Objective To systematically catalogue review studies on digital health to establish extent of evidence on quality healthcare and illuminate gaps for new understanding, perspectives and insights for evidence-informed policies and practices. Methods We systematically searched PubMed database using sensitive search strings. Two reviewers independently conducted two-phase selection via title and abstract, followed by full-text appraisal. Consensuses were derived for any discrepancies. A standardized data extraction tool was used for reliable data mining. Results A total of 54 reviews from year 2014 to 2021 were included with notable increase in trend of publications. Systematic reviews constituted the majority (61.1%, (37.0% with meta-analyses)) followed by scoping reviews (38.9%). Domains of quality being reviewed include effectiveness (75.9%), accessibility (33.3%), patient safety (31.5%), efficiency (25.9%), patient-centred care (20.4%) and equity (16.7%). Mobile apps and computer-based were the commonest (79.6%) modalities. Strategies for effective intervention via digital health included engineering improved health behaviour (50.0%), better clinical assessment (35.1%), treatment compliance (33.3%) and enhanced coordination of care (24.1%). Psychiatry was the discipline with the most topics being reviewed for digital health (20.3%). Conclusion Digital health reviews reported findings that were skewed towards improving the effectiveness of intervention via mHealth applications, and predominantly related to mental health and behavioural therapies. There were considerable gaps on review of evidence on digital health for cost efficiency, equitable healthcare and patient-centred care. Future empirical and review studies may investigate the association between fields of practice and tendency to adopt and research the use of digital health to improve care.
Formative assessments are commonly being mixed up with summative assessments which provide feedback. The ambiguity leads to a loss of distinction between the two. This blending is in direct contrast to the best practice of education, which advocates clarity of formative and summative function as a precursor to a quality assessment. In this commentary, we emphasise the non-credit bearing as the discriminatory feature, which illuminates the formative purpose of an assessment. We begin by revisiting the history from the time of the founding scholars who conceptualised formative and summative ideas. Subsequently, we compare it with the contemporary practice of assessment. Then we elucidate the philosophical underpinning of formative assessment and how the future of education relies on education, which move away from a pure exam-oriented focus of the curriculum. Finally, we relate the revolutionary concept of formative assessment with personalised education as the key curriculum design of tomorrow’s education.
Delivery and implementation strategies are key to curriculum success. There is growing evidence that team-based learning (TBL) is an effective way of interactive teaching. TBL is a method that uses learning teams to enhance student engagement and quality of learning. Individual accountability for out-of-class reading is followed by individual and group assessment. In-class application exercises, which is the hallmark of team-based learning promotes both learning and team development. TBL uses educational principles of transforming traditional content into application of knowledge and problem solving skills in an interactive learning environment. To experience the structural framework and to determine the students' perception about TBL in clinical setting of MBBS program in a Malaysian medical school. A total of 120 students assigned to 22 small subgroups of 5-6 per group underwent a number of TBL sessions delivered in three phases. In Phase I, students were assigned reading material. In Phase II, students were assessed through One Best Answer (OBA) items for individual and group readiness assessment test as individual readiness assessment test (IRAT) and group readiness assurance test (GRAT) respectively followed by a mini-lecture. In Phase III, in-class application of learning activity was performed. Finally, peer assessment evaluated the contribution of peer in TBL. A TBL Classroom Evaluation Inventory (TBLCEI) developed to probe student's perception of TBL, comprised of 40 items composite scale with Cronbach's alpha at 0.881. In addition, students were asked to provide their estimated grade in end of the posting assessment. Grades were categorised into excellent pass >85%, high pass 70%-84%; average to good pass 50%-69% and fail <50%. These grades were measured against students' TBLCEI survey score using analysis of variance (ANOVA). Results were considered significant at p < 0.05. Results of one-way analysis of TBLCEI scores differed significantly across four estimated end of posting achievers groups, F (3,116) = 52.279, p < 0.001. Bonferroni's procedure of multiple comparisons indicated that mean value of TBLCEI score of excellent pass significantly higher [70.90 (3.684)] than high pass [66.57 (3.625)], average to good pass [60.42 (3.583)] and fail [57.67 (5.626)] at p < 0.001. It is concluded that medical students favourably liked TBL for interactive learning irrespective of their grades. A positive response for TBL from students is encouraging to consider
Background: There is a need to analyze a worldwide database of the coronavirus disease of 2019 (COVID-19) pandemic.This may prove valuable to facilitate better strategies and planning on prevention, screening, surveillance, early diagnosis, containment and treatments. Method: We extracted 14,259 case reports of COVID-19 dated 11th November 2019 to 18th March 2020 from Johns Hopkins University Repository Online Databaseof 58 countries. After extensive data preprocessing, a multi-disciplinary expert researcherthen conducted series of vetting to categorizefree-text description of symptoms into discreet standardizedcategories.Continuous variables were presented by using median and inter-quartile range whereas categorical variables were presented by frequency and percentage. Result: A total of 2191 cases (15.4%) were included for demographic analysis. The median age was46 years (IQR26 years) with 787 (35.9%) cases involved patients aged of 60 and above while patients less than18 years of age were reported in 79 (3.6%) cases. Majority of the patients were males (n=1227, 56.7%). There were a total of 20standardized categories ofCOVID-19symptoms.The most prevalent were fever (74.8%), nonproductive cough (42.2%), fatigue (13.1%), sore throat (12.8%) and shortness of breath (11.7%). Other symptoms with frequency of more than 1% were chest discomfort, nasal congestion, muscular pain, chills and rigors, headache, diarrhoea, expectoration and joint pain. Other more uncommon symptoms reported include loss of appetite, conjunctivitis, toothache and abdominal pain. Asymptomatic manisfestations were reported in 8 cases (1.0%).All population are susceptible to COVID-19 especially the older age group. There were 20 standardized categories of symptoms wherefever, non-productive cough, fatigue, sore throat and shortness of breath were the most commonly reported. Conclusion: Findings of this study contribute to a deeper understanding on COVID-19 and may prove useful for researchers to better-design screening and surveillance strategies via more accurate risk-prediction modelling. Bangladesh Journal of Medical Science Vol. 21 No. 03 July’22 Page: 702-709
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