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This study sheds light on the prediction of success using cutoff scores for student grades adopted for a required Physics pathway course for study in a health professions program at King Saud University in Saudi Arabia. Data on course grade and GPA for approximately 10,000 students enrolled in this course between 2008–2014, were analyzed. Receiver Operating Characteristic (ROC) curve analysis was used to determine cutoffs for course grades using ranges of GPA. This procedure has promise as a new method for quantitatively arriving at cutoff scores using an external criterion requiring less human judgment than most existing standard setting methods. The cutoff scores produced show that GPAs of students who complete the Physics course yield successive performance tiers that are lower than expected. In addition, the correlation between GPA and course grade for Physics is only 0.63 and therefore only 39% of the variation in GPA explains course grade. As a result of the findings of the study, the decision was made to maintain the existing standards thereby requiring higher grades in the Physics course for students seeking to enter a health professions course of study.

ﻧﺗﻟا ﺎﮭﺗردﻗو ﺔﯾدﺣﻟا تﺎﺟردﻟا ﻰﻠﻋ ءوﺿﻟا ﺔﯾﻟﺎﺣﻟا ﺔﺳاردﻟا طﻠﺳﺗ ﻲﻓ ﺔﺑﻠطﻟا حﺎﺟﻧ ﻰﻠﻋ ﺔﯾؤﺑﻲﻟوﻻا ءﺎﯾزﯾﻔﻟا ررﻘﻣ زﯾﻓ)145( ، دﻌﯾ يذﻟاوﻠﻋ ﺎﯾﺳﺎﺳا ﺎﺑﻠطﺗﻣكﻠﻣﻟا ﺔﻌﻣﺎﺟ ﻲﻓ ﺔﯾﺣﺻﻟا تﺎﺻﺻﺧﺗﻟا ﺔﺑﻠط ﻰ ﺔﻘﻠﻌﺗﻣﻟا تﺎﻧﺎﯾﺑﻟا ﻊﻣﺟ مﺗ دﻘﻓ ﺔﯾﻠﻋو ،ﺔﯾدوﻌﺳﻟا ﺔﯾﺑرﻌﻟا ﺔﻛﻠﻣﻣﻟﺎﺑ دوﻌﺳ نﻣ برﺎﻘﯾ ﺎﻣﻟ ررﻘﻣﻟا اذھ تﺎﺟردﺑ10000 ماوﻋﻻا نﯾﺑ ررﻘﻣﻟا اذﮭﺑ اوﻘﺣﺗﻟا نﯾذﻠﻟا ﺔﺑﻠطﻟا نﻣ2008 - 2014 .ﺔﯾﻣﻛارﺗﻟا مﮭﺗﻻدﻌﻣو ،م ﺗﻟو مادﺧﺗﺳا مﺗ دﻘﻓ ،تﺎﻧﺎﯾﺑﻟا هذھ لﯾﻠﺣ تﺎﯾﻠﻣﻌﻟا لﯾﻐﺷﺗ ﺔﯾﺻﺎﺧ ﻰﻧﺣﻧﻣReceiver Operating Characteristic (ROC) تﺎﺟردﻟا دﯾدﺣﺗﻟ نﻣ دﺣﻟاو ﺔﯾدﺣﻟا تﺎﺟردﻟا ﻰﻟا لوﺻوﻠﻟ ﺔﺛﯾدﺣﻟا ﺔﯾﻣﻛﻟا قرطﻟا نﻣ ﺔﻘﯾرطﻟا هذھ دﻌﺗ ثﯾﺣ ،ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا نﻣ ﺔﻔﻠﺗﺧﻣ تﺎﻗﺎطﻧﻟ ﺔﯾدﺣﻟارﯾﺛﺄﺗﻟا .يرﺷﺑﻟا نﻣﺿ نﺎﻛ ررﻘﻣﻟا اذھ زﺎﺗﺟا نﻣﻟ ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا نا ﻰﻟا ترﺎﺷا دﻗ ﺎﮭﯾﻠﻋ لوﺻﺣﻟا مﺗ ﻲﺗﻟا ﮫﯾدﺣﻟا تﺎﺟردﻟا نﺎﻓ ﺔﯾﻠﻋو تﻐﻠﺑ ﺔﺑﻠطﻟا تﺎﺟردو ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا نﯾﺑ ﺔﯾطﺎﺑﺗرﻻا ﺔﻗﻼﻌﻟا نا ﺎﻣﻛ ،ﻊﻗوﺗﻣﻟا نﻣ لﻗا تﺎﻗﺎطﻧ0.63 ﻲﻧﻌﯾ ﺎﻣﻣ ، نا 39% نﻣتﺎﻧﯾﺎﺑﺗﻟا ﺔﯾﻣھا نﯾﺑﺗﯾ ﺞﺋﺎﺗﻧ نﻣ ﺔﯾﻠﻋ لوﺻﺣﻟا مﺗ ﺎﻣﻟ ﺎﻘﻓوو .رﻘﻣﻟا كﻟذ ﻲﻓ مﮭﺗﺎﺟرد رﯾﺳﻔﺗ ﻲﻓ مﮭﺳﺗ نا نﻛﻣﯾ ﺔﺑﻠطﻠﻟ ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا ﻲﻓﺔظﻓﺎﺣﻣﻟا ﻰﻠﻋ ررﻘﻣﻟا رﯾﯾﺎﻌﻣﺔﯾﻟﺎﺣﻟا ﻊﻣدﯾﻛﺄﺗ لوﺻﺣﺔﺑﻠطﻟا تﺎﺻﺻﺧﺗﻟﺎﺑ قﺎﺣﺗﻟﻼﻟ نﯾﺑﻏارﻟاﺔﯾﺣﺻﻟا تﺎﺟرد ﻰﻠﻋﺔﻌﻔﺗرﻣ .ءﺎﯾزﯾﻔﻟا ررﻘﻣ ﻲﻓ

This study aimed to develop the Thai gaming disorder scale (T-GDS) in children and adolescents to serve medical staff and investigate the effectiveness of the scale.

This is a research and development study. In total, 217 participants were children and adolescents between 8–18 years, then classified into four groups according to Children's Global Assessment Scale (CGAS). The T-GDS was developed; its content validity was then investigated by three experts. Mock assessment was conducted on 15 individuals replicating the actual sample group before the assessment was tested on the sample group by two medical staff. The quality of the scale is assessed through reliability, validity and cut-off point analysis.

Exploratory factor analysis (EFA) extracted four components with 18 items meeting the criteria and have Cronbach's alpha of 0.95. The analysis of ROC curve, to determine the cut-off point, associated the mild game addiction group with T-GDS score = 14; moderate group score = 28; and severe group score = 42.

Investigation of cut-off point by practitioners is vital to compare whether it aligns with the point determined by doctors in game addiction diagnosis. Future research should select critical item in order to reduce the number of questions and construct validity should be examined using confirmatory factor analysis.

This paper provides a comprehensive insight regarding severity of game addiction based on related criteria. As a result, treatment appropriate for each type of severity could be enhanced.

Classification techniques have been applied to many applications in various fields of sciences. There are several ways of evaluating classification algorithms. The analysis of such metrics and its significance must be interpreted correctly for evaluating different learning algorithms. Most of these measures are scalar metrics and some of them are graphical methods. This paper introduces a detailed overview of the classification assessment measures with the aim of providing the basics of these measures and to show how it works to serve as a comprehensive source for researchers who are interested in this field. This overview starts by highlighting the definition of the confusion matrix in binary and multi-class classification problems. Many classification measures are also explained in details, and the influence of balanced and imbalanced data on each metric is presented. An illustrative example is introduced to show (1) how to calculate these measures in binary and multi-class classification problems, and (2) the robustness of some measures against balanced and imbalanced data. Moreover, some graphical measures such as Receiver operating characteristics (ROC), Precision-Recall, and Detection error trade-off (DET) curves are presented with details. Additionally, in a step-by-step approach, different numerical examples are demonstrated to explain the preprocessing steps of plotting ROC, PR, and DET curves.

Loan default risk or credit risk evaluation is important to financial institutions which provide loans to businesses and individuals. Loans carry the risk of being defaulted. To understand the risk levels of credit users (corporations and individuals), credit providers (bankers) normally collect vast amounts of information on borrowers. Statistical predictive analytic techniques can be used to analyse or to determine the risk levels involved in loans. This paper aims to address the question of default prediction of short-term loans for a Tunisian commercial bank.

The authors have used a database of 924 files of credits granted to industrial Tunisian companies by a commercial bank in the years 2003, 2004, 2005 and 2006. The naive Bayesian classifier algorithm was used, and the results show that the good classification rate is of the order of 63.85 per cent. The default probability is explained by the variables measuring working capital, leverage, solvency, profitability and cash flow indicators.

The results of the validation test show that the good classification rate is of the order of 58.66 per cent; nevertheless, the error types I and II remain relatively high at 42.42 and 40.47 per cent, respectively. A receiver operating characteristic curve is plotted to evaluate the performance of the model. The result shows that the area under the curve criterion is of the order of 69 per cent.

The paper highlights the fact that the Tunisian central bank obliged all commercial banks to conduct a survey study to collect qualitative data for better credit notation of the borrowers.

El riesgo de incumplimiento de préstamos o la evaluación del riesgo de crédito es importante para las instituciones financieras que otorgan préstamos a empresas e individuos. Existe el riesgo de que el pago de préstamos no se cumpla. Para entender los niveles de riesgo de los usuarios de crédito (corporaciones e individuos), los proveedores de crédito (banqueros) normalmente recogen gran cantidad de información sobre los prestatarios. Las técnicas analíticas predictivas estadísticas pueden utilizarse para analizar o determinar los niveles de riesgo involucrados en los préstamos. En este artículo abordamos la cuestión de la predicción por defecto de los préstamos a corto plazo para un banco comercial tunecino.

Utilizamos una base de datos de 924 archivos de créditos concedidos a empresas industriales tunecinas por un banco comercial en 2003, 2004, 2005 y 2006. El algoritmo bayesiano de clasificadores se llevó a cabo y los resultados muestran que la tasa de clasificación buena es del orden del 63.85%. La probabilidad de incumplimiento se explica por las variables que miden el capital de trabajo, el apalancamiento, la solvencia, la rentabilidad y los indicadores de flujo de efectivo.

Los resultados de la prueba de validación muestran que la buena tasa de clasificación es del orden de 58.66% ; sin embargo, los errores tipo I y II permanecen relativamente altos, siendo de 42.42% y 40.47%, respectivamente. Se traza una curva ROC para evaluar el rendimiento del modelo. El resultado muestra que el criterio de área bajo curva (AUC, por sus siglas en inglés) es del orden del 69%.

El documento destaca el hecho de que el Banco Central tunecino obligó a todas las entidades del sector llevar a cabo un estudio de encuesta para recopilar datos cualitativos para un mejor registro de crédito de los prestatarios.

Curva ROC, Evaluación de riesgos, Riesgo de incumplimiento, Sector bancario, Algoritmo clasificador bayesiano.

Artículo de investigación

Using a mobile phone is increasingly becoming recognized as very dangerous while driving. With a smartphone, users feel connected and have access to information. The inability to access smartphone has become a phobia, causing anxiety and fear. The present study’s aims are as follows: first, quantify the association between nomophobia and road safety among motorists; second, determine a cut-off value for nomophobia that would identify poor road safety so that interventions can be designed accordingly.

Participants were surveyed online for nomophobia symptoms and a recent history of traffic contraventions. Nomophobia was measured using the nomophobia questionnaire (NMP-Q).

A total of 1731 participants responded to the survey; the mean age was 33 ± 12, and 43% were male. Overall, 483 (28%) [26–30%] participants received a recent traffic contravention. Participants with severe nomophobia showed a statistically significant increased risk for poor road safety odds ratios and a corresponding 95% CI of 4.64 [3.35-6.38] and 4.54 [3.28-6.29] in crude and adjusted models, respectively. Receiver operator characteristic (ROC)-based analyses revealed that NMP-Q scores of = 90 would be effective for identifying at risk drivers with sensitivity, specificity and accuracy of 61%, 75% and 72%, respectively.

Nomophobia symptoms are quite common among adults. Severe nomophobia is associated with poor road safety among motorists. Developing screening and intervention programs aimed at reducing nomophobia may improve road safety among motorists.

Background: Hyperglycemia in pregnancy (HIP) is a common medical complication during pregnancy and is associated with several short and long-term maternal-fetal consequences. We aimed to determine the prevalence and factors associated with HIP among Ugandan women.

Methods: We consecutively enrolled eligible pregnant women attending antenatal care at Kawempe National Referral Hospital, Kampala, Uganda in September 2020. Mothers known to be living with diabetes mellitus or haemoglobinopathies and those with anemia (hemoglobin <11g/dl) were excluded. Random blood sugar (RBS) and glycated hemoglobin A1c (HbA_1c) were measured on peripheral venous blood samples. HIP was defined as an HbA1c ≥5.7% with its subsets of diabetes in pregnancy (DIP) and prediabetes defined as HbA1c_1c of ≥6.5% and 5.7–6.4% respectively. ROC curve analysis was performed to determine the optimum cutoff of RBS to screen for HIP.

Results: A total of 224 mothers with a mean (±SD) age 26±5 years were enrolled, most of whom were in the 2^nd or 3^rd trimester (94.6%, n=212) with a mean gestation age of 26.6±7.3 weeks. Prevalence of HIP was 11.2% (n=25) (95% CI: 7.7–16.0). Among the mothers with HIP, 2.2% (n=5) had DIP and 8.9% (n=20) prediabetes. Patients with HIP were older (28 years vs. 26 years, p=0.027), had previous tuberculosis (TB) contact (24% vs. 6.5%, p=0.003) and had a bigger hip circumference (107.8 (±10.4) vs. 103.3 (±9.7) cm, p=0.032). However only previous TB contact was predictive of HIP (odds ratio: 4.4, 95% CI: 1.2–14.0; p=0.022). Using HbA_1c as a reference variable, we derived an optimum RBS cutoff of 4.75 mmol/L as predictive of HIP with a sensitivity and specificity of 90.7% and 56.4% (area under the curve=0.75 (95% CI: 0.70–0.80, p<0.001)), respectively.

Conclusions: HIP is common among young Ugandan women, the majority of whom are without identifiable risk factors.

Even though 95% of children with neurodevelopmental disorders, including autism spectrum disorder (ASD), live in low- and middle-income countries, there is a dearth of studies from these countries, including the Republic of Georgia. Several ASD screening tools are available, but few are validated for use in Georgian or other smaller countries. This study aims to adapt and validate the autism spectrum screening questionnaire (ASSQ) for use in Georgia.

The ASSQ was administered for all third-grade students in 402 schools in the five main Georgian cities, n = 27,336. Prior to use, the 27-item ASSQ was translated, back-translated and adapted for use in Georgia. A total of 16,556 students (approximately 61%) were assessed by a parent and/or teacher. Optimal cutoff scores were estimated. Randomly chosen children who screened positive (n = 173) and negative (n = 127) were offered comprehensive assessment using standardized diagnostic procedures.

Data from 15,510 parents- and 13,517 teachers-administered ASSQ revealed statistically significant differences in median and cutoff scores between parents and teachers: 7 versus 4 and 9 versus 6, respectively. Cutoff score = 14, on either parent or teacher ASSQ, had sensitivity of 0.94, indicating that it can be used in school settings.

The Georgian adaptation of the ASSQ creates opportunity for further ASD research, while also providing a valid screening tool for clinicians. Data from Georgia will add to the growing understanding of the broader ASD phenotype.

The purpose of this paper is to develop a brief screening instrument to identify risk factors of factory workers experiencing mass fainting illness (MFI) due to work-environmental determinants.

A factory-based cross-sectional study was conducted among 740 workers in October 2017 and was completed with face-to-face interviews. Data analyses included univariate logistic regression, backward stepwise linear regression and multiple logistic regression. Sum scores on significant items and receiver operator characteristic curves were used to compute potential cut-off points and the sensitivity and specificity rates.

Significant work-environmental factors were identified as working at very high speeds, having less influence on the choice of working partners, perceived high temperature at work, having less opportunity to do their best at work, and concern about losing a job in the next six months. In developing a screening instrument, a 6.5 cut-off point that corresponded to 99.6 percent sensitivity and 92.2 percent specificity was identified.

The study concludes that this MFI-instrument could potentially be used to prevent MFI. By understanding the policy implications, the government body, employers, workers, development partners and stakeholders should work toward preventing MFI. Implementing a preventive measure is therefore warranted due to the health education impact.

The prevalence of overweight and obesity in children and adolescents is on the increase in developing countries. Therefore, a cheap, accessible and simple screening tool such as the mid-upper arm circumference (MUAC) is required for the prompt assessment. The purpose of this paper is to determine the usefulness of MUAC in assessing overnutrition in comparison with bioelectrical impedance analysis (BIA).

Participants included 1,067 children aged 6–18 years recruited from private and public schools in Egor Local Government Area in Benin City, Nigeria. Body fat was estimated by BIA using a Tanita scale, whereas the MUAC was measured with a non-elastic tape. Receiver operating characteristic analysis was used to test the ability of MUAC to determine children and adolescents identified as overweight and obese by BIA.

The prevalence of overnutrition by MUAC (12.4 percent – overweight 6.0 percent and obesity 6.4 percent) was comparable to that by BIA (12.3 percent – overweight 5.4 percent, obesity 6.9 percent). There was a significant correlation between MUAC and body fat percentage, fat mass, fat mass index and fat-free mass index in both males and females (p=0.000).

This study, in contrast to most other studies on the use of MUAC in the assessment of overnutrition, has the advantage of using BIA cut-offs values against body mass index which does not assess body fat composition. BIA is, however, not the gold standard in the measurement of body fat composition. The optimal MUAC cut-off values of this study may not be representative of the entire country because of its restriction to Benin. Similar studies from different parts of Nigeria will be required to validate this smoothed MUAC percentiles for use in the screening of children and adolescents for overnutrition.

MUAC compares well with BIA in this study and can be a useful, alternative and practical screening tool for assessing obesity in the resource-poor setting.

Previous research has studied interactive value formation (IVF) using resource- or practice-based approaches but has neglected the role of emotions. This article aims to show how emotions are correlated in problematic social media interactions and explore their role in IVF.

By combining a text mining algorithm, nonparametric Spearman's rho and thematic qualitative analysis in an explanatory sequential mixed-method design, the authors (1) categorize customers' comments as positive, neutral or negative; (2) pinpoint peaks of negative comments; (3) classify problematic interactions as detrimental, contradictory or conflictual; (4) identify customers' main positive (joy, trust and surprise) and negative emotions (anger, dissatisfaction, disgust, fear and sadness) and (5) correlate these emotions.

Despite several problematic social interactions, the same pattern of emotions appears but with different intensities. Additionally, value co-creation, value no-creation and value co-destruction co-occur in a context of problematic social interactions (peak of negative comments).

This study provides new insights into the effect of customers' emotions during IVF by studying the links between positive and negative emotions and their effects on different sorts of problematic social interactions.