Level Of Experience Research Articles

EFL Teachers’ Perspectives Towards the Use of Textbooks in Classroom

This paper addresses the research of exploring EFL teachers’ perspectives towards using textbooks, their strategies, and challenges in using the textbook in the classroom. The participants of the study were a diverse group of teachers at the language department at the University of Guanajuato, in Guanajuato, Mexico, encompassing various levels of teaching experience and proficiency levels. This was a case study utilizing the qualitative method as the approach, semi-structured, was conducted. The results showed that the perceptions were neutral towards using this material; the participants recognized the benefits and the disadvantages of using instructional material. There were two main difficulties expressed by the teachers: meaningful learning and cultural awareness. Overall, this research contributes to a deeper understanding of the complexities involved in textbook use in EFL classrooms. Finally, these research findings are expected to help other EFL teachers make well-informed choices about textbook selection, adaptation, and enrichment to improve teaching and learning outcomes.

Effects of Experience and Computer Proficiency on the Acceptance Behaviour of Accountants towards Usage of Cloud-Based Accounting Technology. A case of Nigerian Accountants

This paper examined the moderating role of experience and computer proficiency level on the factors of acceptance behaviour of Nigerian accountants towards the usage of cloud-based accounting technology. This study identified three factors influencing an accountant's willingness to adopt CBAT: its perceived usefulness, complexity or ease of use, and external influences such as pressure from professional associations and peers. Data were gathered through a survey questionnaire from 319 chartered accountants in an online-focused group. The analysis, conducted using structural equation modelling, reveals that all three factors - perceived usefulness, ease of use, and external pressure - have a significant and positive direct impact on an accountant's acceptance behaviour, confirming their influential roles in shaping adoption decisions, findings suggest that all direct relationships significantly positively affect acceptance behaviour. After that, experience and computer proficiency levels were introduced separately into the model as moderators. Conclusions of the analysis suggested that all hypothesised effects (except for H1a) moderate the relationships between the endogenous and exogenous variables of the model. Overall, this study observed that accountants recognise CBAT as highly useful and that the years of experience of the accountant, as well as his computer proficiency levels, are important factors that support their desire to adopt the cloud accounting tool.

Nurses during war: Profiles-based risk and protective factors.

Nurses in southern Israel's public hospitals were exposed to unusual traumatic events following the October 7, 2023, Hamas attack on Israel, and the ensuing Swords of Iron War. This study aimed to clarify the complexity of wartime nursing by identifying profiles based on risk factors (i.e., psychological distress and adjustment disorders) and protective factors (i.e., positive affect (PA), resilience, and perceived social support [PSS]). This study utilizes a cross-sectional design. Two hundred nurses at a major public hospital in southern Israel completed self-report questionnaires. A latent profile analysis (LPA) was conducted to identify distinct profiles based on nurses' risk and protective factors. Differences in profiles were examined alongside sociodemographic and occupational variables and traumatic event exposure. The LPA was conducted using MPlus 8.8 Structural Equation Modeling (SEM) software. Two distinct profiles were identified: "reactive" and "resilient." The "reactive" group included nurses who had higher risk factor scores (psychological distress and adjustment disorder), whereas the "resilient" group included nurses who had higher protective factor scores (PA, resilience, and PSS). Furthermore, nurses in the "reactive" group were younger, with greater seniority, worse self-rated health, and a higher frequency of kidnapped family members compared to nurses from the "resilient" group. Nurses in wartime are at risk if identified as "reactive." Identifying these profiles can assist in developing effective support practices to help nurses cope with wartime challenges and maintain their mental well-being. Healthcare organizations should tailor interventions to prepare and support nurses of various ages and experience levels, during and after conflicts. This approach aims to reduce risk factors and promote protective factors among nurses during wartime.

Barriers to postgraduate education in primary dental care: a qualitative study

ObjectivesPostgraduate education for primary care dentists offers numerous benefits in terms of advancing clinical skills and career opportunities, culminating in improved treatment and patient outcomes. There is a strong desire amongst primary care dentists to enhance skills and provide contemporaneous evidence-based dentistry, accredited by higher educational qualifications. However, significant barriers hinder their pursuit of further training and career advancement. The aim of this study is to explore the barriers to undertaking formal postgraduate education for dental practitioners working in primary dental care. Exploration of these perceptions should help to identify further areas of study to help alleviate some of these obstacles, enabling more primary care dentists to access postgraduate education and improve patient care. MethodA qualitative study was undertaken through individual narrative interviews with primary care dental practitioners (n = 20) with varying levels of experience and located across the UK. All interviews were conducted using a study guide, transcribed and analysed thematically. ResultsThe participants indicated that there is a strong desire to undertake postgraduate study amongst primary care dental practitioners. Significant barriers were identified, with three major themes emerging:1.Personal Cost: Time constraints and accessibility, Financial Burden, Family Commitments.2.Business Viability: Business time constraints, Inability to use Enhanced Skills, Remuneration systems.3.Business Culture and Team Dynamics: Stage of Career, Current Practice Business Model, Leadership and Vision.These barriers appear to be multifaceted and interconnected, however participants also identified significant opportunities to address them. ConclusionStudy participants identified a range of personal and professional barriers to undertaking postgraduate dental education whilst working in primary dental care. Practitioners working within predominately NHS orientated practices perceived more professional barriers than those in private practice. The majority of participants indicated their preference for hybrid models of education which would work around clinical commitments. Further research and engagement with stakeholders should be undertaken to help reduce these barriers.

EFL instructors’ perceptions of integration digital transformation in EFL learning context in Higher Education

This paper explores the integration of digital technologies and tools in English as a Foreign Language (EFL) learning in Jordanian Higher Education through a qualitative open-ended online survey. It highlights the perceptions of 100 Jordanian EFL instructors, each with a minimum of five years of experience, on the digital transformation in the EFL learning process. The survey, consisting of ten open-ended questions, gathered in-depth insights on the benefits, challenges, and implications of this transformation. Thematic analysis was employed to analyze the qualitative data, revealing varied levels of experience, the use of diverse digital tools, and both technical and pedagogical challenges. Key findings include the positive impact of digital tools on teaching and learning experiences, enhanced student engagement, and opportunities for personalized learning and collaboration. The study concludes that leveraging digital resources can enhance EFL learner engagement and learning outcomes, inform future pedagogical practices, and shape the landscape of digital transformation in EFL Higher Education for years to come.

Lessons learned from the Sexual Medicine Society of North America fellowship bootcamp.

Sexual Medicine Society of North America (SMSNA) fellowships offer variable experience in sexual health domains: erectile dysfunction, Peyronie's disease, male infertility, male hypogonadism (low testosterone), reconstruction (including male incontinence), benign prostatic hyperplasia, gender affirmation surgery, sexual mental health, and female sexual dysfunction. To evaluate baseline and postbootcamp understanding and trust in these domains. In 2023, 28 of 31 urologists currently enrolled in SMSNA-endorsed fellowships participated in a 3.5-day training bootcamp in Minneapolis, Minnesota. Participants were asked to complete pre- and postbootcamp surveys. The bootcamp curriculum offered American Urological Association guidelines and case-based lectures, hands-on clinical training with cadavers (penile surgery) and models (collagenase training), and interaction with industry. Changes in knowledge, independence, and trust in performing the procedures, as well as billing issues and feedback for future bootcamps. Prebootcamp surveys revealed vastly varied residency experience. Reported time with an expert faculty member was greatest for benign prostatic hyperplasia and least for female sexual dysfunction, gender affirmation surgery, and low testosterone. The lowest prebootcamp confidence in performing surgery independently was for penile grafting procedures and elevating the neurovascular bundle. Postbootcamp results revealed several areas of significant improvement in confidence (P ≤ .03): intralesional injections for Peyronie's disease, manual modeling, penile plication, penile grafting procedures, and elevating the neurovascular bundle. There was a trend for improved confidence with the insertion of inflatable (P = .05) and semirigid (P = .08) penile prostheses. Nonsignificant improvement occurred in artificial urinary sphincter surgery (P = .12). Participants graded the bootcamp very highly and requested that next year's bootcamp have more content on female sexual dysfunction, male incontinence, and low testosterone, as well as more hands-on skills sessions and case-based lecture formats. Offering a bootcamp with hands-on instruction could significantly improve urologists' knowledge and confidence. As the main strength, this study was the first specialized bootcamp for urologists in the subject of men's health, taking into account hands-on and cadaver laboratories, as well as highlighting industrial and pharmaceutical products. The small sample size was the major limitation. Current SMSNA fellows present with varied levels of experience and confidence across sexual health domains. Notable confidence improvements were seen with topics that combined didactic lectures with hands-on trainings.

Expert-Level Detection of Referable Glaucoma from Fundus Photographs in a Safety Net Population: The AI and Teleophthalmology in Los Angeles Initiative.

To develop and test a deep learning (DL) algorithm for detecting referable glaucoma in the Los Angeles County (LAC) Department of Health Services (DHS) teleretinal screening program. Fundus photographs and patient-level labels of referable glaucoma (defined as cup-to-disc ratio [CDR] ≥ 0.6) provided by 21 trained optometrist graders were obtained from the LAC DHS teleretinal screening program. A DL algorithm based on the VGG-19 architecture was trained using patient-level labels generalized to images from both eyes. Area under the receiver operating curve (AUC), sensitivity, and specificity were calculated to assess algorithm performance using an independent test set that was also graded by 13 clinicians with one to 15 years of experience. Algorithm performance was tested using reference labels provided by either LAC DHS optometrists or an expert panel of 3 glaucoma specialists. 12,098 images from 5,616 patients (2,086 referable glaucoma, 3,530 non-glaucoma) were used to train the DL algorithm. In this dataset, mean age was 56.8 ± 10.5 years with 54.8% females and 68.2% Latinos, 8.9% Blacks, 2.7% Caucasians, and 6.0% Asians. 1,000 images from 500 patients (250 referable glaucoma, 250 non-glaucoma) with similar demographics (p ≥ 0.57) were used to test the DL algorithm. Algorithm performance matched or exceeded that of all independent clinician graders in detecting patient-level referable glaucoma based on LAC DHS optometrist (AUC = 0.92) or expert panel (AUC = 0.93) reference labels. Clinician grader sensitivity (range: 0.33-0.99) and specificity (range: 0.68-0.98) ranged widely and did not correlate with years of experience (p ≥ 0.49). Algorithm performance (AUC = 0.93) also matched or exceeded the sensitivity (range: 0.78-1.00) and specificity (range: 0.32-0.87) of 6 LAC DHS optometrists in the subsets of the test dataset they graded based on expert panel reference labels. A DL algorithm for detecting referable glaucoma developed using patient-level data provided by trained LAC DHS optometrists approximates or exceeds performance by ophthalmologists and optometrists, who exhibit variable sensitivity and specificity unrelated to experience level. Implementation of this algorithm in screening workflows could help reallocate eye care resources and provide more reproducible and timely glaucoma care.

Quantitative Testing of a SOLO-Based Automated Quality Control Algorithm for Airborne Tail Doppler Radar Data

An automated quality control pre-processing algorithm for removing non-weather radar echoes from airborne Doppler radar data has been developed. The proposed algorithm can significantly reduce the time and experience level required for interactive radar data editing prior to dual-Doppler wind synthesis or data assimilation. As important as reducing the time required and skill level necessary to process an airborne Doppler dataset can be, the quality of the automated analysis is paramount. Retrieved wind data, recovered perturbation pressure data (with associated momentum check values) and correlation coefficients were computed. To quantitatively test the quality of the automated quality control algorithm, spatial Pearson correlation coefficients and momentum check values were computed. Four different (published) Electra Doppler Radar (ELDORA) datasets of convective echoes were used to stress the algorithm. Four distinct threshold levels for data removal in the automated quality control algorithm were applied to each of four ELDORA datasets. The algorithm threshold levels were labeled as follows: extremely low, low, medium, and high. Extremely low algorithm cases were deemed necessary during the data analyses and were added to the low, medium and high cases. A description of each case and the differences in the perturbation pressure momentum check values and correlation coefficients between the interactively edited fields were computed. These comparisons along with a subjective visual inspection show that the automated quality control algorithm can produce an analysis comparable—and in some cases superior—to an interactive analysis when used properly. A key benefit of this algorithm is that the skill level of a relatively inexperienced airborne radar meteorologist may be effectively increased by using the SOLO QC algorithm.

Computerizing the first step of the two-step algorithm in dermoscopy: A convolutional neural network for differentiating melanocytic from non-melanocytic skin lesions

ImportanceConvolutional neural networks (CNN) have shown performance equal to trained dermatologists in differentiating benign from malignant skin lesions. To improve clinicians’ management decisions, additional classifications into diagnostic categories might be helpful. MethodsA convenience sample of 100 pigmented/non-pigmented skin lesions was used for a cross-sectional two-level reader study including 96 dermatologists (level I: dermoscopy only; level II: clinical close-up images, dermoscopy, and textual information). Dermoscopic images were classified by a binary CNN trained to differentiate melanocytic from non-melanocytic lesions (FotoFinder Systems, Bad Birnbach, Germany). Primary endpoint was the accuracy of the CNN’s classification in comparison with dermatologists reviewing level-II information. Secondary endpoints included dermatologists’ accuracies according to their level of experience and the CNN’s area under the curve (AUC) of receiver operating characteristics (ROC). ResultsThe CNN revealed an accuracy and ROC AUC with corresponding 95 % confidence intervals (CI) of 91.0 % (83.8 % to 95.2 %) and 0.981 (0.962 to 1). In level I, dermatologists showed a mean accuracy of 83.7 % (82.5 % to 84.8 %). With level II information, the accuracy improved to 87.8 % (86.7 % to 88.9 %; p < 0.001). When comparing accuracies of CNN and dermatologists in level II, the CNN’s accuracy was higher (91.0 % versus 87.8 %, p < 0.001). For experts with level II information results were on par with the CNN (91.0 % versus 90.4 %, p = 0.368). ConclusionsThe tested CNN accurately differentiated melanocytic from non-melanocytic skin lesions and outperformed dermatologists. The CNN may support clinicians and could be used in an ensemble approach combined with other CNN models.

The Consumer−E-retailer−Intermediary Triad: Why and When Unfairness Perceptions Undermine Ethicality and Consumer Repurchase Intention

While there is considerable research on consumers and e-retailers; the relationships between the consumers, e-retailers, and their intermediaries—the ecommerce platforms are underexplored. The current research focuses on this triad and examines why and when price unfairness and product unfairness influence consumers’ perception of ethics of the e-retailer and their spillover effects on consumer repurchase intention from the ecommerce platforms. We adopted a mixed-method approach and conducted two studies. The qualitative study performed a content analysis based on 349 real comments of online shoppers. The quantitative study collected data from 632 existing customers of actual ecommerce platforms. The results show negative relationships between unfairness and consumer responses in the context of online retailing. Moreover, perception of e-retailer ethics explains the impacts of price unfairness and product unfairness on consumer repurchase intention from the ecommerce platforms. Besides, the salience of ethicality on repurchase intention depends on the level of prior shopping experience, such that this effect is lessened when shopping experience increases. This research offers significant implications for different stakeholders including e-retailers, ecommerce platforms, policymakers, and consumers to stimulate consumers’ perception of e-retailer ethics and repurchase intention from the ecommerce platforms.

Navigating power dynamics in elite interviews

ABSTRACT Elite interviews, which involve interviewing influential individuals, are an important data collection method. This article delves into the complexities of conducting elite interviews, drawing upon insights gained from interviewing 24 senior organisational leaders in New Zealand. This article argues that the power relations between researchers and elite respondents are not static; rather, they are shaped by the specific socio-political context. Moreover, the article argues that reflexivity plays a crucial role in interrogating the power dynamics between researchers and respondents. This enables a deeper understanding of how a researcher’s identity, including gender, nationality, and experience level, can influence the interview dynamics. This article contributes to the methodological understanding of elite interviews by not only providing empirical research but also by exploring a unique elite group: leaders of teacher unions, who are both professional and political elites.

A Rapid Method to Confine and Safely Handle Bees in the Field.

Improving understanding of the basic biology and ecology of many insect pollinators, particularly specialist or rare taxa, is a priority for many researchers. As such, there is often a need to temporarily confine field-collected organisms in a non-injurious manner in order to gain information or support additional studies. This protocol represents a thoroughly tested, quick, and inexpensive field method for safely handling bees of conservation concern that can easily be tailored toward specific project needs, including organism identification, pollen removal, marking, and/or collection of non-lethal tissue samples for genetic analysis. This methodology can serve as an additional option in the researcher's toolbox to use when certain scenarios arise. It is anticipated that this methodology can be adapted for use with other insect species as well as used by individuals of varying experience and skill levels. It can be of great value to researchers studying specialist bees or conducting host-specific studies. The data collection made possible by this protocol will be invaluable to help researchers address critical data gaps for many pollinator species, plant-pollinator network structures, and pollinator conservation and management initiatives.

An AI-Powered Product Identity Form Design Method Based on Shape Grammar and Kansei Engineering: Integrating Midjourney and Grey-AHP-QFD

Product Identity (PI) is a strategic instrument for enterprises to forge brand strength through New Product Development (NPD). Concurrently, facing increasingly fierce market competition, the NPD for consumer emotional requirements (CRs) has become a significant objective in enterprise research and development (R&amp;D). The design of new product forms must ensure the continuity of PI and concurrently address the emotional needs of users. It demands a high level of experience from designers and significant investment in R&amp;D. To solve this problem, a generative and quantitative design method powered by AI, based on Shape Grammar (SG) and Kansei Engineering (KE), is proposed. The specific method is as follows: Firstly, representative products for Morphological Analysis (MA) are selected, SG is applied to establish initial shapes and transformation rules, and prompts are input into Midjourney. This process generates conceptual sketches and iteratively refines them, resulting in a set of conceptual sketches that preserve the PI. Secondly, a web crawler mines online reviews to extract Kansei words. Factor Analysis (FA) clusters them into Kansei factors, and the Grey Analytic Hierarchy Process (G-AHP) calculates their grey weights. Thirdly, after analyzing the PI conceptual sketches for feature extraction, the features are integrated with CRs into the Quality Function Deployment (QFD) matrix. Experts evaluate the relationships using interval grey numbers, calculating the optimal ranking of PI Engineering Characteristics (PIECs). Finally, professional designers refine the selected sketches into 3D models and detailed designs. Using a Chinese brand as a case study, we have designed a female electric moped (E-moped) to fit the PI and users’ emotional needs. Through a questionnaire survey on the design scheme, we argue that the proposed innovative method is efficient, applicable, and effective in balancing the product form design of PI and user emotions.

An interpretative phenomenological study on nurses’ perceived affective wellbeing at work

Nurses face increasingly complex and challenging workloads, exacerbated by high rates of absenteeism, mental health issues, and low morale, all of which significantly impact patient care. This study focuses on exploring nurses&amp;rsquo; perceived affective wellbeing, perceived workload burden, and the current working conditions they face. The objective was to understand nurses&amp;rsquo; perspectives on affective wellbeing, self-care, and work-life balance. We utilized an interpretative phenomenological approach to design the data collection and management for this study. Through open dialogue, we explored the notion of wellbeing at work with nurses of varying levels of work experience, from fairly novice to expert practitioners who have worked for decades in their fields. The broader responsibilities of nurses of nurses within the National Health Service (NHS) were also examined. Two experts in interpretative phenomenological analysis led the discussion in three different groups, which each consisted of nurses with similar years of work experience, averaging 13 years. Thirty-eight registered nurses volunteered to participate in these discussion groups, with participants recruited from postgraduate courses and representing both acute and community care settings in regional hospitals. Nurses shared insights into what makes nursing a rewarding job but also acknowledged the significant challenges they face. Discussions highlight the stressful and traumatic circumstances nurses often encounter, particularly noting a lack of collegiality among nurses at all levels, limited career aspirations, inadequate support with workloads, and the emotional distress experienced in daily work life. Nurses described their jobs as exhausting and draining, leading to physical and emotional fatigue, detachment, and isolation. These findings hold relevance within the current landscape of nurse and resource shortages in the NHS. Of note, this study identified deeper concerns within the nursing workforce, including emotional dissonance, role dissonance, and disengagement.

Frailty Assessment and Its Impact on Loneliness among Older Adults Receiving Home-Based Healthcare during the COVID-19 Pandemic.

The purpose of this study was to identify the effect of frailty on loneliness among older adults receiving home care, in correlation to their socioeconomic and homebound statuses. This cross-sectional study recruited 218 individuals aged ≥65 years receiving home-based health services from the "Help at Home" program in the Region of Evrytania, Greece through an open invitation from the municipality authorities from March to June 2022. The Tilburg Frailty Indicator (TFI) was used for the evaluation of frailty, the UCLA Loneliness Scale version 3 was used for loneliness, and social isolation was accessed through five questions (living alone, frequency of interaction with children, relatives, friends, and participation in social organizations). The mean age of the participants was 81.48 ± 9.06, 61.9% were female, 54.1% experienced high levels of loneliness (UCLA-3 mean 45.76 ± 11.10 [range 20-68]), and 46.3% of the participants were found to be socially isolated. Also, 58.3% of the individuals were identified as frail (TFI mean 5.95 ± 3.07) [TFI range 0-13], with 57.3% experiencing physical frailty, 43.6% experiencing psychological frailty, and 27.1% experiencing social frailty. An analysis of covariance (ANCOVA) using UCLA-3 as the dependent variable revealed that loneliness across all domains of TFI was significantly higher in participants with frailty (total frailty [Yes] 49.27 vs. [No] 40,87 p < 0.001) (physical frailty [Yes] = 48.99 vs. [No] = 41.42, p < 0.001, psychological: 48.60 vs. 43.57 p < 0.001, and social: 53.38 vs. 42.94 p < 0.001), particularly compared to non-frail individuals, even after adjusting for potential confounding effects (covariates: gender, age, marital status, family status, living status, educational level, annual income, chronic diseases, homebound status, and social isolation). Our findings indicate that frail older adults experienced higher levels of loneliness, suggesting that frailty and loneliness are independently associated among older adults who receive home-based healthcare.

The effect of manager's profile on the social innovation in Cameroonian industrial companies

The aim of this research is to highlight the role of manager's profile in the adoption of social innovation in industrial companies. It has used a quantitative methodology, with a questionnaire administered to 176 managers of Cameroonian industrial companies. The results of the hypotheses tests were derived from the multifactorial ANOVA and multiple linear regression analyses. The results show that among the sociodemographic profile variables, only the level of education and experience of the managers have a significant effect on social innovation, unlike gender and age which have no effect. In addition, the manager's personal values contribute to the adoption of social innovation through his ethical values and community ownership. The study therefore offers relevant implications for managers and owners of industrial companies who aspire to consider social innovation in their offerings to meet profitability objectives and create positive social impact.

Online professional development and cognitive growth: A quantitative analysis for special education educators

This research quantitatively examines how online professional development (OPD) affects cognitive development in special education instructors. 100 individuals took part in outpatient department activities for six months, undergoing cognitive ability examinations before and after the intervention. Descriptive statistics, paired samples t-tests, multiple regression analysis, analysis of covariance (ANCOVA), and Pearson correlation coefficients were used to analyze the data. The findings show a significant rise in post-test scores on the Cognitive Abilities Test (CAT) after taking part in the OPD program. Years of experience and education level were important indicators of cognitive progress, emphasizing the significance of individual traits. Moreover, those with greater expertise and advanced levels of education often had better marks on the post-test. The results highlight the significance of cognitive growth as a crucial result of professional development for special education instructors, adding to the existing knowledge base. The research suggests giving priority to cognitive growth in professional development programs, customizing programs to meet individual requirements, and offering continuous support to educators. Future studies should investigate how OPD impacts cognitive development and analyze its lasting consequences on teacher efficacy and student results.

FluoAnalysis: An Open-Source MATLAB Toolbox for Analysis of Calcium Imaging Measurements of Oscillatory Astrocytic and Neuronal Networks.

Calcium imaging, especially two-photon imaging, has become essential in neuroscience for studying neuronal and astrocytic activity under in vivo and in vitro conditions. Current advances in the development of calcium sensors as well as imaging hardware enable high-frequency measurements of calcium signals in hundreds of cells simultaneously. The analysis of these large datasets requires special tools and usually a certain level of programming experience. Despite advancements in calcium imaging analysis software development, significant gaps remain, particularly for data acquired at a high sampling rate that would allow for the spectral analysis of calcium signals. The FluoAnalysis MATLAB toolbox addresses these gaps by offering a comprehensive solution for analyzing simultaneously measured calcium imaging and electrophysiological data. It features both GUI-based and command-line approaches, emphasizing frequency domain analysis to reveal network-level oscillatory signals linked to single-cell activity. In addition, the toolbox puts special emphasis on differentiating between astrocytes and neurons, revealing the interactions between the network activity of the two major cell types of the brain. It facilitates a streamlined workflow for data loading, ROI identification, cell classification, fluorescence intensity calculation, spectral analysis, and report generation, supporting both manual and automated high-throughput analysis. This versatile platform enables the comprehensive analysis of large imaging datasets. In conclusion, the FluoAnalysis MATLAB toolbox provides a robust and versatile platform for the integrated analysis of calcium imaging and electrophysiological data, supporting diverse neuroscience research applications.

THE COMBINED USE OF SINGLE- AND DUAL-MOBILITY CUPS IN PRIMARY TOTAL HIP ARTHROPLASTY IS SAFE IN A UNIVERSITY HOSPITAL PRACTICE

Dislocation after Total Hip Arthroplasty (THA) is a frequent cause of revision and patients with intrinsic risk factors have been identified. The use of dual mobility (DM) cup has shown great efficiency in preventing dislocation, with questions regarding selective or absolute use. The aim of this study was to compare the outcome of single mobility THA (SM-THA) and DM-THA, when used for selected patients.This retrospective continuous cohort study evaluated 490 patients of whom 275 received SM-THA and 215 received DM-THA. There were 304 primary osteoarthritis (62%), 121 femoral neck fractures (24%) and 65 other indications (14%). The surgical approach was anterior (AA) in 79% and posterior (PA) in 21% of cases. In the DM-THA group, 189 patients (87%) presented at least one dislocation risk factor compared to 128 patients (46%) in the SM-THA group. The primary outcome was revision for all causes, with or without implant removal. Secondary outcomes included length of hospital stay.There was no difference in all cause revision at two years follow up with 9 procedures (3.2%) in SM-THA group and 11 in DM-THA group (5.1%) (p=0.3). There were 3 dislocations in SM-THA group (3 AA) and 3 in DM-THA group (2 PA and 1 AA) (p=0.4).The length of stay was significantly longer in DM-THA group with 7 days (2–12) compared to 4 days (1–7) in SM-THA group (p=0.001).SM-THA and DM-THA are two complementary devices in the management of patients requiring primary THA. SM-THA is a safe option for patients without dislocation risk factors, especially when using AA. The identification of such factors is important to select patients requiring DM-THA and provide reproducible outcomes in a University Hospital practice including various levels of surgeon experience.

Association between dichotomized VASARI feature and overall survival in glioblastoma patients: a single-institution propensity score matching analysis

ObjectivesThis study aimed to investigate the intra- and inter-observer consistency of the Visually Accessible Rembrandt Images (VASARI) feature set before and after dichotomization, and the association between dichotomous VASARI features and the overall survival (OS) in glioblastoma (GBM) patients.MethodsThis retrospective study included 351 patients with pathologically confirmed IDH1 wild-type GBM between January 2016 and June 2022. Firstly, VASARI features were assessed by four radiologists with varying levels of experience before and after dichotomization. Cohen’s kappa coefficient (κ) was calculated to measure the intra- and inter-observer consistency. Then, after adjustment for confounders using propensity score matching, Kaplan-Meier curves were used to compare OS differences for each dichotomous VASARI feature. Next, patients were randomly stratified into a training set (n = 211) and a test set (n = 140) in a 3:2 ratio. Based on the training set, Cox proportional hazards regression analysis was adopted to develop combined and clinical models to predict OS, and the performance of the models was evaluated with the test set.ResultsEleven VASARI features with κ value of 0.61–0.8 demonstrated almost perfect agreement after dichotomization, with the range of κ values across all readers being 0.874–1.000. Seven VASARI features were correlated with GBM patient OS. For OS prediction, the combined model outperformed the clinical model in both training set (C-index, 0.762 vs. 0.723) and test set (C-index, 0.812 vs. 0.702).ConclusionThe dichotomous VASARI features exhibited excellent inter- and intra-observer consistency. The combined model outperformed the clinical model for OS prediction.