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Development of a core outcome set for trials for management of oral submucous fibrosis (OSFCOS): A consensus study protocol
Background The effectiveness of oral submucous fibrosis (OSF) treatment is currently assessed with a broad range of clinical outcome measures. This heterogeneity complicates study comparison, synthesis of results, and evidence-based clinical practice guideline development. A core outcome set (COS) is a set of agreed, standardized outcomes that will be measured and reported across all clinical trials for a particular condition. Objective Our aim is to create a COS (OSFCOS) for efficacy trials that look at the management OSF. Methods An initial list of the potentially relevant outcomes will be drawn by a systematic review of randomized controlled trials focused on OSF treatment. An e-Delphi process will be done to obtain agreement among important stakeholders. The stakeholders will consist of OSF patients, members of the Indian Academy of Oral Medicine & Radiology, the representatives from the Indian Dental Association, clinical researchers, and other oral health specialists. Participants will be asked to rate the importance of each outcome on a structured online questionnaire. Participants will also be allowed to propose new outcomes in Round 1. Feedback and the aggregated scores will be given in later rounds to guide re-rating. If after the second round, there is still no consensus, a third round will be taken.Final consensus on outcome inclusion will be determined based on predefined criteria. Conclusion This protocol outlines a structured, inclusive approach to developing a core outcome set for OSF. The finalized OSFCOS will be made publicly available to guide outcome selection in clinical trials, improve the quality of systematic reviews, and support evidence-based clinical recommendations for the treatment of OSF.
220–325 GHz all-photopolymer Bragg horn antennas towards eco-friendly terahertz applications
Abstract This paper presents the development of the world’s first high-gain, all-photopolymer Bragg horn antennas explicitly designed for the WR-3.4 band (220–325 GHz), marking a groundbreaking advancement in terahertz (THz) antenna technology. Unlike conventional metallic horn antennas, which suffer from conductor losses and manufacturing complexity, this innovative design utilizes eco-friendly photopolymer materials and additive manufacturing, achieving a fractional bandwidth of 38.5% that fully covers the WR-3.4 band. The proposed antenna achieves a measured peak gain of 28.98 dBi at 300 GHz, with a return loss better than − 20dB across the band and a consistent half-power beamwidth (HPBW) of ~ 5°, ensuring precise directivity and minimal sidelobe interference. By employing a novel horn-type adapter for seamless mode conversion from TE 10 to the fundamental HE 11 mode, the design significantly enhances coupling efficiency and reduces signal loss. Additionally, fabrication costs can be reduced by over 50% compared to traditional metallic designs, while maintaining repeatability and enabling rapid prototyping. As the first demonstration of photopolymer-based antennas achieving such high gains in the 220–325 GHz THz spectrum, this work establishes a new benchmark in THz antenna technology, providing an eco-friendly, cost-effective, and high-performance solution for high-speed communication, medical diagnostics, security imaging, and spectroscopy applications.
Additive effects of Trichoderma isolates for enhancing growth, suppressing southern blight and modulating plant defense enzymes in tomato
Southern blight, caused by Sclerotium rolfsii, poses a significant economic threat to tomato cultivation. This study involved the isolation, characterization, and evaluation of three selected Trichoderma isolates (Tri2, Tri3, and Tri6), applied individually and in combination, for their potential to promote plant growth and suppress southern blight under both in vitro and in vivo conditions. These isolates exhibited multiple plant growth-promoting traits, including cellulase, protease, amylase, lipase, catalase, and phosphate-solubilizing activities. Furthermore, they performed as efficient antagonists, inhibiting the mycelial growth by up to 88.8% and the oxalic acid production of S. rolfsii by up to 81.9%. The Trichoderma isolates significantly enhanced tomato seed germination and seedling vigor (p < 0.05). In seed tray and pot, experiments, consortium treatments (dual and triple application) demonstrated significantly greater plant height (≤168.8%), biomass (≤507.3%), leaf number (≤150%), leaf diameter (≤86.2%), chlorophyll content (≤322%), stem diameter (≤129.1%), gas exchange parameters, and root colonization than control and single treatments (p < 0.05). Additionally, these consortium treatments exhibited significantly higher efficacy in reducing damping-off (≤92%) and southern blight severity (≤80%) caused by S. rolfsii, compared to untreated plants (p < 0.05). Biochemical analyses revealed that Trichoderma-treated plants challenged with S. rolfsii showed reduced oxidative stress, evidenced by lower hydrogen peroxide (H₂O₂) and malondialdehyde (MDA) levels. The treatments also increased osmoprotectant levels such as soluble sugars, proline, phenolics, and flavonoids, along with the activities of defense-related enzymes, including peroxidase (PO), polyphenol oxidase (PPO), and phenylalanine ammonia-lyase (PAL), compared to S. rolfsii-infected controls (p < 0.05). Under field conditions, treating S. rolfsii-inoculated plants with Trichoderma isolates, whether singly, in pairs, or as a trio, significantly increased plant height, yield, and fruit Brix content (p < 0.05). The consortium application (Tri2 + Tri3 and Tri2 + Tri3 + Tri6) led to the highest increases in plant height (≤94%), fruit number (≤114%), yield (≤19.59 t/ha), and Brix (≤4.88). These findings suggest that the additive interactions among Trichoderma isolates enhance tomato growth and suppress S. rolfsii, offering an eco-friendly and effective strategy for managing southern blight.
The role of the ventral striatum in the relationship between impulsive decision-making and emotional self-regulation by cognitive reappraisal
Abstract Delay discounting (DD), the preference for smaller, immediate rewards over larger, delayed ones, is a key measure of temporal impulsivity. While its link to behavioral self-regulation is well-studied, the relationship with emotional self-regulation is less understood. This study explored this relationship and its neuroanatomical mediators in the brain’s reward system. We administered the Emotion Regulation Questionnaire (ERQ) and a DD task to 155 young adult college students and collected structural MRI data. Our data revealed that greater use of cognitive reappraisal as an emotion regulation strategy was significantly associated with lower DD rates (i.e., reduced temporal impulsivity). No such relationship was found for expressive suppression. Furthermore, mediation analysis showed that higher cognitive reappraisal scores were associated with lower gray matter volume in the left ventral striatum, which in turn predicted lower DD. While the pattern of results is statistically consistent with full mediation, the cross-sectional nature of our data precludes causal inference. In conclusion, these results identify a novel neuroanatomical mechanism for temporal impulsivity. They suggest that cognitive reappraisal helps control impulsive choice and the process is mediated by the ventral striatum. This may provide a useful biomarker for developing interventions to improve self-control.
Competencies of lower-level community health centre leaders in annual health work planning and their influence on district performance in Busoga sub-region: A retrospective study
Introduction Lower-level community health centres play a crucial role in the delivery of primary healthcare services, and the competencies of their leaders can significantly influence district performance. Annual health work planning in local governments faces implementation obstacles every year. This mostly affects lower-level community health centres in Busoga region. It is evidenced by late submission of annual health work plans to authorized offices and also these work plans are poorly made by lower-level community health centres in Busoga region. This prompted a retrospective study to understand the competencies of leaders in the lower-level community health centres in annual health work plan development. Objective The study assessed the influence of competencies of lower-level community health centre leaders in annual health work planning on the district performance in Busoga region. Methods A retrospective (case-control) study design was employed to understand health centre performance across various districts in Busoga sub-region. There was a comparison of performance between the worst performing (case) and best performing (control) districts in the region according to the Annual Health Sector Performance reports from 2017/18 financial year to 2021/2022. Leaders in the lower-level community health centres were recruited to participate in the study. Data was collected between 17th July, 2024 and 23rd August, 2024. Statistical analysis was conducted on data from 12 case health centres and 12 control health centres using STATA version 16 to determine competencies of lower-level community health centre leaders that influence district performance. Results The study found that the district performance in annual health work planning was poor in both the case and control groups (26.4% and 47.2% respectively). Only three competencies variables of lower-level community health centre leaders were significantly influencing the performance of the districts. Districts with health facilities which reported that their Health Unit Management Committees (HUMCs) were fully constituted as guided by their leaders for annual health work planning, had significantly higher odds (AOR = 13.551, 95% CI: 4.816–38.617, p < 0.001) and performed better than those whose HUMCs were not fully constituted. Additionally, districts with health facilities which indicated that Heads of Departments (HODs) were involved in the annual health work planning process had significantly higher odds (AOR = 6.500, 95% CI: 3.109–10.791, p = 0.007) of better planning outcomes. Furthermore, districts with facilities that organized annual planning meetings by their leaders had significantly increased odds (AOR = 3.060, 95% CI: 1.399–6.916, p = 0.002) of achieving effective planning and the performance of the district. Conclusion The competencies of lower-level community health centre leaders in fully constituting the health unit management committees, involving heads of departments in the annual planning processes and organizing annual meetings for effective planning, highly contributes to the general performance of districts in the Busoga sub-region. Strengthening these competencies through targeted supportive meetings, consistently appointing HUMC members in health centres and creation of active departments of health centres as initiatives are recommended to enhance the overall effectiveness of health service delivery in Busoga sub-region.
Evaluating the potential of phenotypic age to enhance cardiovascular risk prediction over chronological age in the UK Biobank
Brimonidine tartrate 0.15% drops to reduce low post-LASIK residual myopia: A retrospective study
Purpose Residual myopia following Laser-assisted in situ keratomileusis (LASIK) surgery poses a significant concern, with existing literature extensively detailing the use of timolol for treatment. This study aims to assess prediction factors for brimonidine tartrate 0.15% (Alphagan-P) response on post-LASIK residual myopic refraction reduction. Methods The study included consecutive patients who received Alphagan-P during their follow-up for post-LASIK residual myopia. Results We included 61 patients (55% male) with a mean age of 35.18 ± 10.13 Alphagan-P Treatment started at a mean of 4.94 ± 5.64 months after surgery for residual myopia of −0.53 ± 0.71D. Comparison analysis of patients who responded (n = 32, 51.6%) to patients who did not (n = 30, 48.4%) shows that responders were older (38.1 ± 9.1 vs. 32.3 ± 10.3, p = 0.03), had higher baseline myopic Spherical equivalent (SE, −0.82 ± 0.65 vs. −0.26 ± 0.66 p < 0.01), and lower uncorrected visual acuity (Uncorrected visual acuity [UCVA], 0.14 ± 0.2 vs. −0.003 ± 0.12 p = 0.01). Multiple Binary logistic regression confirmed these predictors for response (UCVA (OR=70.6, P = .006), larger SE (OR=3.8, P = .004,) and older age (OR=1.06, P = .03)). Conclusions Alphagan-P can reduce up to 0.5D of post-LASIK residual myopia in roughly 50% of subjects. This treatment might be recommended to fine-tune outcomes for low residual myopia.
An efficient IoT-based crop damage prediction framework in smart agricultural systems
Abstract This paper introduces an efficient IoT-based framework for predicting crop damage within smart agricultural systems, focusing on the integration of Internet of Things (IoT) sensor data with advanced machine learning (ML) and ensemble learning (EL) techniques. The primary objective is to develop a reliable decision support system capable of forecasting crop health status classifying crops as healthy, pesticide-damaged, or affected by other stressors while addressing a critical challenge: the presence of missing data in real-time agricultural datasets. To overcome this limitation, the proposed approach incorporates robust data imputation strategies using both traditional ML methods and powerful EL models. Techniques such as K-Nearest Neighbors, linear regression, and ensemble-based imputers are evaluated for their effectiveness in reconstructing incomplete data. Furthermore, Bayesian Optimization is applied to fine-tune EL classifiers including XGBoost, CatBoost, and LightGBM (LGBM), enhancing their predictive performance. Extensive experiments demonstrate that XGBoost outperforms all other models, achieving an average sensitivity of 88.1%, accuracy of 89.56%, precision of 83.4%, and F1-score of 84.8%. CatBoost and LGBM also deliver competitive results, with CatBoost achieving 90.50% accuracy and LGBM reaching 90.23%. In addition, the imputation capability of the XGBoost model is validated through a low Mean Squared Error (MSE) of 0.0213 and a high R-squared (R2) value of 0.99, confirming its effectiveness for both prediction and data recovery tasks. The key contributions of this innovative work include the design of a low-cost, power-efficient, and scalable crop damage prediction system, the integration of real-time IoT data with optimized ensemble learning, and a comprehensive evaluation of imputation techniques to enhance model robustness. This framework is particularly suited for deployment in resource-constrained agricultural environments, advancing the field of smart farming through intelligent, data-driven solutions.
Comparative effectiveness and safety of insulin reference biologics versus biosimilars for types 1 and 2 diabetes mellitus: Protocol for a systematic review of real-world studies
Introduction Diabetes mellitus is characterized by insulin deficiency or resistance. The two main types of diabetes mellitus are type 1 (T1DM) and type 2 (T2DM). Insulin is the mainstay of therapy for T1DM and often the last-line therapy for T2DM. Biosimilar insulins are cost-saving alternatives to reference products that may improve access for patients and sustainability for healthcare systems. Despite supporting evidence from randomized controlled trials, biosimilar insulin uptake is poor, and real-world evidence of their safety and effectiveness is limited. Objective Our objective is to compare the real-world effectiveness and safety of insulin biosimilars versus reference products in adults with diabetes mellitus. Eligibility criteria We will include observational studies and open-label pragmatic randomized controlled trials. We will exclude other randomized controlled trials, literature reviews, meta-analyses, case series, case reports, study protocols, opinion pieces, and conference abstracts. Our primary effectiveness outcome will be glycated hemoglobin (HbA1c) and our primary safety outcome will be hypoglycemia. Our secondary outcomes will include fasting plasma glucose; time in range; microvascular complications; health-related quality of life; physician visits, emergency department visits, and hospital admissions for hypoglycemia, hyperglycemia, and diabetic ketoacidosis; weight gain; immunogenicity; injection site reactions; and incident cancers. Methods The search strategy combines three key concepts: diabetes, insulin, and biosimilars. We will conduct a structured search in MEDLINE, EMBASE, and International Pharmaceutical Abstracts. We will also search in grey literature databases, targeted websites, and the Google search engine. Finally, we will scan forward and backward citations. Articles will be screened, extracted, and appraised independently by two reviewers. Data will be descriptively summarized. Discussion Our systematic review of the real-world evidence on biosimilar insulins can help support clinical and policy decisions that impact the care of patients with T1DM or T2DM.
DBRSNet: a dual-branch remote sensing image segmentation model based on feature interaction and multi-scale feature fusion
Association of serum Klotho with tinnitus prevalence, duration and severity: A cross-sectional study in middle-aged and older adults
Background As an anti-aging protein, although studies increasingly suggest that the Klotho plays a role in the auditory system, the link between serum Klotho levels and tinnitus remains poorly characterized. The aim of this study was to investigate the associations between serum Klotho levels and tinnitus focusing on prevalence, duration and severity in middle-aged and older adults. Methods We performed a population-based cross-sectional study of individuals in the National Health and Nutrition Examination Survey (NHANES) 2009–2012 and 2015–2016. Univariable and multivariable logistic regression was used to evaluate the relationship between serum Klotho levels and tinnitus, with adjustment for potential confounders and further age-stratified analyses. Restricted cubic splines were applied to assess potential non-linearity in the dose-response relationship. Furthermore, Subgroup and interaction analyses were conducted to assess the consistency of this association. Results In this research of 3280 individuals aged 40–79 years with a median age of 55 (IQR: 48, 62) and 48% male participants, the median serum Klotho level was 779.80pg/mL. Multivariable logistic regression uncovered consistent inverse associations between serum Klotho levels and tinnitus incidence across progressively adjusted models (ORs: 0.68–0.70, p = 0.009–0.01). Age-based stratified analyses suggested the strongest effect was observed in individuals aged 50–59 years (full model ORs: 0.55, p = 0.046). A marginally significant protective effect was observed in the 60–69 age group (unadjusted OR=0.62, 95% CI: 0.39–1.00, p = 0.050). Serum Klotho levels showed no significant correlation with tinnitus severity, while a potential association with the duration of tinnitus was observed (p = 0.058). Additionally, restricted cubic spline analysis revealed a linear inverse association between Klotho and tinnitus risk stratified by age (all p for nonlinear >0.15). Finally, subgroup and interaction analyses revealed no significant effect modification (all p-interaction >0.1). Conclusion Serum Klotho concentrations showed a consistent inverse association with tinnitus prevalence in US adults, with the strongest effect observed in individuals aged 50–69 years.
Mediating role of SII in the association between LC9 and overactive bladder
Low-cost computation for isolated sign language video recognition with multiple reservoir computing
Sign language recognition (SLR) has the potential to bridge communication gaps and empower hearing-impaired communities. To ensure the portability and accessibility of the SLR system, its implementation on a portable, server-independent device becomes imperative. This approach facilitates usage in areas without internet connectivity, addressing the need for data privacy protection. Although deep neural network models are potent, their efficacy is hindered by computational constraints on edge devices. This study delves into reservoir computing (RC), which is renowned for its edge-friendly characteristics. Through leveraging RC, our objective is to craft a cost-effective SLR system optimized for operation on edge devices with limited resources. To enhance the recognition capabilities of RC, we introduce multiple reservoirs with distinct leak rates, extracting diverse features from input videos. Prior to feeding sign language videos into the RC, we employ preprocessing via MediaPipe. This step involves extracting the coordinates of the signer’s body and hand locations, referred to as keypoints, and normalizing their spatial positions. This combined approach, which incorporates keypoint extraction via MediaPipe and normalization during preprocessing, enhances the SLR system’s robustness against complex background effects and varying signer positions. Experimental results demonstrate that the integration of MediaPipe and multiple reservoirs yields competitive outcomes compared with deep recurrent neural and echo state networks and promises significantly lower training times. Our proposed MRC achieved accuracies of 60.35%, 84.65%, and 91.51% for the top-1, top-5, and top-10, respectively, on the WLASL100 dataset, outperforming the deep learning-based approaches Pose-TGCN and Pose-GRU. Furthermore, because of the RC characteristics, the training time was shortened to 52.7 s, compared with 20 h for I3D and the competitive inference time.
Cultural adaptation of the polish version of the brief pain inventory short form among the elderly
Abstract Demographic changes taking place in society require a holistic approach to the health problems of the elderly, including the chronic pain that often accompanies them in various disease entities. The aim of this study was to evaluate the psychometric properties of the Polish version of the Brief Pain Inventory-Short Form (BPI-SF) among the elderly. The study was conducted on a group of 181 patients of both genders, over 65 years of age, with pain lasting longer than 6 months, hospitalized in internal medicine and geriatric wards. Construct validity was assessed using principal component analysis (PCA) method with Quartimax rotation. The goodness of fit of the measurement model, the BPI-SF was based on, in the sample of Polish elderly was tested using the Confirmatory Factor Analysis (CFA). The reliability of the scale, in terms of its internal consistency, was estimated using the Cronbach alpha and Raykow’s Rho coefficients and by analysis of item-total correlation, applying the Kline criterion. The PCA revealed unidimensional structure in the BPI-SF the first factor of the solution was defined by all but two items of the scale. The reliability of the total score was 0.88 and remained at the same level after removing sleep position and average pain intensity from the subscales. Raykow’s Rho for the individual subscales was estimated at 0.78 for severity subscale, 0.66 for affective disturbances involving sleep and 0.82 excluding it, and 0.86 for activity-related difficulties. The Brief Pain Inventory-Short Form (BPI-SF), despite differences in psychometric properties with respect to the original results, may be applicable in monitoring the intensity of chronic non-cancer pain (pain associated with the musculoskeletal system and neuropathic pain) among the elderly as well as in the verification of functional status in daily clinical practice. Trial registration: Statutory research “Chronic pain in people over 65 years of age” K/ZDS/005733, conducted in 2015-2018.
Differentiation of HL-60 cells into primed neutrophils for the evaluation of antiapoptotic effects of poorly soluble nanoparticles
Background Neutrophil apoptosis is an important determinant of intensity and duration of neutrophilic inflammation. The interaction of poorly soluble nanoparticles with primed neutrophils can reduce their natural apoptosis rates. This reaction may contribute to pathogenic consequences of increased neutrophilic inflammation. Toxicological studies aiming to identify hazards of such materials with primary neutrophils are however challenging due to the short life span of these cells and a high donor to donor variability. Our purpose was the establishment of a culturable neutrophil-like cell line as a suitable model for studies of antiapoptotic effects of poorly soluble combustion-derived environmental nanoparticles. Therefore, differentiation protocols for the myeloid HL-60 cell line based on commonly used differentiation inducers all-trans retinoic acid (ATRA) and dimethyl sulfoxide (DMSO) were established and compared. Results The data demonstrate that only a combined cell treatment with ATRA and DMSO for a period of 5 days leads to the complete HL-60 differentiation with the typical neutrophil morphology and characteristic features of neutrophil maturation like cell cycle arrest, increase in differentiation marker CD11b, loss of proliferation marker CD71, and increased phagocytic capacity. Exposure of cells differentiated with ATRA + DMSO to carbon nanoparticles or proinflammatory cytokine granulocyte-macrophage colony-stimulating factor (GM-CSF) revealed a delay of apoptosis causally linked to intracellular reactive oxygen species (ROS). These data verified our earlier findings with human peripheral primed neutrophils from donors with slightly elevated proinflammatory blood plasma factors. Moreover, completely differentiated HL-60 cells possessed similar levels of L-selectin CD62L as neutrophils with primed immunophenotype, thus representing the biology of primed inflammatory neutrophils. Conclusion Neutrophil-like HL-60 cells differentiated according to our protocol could be an appropriate substitute cell line model for studies on the effects of inhalable nanomaterials on primed inflammatory neutrophils like lung neutrophils. For such toxicological studies our cell model is preferable to peripheral neutrophils, as blood neutrophils not always occur in a primed state and primed lung neutrophils from donors are not available for this purpose.
A closed loop fully automated wireless vagus nerve stimulation system
Abstract Vagus nerve stimulation (VNS) has been explored as a treatment for a range of conditions, including epilepsy, cardiovascular disorders, drug-resistant depression, chronic pain, and obesity. Conventionally, VNS is administered using an open-loop approach, in which trained personnel adjust stimulation parameters. Medical supervision is necessary to minimize adverse effects, such as severe bradycardia, which can significantly interfere with daily activities. This requirement limits the feasibility of VNS in unsupervised settings and highlights the need for an automated control system. To address this limitation, we introduce the fully automated wireless VNS (FAW-VNS) system, which dynamically adjusts stimulation parameters to maintain steady-state operation while minimizing bradycardia. The FAW-VNS system operates in real-time and consists of a biocompatible, miniaturized, wirelessly powered implant equipped with cuff electrodes; a handheld device for power delivery and stimulation protocol communication; a sensing patch to collect and transmit heart rate (HR) data; and a central control unit (CCU) that updates stimulation protocols based on the acquired physiological signals. In-vivo studies were conducted on four anesthetized pigs to validate the system’s ability to reach a steady-state response, achieving a controlled HR reduction within 2–4% of baseline during stimulation. This work lays the foundation for developing closed-loop, wireless implants for point-of-care applications.
Serum fibrinogen level and fibrinogen administration in patients with traumatic brain injury: A systematic review and meta-analysis protocol
Introduction Traumatic Brain Injury (TBI) is a leading cause of disability and death globally. It has a significant economic burden. Coagulopathy has been identified as one of the key factors contributing to the poor outcomes observed in TBI patients, and it has been theorised that the management of coagulopathy will improve patient outcomes. Low serum fibrinogen levels denote a coagulopathic state, and the therapeutic administration of fibrinogen has been proposed to correct this state. However, there is no consensus on its efficacy in patients with TBI. Hence, this systematic review and meta-analysis seeks to ascertain the prognostic value of serum fibrinogen levels in patients with TBI and assess the effect of fibrinogen administration on these patients. Methods Using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines, we will perform a comprehensive search of Scopus, Medline, Embase and Cochrane Library to retrieve all original articles that investigate the prognostic value of fibrinogen levels and/or the effect of fibrinogen administration in TBI patients. Primary outcomes include functional outcome and mortality assessments such as the Glasgow Outcome Score and modified Rankin Score. Secondary outcomes include progressive intracranial haemorrhage/contusion and need for surgical intervention. Data collected will encompass participant demographics, measured fibrinogen levels, dose of fibrinogen administered and specified outcome measures. Conclusion Findings from this study, specifically the evidence if fibrinogen level has prognostic value and if fibrinogen administration improves patient outcomes, will help inform future TBI management. It will also enhance shared decision-making between healthcare professionals and patients if fibrinogen has a prognostic value, as this value could be used to communicate more effectively the expected prognosis post-TBI. Thus, TBI patient outcomes can be optimised accordingly. PROSPERO Registration Number CRD42024556497. Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024556497
A hybrid deep learning model for sentiment analysis of COVID-19 tweets with class balancing
Abstract The widespread dissemination of misinformation and the diverse public sentiment observed during the COVID-19 pandemic highlight the necessity for accurate sentiment analysis of social media discourse. This study proposes a hybrid deep learning (DL) model that integrates Bidirectional Encoder Representations from Transformers (BERT) for contextual feature extraction with Long Short-Term Memory (LSTM) networks for sequential learning to classify COVID-19-related sentiments. To enhance data quality, advanced text preprocessing techniques, including Unicode normalization, contraction expansion, and emoji conversion, are applied. Additionally, to mitigate class imbalance, Random OverSampling (ROS) is employed, leading to significant improvements in model performance. Before applying ROS, the model exhibited lower accuracy and inconsistent performance across sentiment categories. After balancing the dataset, accuracy for binary classification increased to 92.10%, with corresponding precision, sensitivity, and specificity of 92.10%, 92.10%, and 91.50%, respectively. For three-class sentiment classification, accuracy improved to 89.47%, with precision, sensitivity, and specificity of 89.80%, 89.47%, and 94.10%, respectively. In five-class sentiment classification, accuracy reached 81.78%, with precision, sensitivity, and specificity of 82.19%, 81.78%, and 95.28%, respectively. These findings demonstrate the efficacy of combining deep learning-based sentiment analysis with advanced text preprocessing and class balancing techniques for accurately classifying public sentiment related to COVID-19 across multiple sentiment categories.
Emergency dispatchers as instructors of laypersons in unplanned out-of-hospital deliveries - Interdisciplinary qualitative study
Introduction Unplanned out-of-hospital delivery tasks are continuously increasing and are challenging to the emergency dispatcher, but there is scant research on them, especially from the perspective of instructing the layperson in delivery. In the Finnish model of one emergency response centre authority, the expertise of the emergency dispatcher is highlighted. However, it’s necessary to develop collaborative and transformative expertise and cooperation in the maternity care service system to respond to risky and unexpected childbirth events. This study adopts concepts from cultural-historical activity theory in the framework of object-oriented activity systems and negotiated knotworking. Our aim is to describe and analyse the perspectives of emergency dispatchers and laypersons when the emergency dispatcher instructs the layperson in handling an unplanned out-of-hospital delivery. Methods This is an interdisciplinary qualitative study. The study data consists of stories written by emergency dispatchers (n = 31) and semi-structured interviews with laypersons (n = 5). The data was collected using both the method of empathy-based stories and semi-structured interviews. The data was analysed using qualitative theory-driven content analysis, data-based theory-driven thematic analysis and text mining. Results The emergency dispatchers’ and laypersons’ descriptions of their actions in the examined delivery situations were structured as elements of activity systems. The thematic analysis produced two themes containing discursive characteristics of negotiated knotworking, which were (i) script innovations requiring midwifery competence and (ii) emotion work. Discussion The object of the emergency dispatcher’s actions was the physical wellbeing of the person giving birth and the newborn, while the layperson’s object was the childbirth experience, including the aforementioned and shared with the person giving birth. The formal script of childbirth services does not serve negotiated knotworking. Further, a midwife’s participation in an emergency call, including video consultation, is desired. The emergency dispatcher should respect the object-oriented conscious agency of the layperson, providing ad hoc information for childbirth.