Babcock University

Transient ischaemic attack (TIA) represents a critical window for stroke prevention, yet physician knowledge and system readiness vary across healthcare settings. Evidence describing national patterns of TIA management knowledge among physicians in low- and middle-income countries remains limited. This national cross-sectional survey aims to evaluate Nigerian physicians’ knowledge of TIA diagnosis and management, identify factors associated with adequate knowledge, and explore perceived barriers to optimal TIA care. A nationwide descriptive cross-sectional survey was conducted among licensed medical doctors practicing in Nigeria using a structured online questionnaire. Knowledge of TIA presentation, investigations, and management was assessed using a composite scoring system categorized as poor, fair, or good. Descriptive statistics summarized participant characteristics and knowledge patterns. Bivariate analyses and multinomial logistic regression were performed to identify independent predictors of knowledge level. A total of 404 physicians participated. Overall, 38.1% demonstrated good knowledge of TIA management, while 40.6% had fair knowledge and 21.3% had poor knowledge. Most respondents correctly identified the high early risk of stroke following TIA (79.0%) and recommended urgent brain imaging (80.2%) and vascular imaging (76.5%). However, only 30.2% had received formal TIA training within the previous five years, and fewer than one-third reported the presence of local referral pathways. The most frequently reported barriers included patient-related factors (71.0%), limited access to urgent neuroimaging (61.4%), and lack of guideline-based protocols (38.9%). Multinomial logistic regression analysis demonstrated significant regional variation in knowledge levels, with lower odds of good knowledge observed outside the South-West region. While Nigerian physicians demonstrate moderate awareness of key TIA management principles, important gaps remain in guideline-based practice and system-level readiness. Targeted educational initiatives, improved access to neuroimaging, and development of structured referral pathways may enhance early stroke prevention efforts.

Customer lifetime value is an important measure for understanding long term profitability in e-commerce, where firms depend on effective customer retention and development in highly competitive digital markets. Traditional statistical approaches have supported early customer lifetime value estimation, but they often rely on assumptions that limit their ability to represent complex and changing customer behavior. This systematic review examined existing studies that applied machine learning methods to customer lifetime value prediction in e-commerce. Guided by the PRISMA framework, the review searched Scopus and IEEE Xplore for studies published between 2020 and 2026, and 12 studies met the inclusion criteria. The findings show that ensemble and deep learning approaches dominate recent research, with stacking, hybrid, and recurrent neural models frequently reporting strong predictive performance. However, the evidence also reveals important limitations, including restricted data accessibility, limited interpretability, high computational demands, and inconsistent evaluation methods, which reduce comparability across studies. The strong predictive performance of these models suggests their potential to support more effective customer segmentation and improved allocation of marketing resources. Future progress in customer lifetime value prediction will depend not only on improved model performance, but also on more transparent methods, publicly available benchmark datasets, and stronger attention to interpretability and practical applicability.

Women experiencing infertility face barriers to access Assisted Reproductive Technology (ART) services in Nigeria. Despite these barriers, some still access these services. This study explored the decision-making pathway and enablers of the use of ARTs among such persons in Lagos State. Using an interpretive phenomenological approach, we explored the decision-making process and enablers motivating the use of ART services among women who have experienced infertility. An open-ended semi-structured in-depth interview guide was used to collect data that were analyzed thematically. The study found that women who have used ART have had varied experiences resulting from their inability to conceive. The participants reported that they were sad, depressed, angry, and worried a lot about their situation and were dissatisfied after failed attempts. The participants reported other emotional moments where they cried, yelled, read their Bibles, and meditated to always feel better because of their condition, which assisted them in coping with their unmet expectations. Most of the participants received support from their husbands which helped them during their treatments and after failed attempts. The findings also revealed that one of the challenges faced by the participants while they used ART was the financial burden associated with it. In addition, the findings revealed that the decision-making pathway involved personal, interpersonal or relational thought processes to use Assisted Reproductive Technology for assisted conception and enablers which were a mix of emotional support from the mother, spouses, social pressures, information about health condition, professional and lay suggestions all contributed to the eventual use of ARTs. Results of this study indicate that infertile women received different forms of support that enabled the use of ARTs. However, women who used ART services experienced several psychosocial challenges. These ARTs have given infertile and childless couples some ray of hope and the chance to escape the burden and social stigma of childlessness. This study recommends that public health professionals collaborate with ART service providers in providing psychosocial care in addition to basic clinical care for infertile and childless women. Future studies can explore the perspectives of significant others as they played a key role in the decision and motivation to use ART.

Psychological intimate partner violence (IPV) is a common but often under-recognised form of gender-based violence, particularly among women in low- and middle-income countries. Evidence on the burden and associated factors of psychological IPV among female healthcare workers in Nigeria remains limited, despite the potential implications for well-being and workforce performance. This study assessed the prevalence and correlates of psychological IPV among female healthcare workers in a Nigerian facility. A cross-sectional study was conducted among female healthcare workers in a tertiary health facility in southwest Nigeria. Psychological IPV was assessed using an adapted Psychological Partner Abuse (PPA) scale. Descriptive statistics were used to summarise the distribution of psychological IPV scores, while bivariate analyses examined associations between psychological IPV and selected socio-demographic characteristics. Participants’ informed consent and ethical approval were obtained. Of the 284 respondents included in the analysis, 98.2% scored within the mild range of the psychological abuse scale. The mean total PPA score was 38.79 ± 9.84 (possible range: 21–147), indicating that reported experiences were predominantly clustered near the lower threshold of the mild category. Jealous/control and ignoring behaviours were the most commonly endorsed dimensions, largely at mild severity levels. Psychological IPV scores were significantly associated with marital status and ethnicity, whereas occupation and years of service were not. Psychological IPV symptoms were widely reported across socio-demographic groups among female healthcare workers in this setting, with most reported experiences clustering at mild levels close to the scale threshold. These findings underscore the importance of increased awareness, routine screening, and accessible support mechanisms within healthcare institutions, while recognising the exploratory nature of the observed associations.

Ethical awareness is fundamental to nursing and midwifery practice, influencing how students recognize and respond to ethical dilemmas in clinical settings. While ethics is well covered in nursing curricula, gaps often remain between theoretical knowledge and practical application. This study aimed to assess the levels of ethical knowledge, perception, and awareness among undergraduate nursing and midwifery students at Babcock University, Nigeria, and to examine the relationships among these constructs. A descriptive cross-sectional design was employed. A total of 206 undergraduate nursing and midwifery students were surveyed using a structured, self-administered questionnaire. Data were analyzed using descriptive statistics, correlation analysis, and regression models to determine associations between ethical knowledge, perception, and awareness. Most students demonstrated high knowledge of general ethical principles, with nearly all respondents familiar with patient rights and informed consent. Positive perceptions of ethics were more strongly correlated with ethical awareness ( r = 0.42, p < .001) than knowledge alone ( r = 0.29, p < .001). Regression analysis confirmed perception as a stronger predictor of ethical awareness. Furthermore, senior-level students with greater clinical exposure had significantly higher ethical awareness. While gender was reported in the demographics (87.4% female, 12.6% male), no statistical test demonstrated gender as a determinant of awareness. The findings highlight that while factual knowledge of ethics is strong, students' perceptions and experiential learning play a more decisive role in shaping ethical awareness. Ethics education should therefore emphasize reflective, practice-based, and culturally sensitive approaches to better prepare students for complex clinical decision-making. La conciencia ética es fundamental en la práctica de enfermería y partería, ya que influye en cómo los estudiantes reconocen y responden a los dilemas éticos en los entornos clínicos. Aunque la ética está ampliamente cubierta en los planes de estudio de enfermería, suelen existir brechas entre el conocimiento teórico y la aplicación práctica. Este estudio tuvo como objetivo evaluar los niveles de conocimiento, percepción y conciencia ética entre estudiantes de licenciatura en enfermería y partería de la Universidad Babcock, Nigeria, y examinar las relaciones entre estos constructos. Se empleó un diseño descriptivo transversal. Un total de 206 estudiantes de licenciatura en enfermería y partería fueron encuestados mediante un cuestionario estructurado y autoadministrado. Los datos se analizaron utilizando estadística descriptiva, análisis de correlación y modelos de regresión para determinar asociaciones entre conocimiento, percepción y conciencia ética. La mayoría de los estudiantes demostró un alto conocimiento de los principios éticos generales, con casi todos los encuestados familiarizados con los derechos del paciente y el consentimiento informado. Las percepciones positivas sobre la ética se correlacionaron más fuertemente con la conciencia ética ( r = 0.42, p < .001) que el conocimiento por sí solo ( r = 0.29, p < .001). El análisis de regresión confirmó la percepción como un predictor más fuerte de la conciencia ética. Además, los estudiantes de niveles avanzados con mayor exposición clínica presentaron una conciencia ética significativamente más alta. Aunque el género se reportó en la demografía (87.4% mujeres, 12.6% hombres), ninguna prueba estadística mostró al género como determinante de la conciencia. Los hallazgos destacan que, si bien el conocimiento factual de la ética es sólido, las percepciones de los estudiantes y el aprendizaje experiencial desempeñan un papel más decisivo en la formación de la conciencia ética. Por lo tanto, la educación en ética debe enfatizar enfoques reflexivos, prácticos y culturalmente sensibles para preparar mejor a los estudiantes frente a la toma de decisiones clínicas complejas.

Abstract Ischemic stroke remains a leading cause of mortality and long-term disability worldwide, necessitating innovative therapeutic approaches beyond conventional treatments. RNA-based therapeutics have emerged as a promising strategy to modulate key pathological processes involved in stroke, including neuroinflammation, apoptosis, oxidative stress, and neurovascular dysfunction. Small interfering RNA (siRNA) and microRNA (miRNA)-based therapies enable post-transcriptional gene silencing to downregulate deleterious pathways, while messenger RNA (mRNA) and long non-coding RNA (lncRNA)-based strategies promote neuroprotection and neuronal recovery. Despite significant preclinical advancements, several challenges hinder clinical translation, including blood-brain barrier (BBB) permeability, RNA stability, immune responses, off-target effects, and efficient intracellular delivery. Recent breakthroughs in nanoparticle-based delivery systems, exosome-mediated transport, and CRISPR-based RNA editing offer novel solutions to these limitations, paving the way for precision medicine approaches in stroke treatment. Future research must focus on optimizing RNA formulations, refining delivery mechanisms, and conducting rigorous clinical trials to establish their safety and efficacy in stroke patients. If successfully translated into clinical practice, RNA-based therapeutics have the potential to revolutionize stroke management by providing targeted, disease-modifying interventions that enhance functional recovery and reduce long-term neurological deficits.

AI-based emotion recognition has emerged as a critical component of affect-aware educational technologies, particularly in online, large-scale, and technology-mediated learning environments where direct observation of learners’ emotional states is limited. By leveraging facial expressions, speech, physiological signals, and interaction data, emotion-aware systems aim to support adaptive instruction, learner engagement, and instructional decision-making. Despite rapid technical progress, the integration of emotion recognition into authentic educational practice remains constrained by dataset limitations, cultural bias, weak pedagogical alignment, and unresolved ethical concerns. This article presents a critical and theory-informed review of recent advances in AI-based emotion recognition in education, with particular emphasis on deep learning architectures and multimodal fusion approaches, while highlighting persistent challenges and future research directions.Purpose:This study aims to critically examine the current state of AI-based emotion recognition in educational contexts by analyzing dominant modeling paradigms, sensing modalities, application domains, and ethical implications, in order to identify key gaps between technical development and pedagogical practice.Methods/Study design/approach:The study adopts a narrative literature review approach grounded in educational and affective computing theories. Representative and influential studies were analyzed across facial, speech, physiological, and multimodal emotion recognition systems, with emphasis on deep learning, attention-based, and transformer architectures. The review synthesizes findings related to system performance, educational applications, dataset characteristics, and ethical considerations.Result/Findings:The findings indicate that multimodal emotion recognition systems generally outperform unimodal approaches in detecting learning-relevant affective states such as engagement, frustration, and confusion. Advances in deep learning, particularly attention-based and transformer models, improve temporal modeling and robustness. However, most systems rely on non-educational datasets, demonstrate limited cultural generalizability, and prioritize recognition accuracy over pedagogical interpretability and long-term educational impact. Ethical challenges related to privacy, consent, bias, and emotional surveillance remain insufficiently addressed.Novelty/Originality/Value:This study provides an integrative and pedagogically grounded synthesis that bridges affective computing research with educational theory and governance perspectives. By reframing AI-based emotion recognition as a decision-support mechanism rather than an automated control system, the article offers a conceptual foundation for responsible, culturally inclusive, and ethically aligned deployment of emotion-aware AI in education, serving as a reference for future interdisciplinary research and policy development.

Abstract Purpose This study explores the strategic convergence of Artificial Intelligence (AI) and Blue Ocean Strategy (BOS) as transformative catalysts for sustainable industrial growth in BRICS countries, contextualised within the framework of Sustainable Development Goal 9 (SDG 9): Industry, Innovation and Infrastructure. Design/Methodology/Approach A qualitative-analytical methodology is employed, integrating systems thinking and comparative geopolitical analysis. The study uses secondary data to construct multi-metric tabulations, interpret policy architectures and evaluate AI-driven strategic trajectories across BRICS nations. Findings The research reveals asymmetrical, yet converging, trajectories in BRICS industrial ecosystems, with China and India emerging as frontrunners in AI adoption and strategic innovation, while Brazil, Russia and South Africa face structural constraints. The Blue Ocean paradigm facilitates non-linear market expansion, value creation without competition and inclusive growth. Research Limitations/Implications The study is conceptual and limited by the availability of real-time longitudinal data on AI deployment and Blue Ocean adoption in public-sector industries. Practical Implications Policymakers and corporate strategists can leverage AI-Blue Ocean synergies to design anticipatory infrastructure, decentralised innovation models and inclusive industrial ecosystems. Originality/Value This is one of the few studies to examine the triangulation of AI, BOS and SDG 9 within BRICS economies, offering a novel strategic blueprint for inclusive and sustainable industrial transformation.

Memory consolidation and the preservation of cognitive function are fundamentally influenced by sleep. Lack of sleep affects synaptic plasticity and neurogenesis, as well as oxidative stress and neuroinflammation, all of which impair memory accuracy, cognitive flexibility, and attention. The behavioural repercussions include decreased learning ability, attentional problems, emotional dysregulation, and heightened vulnerability to false memories. This review examines the neurobiological impact of sleep deprivation on memory and cognition, emphasising how the brain systems performing these functions are disrupted by insufficient sleep. The distinct sleep stages that are in support of declarative, procedural, and emotional memory, drawing on contemporary concepts such as the synaptic homeostasis hypothesis and the active system consolidation theory, were emphasised. We highlighted how sleep deprivation can affect important areas, especially the hippocampus, and cause problems with neurotransmitter systems and immune regulation. Preventative and therapeutic approaches, such as pharmacological supports, behavioural interventions, and the cognitive advantages of recovery sleep and naps, were also enumerated. These insights on how sleep and memory interact are vital for enhancing learning outcomes, mental health, and long-term brain resilience.

Gambling is commonly described as a risk-taking activity. The proliferation of betting outlets such as Bet Naija and Naira Bet, especially around football, has made gambling increasingly visible in Port Harcourt, Nigeria. Some of the gambling activities which are evident in Port Harcourt include, Bet Naija, 1960 Bet, 360 Bet, Naira Bet, lottery, land-based casino, dice and card games, Baba Ijebu, amongst others. Adolescence, marked by physical and psychological changes and a tendency toward risk-taking, may predispose young people to gambling. Although research has established links between adolescent gambling and anxiety, depression, conduct problems, and alcohol use, data on these issues in Nigeria remain sparse. This study sought to answer the following research questions: What is the prevalence of gambling among in-school adolescents in Port Harcourt? What is the relationship between gambling and mental health conditions such as anxiety, depression, conduct problems, alcohol use, and self-esteem? A descriptive cross-sectional survey was conducted in six secondary schools (public and private) across two local government areas, involving 338 students aged 10 to 19. The Massachusetts Gambling Screen (MAGS) and other standardized instruments were employed. The prevalence of gambling was 39.9%. Gambling was significantly associated with anxiety, depression, alcohol use, conduct problems and low self-esteem (P&lt;0.001). Gamblers reported social challenges and neglect of obligations (73%), chasing losses (68%), and family complaints (53%). This study demonstrated a notable prevalence of gambling among in-school adolescents in Port Harcourt, with higher rates observed among males. Gambling behaviour was significantly associated with symptoms of depression, anxiety, and poor academic performance, highlighting its link to adverse mental health outcomes. Weak regulatory enforcement exacerbates adolescent vulnerability to gambling. Keywords: Gambling, adolescents, mental health, correlates, anxiety, depression, alcohol use, self-esteem,