Assessing mental health literacy: What medical sciences students' know about depression

Background: Mental health literacy is an individual's knowledge and belief about mental disorders which aid their recognition, management and prevention. The aim of this study was to investigate mental health literacy among students of Tehran University of Medical Sciences. Methods: In this cross-sectional study, data were collected by the anonymous self-administered questionnaires and finally 324 students participated in the study. Random cluster sampling was used. Questions were in different areas of the mental health literacy for depression include recognition of disorder, intended actions to seek help and perceived barriers, beliefs about interventions, prevention, stigmatization and impact of media. T-test was used for statistical analysis. Results: The mean (±SD) age was 23.5±2.8. The participants were 188 (58.1) females and 136 (41.9) males. In response to the recognition of the disorder 115 (35.6) students mentioned the correct answer. In help-seeking area, 208 (64.3) gave positive answer. The majority of affected students sought for help from their friends and parents. Stigma was the greatest barrier for seeking help. Television and Internet were the most common sources of information related to mental health. Conclusion: Generally students' mental health literacy on depression was low in some areas. Appropriate educational programs specifically for reducing mental disorders stigma seems necessary. Organizing networks of co-helper students for mental health could be considered

Play dough as an educational tool for visualization of complicated cerebral aneurysm anatomy

BACKGROUND: Imagination of the three-dimensional (3D) structure of cerebral vascular lesions using two-dimensional (2D) angiograms is one of the skills that neurosurgical residents should achieve during their training. Although ongoing progress in computer software and digital imaging systems has facilitated viewing and interpretation of cerebral angiograms enormously, these facilities are not always available. METHODS: We have presented the use of play dough as an adjunct to the teaching armamentarium for training in visualization of cerebral aneurysms in some cases. RESULTS: The advantages of play dough are low cost, availability and simplicity of use, being more efficient and realistic in training the less experienced resident in comparison with the simple drawings and even angiographic views from different angles without the need for computers and similar equipment. The disadvantages include the psychological resistance of residents to the use of something in surgical training that usually is considered to be a toy, and not being as clean as drawings or computerized images. CONCLUSION: Although technology and computerized software using the patients' own imaging data seems likely to become more advanced in the future, use of play dough in some complicated cerebral aneurysm cases may be helpful in 3D reconstruction of the real situation

COVID-19 Population Survey of Iran (COPSIR) study protocol: Repeated survey on knowledge, risk perception, preventive behaviors, psychological problems, essential needs, and public trust during COVID-19 epidemic

Background: The worldwide emergence and rapid expansion of COVID-19 emphasizes the need to assess the knowledge gap and to predict the disease-related behaviors and reactions during this epidemic. Methods and design: COVID19 Population Survey of Iran (COPSIR) is a repeated cross sectional survey that will be conducted in 8 waves. In each wave, 515 Iranian adults aged 18 years or older will be randomly selected and interviewed by phone. The study waves will be performed at approximately weekly intervals. The survey tool is adapted from COSMO (COVID-19 Snapshot MOnitoring) study. This study will provide information on trends of knowledge, risk perception, preventive behaviors, psychological problems, essential needs, and public trust among Iranian adults during COVID-19 epidemic. Discussion: The key findings of each wave will be immediately reported to the National Headquarters for Coronavirus Control to set better policies for disease control and prevention. Moreover, if a message is extracted from the results of this study that needs to be communicated to the public, it will be done through the mass media. © Iran University of Medical Sciences

Comparison of artificial neural network and logistic regression models for prediction of mortality in head trauma based on initial clinical data

BACKGROUND: In recent years, outcome prediction models using artificial neural network and multivariable logistic regression analysis have been developed in many areas of health care research. Both these methods have advantages and disadvantages. In this study we have compared the performance of artificial neural network and multivariable logistic regression models, in prediction of outcomes in head trauma and studied the reproducibility of the findings. METHODS: 1000 Logistic regression and ANN models based on initial clinical data related to the GCS, tracheal intubation status, age, systolic blood pressure, respiratory rate, pulse rate, injury severity score and the outcome of 1271 mainly head injured patients were compared in this study. For each of one thousand pairs of ANN and logistic models, the area under the receiver operating characteristic (ROC) curves, Hosmer-Lemeshow (HL) statistics and accuracy rate were calculated and compared using paired T-tests. RESULTS: ANN significantly outperformed logistic models in both fields of discrimination and calibration but under performed in accuracy. In 77.8% of cases the area under the ROC curves and in 56.4% of cases the HL statistics for the neural network model were superior to that for the logistic model. In 68% of cases the accuracy of the logistic model was superior to the neural network model. CONCLUSIONS: ANN significantly outperformed the logistic models in both fields of discrimination and calibration but lagged behind in accuracy. This study clearly showed that any single comparison between these two models might not reliably represent the true end results. External validation of the designed models, using larger databases with different rates of outcomes is necessary to get an accurate measure of performance outside the development population

Creating Physical 3D Stereolithograph Models of Brain and Skull

The human brain and skull are three dimensional (3D) anatomical structures with complex surfaces. However, medical images are often two dimensional (2D) and provide incomplete visualization of structural morphology. To overcome this loss in dimension, we developed and validated a freely available, semi-automated pathway to build 3D virtual reality (VR) and hand-held, stereolithograph models. To evaluate whether surface visualization in 3D was more informative than in 2D, undergraduate students (n = 50) used the Gillespie scale to rate 3D VR and physical models of both a living patient-volunteer's brain and the skull of Phineas Gage, a historically famous railroad worker whose misfortune with a projectile tamping iron provided the first evidence of a structure-function relationship in brain. Using our processing pathway, we successfully fabricated human brain and skull replicas and validated that the stereolithograph model preserved the scale of the VR model. Based on the Gillespie ratings, students indicated that the biological utility and quality of visual information at the surface of VR and stereolithograph models were greater than the 2D images from which they were derived. The method we developed is useful to create VR and stereolithograph 3D models from medical images and can be used to model hard or soft tissue in living or preserved specimens. Compared to 2D images, VR and stereolithograph models provide an extra dimension that enhances both the quality of visual information and utility of surface visualization in neuroscience and medicine

Image overlay surgery based on augmented reality : a systematic review

Acknowledgements We thank the staff of the Medical Library of the University of Aberdeen for their advice and Prof. Jennifer Cleland and Dr Jenny Gregory for discussion and support. This work was funded by the Roland Sutton Academic Trust (0053/R/17) and an Elphinstone PhD Scholarship from the University of Aberdeen.Postprin

Are the distributions of variations of circle of Willis different in different populations? – Results of an anatomical study and review of literature

BACKGROUND: Previous studies have proposed correlation between variants of the cerebral arterial circle (also known as circle of Willis) and some cerebrovascular diseases. Differences in the incidence of these diseases in different populations have also been investigated. The study of variations in the anatomy of the cerebral arterial circle may partially explain differences in the incidence of some of the cerebrovascular diseases in different ethnic or racial groups. While many studies have investigated the variations in the anatomy of each segment of the cerebral arterial circle, few have addressed the variants of the cerebral arterial circle as a whole. Similarly, the frequency of occurrence of such variants in different ethnic or racial groups has not been compared. METHODS: 102 brains of recently deceased Iranian males were dissected, in order to observe variations in the anatomy of the cerebral arterial circle. The dissection process was recorded on film and digitized. One resized picture from each dissection, showing complete circle has been made available online. The variations of the circle as whole and segmental variations were compared with previous studies. RESULTS: On the whole, the frequencies of the different variants of the entire cerebral arterial circle and segmental variations were comparable with previous studies. More specifically variants with uni- and bilateral hypoplasia of posterior communicating arteries were the most common in our study, similar to the previous works. No hypoplasia of the precommunicating part of the left anterior cerebral artery (A1), aplasia of A1 or the precommunicating part of the posterior cerebral artery (P1) was seen. In 3% both right and left posterior communcating arteries were absent. CONCLUSION: The anatomical variations found in the cerebral arterial circle of the Iranian males in the current study were not significantly different to those of more diverse populations reported in the literature. While taking into account potential confounding factors, the authors conclude that based on available studies, there is no evidence suggesting that the distributions of the variations of cerebral arterial circle differ in different populations

Ion-Assisted Nanoscale Material Engineering in Atomic Layers

Achieving deterministic control over the properties of low-dimensional materials with nanoscale precision is a long-sought goal. Mastering this capability has a transformative effect on the design of multifunctional electrical and optical devices. Here, we present an ion-assisted synthetic technique that enables precise control over the material composition and energy landscape of two-dimensional (2D) atomic crystals. Our method transforms binary transition-metal dichalcogenides, like MoSe2, into ternary MoS2αSe2(1-α) alloys with systematically adjustable compositions, α. By piecewise assembly of the lateral, compositionally modulated MoS2αSe2(1-α) segments within 2D atomic layers, we present a synthetic pathway toward the realization of multicompositional designer materials. Our technique enables the fabrication of advanced 2D structures with arbitrary boundaries, dimensions as small as 30 nm, and fully customizable energy landscapes. Our optical characterizations further showcase the potential for implementing tailored optoelectronics in these engineered 2D crystals

Disease-Free Survival after Hepatic Resection in Hepatocellular Carcinoma Patients: A Prediction Approach Using Artificial Neural Network

Background: A database for hepatocellular carcinoma (HCC) patients who had received hepatic resection was used to develop prediction models for 1-, 3- and 5-year disease-free survival based on a set of clinical parameters for this patient group. Methods: The three prediction models included an artificial neural network (ANN) model, a logistic regression (LR) model, and a decision tree (DT) model. Data for 427, 354 and 297 HCC patients with histories of 1-, 3- and 5-year disease-free survival after hepatic resection, respectively, were extracted from the HCC patient database. From each of the three groups, 80 % of the cases (342, 283 and 238 cases of 1-, 3- and 5-year disease-free survival, respectively) were selected to provide training data for the prediction models. The remaining 20 % of cases in each group (85, 71 and 59 cases in the three respective groups) were assigned to validation groups for performance comparisons of the three models. Area under receiver operating characteristics curve (AUROC) was used as the performance index for evaluating the three models. Conclusions: The ANN model outperformed the LR and DT models in terms of prediction accuracy. This study demonstrated the feasibility of using ANNs in medical decision support systems for predicting disease-free survival based on clinical databases in HCC patients who have received hepatic resection