Methodological Rigor Research Articles

Health Outcomes of Produce Prescription Programs Associated with Gus Schumacher Nutrition Incentive Program Funding

The US Department of Agriculture's Gus Schumacher Nutrition Incentive Program (GusNIP) funds produce prescription (PPR) programs that allow healthcare to support patients in accessing fruits and vegetables. This hybrid systematic narrative review identified 16 studies of PPR programs associated with GusNIP funding in some way that examined health outcomes, including clinical measures and healthcare utilization. Program designs were heterogeneous, sample sizes were generally small, and methodological rigor was often low, with most studies using a prepost design and none using a randomized control group. Fewer than half of the studies examining clinical values showed an association between PPR participation and improved health outcomes (for example, three of eight studies measuring weight or body mass index showed a statistically significant reduction, as well as two of the six studies measuring glycosylated hemoglobin). Only three studies examined healthcare utilization, two of which showed improvements in hospitalization and/or emergency department utilization. Overall, evidence for the health impact of PPRs is nascent but growing. PPRs with capacity should engage in rigorous study designs and examine a variety of downstream health and utilization outcomes.

Uncertainty and Innovation: Assessing the Impact of Economic, Monetary, Trade, and Fiscal Shocks in Japan and the United States

ABSTRACTIn today's competitive global economy, innovation is crucial for growth, competitiveness and societal progress. This study examines the relationship between various economic uncertainties and innovation outputs from 1987 to 2022 in the United States and Japan. Using the PMG‐ARDL model, it analyzes the effects of economic policy uncertainty (EPU), monetary policy uncertainty (MPU), trade policy uncertainty (TPU) and fiscal policy uncertainty (FPU) on innovation. Pre‐estimation techniques, including CD analysis, unit root analysis and cointegration analysis, ensure methodological rigour. The findings indicate that EPU, MPU, TPU and FPU negatively affect ICT exports and patent applications (PTA), as uncertainties hinder business decision‐making and investment in research and development. However, MPU and TPU positively affect innovation in Japan, and MPU has a positive effect in the United States. These results highlight the importance of considering country‐specific dynamics in policy formulation. Policymakers should enhance transparency, stability and communication to foster innovation. This study contributes by exploring the diverse impacts of economic uncertainties on innovation.

The Art of Analysis: Crafting Credible and Authentic Qualitative Results.

Qualitative research offers unparalleled insights into complex human experiences. The rigour of qualitative data analysis is critical to ensuring credible and actionable findings. Different qualitative methodologies offer unique lenses to explore human experiences. However, challenges such as context dependency and potential biases necessitate alignment between research aims, analytical strategies and ethical practices to preserve participant voices and ensure methodological rigour. This narrative review synthesises foundational qualitative methodologies and recent research, offering practical strategies to address challenges in data analysis within nursing and health-related research. Robust qualitative analysis requires clear analytical aims, reflexivity and ethical integrity. We explore common pitfalls, such as superficial analyses and a lack of transparency, while emphasising the role of rigorous methodologies in ensuring validity, reliability and meaningful findings. Rigour in qualitative analysis transforms research into actionable insights, informing culturally sensitive care, evidence-based interventions and nursing education. High-quality analysis strengthens the discipline and improves patient outcomes. Qualitative research demands meticulous and ethical analysis to unlock its full potential. Nurse researchers can deliver findings that drive impactful change in healthcare practice and policy by prioritising analytical rigour and transparency. No Patient or Public Contribution.

Effect of Craft Competency on the Implementation of the Five Case Model in Zimbabwe

The Five Case Model (FCM) serves as a robust evaluative and decision-making framework within Public Financial Management (PFM), facilitating the systematic justification, structuring, and implementation of public sector projects. Despite its methodological rigor, its efficacy is often compromised by disparities in craft competency among financial managers, particularly within local authorities in Zimbabwe’s Matabeleland North Province. This study empirically investigates the extent to which variations in craft competency influence the implementation of five case model in eight local authorities in Matabeleland North Province, Zimbabwe. This encompassed technical proficiency, strategic financial acumen and industry-specific expertise with an emphasis on resource allocation efficiency, financial sustainability, and strategic alignment. Employing a quantitative methodology, the study utilizes Regression Analysis to establish causal relationships between craft competency and FCM execution, while controlling for variables such as organizational support, regulatory environment, and technological adoption. The findings depict a significant positive correlation between craft competency and FCM implementation efficacy, revealing that well-trained staff and executives exhibit superior decision-making, enhanced compliance with public financial regulations, and greater project success rates. However, rigid regulatory frameworks and economic volatility emerge as substantial impediments, exacerbating inefficiencies in business case formulation and project execution. The study advocates for targeted capacity-building interventions, regulatory reforms to streamline bureaucratic processes, and the integration of digital financial management tools to augment competency-driven PFM outcomes. These findings contribute to the ongoing discourse on public sector financial governance, offering empirical insights into optimizing financial management practices through enhanced professional expertise and strategic policy interventions.

Multimodal Data-Driven Visual Sensitivity Assessment and Planning Response Strategies for Streetscapes in Historic Districts: A Case Study of Anshandao, Tianjin

The landscape visual sensitivity (LVS) assessment is recognized as a critical tool for identifying areas most sensitive to landscape changes and for informing multi-resource optimization and allocation strategies. However, conventional large-scale LVS assessment criteria and methodologies developed for natural landscapes do not satisfy the precision-oriented assessment requirements of streetscape visual sensitivity (SVS) in historic districts, nor do they facilitate the operational linkage between assessment outcomes and planning applications. This study proposes an innovative SVS–PAP assessment methodology, which is a systematic integration of the SVS assessment and public esthetic perception (PAP) evaluation. The SVS assessment criteria framework was first improved through the integration of enriched multi-modal datasets. Subjective weights were obtained via the analytic hierarchy process (AHP), incorporating expert and public judgments, while objective weights were derived through the entropy weight method (EWM) based on data information entropy. The integration of both approaches enhances the methodological rigor and scientific validity of SVS weight determination. An SVS–PAP analytical matrix was subsequently constructed through integration of SVS assessments and PAP-based scenic beauty estimation (SBE), enabling the derivation of planning strategies. An empirical validation conducted in Anshandao Historic District yielded four key findings: (1) The SVS–PAP methodology, which integrates subjective–objective evaluation factors and incorporates broad public participation, demonstrates strong scientific validity and reliability, establishing a novel paradigm for SVS assessment and strategic planning; (2) The technical framework—leveraging multi-modal data and GIS spatial analysis techniques—improves assessment precision, operability, and replicability; (3) The planning and management strategies formulated by the SVS–PAP analytical matrix were verified as reasonable, demonstrating effective planning-transition capability; (4) Notably, historical and cultural influences showed significantly higher weighting coefficients across assessment criteria compared to non-historic streetscape assessments. Overall, these research results address the persistent undervaluation of the esthetic and spiritual values of historic landscapes in multi-resource value trade-off and decision-making processes, demonstrating both theoretical and practical significance through a systematic methodological advancement.

Mapping Quality Judgment in International Relations: Cognitive Dimensions and Sociological Correlates

Research quality assessment is a cornerstone of academic practice, yet the criteria that inform such judgments are often assumed rather than critically examined through empirical research. This article draws on a global survey of international relations (IR) scholars (N = 820) to analyze the cognitive dimensions underlying research quality evaluation and their variation across sociological and epistemological factors. We identify seven distinct quality factors: theoretical significance, logical style and structure, practical significance, methodological rigor, contribution and value for future research, interest and topicality, and challenge to existing knowledge. Our results suggest that, while personal preferences, disciplinary norms, and professional practices—shaped by variables such as gender, nationality, and political orientation—influence evaluations, research quality judgments are ultimately grounded in shared cognitive frameworks. Our study offers robust evidence that quality assessments, though subject to sociological variation, reflect deeper, common cognitive structures across scholarly communities.

Duration of untreated or undiagnosed bipolar disorder and clinical characteristics and outcomes: systematic review and meta-analysis.

The duration of undiagnosed or untreated bipolar disorder (DUBD) has become a focus of research interest. However, its relationship with clinical characteristics and outcomes remains poorly understood. The objective of this systematic review and meta-analysis was to examine DUBD and explore its relationships with clinical characteristics and outcomes in bipolar disorder. We conducted a systematic search of the literature to identify studies reporting on DUBD and its relationships with clinical characteristics and outcomes including frequency of relapse into mood episodes, severity and persistence of mood symptoms, functional and cognitive measures, suicidality, hospital admission rate, and comorbidities such as substance use disorders. Thirty articles met inclusion criteria for the systematic review, and 23 studies were included in the three different sets of meta-analyses. The pooled mean DUBD across all studies was 9.10 years. Early onset, depression as the polarity of the first mood episode, lifetime suicide attempts, comorbid anxiety and alcohol use disorders, and family history of bipolar disorder were associated with significantly longer DUBD, whereas diagnosis of bipolar I disorder and lifetime psychotic symptoms were associated with shorter DUBD. Studies that investigated outcomes subsequent to the diagnosis of bipolar disorder yielded conflicting results. DUBD may be associated with certain adverse outcomes. This association indicates the importance of adopting a more comprehensive approach to assessing mood disorders, with an emphasis on prioritising early screening for bipolar disorder. The significant heterogeneity among included studies suggests a need for improved methodological rigour in future research.

The Application of Classic Grounded Theory in Nursing Studies: A Qualitative Systematic Review.

To explore the application of Classic Grounded Theory (GT) methodology in nursing research and critically appraise studies employing Classic GT against the validated framework Guideline for Reporting and Evaluating Grounded Theory (GUREGT) research studies. Systematic review without meta-analysis METHODS: The review followed the PRISMA statement and used the Synthesis Without Meta-analysis (SWiM) guideline for data analysis. The quality of included articles was assessed using the CASP qualitative research appraisal tool, and the GUREGT framework was applied to evaluate adherence to Classic GT guiding principles. Databases were PUBMED, CINAHL, Nursing and Allied Health Database (ProQuest). Twenty-nine studies from 2010 to 2024 met the inclusion criteria. Findings revealed inconsistencies in the reporting of Classic GT methodology in nursing research, with frequent omissions of key methodological elements. The GUREGT tool, while user-friendly and practical, highlights gaps in areas such as identifying the main concern, philosophical positioning, and engagement with the literature. These omissions can compromise methodological rigour, suggesting that further refinement of the GUREGT tool is necessary. The GUREGT tool provides a promising framework for improving the reporting and evaluation of Classic GT studies. However, its current version requires enhancement to fully address the unique demands of Classic GT and ensure rigorous application and reporting of the methodology. Development of a dedicated reporting guideline tailored to Classic GT is critical for advancing the quality of nursing research and supporting researchers in generating robust, theory-driven insights. Few studies critically appraise Classic GT methodology in health research. This review highlights the need for dedicated reporting guidelines to support methodological rigour and transparency in Classic GT studies. This review adhered to EQUATOR reporting guidelines. No patient or public contribution.

A Three-Level Meta-Frontier Framework with Machine Learning Projections for Carbon Emission Efficiency Analysis: Heterogeneity Decomposition and Policy Implications

This study proposes a three-level meta-frontier framework enhanced with machine learning-driven projection methods to address the dual heterogeneity in carbon emission efficiency analysis arising from regional disparities and industrial diversification. Methodologically, we introduce two novel projection combinations—“exogenous-exogenous-accumulation (E-E-A) and exogenous-exogenous-consistent (E-E-C)”—to resolve the inconsistency of technology gap ratios (TGRs > 1) in traditional nonradial directional distance function (DDF) models. Reinforcement learning (RL) optimizes dynamic direction vectors, whereas graph neural networks (GNNs) encode spatial interdependencies to constrain the TGR within [0, 1]. Empirical analysis of 60 countries reveals that (1) E-E-C eliminates the TGR overestimation by 12–18% in energy-intensive sectors (e.g., reducing Asia’s secondary industry TGR1 from 1.160 to 1.000); (2) industrial heterogeneity dominates inefficiency in Asia (IHI = 0.207), whereas management gaps drive global secondary sector inefficiency (MI = 0.678); and (3) policy simulations advocate for decentralized renewables in Africa, fiscal incentives for Asian coal retrofits, and expanded EU carbon border taxes. Computational enhancements via Apache Spark achieve a 58% runtime reduction. The framework advances environmental efficiency analysis by integrating machine learning with meta-frontier theory, offering both methodological rigor (via regularization and GNN constraints) and actionable decarbonization pathways. Limitations include static heterogeneity assumptions and data granularity gaps, prompting the future integration of IoT-enabled dynamic models.

Redefining Corporate Social Responsibility: The Role of Strategic Communication Practices

Corporate Social Responsibility (CSR) and its sustainability-focused communications are now recognized as essential corporate activities. As society increasingly holds firms accountable for their social, environmental, and sustainability impacts, academic interest in CSR communications has similarly grown, with scholars exploring how CSR communication influences stakeholder engagement and corporate strategies. In response to this growing interest, we conducted a systematic literature review utilizing bibliometric analysis to identify and examine publication trends and patterns in CSR and CSR-associated communications, drawing from a robust dataset of 3513 documents extracted from Scopus and Web of Science. The analysis was conducted using the Biblioshiny R package and Excel to ensure methodological precision and analytical depth. We explored the characteristics of publications related to topics such as business, authorship, and journals over a four-decade period spanning from 1984 to 2024. Our results reveal four strategic clusters of CSR disclosure, reflecting a shift from symbolic to strategic and stakeholder-focused communication. Thematic evolution highlights the growing integration of ESG frameworks and digital reporting practices. This study is significant not only in its methodological rigor but also in its timely contribution to the intersection of CSR, sustainability, and strategic communication. Also, this study introduces a new theoretical framework through the CSR strategic disclosure indicator metric, which connects the level of disclosure maturity with the focus on different stakeholder groups. We discuss the implications of our findings not only for future scholarly research in CSR but also for corporate sustainability practitioners who look to academia for insights on emerging trends in CSR and CSR reporting.

Current Technological Advances in Dysphagia Screening: Systematic Scoping Review.

Dysphagia affects more than half of older adults with dementia and is associated with a 10-fold increase in mortality. The development of accessible, objective, and reliable screening tools is crucial for early detection and management. This systematic scoping review aimed to (1) examine the current state of the art in artificial intelligence (AI) and sensor-based technologies for dysphagia screening, (2) evaluate the performance of these AI-based screening tools, and (3) assess the methodological quality and rigor of studies on AI-based dysphagia screening tools. We conducted a systematic literature search across CINAHL, Embase, PubMed, and Web of Science from inception to July 4, 2024, following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. In total, 2 independent researchers conducted the search, screening, and data extraction. Eligibility criteria included original studies using sensor-based instruments with AI to identify individuals with dysphagia or unsafe swallow events. We excluded studies on pediatric, infant, or postextubation dysphagia, as well as those using non-sensor-based assessments or diagnostic tools. We used a modified Quality Assessment of Diagnostic Accuracy Studies-2 tool to assess methodological quality, adding a "model" domain for AI-specific evaluation. Data were synthesized narratively. This review included 24 studies involving 2979 participants (1717 with dysphagia and 1262 controls). In total, 75% (18/24) of the studies focused solely on per-individual classification rather than per-swallow event classification. Acoustic (13/24, 54%) and vibratory (9/24, 38%) signals were the primary modality sources. In total, 25% (6/24) of the studies used multimodal approaches, whereas 75% (18/24) used a single modality. Support vector machine was the most common AI model (15/24, 62%), with deep learning approaches emerging in recent years (3/24, 12%). Performance varied widely-accuracy ranged from 71.2% to 99%, area under the receiver operating characteristic curve ranged from 0.77 to 0.977, and sensitivity ranged from 63.6% to 100%. Multimodal systems generally outperformed unimodal systems. The methodological quality assessment revealed a risk of bias, particularly in patient selection (unclear in 18/24, 75% of the studies), index test (unclear in 23/24, 96% of the studies), and modeling (high risk in 13/24, 54% of the studies). Notably, no studies conducted external validation or domain adaptation testing, raising concerns about real-world applicability. This review provides a comprehensive overview of technological advancements in AI and sensor-based dysphagia screening. While these developments show promise for continuous long-term tele-swallowing assessments, significant methodological limitations were identified. Future studies can explore how each modality can target specific anatomical regions and manifestations of dysphagia. This detailed understanding of how different modalities address various aspects of dysphagia can significantly benefit multimodal systems, enabling them to better handle the multifaceted nature of dysphagia conditions.

Perioperative Health Care Disparities in the United States: A Systematic Review.

Perioperative health inequities remain a critical issue, contributing to unequal patient outcomes and financial costs despite increasing awareness and efforts to address these disparities. This systematic review evaluated anesthesiology literature from 2010 to 2023 on perioperative health care disparities related to race, ethnicity, gender, and socioeconomic status. The review aimed to identify gaps and propose research and opportunities for intervention. A comprehensive literature search was conducted using PubMed, Embase, Scopus, and Web of Science, with studies included if they focused on perioperative disparities in the United States, were published in anesthesiology journals, and met criteria for methodological rigor. The review was registered with International Prospective Register of Systematic Reviews (PROSPERO); data extraction followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and study quality was assessed with the Newcastle-Ottawa scale. Out of 1050 abstracts screened, 116 articles were reviewed for full text, with 59 studies meeting inclusion criteria. Included studies comprised retrospective cohort studies, cross-sectional analyses, a case-control study, and a randomized controlled trial, covering various surgical procedures and sample sizes from 100 to over 21 million patients. Disparities were noted in peripartum management (n = 14), mortality (n = 12), complications (n = 8), regional anesthesia use (n = 6), and pain management (n = 3), with evidence of poorer outcomes in Black and Hispanic women, older adolescents, and patients who were uninsured or on Medicaid. This review highlights the persistence of significant perioperative disparities and identifies gaps, such as limited exploration of the causes of these disparities, limited examination of disparities during the preoperative and intraoperative period, and few interventions to address these identified disparities. Reducing these disparities requires stakeholder engagement, multifaceted approaches, culturally agile training for health care teams, enhanced decision support tools, and a more diverse health care workforce. Continued research and targeted interventions at individual, community, and societal levels are essential for improving perioperative outcomes.

Students as co-designers in health professional education: a scoping review

BackgroundOver the last thirteen years, there has been a notable increase in both research and practice related to student-staff partnerships in higher education. However, within health professional education (HPE), studies on these partnerships remain limited and often rely on broader higher education frameworks. Existing research primarily focuses on role dynamics and relational aspects rather than on structured co-design processes, where students actively contribute to shaping educational content, assessments, or curricula. Building upon previous work, this study specifically examines co-design as a distinct dimension of student-staff partnerships in HPE, an area that has not been thoroughly addressed in recent literature reviews.MethodsIn accordance with the PRISMA-ScR 2018 statement, we performed searches in online databases—Cochrane, Ovid, PubMed, ScienceDirect, and Scopus—for original articles published in English from 2010 to 2023. These articles needed to describe empirical studies focused on co-designed training programs in health professions. We then conducted a qualitative and descriptive analysis of the selected articles to examine how the principle of students as co-designers is portrayed and investigated in health professional education.ResultsThe search (title, abstract, keywords) identified 703 potentially relevant abstracts addressing co-design in healthcare education. Screening of these abstracts narrowed it down to 84 articles. Further evaluation of these full articles resulted in a final sample of 20 articles that met the inclusion criteria. We analyzed the content of these 20 articles using the following categories: basic characteristics (year of publication, country, professional domain, educational grade, topic of the training), co-design characteristics (context and initiative, framework and definition, purposes, stakeholders, process), and study characteristics (aim, research framework, population, data collection and analysis, key findings). Our analysis revealed that co-design in HPE lacks standardized frameworks and rigorous empirical evaluation. Many studies emphasize student contributions but do not provide detailed methodological guidance on how co-design is structured, implemented, or assessed. Additionally, findings indicate that most studies focus on undergraduate education, with postgraduate applications remaining underexplored.ConclusionsThis review underscores co-design as an emerging yet underdeveloped approach in health professional education. While its potential benefits—such as enhancing student engagement, fostering innovation, and improving training relevance—are widely acknowledged, the field lacks structured methodologies and theoretical grounding. Future research should focus on developing clear frameworks, assessing co-design’s long-term impact on learning outcomes, and differentiating it from broader collaborative approaches. Strengthening methodological rigor and empirical validation will be essential for positioning co-design as a sustainable and evidence-based practice in health professions education.

Decadal Analysis of Research Trends in Statistical Literacy

This study critically examines the evolving landscape of statistical literacy research from 2015 to 2024 through bibliometric analysis of publication trends, co-authorship networks, co-citation patterns, and keyword clusters. Findings reveal a field marked by dynamic growth but persistent fragmentation, with publication output rebounding after early fluctuations to peak in 2024. While interdisciplinary connections between statistical literacy, healthcare, and education demonstrate strength, the analysis uncovers significant gaps in equity-focused research, representation of emerging scholars, and integration with modern data science paradigms. Co-citation networks highlight the dominance of established figures, suggesting systemic barriers to broader recognition, while keyword analysis reveals tensions between methodological rigor and practical application. The study identifies three key recommendations: fostering inclusive collaboration to amplify underrepresented voices, bridging theory and practice through innovative educational tools, and systematizing research agendas through standardized frameworks. These findings underscore the need for intentional strategies to ensure statistical literacy research remains relevant, equitable, and impactful in addressing contemporary data-driven challenges.

Navigating the Use and Misuse of Likert Scales in Counseling and Development Research

Likert scales are crucial for advancing counseling and development research by quantifying subjective responses. However, their ordinal nature often leads to misuse, particularly when ordinal data are misinterpreted as interval data, skewing results. This paper explores the methodological intricacies of Likert scales, integrating theoretical insights and empirical findings to provide a comprehensive understanding. Drawing on seminal works by Likert and contemporary discussions, the authors emphasize the importance of straightforward, unbiased item design and adherence to best practices in data management. The paper examines the benefits of comparative research and the risks of misinterpretations when scales are adapted without contextual adjustments. It concludes with recommendations for improving methodological rigor in Likert scale applications and promoting critical awareness, leveraging the Rasch model, an Item Response Theory (IRT) statistical approach, as the preferred modeling framework.

Measuring the Marginal Gap of Pre-Cemented All-Metal Single Crowns: A Systematic Review of In Vitro Studies

Background: Different methods have been used to fabricate and measure marginal gap in all-metal crowns, yet a systematic review on this topic has not been conducted. Objective: To review the existing literature regarding the measurement methods employed for the in vitro marginal gap measurement of pre-cemented all-metal single crowns and examine the influence of crown fabrication method on the marginal gap. Materials and Methods: A systematic search was performed from December 2024 backwards across EBSCO Host, Scopus, PubMed, and Web of Science databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and predefined eligibility criteria. The quality of included articles was evaluated using the Joanna Briggs Critical Appraisal Checklist. Results: Ten studies, involving 180 crowns, assessed marginal gaps using computerised superimposition (102 µm), scanning electron microscopy (89 µm), profilometry (100 µm), photogrammetry (59 µm), impression replica techniques (124 µm), and direct view microscopy (35 µm). Marginal gaps varied across crowns constructed with cobalt–chromium (97 µm), titanium (56 µm), noble metals (127 µm), and base metal alloys (35 µm). No significant differences (t = 1.06, p = 0.315) were observed between CAD/CAM (103.21 ± 58.56 µm) and lost wax casting method (71.59 ± 43.94 µm) of crown fabrication when analysed using an independent t-test. Conclusions: Cobalt–chromium was the most used material for AMCs, while titanium alloys produced the lowest mean marginal gap per crown. No significant differences in reported marginal gaps were observed between crowns fabricated using lost wax casting and CAD/CAM techniques. However, the limited number of studies, variation in measurement methods, and inconsistency in methodological rigour restricted the generalisability of the findings.

Perceptions of artificial intelligence on the future of employees' job security in Africa: secondary data analysis

In the rapidly evolving digital era, introducing AI has become a pivotal factor across all organisational levels. However, the global proliferation of artificial intelligence has sparked immediate apprehension among the currently employed and those seeking employment. As we navigate the societal transformations of the twenty-first century, the dynamic interplay between AI and job security has risen as a crucial area of investigation within Human Resources Management research. This investigation delves into the global perceptions of artificial intelligence on the future of employees' job security in the workplace, a question of paramount importance in the current landscape. This study is a systematic review, with the data comprising previously published research articles, reports, and studies collected and analysed to gain comprehensive insights. The systematic literature review was conducted in five steps: developing explicit questions for critique, collecting and categorising data, evaluating, summarising evidence, and discussing. The process necessitated retrieving data from various databases, including Scopus, Sabinet, Science Direct and Elicit. The research adhered to the PRISMA guidelines, a widely accepted framework for conducting systematic reviews, to ensure methodological rigour and transparency in the research process. The findings offer mixed perceptions of artificial intelligence on future employees' job security in Africa. The study provides themes in relation to how employees in the African affiliation view the integration of AI in the workplace: Future uncertainties, Role of AI in HR Practices, Employee well-being, training and development, Positive attitudes towards AI and job opportunities. The investigation highlighted AI challenges and opportunities in Africa, making sense of why employees do not trust the introduction of AI, as it is perceived as a threat to their jobs. It offers valuable guidelines for decision-makers in Africa to ensure that AI is utilised legally and ethically and that steps are in place to mitigate employment losses.

Difficult Airway Management: An Analysis of Systematic Review Evidence Underpinning Clinical Practice Guidelines.

Difficult Airway Management: An Analysis of Systematic Review Evidence Underpinning Clinical Practice Guidelines.

Scoping Review on the Effects of Simulation-Based Interventions on Reducing Stigma Toward People with Schizophrenia

IntroductionSchizophrenia imposes a significant burden on global public health and is associated with pervasive stigmatization, perpetuating misconceptions of danger and incompetence. This review examines the efficacy of simulation interventions in reducing stigmas associated with schizophrenia and fostering empathy towards affected individuals.MethodsA comprehensive literature review spanning from August 2021 to September 2022 identified 14 relevant studies meeting inclusion criteria.ResultsAnalysis revealed a diverse landscape of simulation-based interventions, characterized by variability in methodological rigor, intervention design, and technological modalities. While some studies demonstrated promising outcomes in stigma reduction and empathy enhancement, methodological limitations and inconsistencies underscore the need for cautious interpretation of findings. Furthermore, mixed outcomes in stigma characteristics and empathy development highlight the complexity of intervention effectiveness.DiscussionDespite these challenges, simulation interventions, particularly when integrated with additional components, hold potential in mitigating stigmatization and promoting empathy. Future research should prioritize methodological rigor, comprehensive outcome assessment, and tailored intervention strategies to advance the field of stigma reduction in schizophrenia.

The effects of Hyperkyphosis on Balance and Fall Risk in older adults: A Systematic Review.

The effects of Hyperkyphosis on Balance and Fall Risk in older adults: A Systematic Review.