systematic review was registered in PROSPERO (CRD42023444661). Additionally, a mapping process was employed to derive essential paradigms serving as the foundation for the research architectural design. To validate the architecture based on its features, professional experts utilized a Likert scale.
RESULTS: Through the review, the authors identified six fundamental paradigms crucial for designing architecture. Leveraging these paradigms, the authors crafted an adaptive data-driven architecture, subsequently validated by professional experts. The validation resulted in a mean score exceeding four for each evaluated feature, confirming the architecture's effectiveness. To further assess the architecture's practical application, a prototype architecture for predicting pandemic anxiety was developed.
METHODS: SEIRV models were developed and validated using COVID-19 case and vaccination data from the Ministry of Health, Malaysia, from June 21, 2021 to July 21, 2021 to generate forecasts of COVID-19 cases from July 22, 2021 to December 31, 2021. Three scenarios were examined to measure the effects of vaccination on COVID-19 case trends. Scenarios 1 and 2 represented the trends taking into account the earliest and latest possible times of achieving full vaccination for 80% of the adult population by October 31, 2021 and December 31, 2021, respectively. Scenario 3 described a scenario without vaccination for comparison.
RESULTS: In scenario 1, forecasted cases peaked on August 28, 2021, which was close to the peak of observed cases on August 26, 2021. The observed peak was 20.27% higher than in scenario 1 and 10.37% lower than in scenario 2. The cumulative observed cases from July 22, 2021 to December 31, 2021 were 13.29% higher than in scenario 1 and 55.19% lower than in scenario 2. The daily COVID-19 case trends closely mirrored the forecast of COVID-19 cases in scenario 1 (best-case scenario).
CONCLUSIONS: Our study demonstrated that COVID-19 vaccination reduced COVID-19 case trends during the Delta outbreak. The compartmental models developed assisted in the management and control of the COVID-19 pandemic in Malaysia.
METHODS: The WoCKSS was developed with 20 and 31 items for knowledge and stigma domains, respectively, based on an extensive review of COVID-19 literature. Content validation was conducted by four experts using a content validation form to assess the relevancy of each item to the intended construct. Content Validity Index (CVI) was calculated to measure the agreement between the experts on the relevance of each item to the intended construct. Face validation was then conducted by randomly selecting 10 respondents from the manufacturing industry, who rated the clarity and comprehension of each item using a face validation form. The Item Face Validity Index (I-FVI) was calculated to determine the clarity and comprehension of each question, and only items with an I-FVI ≥ 0.83 were retained.
RESULTS: The WoCKSS achieved excellent content validity in both knowledge and stigma domains. Only 19 items from the knowledge domain and 24 items from the stigma domain were retained after CVI analysis. All retained items received a CVI score of 1.00, indicating perfect agreement among the experts. FVI analysis resulted in 17 items for the knowledge domain and 22 items for the stigma domain. The knowledge domain achieved a high level of agreement among respondents, with a mean I-FVI of 0.91 and a S-FVI/UA of 0.89. The stigma domain also showed high agreement, with a mean I-FVI of 0.99 and a S-FVI/UA of 0.86.
CONCLUSION: In conclusion, the WoCKSS demonstrated high content and face validity. However, further testing on a larger sample size is required to establish its construct validity and reliability.
METHODS: A cross-sectional study was conducted from 27 May 2020 to 17 June 2020 using the convenient sampling technique in the general population of Pakistan. Data were collected by designing an online questionnaire consisting of demographic information, knowledge, attitude perceptions, barriers, utilization, and the impact of the COVID-19 pandemic on telemedicine.
RESULTS: Of the 602 participants included in the study, 70.1% had heard about telemedicine, 54.3% had a good understanding of the definition of "telemedicine," 81.4% had not used telemedicine in the past, 29.9% did not know that telemedicine was available before the COVID-19 pandemic, and 70.4% responded that the COVID-19 pandemic had changed their attitudes toward telemedicine. Gender (p = 0.017) and family income (p = 0.027) had a significant association with the perception of the benefits of telemedicine.
CONCLUSION: The knowledge and usage of telemedicine are lacking due to inadequate awareness and technology. The need of the hour is to maximize the application of telemedicine to overcome the deficiencies of the healthcare system. Hence, it is essential to increase awareness through various means and develop an appropriate infrastructure to attain maximum benefits from telehealth services.