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Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a neuroinflammatory disease mediated by autoantibodies against the NMDAR, typically presenting with psychiatric symptoms, cognitive dysfunction, and motor dysfunction. These neuropsychiatric symptoms may be mimicked by drug abuse, and the development of anti-NMDAR encephalitis may be triggered by certain substance use. Here we report a case of anti-NMDAR encephalitis who developed neuropsychiatric symptoms after illicit substance use, the first report in Korea.

Coronavirus disease 2019 (COVID-19) has become a global pandemic and COVID-19-associated anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis may occur through an immune-mediated pathomechanism.A 21-year-old woman with a history of COVID-19 presented to our hospital with memory decline and psychiatric symptoms.The patient was diagnosed with anti-NMDAR encephalitis.Intravenous methylprednisolone (1 g/day over 5 days) followed by immunoglobulin (0.4 g/kg/day over 5 days) were administered. The patient underwent laparoscopic salpingo-oophorectomy to remove an ovarian teratoma.The patient was discharged with sequelae of short-term memory impairment, without other neuropsychiatric symptoms.Cases of previously reported anti-NMDAR encephalitis with COVID-19 were reviewed and compared with the present case. Clinicians should be aware of the occurrence of anti-NMDAR encephalitis in patients who present with neuropsychiatric complaints during or after exposure to COVID-19. Further studies are required to determine the causal relationship between the 2 diseases and predict the prognosis of anti-NMDAR encephalitis after COVID-19 exposure.

The aim of the current research was to provide recommendations to facilitate the development and use of anchoring vignettes (AVs) for cross-cultural comparisons in education. Study 1 identified six...

Chloroquine and hydroxychloroquine (HCQ) are commonly used antimalarial agents as the treatment for a wide range of autoimmune disorders including dermatological, rheumatoid, and connective tissue diseases. These amphiphilic drugs can cause toxic myopathy in in patients which are commonly characterized as reversible proximal muscle weakness, dysphagia and dyspnea. Herein, we report a case of a patient on HCQ, who suffered from toxic myopathy presenting as proximal muscle weakness and dysarthria, which was fully recovered after the cessation.

As urban structures become larger, higher, and more complex, utilizing high-precision spatial information in fire management is necessary to provide efficient countermeasures for urban safety. In this paper, a convergence model for integrating both fire safety and spatial information is defined addressing the following research problems: utilization of indoor spatial information as well as outdoor information; provision of various types of fire safety information; integration of fire safety and spatial information; and formalization of the integrated information. Also, a platform and systems for creating, managing and distributing convergence information based on the proposed model are presented. This is remarkable work to provide fire management based on the convergence model of fire safety and indoor/outdoor spatial information. Prototypes of the proposed platform and systems were implemented and tested with real data to validate the proposed approach. The validation results demonstrated that the proposed model has sufficient expressiveness to specify various types of fire safety and spatial information and has applicability to be utilized in urban fire management.

This study examined whether cutoffs in fit indices suggested for traditional formats with maximum likelihood estimators can be utilized to assess model fit and to test measurement invariance when a multiple group confirmatory factor analysis was employed for the Thurstonian item response theory (IRT) model. Regarding the performance of the evaluation criteria, detection of measurement non-invariance and Type I error rates were examined. The impact of measurement non-invariance on estimated scores in the Thurstonian IRT model was also examined through accuracy and efficiency in score estimation. The fit indices used for the evaluation of model fit performed well. Among six cutoffs for changes in model fit indices, only ΔCFI > .01 and ΔNCI > .02 detected metric non-invariance when the medium magnitude of non-invariance occurred and none of the cutoffs performed well to detect scalar non-invariance. Based on the generated sampling distributions of fit index differences, this study suggested ΔCFI > .001 and ΔNCI > .004 for scalar non-invariance and ΔCFI > .007 for metric non-invariance. Considering Type I error rate control and detection rates of measurement non-invariance, ΔCFI was recommended for measurement non-invariance tests for forced-choice format data. Challenges in measurement non-invariance tests in the Thurstonian IRT model were discussed along with the direction for future research to enhance the utility of forced-choice formats in test development for cross-cultural and international settings.

The purpose of the current study was to examine the impact of item parameter drift (IPD) occurring in context questionnaires from an international large-scale assessment and determine the most appropriate way to address IPD. Focusing on the context of psychometric and educational research where scores from context questionnaires composed of polytomous items were employed for the classification of examinees, the current research investigated the impacts of IPD on the estimation of questionnaire scores and classification accuracy with five manipulated factors: the length of a questionnaire, the proportion of items exhibiting IPD, the direction and magnitude of IPD, and three decisions about IPD. The results indicated that the impact of IPD occurring in a short context questionnaire on the accuracy of score estimation and classification of examinees was substantial. The accuracy in classification considerably decreased especially at the lowest and highest categories of a trait. Unlike the recommendation from...

The current simulation study examined the effects of Item Parameter Drift (IPD) occurring in a short scale on parameter estimates in multilevel models where scores from a scale were employed as a time-varying predictor to account for outcome scores. Five factors, including three decisions about IPD, were considered for simulation conditions. It was revealed that IPD occurring in a relatively shorter scale led to a substantial increase in the amount of relative bias in parameter estimates. The bias was more prominent in the estimates of level-2 time-varying predictors relative to those of level-1 time-varying predictors. Regarding the decisions about IPD, keeping items exhibiting IPD was more appropriate than removing them based on the results from relative bias of standard errors of estimates. Based on the findings, it can be concluded that removing items exhibiting IPD may lead to an increase of Type II errors due to the underestimation of parameter estimates and overestimation of standard errors...