Discrimination Index Research Articles

Carotid Plaque-Burden scale and outcomes: A real-life study

BackgroundThe value of carotid ultrasound in real-world practice remains controversial. We investigated the outcomes of people with vascular risk factors according to an easy carotid-plaque burden scale (CPB-scale). Predictive yield of the addition CPB-scale to ESC-SCORE2 (CPB-SCORE2 table) was assessed. MethodsA cohort of participants without preexisting cardiovascular disease (CVD) was evaluated for clinical outcomes according to the number of plaques by segment. The usefulness of the CPB-SCORE2 table was investigated. ResultsA total of 1004 patients were followed for a mean of 12.5 years for major adverse cardiovascular events (MACEs) and death. The CPB-scale was independently associated with MACEs; compared to those in the low-risk group, the corresponding adjusted hazard ratios (95% confidence intervals) for MACEs among the intermediate and high-risk groups were 13.1 (4.87–35.5) and 19.4 (7.27–51.9), respectively. Similarly, the risk of death was greater for participants stratified as high-risk than for those in the low-risk group (adjusted HR 3.36 [1.58–7.15]). According to our CPB-SCORE2 table, 149 of 178 (84%) CV events were detected in the high-risk group and exhibited greater sensitivity than did the SCORE2 Table, 84%; vs. 62%; but slightly less specificity, 62%; vs. 68%. Our table shows the improved performance of SCORE2; c-statistics: 0.74 vs. 0.68; p<0.001 for net reclassification index and integrated discrimination index. ConclusionsA simple prognostic CPB-scale was strongly associated with the long-term risk of developing a first MACE and all-cause death. Adding the CPB-scale to the SCORE2 may improve risk prediction with easy applicability in clinical practice.

Adding ethnicity to cardiovascular risk prediction: external validation and model updating of SCORE2 using data from the multiethnic HELIUS population cohort

Abstract Background Current prediction models for mainland Europe do not include ethnicity, despite ethnic disparities in cardiovascular disease (CVD) risk. Purpose We evaluated the performance of SCORE2 across the largest ethnic groups in the Netherlands with and without the factor of ethnicity. Methods We linked data from 11,614 participants enrolled between 2011 and 2015 in the prospective, multi-ethnic HELIUS cohort study, the Netherlands, aged between 40 and 70 years without CVD with hospital data. Variables (age, sex, smoking status, blood pressure, cholesterol) and outcome first CVD event (myocardial infarction, stroke, CVD death) were consistent with SCORE2. We used Fine and Gray models to calculate sub-distribution hazard ratios (SHR) for South-Asian Surinamese, African Surinamese, Ghanaian, Turkish and Moroccan origin groups, relative to the Dutch origin group, on top of individual SCORE2 risk predictions. Model performance was evaluated by discrimination, calibration and net reclassification index (NRI). Results Overall, 274 fatal and non-fatal CVD events, and 146 non-cardiovascular deaths were observed during a median of 7.8 years follow-up (IQR 6.8–8.8). SHRs for CVD events were 1.86 (95% CI 1.31-2.65, p=0.0005) for the South-Asian Surinamese, 1.09 (95% CI 0.76-1.56) for the African-Surinamese, 1.48 (95% CI 0.94-2.31) for the Ghanaian, 1.63 (95% CI 1.09-2.44, p=0.018) for the Turkish, and 0.67 (95% CI 0.39-1.18) for the Moroccan origin groups. Adding ethnicity to SCORE2 led to comparable calibration and discrimination [0.76 (0.74-0.79) vs. 0.77 (95% CI 0.74-0.78)]. The NRI for adding ethnicity to SCORE2 was 0.24 (95% CI 0.18-0.31) for events and -0.12 (95% CI -0.13--0.12) for non-events. Conclusion Adding ethnic backgrounds improves risk classification of the SCORE2 risk prediction model in a middle-aged, multi-ethnic Dutch population, which may help to address disparities in CVDs through timely treatment.

Incremental prognostic value of late gadolinium enhancement granularity in patients with hypertrophic cardiomyopathy

Abstract Background The prognostic stratification of hypertrophic cardiomyopathy (HCM) using cardiac magnetic resonance (CMR) is based on the extent of late gadolinium enhancement (LGE). To enhance risk stratification for sudden cardiac death (SCD), the ESC has recently added LGE extent in the guidelines, at ≥15% of LV mass. However, SCD has become an uncommon event in this population, and mortality is now mostly related to other phenotypes, such as atrial fibrillation, stroke, and heart failure. While previous studies have showed the prognostic value of LGE to predict all-cause mortality, the prognostic impact of additional LGE features is not well established. Therefore, we aimed to assess the incremental prognostic value of the granularity of LGE including extent, location, and pattern in patients with HCM to predict all-cause death. Methods Between 2008 and 2021, all patients referred for HCM assessment using CMR, without history of coronary artery disease (CAD) or clinical history of myocarditis were prospectively recruited in two French centers. The outcome was all-cause death using the French National Registry of Death. The concept of "LGE granularity" was defined as a comprehensive model combining all the following LGE features with extent (by segment), location (septal or others), and pattern (midwall and/or subepicardial). Using nested Cox proportional hazard models, the additional predictive value of LGE features was assessed by the C-statistic increment, the continuous net reclassification improvement (NRI), the integrative discrimination index (IDI) and the global Chi-2. Results Among the 2,672 included patients (52±7 years, 56% males), 862 (32%) had LGE. After a median (IQR) follow-up of 9 (7–11) years, 447 (17%) patients died. Survival curves show an increased risk for LGE presence (log-rank p&amp;lt;0.001, Figure 1A). After adjustment for traditional prognosticators in the overall population (N=2,672), the presence of LGE was strongly associated with all-cause death (adjusted hazard ratio (HR) 3.96, 95% CI: 3.26-4.80, p&amp;lt;0.001). In the subgroup of patients with LGE (n=862), survival curves showed that all parameters defining the LGE granularity were associated with a higher risk of all-cause death (all p&amp;lt;0.001, Figure 1B). A nested Cox model adjusted on traditional prognosticators showed that the LGE extent, location and pattern were all independently associated with all-cause death (all p&amp;lt;0.001, Figure 2). The model of "LGE granularity" combining all independently significative LGE features showed the best improvement in model discrimination and reclassification above traditional prognosticators (C-statistic improvement: 0.90; NRI=41.9%; IDI=13.2%, Chi-2 global=450, all p&amp;lt;0.001; LR-test p&amp;lt;0.001, Figure 2). Conclusion In a large cohort of HCM patients, the "LGE granularity" model combining the extent, location, and pattern of LGE had an incremental prognostic value over and above traditional prognosticators to predict all-cause death.Prognostic value of LGE granularityIncremental prognostic value LGE granula

Prognostic value of additional midwall late gadolinium enhancement in patients with ischemic cardiomyopathy

Abstract Background Although several studies have reported the additional presence of midwall late gadolinium enhancement (LGE) using cardiac magnetic resonance (CMR) in patients with ischemic cardiomyopathy (ICM), its prognostic value is not well established. Purpose To assess the prognostic value of the additional presence of midwall-LGE in a large cohort of patients with ICM and reduced left ventricular ejection fraction (LVEF). Methods Between 2008 and 2022, all consecutive patients referred for myocardial viability assessment using CMR with an history of ICM (≥70% stenosis in ≥1 epicardial coronary vessel on angiography and/or history of myocardial infarction and/or coronary revascularization) and LVEF &amp;lt;50% were included. Midwall-LGE was defined by non-ischemic LGE corresponding to non-specific myocardial fibrosis. All patients with a history of acute myocarditis and/or sub-epicardial LGE were excluded. The primary outcome was all-cause death. Nested Cox proportional hazard models were used to assess the prognostic value of additional midwall-LGE including its location (lateral and/or septal and other location) and extent (1 or ≥2 segments), above the presence of ischemic-LGE and traditional prognostic factors. The incremental prognostic value of midwall-LGE extent and location was assessed by the C-statistic increment, the continuous net reclassification improvement (NRI), the integrative discrimination index (IDI) and the global Chi-2. Results Among the 6,082 included patients (65±12 years, 73% males), 702 (11.5%) had an additional midwall-LGE. During a median follow-up of 9 (IQR, 7-12) years, 652 (11%) patients died. The presence of midwall-LGE alone was strongly associated with the risk of death compared to patients without midwall-LGE (p&amp;lt;0.001, Figure 1A). Among these patients with midwall-LGE (N=702), survival curves showed an increased risk for midwall-LGE in lateral and/or septal location (p&amp;lt;0.001), for larger extent (p&amp;lt;0.001) and the presence of ischemic-LGE (p&amp;lt;0.001, Figure 1B). In this population with midwall-LGE (N=702), after adjustment for risk factors and extent of ischemic-LGE, midwall-LGE with septal and/or lateral location (adjusted HR: 2.6; 95%CI: 1.8-3.6) and extent ≥2 segments (adjusted HR: 2.6; 95%CI: 1.8-3.7, both p&amp;lt;0.001) were independently associated with all-cause death. A comprehensive LGE model combining all the characteristics of midwall-LGE showed the best improvement in model discrimination and reclassification above traditional prognosticators (C-statistic improvement: 0.13; NRI=46%; IDI=19%, Chi-2 global=261, all p&amp;lt;0.05; LR-test p&amp;lt;0.001, Figure 2). Conclusion In a large cohort of ICM patients, the presence of an additional non-ischemic midwall-LGE is an independent prognosticator of all-cause death, particularly for larger extent or when present in the septal and/or lateral location.Prognostic value of midwall-LGEIncremental prognostic value

Prognostic impact of the concept of late gadolinium enhancement granularity in non-ischaemic dilated cardiomyopathy

Abstract Background The prognostic stratification of non-ischaemic dilated cardiomyopathy (DCM) to predict the risk of death is mainly driven by the left ventricular ejection fraction (LVEF). Indeed, LVEF&amp;lt;35% is currently the only indication for primary prevention with implantable cardioverter-defibrillator (ICD) in these patients. Beyond LVEF, several cardiac magnetic resonance imaging (MRI) studies have suggested the strong prgnostic impact of late gadolinium enhancement (LGE), and particularly its extent and location. Therefore, we assumed that a more granular approach combining detailed LGE findings including extent, location and pattern could improve risk stratification in this population. Purpose To assess the additional prognostic value of the concept of "Late Gadolinium Enhancement (LGE) Granularity" that includes extent, location, and pattern in non-ischaemic dilated cardiomyopathy (DCM) patients to predict all-cause death. Methods Between 2008-2021, all consecutive patients with DCM without ICD or history of sustained ventricular arrythmia referred for cardiac MRI were included in two French centres. In line with the current ESC and AHA guidelines, DCM was defined by the LV dilation and LVEF&amp;lt; 50% using cardiac MRI. All patients with history of coronary artery disease or clinical history of myocarditis were excluded. The primary outcome was all-cause death using the French National Registry of Death. Cox regressions were performed to determine the prognostic value of each LGE findings. The additional prognostic value of the LGE granularity was assessed by the C-statistic increment, the continuous net reclassification improvement (NRI), and the integrative discrimination index (IDI). Results Of 1,668 DCM patients (age 52±8 years, 54% males), 268 (16%) died after a median (interquartile range) follow-up of 9 (7-12) years. With a median LVEF value of 39% (30-46), 472 (28%) patients had non-ischemic LGE. Using survival curves, patients with LVEF&amp;gt;35% but the LGE septal location showed a higher risk of death compared to all patients with LVEF≤35% with or without LGE (except for the septal location, all p&amp;lt;0.001). In DCM patients with LGE (N=472), LGE extent (adjusted HR: 4.27, 95% CI: 2.22-8.22), septal location (HR: 5.74, 95% CI: 3.35-9.85) and multiple areas of LGE (HR: 4.38, 95% CI: 2.08-9.22; all p&amp;lt;0.001) were all independently associated with death after adjustment for prognosticators. The concept of "LGE granularity" combining all these LGE features showed the best improvement in model discrimination and reclassification over traditional prognosticators including LVEF (C-statistic improvement: 0.14; net reclassification improvement=64.3%; integrative discrimination index=29.0%; all p&amp;lt;0.05). Conclusion In a large cohort of DCM patients, the concept of "LGE granularity" combining LGE extent, location and the presence of multiple areas had an additional prognostic value above traditional prognosticators including LVEF to predict all-cause death.

Psychometric Properties of Turkish Versions of the Non-Attachment Scale Short Form

This study aimed to examine the psychometric properties of the Non-Attachment Scale Short Form in a Turkish sample. With the participation of 244 adults over 18 years of age, the Short Form of the Nonattachment Scale, the Resilience Scale and the Ontological Addiction Scale were used as data collection tools. Cronbach's alpha and McDonald's omega coefficient were used for the reliability of the Non-Attachment Scale Short Form. According to the results of the analyses, the internal consistency coefficient and McDonald's value were found to be .77 and .78, respectively. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were used to test the construct validity of the scale. The results of the analyses showed that the model fit and Kaiser-Meyer-Olkin (KMO) values were at an acceptable level. Item factor loadings ranged between .40 and .67 and the scale was found to have a single factor structure. The statistically significant difference between the 27% lower and upper groups among the participants showed that the item discrimination index of the scale was at a good level. According to the correlation findings conducted to test the criterion validity of the scale, non-attachment was found to have positive significant relationships with resilience (r = .60) and negative significant relationships with ontological dependence (r = -.39). As a result, adaptation of the Short Form of the Non-Attachment Scale can be said to be a valid and reliable measurement tool.

The Effect of Presenting Geometry Items with and without Shapes on the Psychometric Properties of the Test and Students’ Test Scores

This research intended to examine the effects of presenting geometry items with and without shapes on the psychometric properties of the test and students’ test scores. The study was conducted on 480 eighth grade students. Within the scope of the study, two geometry tests were crafted, one with shapes and the other without shapes. Both tests consisted of 15 multiple-choice items. In the data collection process, a counterbalanced design was followed and the two tests were administered to the students three weeks apart. Analyses were carried out on 405 students who participated in both applications and whose test forms could be matched. The factor analysis results revealed that the factor loadings of the items and extracted variance were higher for the test with shapes compared to the shape-free form. The Cronbach’s alpha coefficient of the test containing shapes was found to be significantly higher than that calculated for the test without shapes. According to item difficulties, the questions with shapes were easier for the students than the shape-free questions. In terms of discrimination indices a difference in favor of the shape-containing test was observed in almost all items. Ferguson delta statistic, which is a measure of discrimination for the overall test, was higher in the shape-contaninig test. Correlation analysis denoted a strong positive relationship between student scores on the two tests. The paired sample t-test proved that there was a statistically significant difference between students’ scores on the shape-containing and shape-free tests. These results indicate that the geometry tests with and without shapes differ in terms of both psychometric properties and students’ test scores.

Fault diagnosis method of rolling bearing of BN ball mill based on AESL-GA

Aiming at the shortcomings of incomplete and inaccurate knowledge-based Bayesian network (BN) construction methods, a BN structure construction method based on knowledge guidance and data mining is proposed. Aiming at the problem of inaccurate single signal fault diagnosis results and the uncertainty problem in fault information, the current signal and the vibration signal are fused to establish the feature nodes of the BN network, and the fault feature parameters of the two signals are extracted respectively. The feature basket is selected using the discrimination index method and used as the node of the BN structure feature layer. The initial BN structure constructed by expert knowledge is combined with the adaptive elite structure genetic algorithm (AESL-GA) for structural optimization. By adaptively restricting the search space in the evolution process, reducing the number of free parameters, improving its global search ability, and obtaining the optimal BN structure. The method is verified by the measured data of the ball mill rolling bearing of Jinchuan Company and the Paderborn University data set, which proves the effectiveness of the proposed method.

Design, Implementation, and Analysis of an Assessment and Accreditation Model to Evaluate a Digital Competence Framework for Health Professionals: Mixed Methods Study.

Although digital health is essential for improving health care, its adoption remains slow due to the lack of literacy in this area. Therefore, it is crucial for health professionals to acquire digital skills and for a digital competence assessment and accreditation model to be implemented to make advances in this field. This study had two objectives: (1) to create a specific map of digital competences for health professionals and (2) to define and test a digital competence assessment and accreditation model for health professionals. We took an iterative mixed methods approach, which included a review of the gray literature and consultation with local experts. We used the arithmetic mean and SD in descriptive statistics, P values in hypothesis testing and subgroup comparisons, the greatest lower bound in test diagnosis, and the discrimination index in study instrument analysis. The assessment model designed in accordance with the competence content defined in the map of digital competences and based on scenarios had excellent internal consistency overall (greatest lower bound=0.91). Although most study participants (110/122, 90.2%) reported an intermediate self-perceived digital competence level, we found that the vast majority would not attain a level-2 Accreditation of Competence in Information and Communication Technologies. Knowing the digital competence level of health professionals based on a defined competence framework should enable such professionals to be trained and updated to meet real needs in their specific professional contexts and, consequently, take full advantage of the potential of digital technologies. These results have informed the Health Plan for Catalonia 2021-2025, thus laying the foundations for creating and offering specific training to assess and certify the digital competence of such professionals.

Associations of perceived discrimination with health outcomes and health disparities in the All of Us cohort.

The goal of this study was to investigate the association of perceived discrimination with health outcomes and disparities. The study cohort consists of 60,180 participants from the four largest SIRE groups in the All of Us Research Program participant body: Asian (1,291), Black (4,726), Hispanic (5,336), and White (48,827). A perceived discrimination index (PDI) was derived from participant responses to the "Social Determinants of Health" survey, and the All of Us Researcher Workbench was used to analyze associations and mediation effects of PDI and self-identified race and ethnicity (SIRE) with 1,755 diseases. The Black SIRE group has the greatest median PDI, followed by the Asian, Hispanic, and White groups. The Black SIRE group shows the greatest number of diseases with elevated risk relative to the White reference group, followed by the Hispanic and Asian groups. PDI was found to be positively and significantly associated with 489 out of 1,755 (27.86%) diseases. 'Mental Disorders' is the disease category with the greatest proportion of diseases positively and significantly associated with PDI: 59 out of 72 (81.94%) diseases. Mediation analysis showed that PDI mediates 69 out of 351 (19.66%) Black-White disease disparities. Perceived discrimination is significantly associated with risk for numerous diseases and mediates Black-White disease disparities in the All of Us participant cohort. This work highlights the role of discrimination as an important social determinant of health and provides a means by which it can be quantified and modeled on the All of Us platform.

An analysis of calculus application questions in grade 12 mathematics exams in South Africa

This study employed a quantitative survey methodology to analyze the 2021-2023 grade 12 calculus application exam questions in the context of South Africa. A total of 11 grade 12 teachers and 220 grade 12 students participated in the study. Analysis of the survey data and students’ test results points to the view that examiners sometimes misjudge the level of difficulty of the exam questions and include questions that are very difficult, which fail to discriminate between strong and weak candidates. It was noticed that calculus applications questions that most students could not correctly answer included multiple mathematical skills that were compacted in a short statement. This paper recommends that mathematics examiners should continuously reflect on their own work and find ways to improve their skills in setting future exam papers. The inclusion of item difficulty and item discrimination indices in post-exam analysis of results could be part of the examiners’ reflective practice. Feedback from the grade 12 mathematics teachers on the standard of each exam question is just as important to the examiners as the examiners’ reports are to the teachers.

The Measurement Model of Family Strengths for Generation Alpha in the Thai Context.

The concept of the Thai family has shifted from the traditional family to families of various forms, such as single-parent families, same-sex families, skipped-generation families, and one-person households, which affects not only mental health, but future relationships of the children. This research aimed to analyze the factors that contribute to family strengths in the context of Generation Alpha and develop a measurement model tailored to a Thai context. The sample consisted of parents and caregivers of Generation Alpha, divided into two sections, with 521 participants for exploratory factor analysis and 508 participants for confirmatory factor analysis. Using stratified random sampling, data were collected via questionnaires distributed across four regions of Thailand. The discrimination index ranged from 0.280-0.896, with a Cronbach's alpha of 0.952. The results revealed a measurement model consisting of five key factors contributing to family strengths. The factor with the highest score was positive relationships, with a factor loading of 0.92. Additional factors included technology and media literacy, parental roles, good attributes, and mental immunity, with a factor loading of 0.80, 0.74, 0.55, and 0.44, respectively. The measurement model of family strengths for Generation Alpha in the Thai context was found to be consistent with the empirical data. These findings suggest that understanding these family strengths can significantly enhance the well-being of both Generation Alpha and their family members.

ChatGPT's quality: Reliability and validity of concept inventory items.

The recent advances of large language models (LLMs) have opened a wide range of opportunities, but at the same time, they pose numerous challenges and questions that research needs to answer. One of the main challenges are the quality and correctness of the output of LLMs as well as the overreliance of students on the output without critically reflecting on it. This poses the question of the quality of the output of LLMs in educational tasks and what students and teachers need to consider when using LLMs for creating educational items. In this work, we focus on the quality and characteristics of conceptual items developed using ChatGPT without user-generated improvements. For this purpose, we optimized prompts and created 30 conceptual items in kinematics, which is a standard topic in high-school level physics. The items were rated by two independent experts. Those 15 items that received the highest rating were included in a conceptual survey. The dimensions were designed to align with the ones in the most commonly used concept inventory, the Force Concept Inventory (FCI). We administered the designed items together with the FCI to 172 first-year university students. The results show that ChatGPT items have a medium difficulty and discriminatory index but they overall exhibit a slightly lower average values as the FCI. Moreover, a confirmatory factor analysis confirmed a three factor model that is closely aligned with a previously suggested expert model. In this way, after careful prompt engineering, thorough analysis and selection of fully automatically generated items by ChatGPT, we were able to create concept items that had only a slightly lower quality than carefully human-generated concept items. The procedures to create and select such a high-quality set of items that is fully automatically generated require large efforts and point towards cognitive demands of teachers when using LLMs to create items. Moreover, the results demonstrate that human oversight or student interviews are necessary when creating one-dimensional assessments and distractors that are closely aligned with students' difficulties.

Steps to developing a DXA-based risk score for cardiovascular outcomes among older adults: the health, aging, and body composition study

Cardiovascular disease (CVD) is a major chronic disease worldwide and its risk factors have long been investigating in epidemiological studies. Our study aims to develop a body composition-based risk score and integrate it into the Framingham Risk Score (FRS) to improve CVD prediction among well-functioning older adults. We included 1882 older adults from the Health, Aging and Body Composition (Health ABC) study to screen body composition variables obtained from the Dual-energy X-ray absorptiometry (DXA). Three models were developed and compared: the 4-DXA model, the refit FRS, and the refit FRS plus 4-DXA model. C-statistics were 0.62 (95% CI: 0.59, 0.65) for the refit FRS, 0.58 (95% CI: 0.55, 0.61) for the 4-DXA model, and 0.63 (95% CI: 0.60, 0.66) for the refit FRS plus 4-DXA model. Compared to the refit FRS, the refit FRS plus 4-DXA model slightly improved CVD outcome prediction as the discrimination slope, net reclassification index, and the integrated discrimination index were 0.053 (95% CI: 0.041, 0.066), 0.098 (95% CI = – 0.0033, 0.20) and 0.013 (95% CI: 0.0069–0.019). This study provides a model for more accurate risk stratification and draws more attention on DXA-based indices in the clinical setting. It also encourages further research in validating the developed risk score in more diverse population and in investigating a broader range of CVD risk factors.

Evaluating the Quality of Multiple-Choice Test Questions in the Postlicensure Environment.

Multiple-choice test questions are among the main measures of knowledge used by educators in the postlicensure environment; however, these tests are often constructed in the absence of guidelines or the means to evaluate examination quality after administration. Previously, guidance was provided on constructing quality test items. Here we present instruction for professional development specialists to use postadministration test data for an item analysis, providing insight on test flaws and opportunities for iterative examination improvement. The topics of item difficulty, index of discrimination, and distractor analysis are covered for independent analysis, and topics such as reliability are addressed for those who have access to a formal program. Three levels of strategies are described: using a learning management system for item analysis, using free open-source software, and using a minimal standards method of evaluating test items. [J Contin Educ Nurs. 2024;55(10):487-492.].

Effect of 2-PL and 3-PL Models on the Ability Estimate in Mathematics Binary Items

The investigation delves into examining the influence of 2-parameter logistic (PL) and 3-parameter logistic models on the ability estimates of students in mathematical binary items. It ascertained the parameters of the items in the 2-PL and 3-PL models. We employed Item Response Theory (IRT) in the design of this research survey, with a sample comprising 1015 senior secondary (SS) students in SS III classes who were analyzed using both models in the investigation. The Mathematics Achievement Test instrument was adapted from the General Mathematics Paper 1 of the Senior School Certificate Examination administered by the West Africa Examinations Council (WAEC). Results indicated that the 2-PL model shows lower difficulty levels but higher discriminatory indices. Statistical analysis revealed a significant (F = 19.52, p &lt; 0.05 and F = 18.52, p &lt; 0.05) effect of both models, respectively, on ability estimates in mathematics binary items among Nigerian secondary school students. We established that item parameters in the 2-PL and 3-PL models significantly affected the ability estimate of Nigeria secondary school students in binary mathematics items, while the 3-PL model provided a better ability estimate than the 2-PL model.

Automated analysis of a novel object recognition test in mice using image processing and machine learning

The novel object recognition test (NORT) is one of the most commonly employed behavioral tests in experimental animals designed to evaluate an animal's interest in and recognition of novelty. However, manual procedures, which rely on researchers’ observations, prevent high throughput analysis. In this study, we developed an automated analysis method for NORT utilizing machine learning-assisted exploratory behavior detection. We recorded the exploratory behavior of the mice using a video camera. The coordinates of the mouse nose and tail base in recorded video files were detected using a pre-trained machine learning model, DeepLabCut. Each video was then segmented into frame images, which were categorized into "exploratory,” or "non-exploratory" frames based on manual observation. Mouse feature vectors were calculated as vectors from the nose to the vertices of the object and were utilized for SVM training. The trained SVM effectively detected exploratory behaviors, showing a strong correlation with human observer assessments. Upon application to NORT, the duration of mouse exploratory behavior towards objects predicted by the SVM exhibited a significant correlation with the assessments made by human observers. The novelty discrimination index derived from the SVM predictions also aligned well with that from human observations.

Thymoquinone ameliorate oxidative stress, GABAergic neuronal depletion and memory impairment through Nrf2/ARE signaling pathway in the dentate gyrus following cypermethrin administration

BackgroundExposure to chemical toxins, including insecticides, harms bodily organs like the brain. This study examined the neuroprotective of thymoquinone on the cypermethrin’s harmful effects on the histoarchitecture of the dentate gyrus and motor deficit in the dentate gyrus.MethodsForty adult male rats (180–200 g) were randomly divided into 5 groups (n = 8 per group). Groups I, II, III, IV, and V received oral administration of 0.5 ml of phosphate-buffered saline, cypermethrin (20 mg/kg), thymoquinone (10 mg/kg), cypermethrin (20 mg/kg) + thymoquinone (5 mg/kg), and cypermethrin (20 mg/kg) + thymoquinone (10 mg/kg) for 14 days respectively. The novel object recognition test that assesses intermediate-term memory was done on days 14 and 21 of the experiment. At the end of these treatments, the animals were euthanized and taken for cytoarchitectural (hematoxylin and eosin; Cresyl violet) and immunohistochemical studies (Nuclear factor erythroid 2-related factor 2 (Nrf2), Parvalbumin, and B-cell lymphoma 2 (Bcl2).ResultThe study shows that thymoquinone at 5 and 10 mg/kg improved Novelty preference and discrimination index. Thymoquinone enhanced Nissl body integrity, increased GABBAergic interneuron expression, nuclear factor erythroid 2-derived factor 2, and enhanced Bcl-2 expression in the dentate gyrus. It also improved the concentration of nuclear factor erythroid 2-derived factor 2, increased the activities of superoxide dismutase and glutathione, and decreased the concentration of malondialdehyde level against cypermethrin-induced neurotoxicity.Conclusionthymoquinone could be a therapeutic agent against cypermethrin poisoning.

Weight discrimination and body mass indexes as predictors of body esteem in members of the Bear subculture

Aim of the studyThe Bear subculture is a community of sexual minority men who are distinguished by their preference for muscular or large body build and pronounced body hair in men. Previous studies indicated that Bears experienced weight stigma within and outside the gay community. In this study we focused on body esteem in members of the Bear subculture and explored its associations with anthropological body mass indexes and experiences of weight discrimination.Subject or material and methodsThe study, which included questionnaires and anthropological measurements, involved 64 cisgender sexual minority men from the Polish Bear community. Analyses focused on predictors of body esteem measured with The Body-Esteem Scale, including body mass indexes (e.g., waist circumference) and self-reported exposure to weight discrimination.ResultsEvery three out of four study participants reported exposure to weight stigma in the past. Greater exposure to weight discrimination predicted lower ratings of Physical Attractiveness, Upper Body Strength and Physical Condition. Body mass indexes were significantly and negatively related only to Physical Condition factor.DiscussionOur study confirms previous observations of increased body mass indexes and exposure to weight stigma among Bears. Interestingly, weight discrimination but not body mass indexes consistently and negatively predicted self-assessed body esteem across its all dimensions.ConclusionsMen from the Bear community constitute a population that may be particularly vulnerable to health inequalities due to increased body mass and weight stigma exposure. Health promotion interventions targeting this population should be tailored to Bears’ subcultural norms, support healthier lifestyles and effective coping with stigma as opposed to focus on weight loss.

New Metrics for Analysing Multiple-choice Questions

While the ideal of constructive alignment in curriculum is well established, and the importance of evaluating learning and teaching is well known, evaluating assessments remains a complex task and gaps can arise between learning outcomes, learning activities and assessments. Our study outlines an innovative way of analysing multiple-choice question (MCQ) examinations, which reveals possible weaknesses in the examination design and gaps in the alignment of curriculum. Individual examination questions are analysed through traditional metrics of the Discrimination Index (DI) and Difficulty Index (DIFF), combined with two novel metrics called the Grade Inversion Score (GIS) and Association with Total Score (ATS). Focusing on examination marks from a data science examination from The University of Sydney, we perform two investigations. First, we identify poorly designed questions using DI, DIFF, GIS and ATS. Second, as multiple questions arise as deficient in these metrics, we explore specific areas in the curriculum where there may be misalignment of course material with the learning outcomes. Our analysis provides a simple visual way for examiners to inspect the validity of an examination design and encourages an evidence-based approach to exploring curriculum alignment using multiple-choice assessments.