Tag: statistics

Sci Rep. 2025 Feb 17;15(1):5802. doi: 10.1038/s41598-025-89954-6.

ABSTRACT

Accessibility of interactive services is vital for building an inclusive society. While accessibility standards are increasingly being adopted, there remains a gap in user experience evaluation approaches tailored to deaf participants. To address this, the User Experience Questionnaire (UEQ) was translated to Slovenian Sign Language (SSL) and its appropriateness and reliability evaluated in a research study. Two interactive TV solutions for deaf viewers were developed and evaluated using a standard written UEQ in Slovenian (UEQ TXT) and a UEQ translated to Slovenian Sign Language (UEQ SSL). A total of 27 deaf participants and 6 Slovenian Sign Language interpreters participated in the study. A thorough statistical analysis of the results was conducted on both individual UEQ attributes and overall scales. The results show no statistically significant differences in evaluation results when gathered with UEQ SSL and UEQ TXT. Participants expressed a strong preference for UEQ SSL, as it enabled them to express their opinions more accurately and completely in their primary language, fostering greater independence and ensuring their perspectives are fully represented. The findings show that the UEQ SSL is a valid and effective tool, with the potential to bridge the inclusion gap for deaf and hard-of-hearing users in UX evaluation studies.

PMID:39962301 | DOI:10.1038/s41598-025-89954-6

J Dent Educ. 2025 Feb 17. doi: 10.1002/jdd.13840. Online ahead of print.

ABSTRACT

PURPOSE/OBJECTIVES: Several studies have evaluated resident and trainee remediation strategies across various surgical subspecialties. However, limited research exists on this topic within the Oral and Maxillofacial Surgery (OMS) literature. The purpose of this study was to identify cross-sectional patterns of evaluation and remediation strategies for underperforming OMS residents in the United States.

METHODS: A cross-sectional cohort study was conducted using a 22-question survey administered to OMS residency Program Directors of all programs approved by the Commission on Dental Accreditation (CODA) within the United States. The predictor variables included the demographics and resident assessment methods of responding programs. The outcome variables included the results of remediation strategies and corrective action plans for residents identified as struggling over the preceding 10 years. Responses were anonymized, and descriptive statistics were used to analyze the collected data.

RESULTS: Completed surveys were obtained from 29 (29%) CODA-approved programs. Twenty-five of 29 (86%) programs reported placing 64 residents on corrective action plans. Nine of 29 (31%) programs reported that 14 residents were dismissed during that period. The most common deficiencies in residents requiring corrective action plans were cognitive skills (37.9%), clinical skills (20.7%), and interpersonal skills (20.7%). Residents were almost always given a warning prior to initiating remediation or probation (96.6%), with verbal (46.4%) and written (53.4%) warnings being used with nearly equivalent frequency. Remedial action most often included general counseling (15.9%), more frequent feedback sessions (15.9%), assignment of a mentor (15.2%), didactic remediation (13.3%), psychiatric/psychologic counseling (11.26%), and lengthened training time (6.6%). Most programs reported utilization of a formal remediation protocol (75.9%) and 85.7% of programs subjectively felt their process was effective. Almost one-quarter of respondents (24.1%) stated that no formal remediation protocol exists at their institution.

CONCLUSIONS: Most OMS programs utilized some form of remediation protocols, but their usage was inconsistent and infrequent. The evaluation and remediation processes among OMS residency programs have significant variability, relying heavily on program or institution-specific protocols.

PMID:39962291 | DOI:10.1002/jdd.13840

Sci Rep. 2025 Feb 17;15(1):5813. doi: 10.1038/s41598-025-90441-1.

ABSTRACT

Both tuberculosis (TB) and diabetes mellitus (DM) are major global public health concerns, and their prevalence has been rising rapidly in developing countries like Ethiopia. A challenge to TB control could arise from the rising incidence of diabetes and undermine efforts to eradicate the disease. In Ethiopia, particularly in the research region, there is a lack of data regarding TB-DM comorbidity and associated risk factors. To assess the prevalence and determinants of DM in patients with tuberculosis at South Gondar Zone Hospitals in Ethiopia. A facility-based cross-sectional study was conducted in South Gondar Zone health facilities from December, 2023 to May 2024. A total of 1174 participants were selected using a systematic sampling technique. The data were collected using an interviewer-administered structural questionnaire. Previously and newly diagnosed TB at any stage of anti-TB treatment were subjected to a fasting blood sugar measurement. The collected data was entered into EPI Data 3.1 and exported to SPSS version 24 for analysis. To determine the risk factors, logistic regression was employed. An odds ratio with a 95% CI and a P-value < 0.05 were used to declare statistical significance. The prevalence of diabetes mellitus and prediabetes was found to be 9.8% (95% CI: 7.1-1.35) and 13.5% (95% CI: 11.4-16.1), respectively. TB patients aged 40-50 years (AOR = 3.65, 95% CI: 1.32-10.14), > 50 years of age (AOR = 5.65, 95% CI: 2.01-16.35), being married (AOR = 3.68, 95% CI: 2.31-7.2), having no formal education (AOR = 3.87, 95% CI: 1.21-9.2), and being overweight or obese (AOR = 3.41, 95% CI: 1.85-8.62) were significantly associated with diabetes mellitus. The prevalence of DM among TB patients in our study was high. Older age, being married, having no formal education, and being overweight or obese were significant risk factors for TB. Integrating TB and DM screening as well as care delivery in clinical practice is essential to achieving the goal of TB control and improving the health outcomes of both diseases.

PMID:39962284 | DOI:10.1038/s41598-025-90441-1

Sci Rep. 2025 Feb 17;15(1):5777. doi: 10.1038/s41598-025-89293-6.

ABSTRACT

Although a robust association between metabolic dysfunction-associated fatty liver disease (MASLD) and cardiovascular disease (CVD) has been established, the impact of MASLD on CVD risk in young adults has not been fully evaluated. This population-based study included adults aged 20-39 years who underwent health screening examinations from 2009 to 2012 based on Korean National Health Insurance Service database. MASLD was defined as a fatty liver index ≥ 30 without any other cause of steatosis, and presence of one or more cardiometabolic risk factors. The primary outcome was newly developed CVD, including myocardial infarction, ischemic stroke, and congestive heart failure. During the median 10.6 years of follow-up, MASLD was observed in 1,435,659 (25.3%) of the 5,666,728 participants. Cumulative incidence of major adverse cardiovascular events was significantly higher in individuals with MASLD compared those without steatosis (P < 0.001). The adjusted hazard ratio (HR) for myocardial infarction was 1.23 [95% CI (confidence interval): 1.18-1.27] in individuals with MASLD compared to those without steatosis. The HR for ischemic stroke and congestive heart failure were higher in individuals with MASLD compared to those without steatosis (HR, 1.12; 95% CI, 1.07-1.17 and HR, 1.18; 95% CI, 1.15-1.21, respectively]. In the subgroup analysis, the elevated HR for CVD in the MASLD group was prominent among individuals who were female and obese. MASLD was associated with an increased risk of CVD in young adults. These findings highlight the need for early intervention in patients with MASLD before they reach middle to reduce the risk of CVD, particularly among young adults in South Korea.

PMID:39962282 | DOI:10.1038/s41598-025-89293-6

Sci Rep. 2025 Feb 17;15(1):5696. doi: 10.1038/s41598-025-89957-3.

ABSTRACT

Adolescents differ from adults not only in biological factors related to age but also in social and psychological characteristics, which may heighten their risk of adverse obstetrical outcomes. This study explores the relationship between maternal age and adverse obstetrical outcomes by comparing adolescent and adult mothers in North Wollo Zone public hospitals, by adjusting for potential confounders such as sociodemographic factors, healthcare access, antenatal care utilization, and pregnancy-related variables. A comparative cross-sectional study was conducted from November 20, 2022, to February 20, 2023, involving 488 mothers to assess adverse obstetrical outcomes among adolescent and adult mothers who gave birth at 28 or more weeks of gestation in North Wollo Zone Public Hospitals, Northern Ethiopia. Data were collected through interviews and clinical chart reviews, then entered into EPI DATA version 4.6.6.0 and analyzed using SPSS version 26. Descriptive statistics summarized the data, and logistic regression identified significant variables (p < 0.05). Adolescent mothers exhibited significantly higher rates of adverse obstetrical outcomes compared to adult mothers, including preterm labor (7.0% vs. 2.0%, p = 0.04), antepartum hemorrhage (11.9% vs. 4.9%, p = 0.014), anemia (19.3% vs. 10.2%, p = 0.006), pregnancy-induced hypertension (11.9% vs. 7.0%, p = 0.047), malpresentation (9.0% vs. 2.5%, p = 0.008), cephalopelvic disproportion (6.1% vs. 1.2%, p = 0.046), major perineal tears (8.6% vs. 3.3%, p = 0.016), and cesarean delivery (16.0% vs. 9.8%, p = 0.04). Adolescent pregnancy is strongly linked to a range of adverse obstetrical outcomes, including preterm labor, antepartum hemorrhage, malpresentation, oligohydramnios, anemia, major perineal tears, and an increased likelihood of cesarean delivery. To mitigate these risks, it is crucial to implement targeted community and health facility-based interventions that focus on preventing adolescent pregnancies and addressing contributing factors, ultimately improving maternal health outcomes among adolescents.

PMID:39962217 | DOI:10.1038/s41598-025-89957-3

J Dent Educ. 2025 Feb 17. doi: 10.1002/jdd.13855. Online ahead of print.

ABSTRACT

PURPOSE/OBJECTIVES: This study examined the relationship between environmental factors (e.g., working position, patient position, and scaling instruments) and poor posture in dental hygiene students.

METHODS: A longitudinal cohort study was conducted from 2017 to 2019 to observe dental hygiene students’ clinical rotation performance at two undergraduate universities. Samples of video observations (n = 1487) of dental hygiene students performing scaling activities during oral care sessions were evaluated using the Rapid Upper Limb Assessment (RULA). Descriptive analysis and exploratory prediction modeling were performed to assess clinical environmental factors that predicted higher risks of developing WMSDs.

RESULTS: RULA scores (mean = 4.8, median = 5, range = 2-7) indicate dental hygiene students are at high risk of developing upper extremity MSDs. The type of scaling instrument, clock positioning relative to the patient, and sitting versus standing had statistically significant associations (p < 0.001) with the RULA outcome. In univariate analyses, clock positions 7 and 8 were the worst, having an increased risk of poor RULA outcomes (scores 5-7) by nearly nine times over working in clock position 12 (odds ratio [OR] 9.11, 95% CI 5.48-15.60). Multivariate predictive modeling indicated that the riskiest combination of factors is using a manual scaling instrument (OR 1.67, 95% CI 1.28-2.18), standing (OR 1.42, 95% CI 1.03-1.96), and working clock positions 7 and 8 (OR 8.4, 95% CI 5.02-14.50).

CONCLUSIONS: There is a need to consider the combined contribution of multiple environmental factors on working positions to optimize ergonomic training during dental hygiene and protect emerging dental health professionals from the negative health impacts of prolonged awkward postures.

PMID:39962215 | DOI:10.1002/jdd.13855

Sci Rep. 2025 Feb 17;15(1):5769. doi: 10.1038/s41598-025-86648-x.

ABSTRACT

The presence of microorganisms in the bloodstream can result in severe, potentially life-threatening conditions, which are a significant cause of morbidity and mortality worldwide. The rise of antimicrobial-resistant strains further exacerbates these outcomes. However, the data concerning bacterial profiles and resistance to antimicrobials, particularly against extended-spectrum beta-lactams and carbapenems, are limited. Aimed to characterize pathogens isolated from positive blood cultures, including bacterial profiles and antibiotic susceptibility patterns, and to identify predictors of blood culture positivity in septicemia-suspected patients at the University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia. A hospital-based cross-sectional study was conducted from February 15 to May 30, 2023. The study involved 341 patients suspected of having septicaemia who were selected consecutively through a convenience sampling technique. Blood samples were collected aseptically from each patient (10 ml from adults, 5 ml from children, and 1 ml from neonates) and inoculated into bottles containing tryptic soy broth in volumes appropriate for the patient’s age. The samples were incubated at 35-37 °C for up to 7 days to detect bacterial growth. Positive blood cultures were subcultured onto various media, including chocolate agar, blood agar, modified Thayer-Martin agar, MacConkey agar, and mannitol salt agar, and incubated again at 35-37 °C for 24 h. The suspected bacteria were identified on the basis of colony morphology, Gram staining, and biochemical tests. Antimicrobial susceptibility testing was conducted via both the Kirby-Bauer and modified Kirby-Bauer disk diffusion methods. Resistance to methicillin, extended-spectrum beta-lactams, and carbapenems was determined via the cefoxitin disc test, combined-disk diffusion method, and modified carbapenem inactivation method, respectively. The data were entered into Epi-Data version 4.6 and analysed via SPSS version 25. Binary logistic regression analyses were employed to identify factors associated with bloodstream infections (BSI), with a P value of less than 0.05 considered statistically significant. Out of 341 patients suspected of septicemia, 196 (57.5%) were male and 145 (42.5%) were female, with a mean (± SD) age of 16.5 (± 7.5) years. Bloodstream infection was identified in 87 (25.5%) patients (95% CI: 21.1-30.4). Among these positive cases, 67 (77%) were from ward patients, while 20 (23%) were from those visiting outpatient departments. The primary gram-positive bacteria identified included S. aureus 27 (31.0%), CoNS 14 (16.1%), S. viridans 8 (9.2%), and S. agalactiae 4 (4.6%). The gram-negative isolates were predominantly K. pneumoniae 11 (12.6%), followed by E. coli 9 (10.3%), E. cloacae 6 (6.9%), Acinetobacter spp. 3 (3.5%), N. meningitidis 3 (3.5%), and P. aeruginosa 2 (2.3%). Methicillin resistance was detected in 17/27 (63.0%) S. aureus strains and 2/14 (14.3%) CoNS strains. Multidrug resistance was detected in 63/87 (72.4%, 95% CI: 67.2-84.7%) of the isolates. Extended-spectrum beta-lactamase and carbapenemase production were observed in 12/31 (38.7%) and 5/31 (16.1%) of isolates, respectively. The factors associated with BSI were the presence of wounds and burns (AOR = 2.103, 95% CI: 1.365-3.241, P = 0.041), length of hospital stay (≥ 5) (AOR = 2.209, 95% CI: 1.122-4.347, P = 0.022), and prior medical procedures (AOR = 1.982, 95% CI: 1.125-3.492, P = 0.018). Bloodstream infection was identified in 25.5% of suspected septicemia cases, with multidrug-resistant bacteria present in 72.4% of isolates. Gram-positive bacteria, particularly S. aureus, and gram-negative bacteria like K. pneumoniae and E. coli were predominant. High rates of methicillin, beta-lactam, and carbapenem resistance were observed, emphasizing the magnitude of antimicrobial resistance. Risk factors such as wounds, extended hospital stays, and prior medical procedures significantly increased the likelihood of culture positivity. This suggests the need for regular antimicrobial susceptibility testing to guide antibiotic selection and track resistance trends, proper wound care and medical device usage to reduce the risk of BSI in healthcare settings.

PMID:39962179 | DOI:10.1038/s41598-025-86648-x

Sci Rep. 2025 Feb 17;15(1):5805. doi: 10.1038/s41598-024-72539-0.

ABSTRACT

Cervical spinal cord injury is often catastrophic, frequently leading to irreversible impairment. MRI has become the gold standard for evaluating spinal cord injuries (SCI). Our study aimed to assess the accuracy of a radiomics approach, based on machine learning and utilizing conventional MRI, in predicting the prognosis of patients with SCI. In a retrospective analysis of 82 SCI patients from three hospitals, we categorized them into good (n = 49) and poor (n = 33) prognosis groups. Preoperative T2-weighted MRI images were segmented using 3D-Region of Interest (ROI) techniques, and both radiomic and deep transfer learning features were extracted. These features were normalized using Z-score and harmonized via ComBat. Feature selection was performed using a greedy algorithm and Least absolute shrinkage and selection operator (LASSO), and others, followed by the calculation of radiomics scores through linear regression. Machine learning was then used to identify the most predictive radiomic features. Model performance was evaluated by analyzing the area under the curve (AUC) and other indicators.Univariate analysis indicated that the demographic characteristics of cervical spinal cord injury were not statistically significant. In the test dataset, the random forest (RF) combined with radiomics and ResNet34 demonstrated better performance, with an accuracy of 0.800 and an AUC of 0.893.Using MRI, deep learning-based radiomics signals show promise in evaluating and predicting the postoperative prognosis of these patients.

PMID:39962172 | DOI:10.1038/s41598-024-72539-0

Sci Rep. 2025 Feb 17;15(1):5735. doi: 10.1038/s41598-025-89289-2.

ABSTRACT

Simulated by nature’s evolution, numerous evolutionary algorithms had been proposed. These algorithms perform better for a particular problem domain and extensive parameter fine tuning and adaptations are required in optimizing problems of varied domain. This paper aims to develop robust and self-adaptive memetic algorithm by combining Differential Evolution based algorithm, a popular population based global search method with the Controlled Local search procedure to solve multi-objective optimization problems. Memetic Algorithm is an enhanced evolutionary algorithm, it combines global search method with local search techniques for faster convergence. Memetic algorithm improves both exploration and exploitation, preventing premature convergence and also refines the current best solutions efficiently. Proposed algorithm is named as Fuzzy based Memetic Algorithm using Diversity control (F-MAD). In F-MAD, population diversity is controlled through the control parameters self-adaptation of Differential Evolution algorithm (DE) such as, crossover rate and scaling factor by using two fuzzy systems. A controlled local search procedure is adapted for guiding convergence process thus balancing explore-exploit cycle. The control parameter self-adaptation and enhanced selection method with controlled local search method aid population diversity control in decision space and attaining optimal solutions with uniform distribution in terms of diversity and convergence metrics in objective space. These characteristics help the proposed method suitable to be extended to different application domain without the need of trial-and-error fine tuning of the parameters. The performance is tested through standard benchmark test problems-CEC 2009 test problems and DTLZ test problem and further validated through performance metrics and statistical test. It is compared with popular optimization algorithms and experiment results indicate that F-MAD perform well than State of-The-Art (SOTA) algorithms taken for comparison. F-MAD algorithm attains better results for 8 out of 10 CEC 2009 test problems (UF1-UF10) when compared to 20 other algorithms taken for comparison. For DTLZ problems, F-MAD attains better results for ALL 7 problems (DTLZ 1-DTLZ7) when compared to 8 other SOTA algorithms. The performance is further evaluated using Friedman rank test and the proposed F-MAD significantly outperformed other algorithms.

PMID:39962162 | DOI:10.1038/s41598-025-89289-2

Sci Rep. 2025 Feb 17;15(1):5699. doi: 10.1038/s41598-025-89527-7.

ABSTRACT

The flexible job shop scheduling problem with parallel batch processing operation (FJSP_PBPO) in this study is motivated by real-world scenarios observed in electronic product testing workshops. This research aims to tackle the deficiency of effective methods, particularly global scheduling metaheuristics, for FJSP_PBPO. We establish an optimization model utilizing mixed-integer programming to minimize makespan and introduce an enhanced walrus optimization algorithm (WaOA) for efficiently solving the FJSP_PBPO. Key innovations of our approach include novel encoding, conversion, inverse conversion, and decoding schemes tailored to the constraints of FJSP_PBPO, a random optimal matching initialization (ROMI) strategy for generating diverse and high-quality initial solutions, as well as modifications to the original feeding, migration, and fleeing strategies of WaOA, along with the introduction of a novel gathering strategy. Our approach significantly improves solution quality and optimization efficiency for FJSP_PBPO, as demonstrated through comparative analysis with four enhanced WaOA variants, eleven state-of-the-art algorithms, and validation across 30 test instances and a real-world engineering case.

PMID:39962149 | DOI:10.1038/s41598-025-89527-7