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Effect of constraint-induced music therapy in idiopathic sudden sensorineural hearing loss: A systematic review and meta-analysis

Vasiwala RA, Elhariri SY, Teng CL, Mohamad I

Noise Health, 2022;24(113):75-81.
PMID: 35900392 DOI: 10.4103/nah.nah_33_21

BACKGROUND: Idiopathic sudden sensorineural hearing loss (ISSNHL) is commonly encountered in audiologic and otolaryngologic practice. Constraint-induced music/sound therapy (CIMT) is characterized by the plugging of the normal ear (constraint) and the simultaneous, stimulation of the affected ear with music, which is based on a well-established neurorehabilitation approach. Corticosteroid therapy (CST) is the current mainstay of treatment. The prognosis for hearing recovery depends on many factors including the severity of hearing loss, age, and presence of vertigo.
OBJECTIVE: To analyze the effectiveness of CIMT with CST in ISSNHL.
METHODS: We performed a systematic search, using specific keywords relevant to our study, in PubMed, Cochrane Central Register of Controlled Trials, and additional sources of published trials till December 2020. We then screened all search results obtained according to our inclusion/exclusion criteria and performed a quality assessment on all studies using the Newcastle-Ottawa scale and using MedCalc, a meta-analysis was performed on suitable studies.
RESULTS: The recovery rates of three included nonrandomized studies were assessed at 1 to 3 months. A total of 229 (CST: 131, CST + CIMT: 98) patients were pooled for meta-analysis. The meta-analysis using the random-effect model found the relative risk of recovery rate within 3 months to be 1.213 (95% confidence interval 0.709-2.074), a result that is not statistically significant.
CONCLUSION: Although our analysis results do not demonstrate the noticeable effect of CIMT in ISSNHL, it can support be a gainful adjunct to CST for better hearing results than CST alone. Therefore, it needs further prospective randomized controlled multicenter trials with a large sample.

Matched MeSH terms: Humans
Prevalence of Traumatic Injuries to Primary Anterior Teeth among Children aged 2-6 Years in National Capital Region of Delhi, India

Sharma HK, Gupta K, Singh S

J Contemp Dent Pract, 2022 Jul 01;23(7):720-724.
PMID: 36440519

AIMS: The aim of this study was to assess subject wise and tooth wise distribution and prevalence of traumatic injuries to the anterior teeth of 2- to 6-year-old children.
MATERIALS AND METHODS: A cross-sectional survey was performed. Primary maxillary and mandibular anterior teeth of 1,800 children aged between 2 years and 6 years, who attended 20 pre-schools in National Capital Region Delhi, India, were examined by a single examiner, and a questionnaire was filled in person by the parent/guardian. Andreasen's classification was used to classify the traumatic injuries. The Chi-square test was used to statistically analyze the variation in traumatic dental injuries (TDIs) with age and gender. Multiple logistic regression was used to determine the influence of independent variables on the occurrence of TDIs.
RESULTS: The prevalence of TDIs was 17%. Significant and highly significant differences were found between boys and girls for cause and location of trauma (p < 0.05) and tooth type involved (p < 0.001) with boys being more prone to such injuries. The commonest cause of injury was due to falls and the location was playground. The teeth most commonly affected were the maxillary central incisors (36.9%) followed by maxillary lateral incisors (3.3%), and the least affected were the maxillary and mandibular canines (0.3%).
CONCLUSION: The prevalence of traumatic injuries to the anterior teeth in 2- to 6-year-old children in National Capital Region of Delhi, India, was 17%. There is a need to run educational programs to increase parents' awareness of the risks of dental trauma and emphasize preventive measures.
CLINICAL SIGNIFICANCE: Parents should be made aware of the widespread prevalence, risk factors, and consequences of trauma to primary dentition, so that they can seek appropriate care timely. The time elapsed between injury and dental care is of utmost importance.

Matched MeSH terms: Humans
Impact of increased digital use and internet gaming on nursing students' empathy: A cross-sectional study

Lee WL, Rambiar PNIMS, Rosli NQB, Nurumal MS, Abdullah SSS, Danaee M

Nurse Educ Today, 2022 Dec;119:105563.
PMID: 36150294 DOI: 10.1016/j.nedt.2022.105563

BACKGROUND: The COVID-19 restrictions and quarantines had led to increased dependence and usage of digital devices for various human activities and internet gaming to the extent of risking vulnerable individuals to develop addiction towards it. Little is known on such risks among populations of nursing students and its impact on their empathy skills or trait.
OBJECTIVE: Determining the impact of digital use and internet gaming on empathy of nursing students undergoing remote learning during closure of learning institutions nationwide.
DESIGN: Cross-sectional online survey was conducted from October to December 2020.
SETTINGS: Two established public institutions located in Malaysia.
PARTICIPANTS: A total of 345 nursing students pursuing diploma and bachelor nursing programs.
METHODS: Toronto Empathy Questionnaire (TEQ), Digital Addiction Scale (DAS) and Internet Gaming Disorder Scale-Short form (IGDS9-SF) were self-administered via Google Form™. Following principal component analysis of TEQ using IBM-SPSS™ (V-27), path analyses was performed using SmartPLS™ (V-3).
RESULTS: Despite the increased time spent on digital devices (∆ 2.8 h/day) and internet gaming (∆ 1 h/week) before and during the pandemic, the proportion of high digital users (1.4 %) and gamers (20.9 %) were low; and sizable ≈75 % had higher-than-normal empathy. Digital-related emotions and overuse of them were associated with lower empathy (β = -0.111, -0.192; p values < 0.05) and higher callousness (β = 0.181, 0.131; p values < 0.05); internet gaming addiction predicted callousness (β = 0.265, p

Matched MeSH terms: Humans
Multiclass tumor identification using combined texture and statistical features

Latif G, Bashar A, Awang Iskandar DNF, Mohammad N, Brahim GB, Alghazo JM

Med Biol Eng Comput, 2023 Jan;61(1):45-59.
PMID: 36323980 DOI: 10.1007/s11517-022-02687-w

Early detection and diagnosis of brain tumors are essential for early intervention and eventually successful treatment plans leading to either a full recovery or an increase in the patient lifespan. However, diagnosis of brain tumors is not an easy task since it requires highly skilled professionals, making this procedure both costly and time-consuming. The diagnosis process relying on MR images gets even harder in the presence of similar objects in terms of their density, size, and shape. No matter how skilled professionals are, their task is still prone to human error. The main aim of this work is to propose a system that can automatically classify and diagnose glioma brain tumors into one of the four tumor types: (1) necrosis, (2) edema, (3) enhancing, and (4) non-enhancing. In this paper, we propose a combined texture discrete wavelet transform (DWT) and statistical features based on the first- and second-order features for the accurate classification and diagnosis of multiclass glioma tumors. Four well-known classifiers, namely, support vector machines (SVM), random forest (RF), multilayer perceptron (MLP), and naïve Bayes (NB), are used for classification. The BraTS 2018 dataset is used for the experiments, and with the combined DWT and statistical features, the RF classifier achieved the highest average accuracy whether for separated modalities or combined modalities. The highest average accuracy of 89.59% and 90.28% for HGG and LGG, respectively, was reported in this paper. It has also been observed that the proposed method outperforms similar existing methods reported in the extant literature.

Matched MeSH terms: Humans
Fulltext A Participatory, Needs-Based Approach to Breastfeeding Training for Confinement Centres

Foong SC, Foong WC, Tan ML, Ho JJ, Omer-Salim A

Int J Environ Res Public Health, 2022 Sep 01;19(17).
PMID: 36078639 DOI: 10.3390/ijerph191710914

With a focus on traditional practices rather than evidence-based practices, breastfeeding support is sub-optimal in confinement centres (CCs). We used a participatory, needs-based approach to develop a training module for CC staff adopting Kern's six-step approach as our conceptual framework. Of 46 identified CCs, 25 accepted our invitation to a dialogue aimed at establishing relationships and understanding their needs. An interactive training workshop was developed from the dialogue's findings. The workshop, attended by 32 CCs (101 participants), was conducted four times over a four-month period. Questions raised by the participants reflected deficits in understanding breastfeeding concepts and erroneous cultural beliefs. Correct answers rose from 20% pre-test to 51% post-test. Post-workshop feedback showed that participants appreciated the safe environment to ask questions, raise concerns and correct misconceptions. An interview conducted 14 months later showed that while some CCs improved breastfeeding support, others made no change due to conflict between breastfeeding and traditional postnatal practices, which was aggravated by a lack of support due to the COVID-19 pandemic. A participatory approach established a trustful learning environment, helping CCs appreciate the value of learning and adopting new concepts. However, cultural perceptions take time to change, hence continuous training and support are vital for sustained changes.

Matched MeSH terms: Humans
Fulltext In-Depth Review of Augmented Reality: Tracking Technologies, Development Tools, AR Displays, Collaborative AR, and Security Concerns

Syed TA, Siddiqui MS, Abdullah HB, Jan S, Namoun A, Alzahrani A, et al.

Sensors (Basel), 2022 Dec 23;23(1).
PMID: 36616745 DOI: 10.3390/s23010146

Augmented reality (AR) has gained enormous popularity and acceptance in the past few years. AR is indeed a combination of different immersive experiences and solutions that serve as integrated components to assemble and accelerate the augmented reality phenomena as a workable and marvelous adaptive solution for many realms. These solutions of AR include tracking as a means for keeping track of the point of reference to make virtual objects visible in a real scene. Similarly, display technologies combine the virtual and real world with the user's eye. Authoring tools provide platforms to develop AR applications by providing access to low-level libraries. The libraries can thereafter interact with the hardware of tracking sensors, cameras, and other technologies. In addition to this, advances in distributed computing and collaborative augmented reality also need stable solutions. The various participants can collaborate in an AR setting. The authors of this research have explored many solutions in this regard and present a comprehensive review to aid in doing research and improving different business transformations. However, during the course of this study, we identified that there is a lack of security solutions in various areas of collaborative AR (CAR), specifically in the area of distributed trust management in CAR. This research study also proposed a trusted CAR architecture with a use-case of tourism that can be used as a model for researchers with an interest in making secure AR-based remote communication sessions.

Matched MeSH terms: Humans
Antimicrobial betalains

Wijesinghe VN, Choo WS

J Appl Microbiol, 2022 Dec;133(6):3347-3367.
PMID: 36036373 DOI: 10.1111/jam.15798

Betalains are nitrogen-containing plant pigments that can be red-violet (betacyanins) or yellow-orange (betaxanthins), currently employed as natural colourants in the food and cosmetic sectors. Betalains exhibit antimicrobial activity against a broad spectrum of microbes including multidrug-resistant bacteria, as well as single-species and dual-species biofilm-producing bacteria, which is highly significant given the current antimicrobial resistance issue reported by The World Health Organization. Research demonstrating antiviral activity against dengue virus, in silico studies including SARS-CoV-2, and anti-fungal effects of betalains highlight the diversity of their antimicrobial properties. Though limited in vivo studies have been conducted, antimalarial and anti-infective activities of betacyanin have been observed in living infection models. Cellular mechanisms of antimicrobial activity of betalains are yet unknown; however existing research has laid the framework for a potentially novel antimicrobial agent. This review covers an overview of betalains as antimicrobial agents and discussions to fully exploit their potential as therapeutic agents to treat infectious diseases.

Matched MeSH terms: Humans
Fulltext Health motivations and perceived barriers are determinants of self-care behaviour for the prevention of hypertension in a Malaysian community

Tan PPS, Sandhu RS, Zain SM, Hall D, Tan NC, Lim HM, et al.

PLoS One, 2022;17(12):e0278761.
PMID: 36477162 DOI: 10.1371/journal.pone.0278761

INTRODUCTION: Self-care behaviour is fundamental in preventing hypertension in the general population. According to the Health Belief Model, health beliefs and perceptions influence the success in adopting disease prevention strategies. While factors influencing hypertension self-care behaviour have been examined previously in patient populations, they have not been assessed in the general community.
METHODS: This was a cross-sectional study conducted between 12 June 2020 to 26 July 2021. An online survey was administered via email and social media to Malaysians in the Selangor and Kuala Lumpur communities. Respondents were over 18 years old, without a formal diagnosis of hypertension. The survey evaluated hypertension knowledge, Health Belief Model constructs, self-care behaviour frequency, and motivators and barriers to self-care behaviour. Multiple linear regression was performed to determine the main predictors of self-care behaviour, and descriptive statistics were used to characterise motivators and barriers of each self-care behaviour.
RESULTS: Only health motivations (β = 0.217, p < 0.001) and perceived barriers (β = 0.571, p < 0.001) significantly influenced self-care behaviour. Maintaining a healthy diet, regular physical activity and blood pressure checks need to be improved in the community, particularly in reducing salt and calorie intake. Lack of time, limited choices and laziness are the biggest challenges that need to be tackled in adopting a healthy diet and an active lifestyle in the community. Many are ignorant towards their health status, therefore, do not prioritize blood pressure screenings, suggesting a need to enhance community blood pressure checks for early diagnosis of hypertension.
CONCLUSION AND IMPLICATIONS: Motivations and barriers were the main determinants of self-care behaviour in the Selangor and Kuala Lumpur community. Targeting these aspects of self-care behaviour should be considered when developing interventions and education programmes tailored to local cultural, environmental and personal factors, to more effectively reduce the hypertension prevalence and burden.

Matched MeSH terms: Humans
Fulltext DeepNC: a framework for drug-target interaction prediction with graph neural networks

Tran HNT, Thomas JJ, Ahamed Hassain Malim NH

PeerJ, 2022;10:e13163.
PMID: 35578674 DOI: 10.7717/peerj.13163

The exploration of drug-target interactions (DTI) is an essential stage in the drug development pipeline. Thanks to the assistance of computational models, notably in the deep learning approach, scientists have been able to shorten the time spent on this stage. Widely practiced deep learning algorithms such as convolutional neural networks and recurrent neural networks are commonly employed in DTI prediction projects. However, they can hardly utilize the natural graph structure of molecular inputs. For that reason, a graph neural network (GNN) is an applicable choice for learning the chemical and structural characteristics of molecules when it represents molecular compounds as graphs and learns the compound features from those graphs. In an effort to construct an advanced deep learning-based model for DTI prediction, we propose Deep Neural Computation (DeepNC), which is a framework utilizing three GNN algorithms: Generalized Aggregation Networks (GENConv), Graph Convolutional Networks (GCNConv), and Hypergraph Convolution-Hypergraph Attention (HypergraphConv). In short, our framework learns the features of drugs and targets by the layers of GNN and 1-D convolution network, respectively. Then, representations of the drugs and targets are fed into fully-connected layers to predict the binding affinity values. The models of DeepNC were evaluated on two benchmarked datasets (Davis, Kiba) and one independently proposed dataset (Allergy) to confirm that they are suitable for predicting the binding affinity of drugs and targets. Moreover, compared to the results of baseline methods that worked on the same problem, DeepNC proves to improve the performance in terms of mean square error and concordance index.

Matched MeSH terms: Humans
Fulltext Effectiveness of digital mental health interventions for university students: an umbrella review

Harith S, Backhaus I, Mohbin N, Ngo HT, Khoo S

PeerJ, 2022;10:e13111.
PMID: 35382010 DOI: 10.7717/peerj.13111

BACKGROUND: Poor mental health among university students remains a pressing public health issue. Over the past few years, digital health interventions have been developed and considered promising in increasing psychological wellbeing among university students. Therefore, this umbrella review aims to synthesize evidence on digital health interventions targeting university students and to evaluate their effectiveness.
METHODS: A systematic literature search was performed in April 2021 searching PubMed, Psychology and Behavioural Science Collection, Web of Science, ERIC, and Scopus for systematic reviews and meta-analyses on digital mental health interventions targeting university students. The review protocol was registered in the International Prospective Register of Systematic Reviews PROSPERO [CRD42021234773].
RESULTS: The initital literature search resulted in 806 records of which seven remained after duplicates were removed and evaluated against the inclusion criteria. Effectiveness was reported and categorized into the following six delivery types: (a) web-based, online/computer-delivered interventions (b) computer-based Cognitive Behavior Therapy (CBT), (c) mobile applications and short message service (d) virtual reality interventions (e) skills training (f) relaxation and exposure-based therapy. Results indicated web-based online/computer delivered-interventions were effective or at least partially effective at decressing depression, anxiety, stress and eating disorder symptoms. This was similar for skills-training interventions, CBT-based intervention and mobile applications. However, digital mental health interventions using virtual reality and relaxation, exposure-based therapy was inconclusive. Due to the variation in study settings and inconsistencies in reporting, effectiveness was greatly dependent on the delivery format, targeted mental health problem and targeted purpose group.
CONCLUSION: The findings provide evidence for the beneficial effect of digital mental health interventions for university students. However, this review calls for a more systematic approach in testing and reporting the effectiveness of digital mental health interventions.

Matched MeSH terms: Humans
Fulltext Immunogenicity mechanism of mRNA vaccines and their limitations in promoting adaptive protection against SARS-CoV-2

Salleh MZ, Norazmi MN, Deris ZZ

PeerJ, 2022;10:e13083.
PMID: 35287350 DOI: 10.7717/peerj.13083

Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19) in late 2019, hundreds of millions of people have been infected worldwide. There have been unprecedented efforts in acquiring effective vaccines to confer protection against the disease. mRNA vaccines have emerged as promising alternatives to conventional vaccines due to their high potency with the capacity for rapid development and low manufacturing costs. In this review, we summarize the currently available vaccines against SARS-CoV-2 in development, with the focus on the concepts of mRNA vaccines, their antigen selection, delivery and optimization to increase the immunostimulatory capability of mRNA as well as its stability and translatability. We also discuss the host immune responses to the SARS-CoV-2 infection and expound in detail, the adaptive immune response upon immunization with mRNA vaccines, in which high levels of spike-specific IgG and neutralizing antibodies were detected after two-dose vaccination. mRNA vaccines have been shown to induce a robust CD8+T cell response, with a balanced CD4+ TH1/TH2 response. We further discuss the challenges and limitations of COVID-19 mRNA vaccines, where newly emerging variants of SARS-CoV-2 may render currently deployed vaccines less effective. Imbalanced and inappropriate inflammatory responses, resulting from hyper-activation of pro-inflammatory cytokines, which may lead to vaccine-associated enhanced respiratory disease (VAERD) and rare cases of myocarditis and pericarditis also are discussed.

Matched MeSH terms: Humans
Fulltext The Implementation of a Primary HPV Self-Testing Cervical Screening Program in Malaysia through Program ROSE-Lessons Learnt and Moving Forward

Woo YL, Khoo SP, Gravitt P, Hawkes D, Rajasuriar R, Saville M

Curr Oncol, 2022 Oct 02;29(10):7379-7387.
PMID: 36290856 DOI: 10.3390/curroncol29100579

Program ROSE (removing obstacles to cervical screening) is a primary HPV-based cervical screening program that incorporates self-sampling and digital technology, ensuring that women are linked to care. It was developed based on the principles of design thinking in the context of Malaysia. The program illustrates the importance of collaborative partnerships and addressing the multi-faceted barriers from policy changes, and infrastructure readiness to the implementation of a radically new cervical screening program in communities. The paradigm shift in cervical cancer requires a monumental and concerted effort in educating both the healthcare providers and the general public. In this short review, we highlight how Pilot Project ROSE incorporated evidence-based tools that rapidly scaled up to Program ROSE. These ideas and solutions can be adapted and adopted by other countries. Notwithstanding the impact of COVID-19, it is incumbent on countries to pave the road towards the elimination of cervical cancer with pre-existing footpaths.

Matched MeSH terms: Humans
Fulltext Using cascade CNN-LSTM-FCNs to identify AI-altered video based on eye state sequence

Saealal MS, Ibrahim MZ, Mulvaney DJ, Shapiai MI, Fadilah N

PLoS One, 2022;17(12):e0278989.
PMID: 36520851 DOI: 10.1371/journal.pone.0278989

Deep learning is notably successful in data analysis, computer vision, and human control. Nevertheless, this approach has inevitably allowed the development of DeepFake video sequences and images that could be altered so that the changes are not easily or explicitly detectable. Such alterations have been recently used to spread false news or disinformation. This study aims to identify Deepfaked videos and images and alert viewers to the possible falsity of the information. The current work presented a novel means of revealing fake face videos by cascading the convolution network with recurrent neural networks and fully connected network (FCN) models. The system detection approach utilizes the eye-blinking state in temporal video frames. Notwithstanding, it is deemed challenging to precisely depict (i) artificiality in fake videos and (ii) spatial information within the individual frame through this physiological signal. Spatial features were extracted using the VGG16 network and trained with the ImageNet dataset. The temporal features were then extracted in every 20 sequences through the LSTM network. On another note, the pre-processed eye-blinking state served as a probability to generate a novel BPD dataset. This newly-acquired dataset was fed to three models for training purposes with each entailing four, three, and six hidden layers, respectively. Every model constitutes a unique architecture and specific dropout value. Resultantly, the model optimally and accurately identified tampered videos within the dataset. The study model was assessed using the current BPD dataset based on one of the most complex datasets (FaceForensic++) with 90.8% accuracy. Such precision was successfully maintained in datasets that were not used in the training process. The training process was also accelerated by lowering the computation prerequisites.

Matched MeSH terms: Humans
Role of Medicinal plant-derived Nutraceuticals as a potential target for the treatment of breast cancer

Alharbi KS, Almalki WH, Makeen HA, Albratty M, Meraya AM, Nagraik R, et al.

J Food Biochem, 2022 Dec;46(12):e14387.
PMID: 36121313 DOI: 10.1111/jfbc.14387

Breast cancer (BC) is one of the most challenging cancers to treat, accounting for many cancer-related deaths. Over some years, chemotherapy, hormone treatment, radiation, and surgeries have been used to treat cancer. Unfortunately, these treatment options are unsuccessful due to crucial adverse reactions and multidrug tolerance/resistance. Although it is clear that substances in the nutraceuticals category have a lot of anti-cancer activity, using a supplementary therapy strategy, in this case, could be very beneficial. Nutraceuticals are therapeutic agents, which are nutrients that have drug-like characteristics and can be used to treat diseases. Plant nutraceuticals categorized into polyphenols, terpenoids, vitamins, alkaloids, and flavonoids are part of health food products, that have great potential for combating BC. Nutraceuticals can reduce BC's severity, limit malignant cell growth, and modify cancer-related mechanisms. Nutraceuticals acting by attenuating Hedgehog, Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), Notch, and Wnt/β-catenin signaling are the main pathways in controlling the self-renewal of breast cancer stem cells (BCSCs). This article reviews some important nutraceuticals and their modes of action, which can be very powerful versus BC. PRACTICAL APPLICATIONS: Nutraceuticals' importance to the control and diagnosis of breast cancer is undeniable and cannot be overlooked. Natural dietary compounds have a wide range of uses and have been used in traditional medicine. In addition, these natural chemicals can enhance the effectiveness of other traditional medicines. They may also be used as a treatment process independently because of their capacity to affect several cancer pathways. This study highlights a variety of natural chemicals, and their mechanisms of action, routes, synergistic effects, and future potentials are all examined.

Matched MeSH terms: Humans
Exploration of motorcyclists' red-light running and helmet use at signalized intersections in Ghana

Amegah ML, Adanu EK, Kolawole Ojo T, Bukari S, Asare-Akuffo F

Traffic Inj Prev, 2023;24(1):94-97.
PMID: 36178858 DOI: 10.1080/15389588.2022.2127321

OBJECTIVE: There is a dearth of empirical studies on motorcyclists' red-light running and helmet use at signalized intersections in low and middle-income countries like Ghana, Nigeria and Malaysia. This study seeks to fill the gap by looking at red-light running and helmet use at signalized intersections in the Cape Coast metropolis, Ghana. The study also identified potential areas of intervention to reduce the dangers posed by motorcyclists' red-light running in the Cape Coast Metropolis without the use of a helmet.
METHOD: A naturalistic exploratory un-obstructive observational approach was used in assessing this phenomenon. The relationship between motorcyclists' behaviors and motorcyclists' observed demographic characteristics, the locality of the intersection, time of the week and presence of pillion passengers were analyzed. Chi-Square test of independence was used to establish the statistically significant relationships between dependent and independent variables.
RESULTS: In all, 2,225 motorcyclists and 744 pillion passengers were observed. The results revealed that 33.1% of the motorcyclists ran a red light with 45.4% not using a helmet. Red-light running at signalized intersections was significantly linked to the locality of the intersection, time of the week, and helmet use. The helmet use was low and significantly associated with the presence of a pillion passenger and whether the pillion passenger used a helmet or not.
CONCLUSION: Red-light running is influenced by locality of intersection, time of the week and helmet use. Efforts to reduce red-light running and improve helmet use should involve road safety education, awareness creation, and enforcement of traffic laws by the officials of the National Road Safety Authority and Motor Transport and Traffic Department of the Ghana Police Service. City managers in other low and middle-income countries can use the findings in the study to inform policy.

Matched MeSH terms: Humans
Fulltext The relationship between religiosity and meaningful work among Malaysian Muslim employees: The mediating role of existential labor

Seo JK, Mahudin MB, Sohn YW

PLoS One, 2022;17(12):e0279251.
PMID: 36520874 DOI: 10.1371/journal.pone.0279251

This study aimed to explore how religiosity affects the level of meaningful work among Malaysian Muslims, owing to Malaysia's highly religious background. Although religiosity constitutes a major part of an individual's value system, the influence of religiosity on the meaningfulness of work remains unclear. To address this gap, this study examined the indirect effects of the two types of religiosity-intrinsic religiosity (IR) and extrinsic religiosity (ER)-on meaningful work through existential labor, namely, surface acting and deep acting. Self-reported survey responses from 303 Malaysian Muslim employees were analyzed using structural equation modeling and bootstrapping analysis. The results showed that both surface acting and deep acting had significant mediation effects on the relationship between IR and meaningful work. By contrast, in the relationship between ER and meaningful work, surface acting's mediation effect was not significant, whereas deep acting showed a positive mediation effect. Our findings suggest that even if employees share the same religion, meaningful work is shaped differently by the specific type of religiosity and those existential labor strategies that individuals develop. This study advances the understanding of the underlying psychological mechanisms of the impact of individual religious values in the workplace. Implications and limitations were discussed.

Matched MeSH terms: Humans
Gene Therapy for Duchenne Muscular Dystrophy: Unlocking the Opportunities in Countries in the Middle East and Beyond

Elbashir H, Fathalla W, Mundada V, Iqbal M, Al Tawari AA, Chandratre S, et al.

J Neuromuscul Dis, 2022;9(6):787-801.
PMID: 36245386 DOI: 10.3233/JND-221528

BACKGROUND: Duchenne muscular dystrophy (DMD) is a severe neuromuscular disorder which leads to progressive muscle degeneration and weakness. Most patients die from cardiac or respiratory failure. Gene transfer therapy offers a promising approach to treating this disorder.
OBJECTIVE: Given the genetic disease burden, family size, and the high consanguinity rates in the Middle East, our objective is to address current practices and challenges of DMD patient care within two countries in this region, namely the United Arab Emirates and Kuwait, and to outline readiness for gene therapy.
METHODS: An expert panel meeting was held to discuss the DMD patient journey, disease awareness, current management of DMD, challenges faced and recommendations for improvement. Opportunities and challenges for gene therapy in both countries were also deliberated. A pre-meeting survey was conducted, and the results were used to guide the discussion during the meeting.
RESULTS: DMD awareness is poor resulting in a delay in referral and diagnosis of patients. Awareness and education initiatives, along with an interconnected referral system could improve early diagnosis. Genetic testing is available in both countries although coverage varies. Corticosteroid therapy is the standard of care however there is often a delay in treatment initiation. Patients with DMD should be diagnosed and managed by a multi-disciplinary team in centers of excellence for neuromuscular disorders. Key success factors to support the introduction of gene therapy include education and training, timely and accessible genetic testing and resolution of reimbursement and cost issues.
CONCLUSION: There are many challenges facing the management of DMD patients in the United Arab Emirates and Kuwait and most likely other countries within the Middle East. Successful introduction of gene therapy to treat DMD will require careful planning, education, capacity building and prioritization of core initiatives.

Matched MeSH terms: Humans
Fulltext Effectiveness of home-based pulmonary rehabilitation: systematic review and meta-analysis

Uzzaman MN, Agarwal D, Chan SC, Patrick Engkasan J, Habib GMM, Hanafi NS, et al.

Eur Respir Rev, 2022 Sep 30;31(165).
PMID: 36130789 DOI: 10.1183/16000617.0076-2022

INTRODUCTION: Despite proven effectiveness for people with chronic respiratory diseases, practical barriers to attending centre-based pulmonary rehabilitation (centre-PR) limit accessibility. We aimed to review the clinical effectiveness, components and completion rates of home-based pulmonary rehabilitation (home-PR) compared to centre-PR or usual care.
METHODS AND ANALYSIS: Using Cochrane methodology, we searched (January 1990 to August 2021) six electronic databases using a PICOS (population, intervention, comparison, outcome, study type) search strategy, assessed Cochrane risk of bias, performed meta-analysis and narrative synthesis to answer our objectives and used the Grading of Recommendations, Assessment, Development and Evaluations framework to rate certainty of evidence.
RESULTS: We identified 16 studies (1800 COPD patients; 11 countries). The effects of home-PR on exercise capacity and/or health-related quality of life (HRQoL) were compared to either centre-PR (n=7) or usual care (n=8); one study used both comparators. Compared to usual care, home-PR significantly improved exercise capacity (standardised mean difference (SMD) 0.88, 95% CI 0.32-1.44; p=0.002) and HRQoL (SMD -0.62, 95% CI -0.88--0.36; p<0.001). Compared to centre-PR, home-PR showed no significant difference in exercise capacity (SMD -0.10, 95% CI -0.25-0.05; p=0.21) or HRQoL (SMD 0.01, 95% CI -0.15-0.17; p=0.87).
CONCLUSION: Home-PR is as effective as centre-PR in improving functional exercise capacity and quality of life compared to usual care, and is an option to enable access to pulmonary rehabilitation.

Matched MeSH terms: Humans
Fulltext A non-invasive machine learning mechanism for early disease recognition on Twitter: The case of anemia

Sarsam SM, Al-Samarraie H, Alzahrani AI, Shibghatullah AS

Artif Intell Med, 2022 Dec;134:102428.
PMID: 36462907 DOI: 10.1016/j.artmed.2022.102428

Social media sites, such as Twitter, provide the means for users to share their stories, feelings, and health conditions during the disease course. Anemia, the most common type of blood disorder, is recognized as a major public health problem all over the world. Yet very few studies have explored the potential of recognizing anemia from online posts. This study proposed a novel mechanism for recognizing anemia based on the associations between disease symptoms and patients' emotions posted on the Twitter platform. We used k-means and Latent Dirichlet Allocation (LDA) algorithms to group similar tweets and to identify hidden disease topics. Both disease emotions and symptoms were mapped using the Apriori algorithm. The proposed approach was evaluated using a number of classifiers. A higher prediction accuracy of 98.96 % was achieved using Sequential Minimal Optimization (SMO). The results revealed that fear and sadness emotions are dominant among anemic patients. The proposed mechanism is the first of its kind to diagnose anemia using textual information posted on social media sites. It can advance the development of intelligent health monitoring systems and clinical decision-support systems.

Matched MeSH terms: Humans
Malaysian Disaster Medicine Research: A Bibliographic Study of Publication Trends

Adnan MSB, Hart A, Hertelendy AJ, Tin D, Abelanes SM, Issa F, et al.

Prehosp Disaster Med, 2022 Dec;37(6):836-842.
PMID: 36373499 DOI: 10.1017/S1049023X22002187

INTRODUCTION: Despite the increasing risks and complexity of disasters, education for Malaysian health care providers in this domain is limited. This study aims to assess scholarly publications by Malaysian scholars on Disaster Medicine (DM)-related topics.
METHODOLOGY: An electronic search of five selected journals from 1991 through 2021 utilizing multiple keywords relevant to DM was conducted for review and analysis.
RESULTS: A total of 154 articles were included for analysis. The mean number of publications per year from 1991 through 2021 was 5.1 publications. Short reports were the most common research type (53.2%), followed by original research (32.4%) and case reports (12.3%). Mean citations among the included articles were 12.4 citations. Most author collaborations were within the same agency or institution, and there was no correlation between the type of collaboration and the number of citations (P = .942). While a few clusters of scholars could build a strong network across institutions, most research currently conducted in DM was within small, isolated clusters.
CONCLUSION: Disaster Medicine in Malaysia is a growing medical subspecialty with a significant recent surge in research activity, likely due to the SARS-CoV-2/coronavirus disease 2019 (COVID-19) global pandemic. Since most publications in DM have been on infectious diseases, the need to expand DM-related research on other topics is essential.

Matched MeSH terms: Humans

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