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Unraveling the hidden link between asthma and depression among University students in Bangladesh

Background Asthma is a severe long-term respiratory and multidimensional disease. It affects a large proportion of people worldwide. Knowledge regarding asthma and its impact on depression among university students in Bangladesh is very limited. The objective of this study was to investigate asthma, as well as to explore the relationship between asthma and depressive symptoms among university students in Bangladesh. Methods This study employed a cross-sectional design. Data was collected from Rajshahi University, Bangladesh. A total of 400 university students were recruited for this study. A semi-structured questionnaire was utilized to gather information from the participants. The primary outcome variable was asthma, which was assessed with the question: “Are you suffering from asthma (diagnosed by a doctor within the past year)?” Depressive symptoms were measured using the nine-item Patient Health Questionnaire (PHQ-9). Factors influencing asthma and its association were examined using a binary logistic regression model. Results The study revealed that 53 (13.3%, 95% CI: 10.1% − 17.0%) of the students were suffering from asthma. Three significant predictors of asthma among university students were found: (i) having a family history of asthma (p < 0.01), (ii) being underweight (p < 0.01), and (iii) being born as a second or later child (p < 0.01). Findings also revealed that 48.8% of students exhibited symptoms of depression, with a significantly higher prevalence among female students compared to males (65.3% vs. 38.8%). Having asthma was found to be significantly associated with increased odds of depression (OR = 2.65, p < 0.002). Students with a history of asthma had 165% of more likelihood to depressive symptoms compared to their non-asthmatic peers suggesting a significant association between depressive symptoms and asthma in this population. Conclusion A considerable number of university students in Bangladesh suffer from asthma, with several modifiable factors such as depressive symptoms associated with the condition. The findings of this research will assist health professionals, policymakers, and university authorities in addressing the health challenges faced by students.

Ovalbumin-specific regulatory T cells differentiated from the naïve phenotype (CD44loCD62Lhi) in mesenteric lymph nodes stably suppress enteropathy even in severe food-allergic mice

Impaired expansion, stability, and function of regulatory T cells (Tregs) are reported in patients with severe allergy. Transfer of Tregs is a potential means of treating severe food allergy; however, methods to obtain allergen-specific Tregs with stable regulatory activities are needed. To achieve our goal, we examined the characteristics of allergen-specific Tregs by comparing two mouse strains transgenic for the ovalbumin (OVA)-specific T cell receptor gene: Rag23−3 and RagD10 mice (OVA23−3 and DO11.10 crossed with Rag2 knockout mice, respectively). RagD10 is a tolerant model, whereas Rag23−3 shows severe allergy when fed egg white (EW). To examine the differentiation of CD4+ T cells into Foxp3+ Tregs (induced Tregs; iTregs), CD4+ T cells or whole cells from mesenteric lymph nodes or spleens were cultured under Treg-polarization conditions and stimulated with either a combination of anti-CD3 and anti-CD28 antibodies or OVA plus antigen-presenting cells. After stimulation with the antibodies, iTregs were induced at comparable levels from CD4+ T cells from untreated Rag23−3 and RagD10 mice. Transfer of the resultant iTregs from untreated Rag23−3 mice suppressed allergic responses in EW-fed Rag23−3 mice. In contrast, stimulation with OVA plus antigen-presenting cells prevented the differentiation of iTregs from CD4+ T cells from untreated Rag23−3 mice, suggesting that OVA-induced T-cell receptor signaling inhibits effective Treg differentiation. Furthermore, antibody-mediated differentiation afforded significantly more iTregs differentiation of naïve (CD44loCD62Lhi) CD4+ T cells than of effector/effector memory (CD44hiCD62Llo) T cells isolated from the mesenteric lymph nodes of EW-fed Rag-23–3 mice. Excessive production of interleukin-4 and interferon-gamma by CD4+ T cells from EW-fed Rag23−3 mice significantly inhibited Treg induction in RagD10 mice, suggesting the severe allergic cytokine milieu likely prevents their differentiation. However, our study showed that allergen-specific Tregs with regulatory activity can be obtained from naïve CD4+ T cells from the intestinal immune system of mice even with severe allergy.

Staff, resident, and care partner perceptions on the use of a personalized tablet to mitigate the impact of isolation in long-term care residents

Background and Objectives The Dementia Isolation Toolkit (DIT) project developed DIT-Tech, a tablet-based tool to engage residents. Implementing such technology faces challenges like digital literacy and organizational resistance. This study aimed to develop an understanding of the staff, resident and care partner experiences, including barriers and facilitators to the adoption of remote-access personal tablets in long-term care homes (LTCHs). Research Design and Methods Guided by the FITT framework, which emphasizes the alignment between technology, users, and clinical activities, this investigation sought to uncover the obstacles and drivers influencing the integration of DIT-Tech within the LTCH setting. Recruitment involved voluntary participation of various stakeholders within the LTCHs: 20 staff members, 23 care partners, and 7 residents who received the DIT-Tech tablets. Purposeful selection ensured representation across demographics and levels of tablet usage. Over the research period, a total of 59 in-depth interviews were conducted via telephone or video calls. Data collection and analysis occurred simultaneously. Coding strategies, incorporating both inductive and deductive approaches, were employed. Results The study highlighted pivotal factors in DIT-Tech implementation within LTCHs. Initial enthusiasm among staff and care partners was countered by staff resistance due to workload and past tech issues. Personalization benefited residents but usability challenges and poor integration posed barriers. Aligning tech with organizational goals is crucial. Privacy measures were valued. Care partners and residents embraced DIT-Tech, emphasizing the need for targeted support for staff. Discussion and Implications These findings stress the necessity of robust guidelines for implementing remote-controlled tablets in LTCHs, providing vital insights for enhancing technology in care settings.

The maternal postnatal six-week check in women with epilepsy: Does the prevalence or subsequent postpartum health differ from the general postnatal population?

Objectives To examine the prevalence of the maternal postnatal six-week check (SWC) in women with epilepsy compared to a sample of the postnatal population without epilepsy, and assess whether the SWC is associated with health outcomes in the first year postpartum. Methods Clinical Practice Research Datalink Aurum and Hospital Episode Statistics data were used to identify births between January1998-March2020 to women with epilepsy (n = 23,533) and a random sample of births to women without epilepsy (n = 317,369). The adjusted risk ratio (aRR) for not having a SWC in women with compared to without epilepsy was estimated using modified Poisson regression. The association between receiving a SWC and postpartum health outcomes was assessed using Cox regression. Results The likelihood of not having a SWC did not differ between those with and without epilepsy (42.7% vs 43.4%, aRR = 1.01, 95%CI = 0.99–1.03). Among all women, not having a SWC was associated with a lower subsequent likelihood of being prescribed prophylactic (aHR = 0.59, 95%CI = 0.58–0.60) and emergency (aHR = 0.95, 95%CI = 0.91–0.99) contraception and having urinary and/or faecal incontinence (aHR = 0.67, 95%CI = 0.61–0.73) or dyspareunia, perineal and/or pelvic pain (aHR = 0.70, 95%CI = 0.65–0.75) recorded in the year postpartum, with no evidence these associations differed according to whether a woman had epilepsy. Not having a SWC was also associated with a lower likelihood of having depression and/or anxiety recorded in the first year postpartum among those without (aHR = 0.86, 95%CI = 0.84–0.89) but not with epilepsy (aHR = 1.01, 95%CI = 0.93–1.09). The SWC was not associated with epilepsy relevant outcomes (Accident and emergency visits or unplanned hospital admission for epilepsy, mortality). Conclusions Around 2 in every 5 women had no evidence of a maternal SWC, with no evidence epileptic women had a different prevalence to the general postnatal population. The maternal SWC may play a role in increasing the use of contraception and the detection or treatment of adverse health outcomes in the first year postpartum.

Registered report protocol: Factors associated with inter-rater agreement in grant peer review

Grant peer review processes are pivotal in allocating substantial research funding, yet concerns about their reliability persist, primarily due to low inter-rater agreement. This study aims to examine factors associated with agreement among peer reviewers in grant evaluations, leveraging data from 134,991 reviews across four Norwegian research funders. Using a cross-classified linear regression model, we will explore the relationship between inter-rater agreement and multiple factors, including reviewer similarity, experience, expertise, research area, application characteristics, review depth, and temporal trends. Our findings are expected to shed light on whether similarity between reviewers (gender, age), their experience, or expertise correlates with higher agreement. Additionally, we investigate whether characteristics of the applications—such as funding amount, research area, or variability in project size—affect agreement levels. By analyzing applications from diverse disciplines and funding schemes, this study aims to provide a comprehensive understanding of the drivers of inter-rater agreement and their implications for grant peer review reliability. The results will inform improvements to peer review processes, enhancing the fairness and validity of funding decisions. All data and analysis scripts will be publicly available, ensuring transparency and reproducibility.

Host-pathogen protein interaction studies: quality control of cDNA libraries using nanopore sequencing

Protein-protein interactions (PPI) play a key role in host-pathogens interaction studies, as proteins are essential to many cellular mechanisms. The yeast two-hybrid (Y2H) approach is a well-established method for high-throughput PPI screening and mapping of protein interaction networks. The success of this approach partially depends on the quality and representativeness of the host cDNA library, which can be constructed from the transcriptomic content of a selected host cellular type. However, evaluating the relevance of the cDNA library content remains challenging, and one of the key limitations of this interactomic approach is the occurrence of false-negative results (i.e., the absence of detectable interactions). Here, we report a direct, long read, high-throughput sequencing method using Oxford Nanopore Technologies, to assess the completeness of the host cDNA library used in host-pathogen interactions Y2H screening. This approach enables easy identification of possible downstream screened genes in PPI assays, minimizing sequencing biases and bioinformatics handling of the data. This study was performed on a cDNA library, generated from A549 human lung carcinoma cells. We were able to identify 12,123 protein coding genes from the sequencing of whole plasmids containing the cDNA inserts, that were further analyzed via functional pathways enrichment for deeper characterization. This diversity and relative abundance evaluation method could be a first step when generating new cDNA libraries of interest for PPI studies, ensuring the validity and suitability of the host library before proceeding with all Y2H screening steps.

Correction: Face masks to prevent transmission of respiratory infections: Systematic review and meta-analysis of randomized controlled trials on face mask use

Glycaemic level and glycaemic variability in acute ischaemic stroke and functional outcome: An observational continuous glucose monitoring study

Introduction Glycaemic variability has been associated with poor outcomes in critically ill patients. We aimed to study the association between glycaemic variability and functional outcome in patients with acute ischaemic stroke using continuous glucose monitoring to ensure all episodes of hyper- and hypoglycaemia were captured. Research design and methods Participants with acute ischaemic stroke were enrolled and started blinded continuous glucose monitoring (Dexcom G6) between November 2020 and December 2022. Glucose data from the first 72 hours after admission were analysed. Patients were classified into 3 groups based on change in functional status (Modified Rankin Scale) between admission and discharge. These included (i) remained independent (RI); (ii) deteriorated to dependent (DD); and (iii) remained dependent (RD). Results Data of 67 patients (mean±SD age 72.1 ± 14 years) were analysed; 19 participants had diabetes. The median (IQR) National Institutes of Health Stroke Scale (NIHSS) was 8 (3,14), and 34.3% received reperfusion therapy. The percentage of patients with RI, DD, and RD was 25.4, 55.2, 19.4%. Patients with DD had older age, higher rate of atrial fibrillation, systolic blood pressure, rate of in-hospital infection, NIHSS at admission and at 24 hours after reperfusion therapy compared to those RI. Continuous glucose monitoring was started at 38.4 (29.5,51) hours after stroke onset. Those with DD had higher mean glucose, %time above 180 mg/dL, and glucose standard deviation than the RI group at discharge. Multivariate analysis showed only an association between NIHSS at admission and deterioration in functional status. Conclusions In this pilot study, an association between glycaemic variability and functional deterioration after acute ischaemic stroke was not observed. Clinical Trial Registration numberNCT04521634

Linking expression and function of Drosophila type-I TGF-β receptor baboon isoforms: Multiple roles of BaboA isoform in shaping of the adult central nervous system

Evolutionarily conserved transforming growth factor β (TGF-β) signaling is used in both vertebrates and invertebrates to regulate a variety of developmental and cellular processes. The baboon ( babo ) gene encoding a Drosophila type-I TGF-β receptor produces three isoforms via alternative splicing: BaboA, BaboB, and BaboC. In this study, we generated three fly lines, each carrying an isoform-specific GFP tag, and another line with a GFP conjugated at the C-terminus common to all isoforms. Using these lines, we assessed (1) whether the tagged proteins function properly in rescue assays and (2) how the isoform expression is regulated in various tissues including the central nervous system (CNS). A Gal4 knock-in line in the babo locus was also characterized for reporter expression, mutant phenotypes, and isoform-specific knockdown phenotypes. We found that the C-terminal tag does not interrupt the subcellular targeting and functions of the tagged isoforms, but the internal isoform tags do so in a cell- and isoform-specific fashion. Nevertheless, our results demonstrated that these tags faithfully reflect endogenous expression of individual isoforms. Certain cell types express single or multiple isoforms at different levels, suggesting that alternative splicing could determine the isoform types and their levels depending on cell (or tissue) type. The larval CNS displays distinct patterns of two isoforms, BaboA and BaboC. BaboC is mostly expressed in neural cells originating during embryogenesis, while BaboA is broadly expressed in neural cells produced from both embryonic and postembryonic stages. Assays of both isoform-specific mutants and cell-specific knockdown of individual isoforms revealed broad roles played by BaboA in postembryonic neurogenesis and differentiation of precursor neurons, remodeling processes of persisting larval neurons, and metamorphic CNS reorganization, which are essential for establishing of the adult CNS. Taken together, this study demonstrates that the GFP-tagged lines permit visualization of endogenous expression of individual isoforms, which further provides clues about cell- and stage-specific functions played by each isoform.

Implementing injury prevention strategies in community-based youth football: The role of parents, coaches, and organizational leaders

The objective of the study was to gather perspectives and experiences of parents, coaches, and organizational leaders surrounding safety in youth football as it relates to roles and responsibilities of the coach. Parents (n = 13) and coaches (n = 10) of two youth football teams participated in separate, team-specific monthly focus groups to gather their perspectives and experiences surrounding youth football safety. Six organizational leaders participated in one-on-one interviews. Focus groups were coded in Atlas.ti. Interviews were summarized using methods of rapid analysis. Data from focus groups and interviews were integrated and analyzed for thematic content. Parents, coaches, and organizational leaders regarded the youth football coach’s role as “so much more than football,” often serving as role models, mentors, and father figures to athletes. Parents place trust in their son’s coaches and expect them to have knowledge and skills necessary to coach football and teach proper skills to prevent injuries. Organizational leaders set expectations of coaches but recognized the coaches’ autonomy in determining team activities and responsibility for safety. Coaches who teach techniques that are not aligned with current practices and coaches who prioritize winning over safety were identified as concerns for safety. Results demonstrate the important role coaches play in the personal and technical skill development and safety of youth football players and should be considered in the development and implementation of evidence-based strategies to improve safety in community-based sports.

Reversible neuropathic pain model created by long-term optogenetic nociceptor stimulation using light-responsive pain mice

Neuropathic pain has a significant social impact, with high morbidity and reduced productivity, the underlying mechanisms of neuropathic pain remain poorly understood, and effective therapeutic strategies remain elusive. The development of animal models of neuropathic pain that stimulate only the nociceptors and not the other sensory receptors or motor nerves is desirable for elucidating the complex pathogenesis of neuropathic pain. We have previously reported the generation of NaV1.7−channelrhodopsin-2 (ChR2), NaV1.8−ChR2, and NaV1.9−ChR2 mice. Optogenetics was employed in these light-responsive pain mice for generating nociceptive pain by specifically exciting the spinal dorsal root ganglion neurons, in which the respective Na+ channels are expressed through exposure to blue light. This study aimed to compare the neuropathic pain produced by the prolonged exposure of light-responsive pain mice to blue light. A reversible neuropathic pain state was established persisting for a minimum of 24 hours when each light-responsive pain mouse was irradiated with light of an intensity that consistently elicited pain. Furthermore, the mice also showed pain sensitivity to light irradiation and mechanical stimulation. The expression of c-Fos, a marker for neuronal activity following noxious stimulation, was increased in the dorsal horn of the spinal cord on the light irradiated side. DS-1971a, a selective NaV1.7 inhibitor, was effective in attenuating neuropathic pain in all light-responsive pain mice. In conclusion, optogenetics helps elucidate the specific functions of sodium channel subtypes in pain signaling, thereby advancing our understanding and paving the way for the development of further effective treatments for pain disorders in the future.

Molecular epidemiology and phylogeny of Anaplasma species in goats from Pakistan

Despite a goat population of approximately 80 million in Pakistan during 2020−2021, the prevalence of vector-borne pathogens in goats remains largely underexplored. This study aimed to assess the molecular prevalence and phylogenetic characteristics of Anaplasma ovis, Anaplasma marginale and Anaplasma phagocytophilum in goat blood samples (N = 239) collected from three districts (Muzaffargarh, Rajanpur, and Dera Ghazi Khan) in Punjab between September 2023 and October 2024. Blood samples were first screened with generic and then with species specific primers. Molecular analyses revealed a prevalence of 39% for Anaplasma spp. and 14% for A. ovis. A. marginale and A. phagocytophilum were not detected. DNA sequencing, by targeting 16S rRNA and msp4 genes, and BLAST analysis confirmed the presence of Anaplasma spp. and A. ovis, respectively. For both screening, bacterial prevalence rates varied significantly across sampling sites (P = 0.01 for Anaplasma spp. and P = 0.04 for A. ovis). Additionally, the prevalence of Anaplasma spp. significantly differed among goat breeds (P = 0.004), while no association was found between goat sex and bacterial infections (P > 0.05 for both screening). Notably, Anaplasma spp. infection was associated with a significant decrease in red blood cell count and hemoglobin concentration, while A. ovis infection did not affect the complete blood count profile. Phylogenetic analysis revealed that our Anaplasma spp. isolates clustered with those from Iran, Cyprus and China while our A. ovis isolates clustered with those from Pakistan, China, and Sudan. In conclusion, this study reports the presence of Anaplasma spp. and A. ovis in Pakistani goats and recommends large-scale studies across diverse geo-climatic regions to further investigate the epidemiology, genetic diversity and host-parasite interactions for effective control of these infections in local goat populations.

Undesired nexus poor health status of child under-five: A case study of Pakistan

Childhood morbidity and mortality are key indicators of human development, particularly reflecting poor health conditions in children. In Pakistan, child mortality remains a serious problem despite efforts to reduce it. One factor that may be associated with child mortality is an undesired pregnancy, whether unwanted (the parents did not want more children) or mistimed (the pregnancy occurred earlier than desired). Unwanted pregnancies and births are psychological factors that negatively impact children’s nutritional health. The main objective of the study is to measure the impact of mothers’ aspired status on child mortality and morbidity in Pakistan. We limited our analysis to children under 5 before the survey and used Pakistan demographic health survey conducted in 2017-2018, a national representative cross-sectional survey. We were able to predict the unwanted state (excess in boys, girls, both, and parity) by subtracting the ideal number of children from total live births. Morbidity (fever, diarrhea, cough, acute respiration infection, and Short rapid breathing), nutritional status, and mortality were also evaluated. We perform machine learning techniques such as random forest (RF) and neural network (NN) in the analysis of the data. The findings revealed that the overall percentage of the undesired child was 8%, 4%, 15%, and 27% for boys, girls, parity, and dual excess, respectively. Finally, we perform multivariate analysis following the principal component analysis (PCA) to study the relationship between variables. All the variables were associated with the unwanted child. Child morbidity, fever, and cough were higher among the undesired children. We found evidence that undesired children have acute respiration infection and that an unwanted child has a significant impact on childhood diseases. The ratio of child mortality was lower for boys but higher for girls.

Optimized tacrolimus dosing strategy in kidney transplant recipients receiving nirmatrelvir-ritonavir for COVID-19

Kidney transplantation recipients (KTRs) represent a vulnerable population for COVID-19 infection and severe disease. Nirmatrelvir-ritonavir has demonstrated efficacy in treating COVID-19 among KTRs, and interacts with tacrolimus leading to a precipitous increase in tacrolimus blood levels when co-administered, which may potentially result in toxicity. To explore a safe strategy for the combination of nirmatrelvir-ritonavir and tacrolimus, we established a new administration strategy to restore tacrolimus after the discontinuation of nirmatrelvir-ritonavir and conducted a real-world retrospective observational cohort study to evaluate its clinical efficacy. In the experimental group, tacrolimus was initiated at 20–25% of the baseline dose 48 hours after the discontinuation of nirmatrelvir-ritonavir, with daily increments of 20–25% until the baseline dose was restored. The patients who did not follow the experimental protocol were included in the control group. Results showed that withholding tacrolimus 12 hours before starting nirmatrelvir-ritonavir maintained tacrolimus blood levels above 83% of the baseline throughout the nirmatrelvir-ritonavir treatment period. Compared with the control group, the experimental group achieved target trough concentrations of tacrolimus more quickly and maintained a higher proportion within the therapeutic range ( p  = 0.029), and had significantly lower rates of adverse events ( p =  0.002, OR = 0.308, 95%CI:0.136–0.695). This study provides a safe and effective pharmacological strategy for KTRs infected with COVID-19, allowing the safe co-administration of nirmatrelvir-ritonavir and tacrolimus.

Integrated plasma and vegetation proteomic characterization of infective endocarditis for early diagnosis and treatment

Abstract Infective endocarditis, a life-threatening condition, poses challenges for early diagnosis and personalized treatment due to insufficient biomarkers and limited understanding of its pathophysiology. Here, we performed proteomic profiling of plasma and vegetation samples from 238 patients with infective endocarditis and 100 controls, with validation in two external plasma cohorts (n = 328). We developed machine learning-based diagnostic and prognostic models for infective endocarditis, with area under the curve values of 0.98 and 0.87, respectively. Leucine-rich alpha-2-glycoprotein 1 and NADH:ubiquinone oxidoreductase subunit B4 are potential biomarkers associated with infection severity. Pathologically, protein networks characterized by glycometabolism, amino acid metabolism, and adhesion are linked to adverse events. Liver dysfunction may exacerbate the condition in patients with severe heart failure. Neutrophil extracellular traps emerge as promising therapeutic targets in Streptococcus or Staphylococcus aureus infections. Our findings provide insights into biomarker discovery and pathophysiological mechanisms in infective endocarditis, advancing early diagnosis and personalized medicine.

Preoperative kidney tumor risk estimation with AI: From logistic regression to transformer

We consider the problem of renal mass risk classification to support doctors in adjuvant treatment decisions following nephrectomy. Recommendation of adjuvant therapy based on the mass appearance poses two major challenges: first, morphologic patterns may sometimes overlap across subtypes of varying risks. Second, interobserver variability is large. These complexities encourage the use of computational models as accurate noninvasive tools to find relevant relationships between individual perioperative renal mass characteristics and patient risk. In addition, recent evidence highlights the importance of clinical context as a promising direction to inform treatment decisions post-nephrectomy. In this work, we aim to identify relevant clinical markers that can be predictive of renal cancer prognosis. As a starting point, we perform a clinical feature ablation study by training a logistic regression baseline model to predict renal cancer patients’ eligibility for adjuvant therapy. The training dataset consisted of medical records of 300 individuals with renal tumors who underwent partial or radical nephrectomy between 2011 and 2020. In addition, we evaluate the same task using a transformer-based model pretrained on a much larger dataset of over 300,000 clinical records of individuals from the UK Biobank. Our findings demonstrate the pretrained model’s efficacy in knowledge transfer across different populations, with radiographic data from preoperative cross-sectional imaging playing an important role in informing renal risk and treatment decisions.

Transcriptomic insights into fate choice of pallial versus subpallial GABAergic neurons

Kernel generalized least squares regression for network-structured data

In this paper, we study a class of non-parametric regression models for predicting graph signals {𝐲t} as a function of explanatory variables {𝐱t}. Recently, Kernel Graph Regression (KGR) and Gaussian Processes over Graph (GPoG) have emerged as promising techniques for this task. The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. Next, we examine the statistical effect of correlated prediction error and propose a method for Generalized Least Squares (GLS) on graphs. In particular, we examine Autoregressive AR(1) vector autoregressive processes, which are commonly found in time-series applications. Finally, we use the Laplace approximation to determine a lower bound for the out-of-sample prediction error and derive a scalable expression for the marginal variance of each prediction. These methods are tested on both real and synthetic data, with the former taken from a network of air quality monitoring stations across California. We find evidence that the generalised GLS-KGR algorithm is well-suited to such time-series applications, outperforming several standard techniques on this dataset.

DeepDTAGen: a multitask deep learning framework for drug-target affinity prediction and target-aware drugs generation

Exploring how complex multiple-choice questions could contribute to inequity in introductory physics

Introduction: High-stakes exams significantly impact introductory physics students’ final grades and have been shown to be inequitable, often to the detriment of students identifying with groups historically marginalized in physics. Certain types of exam questions may contribute more than other types to the observed equity gaps. Objective: The primary objective of this study was to determine whether complex multiple-choice (CMC) questions may be a potential cause of inequity. Methods: We used four years of data from Problem Roulette, an online, not-for-credit exam preparation program, to address our objective. This data set included 951 Physics II (Electricity and Magnetism) questions, each of which we categorized as CMC or non-CMC. We then compared student performance on each question type and created a multi-level logistic regression model to control individual student and question differences. Results: Students performed 7.9 percentage points worse on CMC questions than they did on non-CMC questions. We find minimal additional performance differences based on student performance in the course. The results from mixed-effects models suggest that CMC questions may be contributing to the observed equity gaps, especially for male and female students, though more evidence is needed. Conclusion: We found CMC questions are more difficult for everyone. Future research should examine the source of this difficulty and whether that source is functionally related to learning and assessment. Our data does not support using CMC questions instead of non-CMC questions as a way to differentiate top-performing students from everyone else.