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Nevin Manimala Statistics

The mediating role of psychological resilience in the relationship between workplace violence and job stress among healthcare workers

BMC Public Health. 2025 Sep 1;25(1):3005. doi: 10.1186/s12889-025-23560-z.

ABSTRACT

BACKGROUND: Workplace violence is a widespread, global public healthcare concern among healthcare employees. The present study aimed to examine the mediating role of psychological resilience in the relationship between workplace violence and job stress among healthcare employees.

MATERIALS AND METHODS: The population of the study, which had a descriptive and correlational design, consisted of all healthcare employees working in a hospital in the southeast of Turkey, and the study was completed with 515 healthcare employees. The data were collected between 20.05.2024 and 15.09.2024 using a face-to-face interview technique with a data form consisting of 4 sections. The data collection form consists of 4 sections: socio-demographic characteristics, Psychological Violence Behaviors at Workplace Scale, A Work Stress Scale-20, Brief Psychological Resilience Scale. The data were then analyzed by using the SPSS software. Descriptive statistics and parametric methods, Pearson Correlation Analysis, and Linear Regression were used in the evaluation of the data, and hierarchical regression analyses regarding the mediation effect were made by using the PROCESS Model 4. A p-value < 0.05 was accepted as significant in the analyses.

RESULTS: A total of 55.9% of the participants were female and 44.1% were male. When the occupational distribution was evaluated, the largest group was nurses with 55.3%, followed by midwives with 12.6% and physicians with 7.4%. The total mean score on the Scale of Psychological Violence Behaviors in the Workplace was 37.27 ± 39.51, the total mean score on the Short Psychological psychological resilience Scale was 20.41 ± 4.32, and the total mean score on the Job Stress Scale was 46.51 ± 20.72. A negative and significant relationship was detected between the psychological psychological resilience scale total score and the total score of Psychological Violence Behaviors in the Workplace. A positive and highly significant relationship was detected between the total score of the Job Stress Scale and the total score of Psychological Violence Behaviors in the Workplace. A negative and significant relationship was detected between psychological resilience and job stress. The effect of psychological violence in the workplace on psychological resilience was significant.

CONCLUSION: This study suggests that workplace violence increases job stress by weakening psychological resilience. Psychological resilience plays a partial role in moderating this effect. Reducing the negative impacts of Job Stress and psychological violence on individuals and protecting and developing the psychological resilience of healthcare staff is a critical priority for the well-being of employees and for institutions to achieve their sustainable targets.

PMID:40890731 | DOI:10.1186/s12889-025-23560-z

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Nevin Manimala Statistics

Links between Korean baby boomers’ physical activity and health outcomes: a community health survey study

BMC Public Health. 2025 Sep 1;25(1):2988. doi: 10.1186/s12889-025-23998-1.

ABSTRACT

BACKGROUND: This study aimed to explore the association between physical activity (PA) levels and major health issues (obesity, hypertension, and diabetes mellitus) and mental health factors (depression, stress, suicidal thoughts, and cognitive impairment) among South Korean baby boomers (BBs) to help improve national health policies. Given the global trend of aging populations and the increasing burden of non-communicable diseases, understanding the role of PA in promoting healthy aging has become a critical public health issue not only in South Korea but also worldwide.

METHODS: Using 2022 Community Health Survey data, we analysed PA levels (low, moderate, and high) and their associations with health outcomes in BBs aged 59-67 years. PA was assessed using the metabolic equivalent of task of the International Physical Activity Questionnaire. Health outcomes were evaluated based on obesity, hypertension, diabetes, mental health issues, and stress levels. Complex sample logistic regression was used to evaluate the interrelation between PA and health outcomes, adjusting for household income, marital status, and educational level.

RESULTS: In men, moderate and high-intensity PA was associated with lower obesity and diabetes rates compared with low-intensity PA, with only moderate PA levels showing consistent links to reduced obesity. In women, both moderate and high PA levels were associated with reduced obesity, hypertension, and diabetes rates. For mental health, PA at both levels was associated with lower odds of all outcomes in both sexes, with moderate PA showing stronger associations than high PA for stress, suicidal thoughts, and cognitive impairment in women.

CONCLUSIONS: PA is meaningfully associated with health issues and mental well-being among South Korean BBs. These findings underscore the relevance of tailored PA recommendations and community-based strategies that reflect population characteristics. Further research is warranted to explore the effects of different types of physical activities and their impact on health risk factors.

PMID:40890726 | DOI:10.1186/s12889-025-23998-1

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Nevin Manimala Statistics

“The more I know, the more you know” Using culturally responsive marketing strategies to develop tools that increase awareness about clinical trials among Black communities

BMC Public Health. 2025 Sep 1;25(1):3003. doi: 10.1186/s12889-025-24194-x.

ABSTRACT

BACKGROUND: Ineffective dissemination of cancer research and information among the public contributes to cancer inequities. Dissemination rarely involves efforts to engage non-research audiences and end-users in developing effective messaging. Efforts to promote equity in clinical trial participation may benefit from marketing strategies traditionally applied in the business sector. Black Americans suffer the highest death rates from most cancers than any other race/ethnicity, yet only 5% of patients enrolled in cancer clinical trials are Black. Our team used a marketing strategy framework to create a culturally responsive public service announcement (PSA) video to increase awareness of clinical trials among Black audiences.

METHODS: We partnered with a marketing recruitment firm and a marketing agency to conduct six focus groups (n = 54) with social support networks of Black cancer survivors and Black community members. Maximum variation sampling was used to recruit a national sample of eligible participants that varied in age, education, geographic region, and gender. Focus groups were conducted over three phases that informed script development, script and storyline testing, and sought feedback on the PSA video post-production. We used the Marketing and Clinical Trials Reference Model to guide marketing strategies, data collection, video content development and production. We used rapid qualitative data analysis techniques to identify themes for each phase to guide PSA development.

RESULTS: Partnered with a film production company, we produced a 2-min PSA video that uses professional actors and storytelling and marketing techniques to describe clinical trials, provide relevant statistics, address barriers to participation expressed by participants, and provide credible resources to seek further information. We also produced 30 s and 60 s versions of the PSA to accommodate different marketing media outlets. Participants felt the videos were engaging and relatable and that the messaging was clear. The videos ignited meaningful discussions about clinical trial participation and motivated participants to share the information learned.

CONCLUSIONS: Using marketing communication strategies is a low-tech, pragmatic approach to effectively produce health information that is meaningful, can be tailored for specific audiences, and disseminated to broader audiences.

PMID:40890722 | DOI:10.1186/s12889-025-24194-x

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Nevin Manimala Statistics

Can artificial intelligence with multimodal imaging outperform traditional methods in predicting age-related macular degeneration progression? A systematic review and exploratory meta-analysis

BMC Med Inform Decis Mak. 2025 Sep 1;25(1):321. doi: 10.1186/s12911-025-03119-z.

ABSTRACT

PURPOSE: Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss, and its prevalence is expected to rise with aging populations. Early prediction of AMD progression is critical for effective management. This systematic review and meta-analysis evaluate the accuracy, sensitivity, and specificity of artificial intelligence (AI) algorithms in in detecting and predicting progression of AMD.

METHODS: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic review and meta-analysis were conducted from inception to February 7th, 2025. We included five studies that assessed the performance of AI algorithms in predicting AMD progression using multimodal imaging. Data on accuracy, sensitivity, and specificity were extracted, and meta-analysis was performed using Comprehensive Meta-Analysis software version 3.7. Heterogeneity was assessed using the I² statistic.

RESULTS: Of the five studies, AI models demonstrated superior accuracy (mean difference: 0.07, 95% CI: 0.07, 0.07; p < 0.00001) and sensitivity (mean difference: 0.08, 95% CI: 0.08, 0.08; p < 0.00001) compared to retinal specialists. Specificity also showed a minimal but significant advantage for AI (mean difference: 0.01, 95% CI: 0.01, 0.01; p < 0.00001). Importantly, heterogeneity was minimal to absent across all analyses (I² = 0-0.42%), supporting the reliability and consistency of pooled findings.

CONCLUSION: AI algorithms outperform retinal specialists in predicting AMD progression, particularly in accuracy and sensitivity. These findings support the potential of AI in AMD prediction; however, given the limited number of included studies, the results should be interpreted as exploratory and in need of validation through future large-scale, prospective studies.

PMID:40890721 | DOI:10.1186/s12911-025-03119-z

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Nevin Manimala Statistics

Feasibility of AI-powered assessment scoring: Can large language models replace human raters?

Clin Neuropsychol. 2025 Sep 1:1-14. doi: 10.1080/13854046.2025.2552289. Online ahead of print.

ABSTRACT

Objective: To assess the feasibility, accuracy, and reliability of using ChatGPT-4.5 (early-access), a large language model (LLM), for automated scoring of Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) protocols. Performance of ChatGPT-4.5 was compared against human raters on scoring record forms (i.e. word lists, numeric tables, and drawing responses). Method: Thirty-five deidentified BICAMS protocols, including the Symbol Digit Modalities Test (SDMT), California Verbal Learning Test-II (CVLT-II), and Brief Visuospatial Memory Test-Revised (BVMT-R), were independently scored by two trained human raters and ChatGPT-4.5. Scoring with ChatGPT-4.5 involved uploading protocol scans and structured prompts. Scoring discrepancies were resolved by a blinded third rater. Intraclass correlation coefficients (ICCs), paired samples t-tests, and descriptive statistics evaluated interrater reliability, accuracy, and speed. Results: Before public release of ChatGPT-4.5, strong interrater reliability was found between ChatGPT-4.5 and human raters on all total scores (e.g. CVLT-II ICC = 0.992; SDMT ICC = 1.000; BVMT-R ICC = 0.822-853), with minimal scoring discrepancies per test (CVLT = 1.05, SDMT = 0.05, BVMT-R = 1.05-1.19). ChatGPT-4.5 identified scoring errors overlooked by two human raters and completed scoring of each BICAMS protocol in under 9 min. After ChatGPT-4.5 was publicly released, reliability decreased notably (e.g. ICC = -0.046 for BVMT-R Trial 3), and average scoring discrepancies per test increased (e.g. SDMT = 6.79). Conclusions: ChatGPT-4.5 demonstrated comparable accuracy relative to human raters, though performance variability emerged after public release. With adequate computational resources and prompt/model optimization, LLMs may streamline neuropsychological assessment, enhancing clinical efficiency, and reducing human errors.

PMID:40889122 | DOI:10.1080/13854046.2025.2552289

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Nevin Manimala Statistics

scSorterDL: a deep neural network-enhanced ensemble LDAs for single cell classifications

Brief Bioinform. 2025 Aug 31;26(5):bbaf446. doi: 10.1093/bib/bbaf446.

ABSTRACT

The emergence of single-cell RNA sequencing (scRNA-seq) technology has transformed our understanding of cellular diversity, yet it presents notable challenges for cell type annotation due to data’s high dimensionality and sparsity. To tackle these issues, we present scSorterDL, an innovative approach that combines penalized Linear Discriminant Analysis (pLDA), swarm learning, and deep neural networks (DNNs) to improve cell type classification. In scSorterDL, we generate numerous random subsets of the data and apply pLDA models to each subset to capture varied data aspects. The model outputs are then consolidated using a DNN that identifies complex relationships among the pLDA scores, enhancing classification accuracy by considering interactions that simpler methods might overlook. Utilizing GPU computing for both swarm learning and deep learning, scSorterDL adeptly manages large datasets and high-dimensional gene expression data. We tested scSorterDL on 13 real scRNA-seq datasets from diverse species, tissues, and platforms, as well as on 20 pairs of cross-platform datasets. Our method surpassed nine current cell annotation tools in both accuracy and robustness, indicating exceptional performance in both cross-validation and cross-platform contexts. These findings underscore the potential of scSorterDL as an effective and adaptable tool for automated cell type annotation in scRNA-seq research. The code is available on GitHub: https://github.com/kellen8hao/scSorterDL.

PMID:40889117 | DOI:10.1093/bib/bbaf446

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Significantly enhancing human antibody affinity via deep learning and computational biology-guided single-point mutations

Brief Bioinform. 2025 Aug 31;26(5):bbaf445. doi: 10.1093/bib/bbaf445.

ABSTRACT

Enhancing antibody affinity is a critical goal in antibody design, as it improves therapeutic efficacy, specificity, and safety while reducing dosage requirements. Traditional methods, such as single-point mutations or combinatorial mutagenesis, are limited by the impracticality of exhaustively exploring the vast mutational space. To address this challenge, we developed a novel computational pipeline that integrates evolutionary constraints, antibody-antigen-specific statistical potentials, molecular dynamics simulations, metadynamics, and a suite of deep learning models to identify affinity-enhancing mutations. Our deep learning framework includes MicroMutate, which predicts microenvironment-specific amino acid mutations, and graph-based models that evaluate postmutation antigen-antibody-binding probabilities. Using this approach, we screened 12 single-point mutant antibodies targeting the hemagglutinin of the H7N9 avian influenza virus, starting from antibodies with initial affinities in the subnanomolar range, with one showing a 4.62-fold improvement. To demonstrate the generalizability of our method, we applied it to engineer an antibody against death receptor 5 with initial affinities in the subnanomolar range, successfully identifying a mutant with a 2.07-fold increase in affinity. Our work underscores the transformative potential of integrating deep learning and computational methods for rapidly and precisely discovering affinity-enhancing mutations while preserving immunogenicity and expression. This approach offers a powerful and universal platform for advancing antibody therapeutics.

PMID:40889116 | DOI:10.1093/bib/bbaf445

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Utility of whole-slide imaging for rapid evaluation of thyroid FNA: A multireader prospective study

Cancer Cytopathol. 2025 Sep;133(9):e70046. doi: 10.1002/cncy.70046.

ABSTRACT

BACKGROUND: Rapid on-site evaluation (ROSE) of thyroid fine-needle aspiration biopsy (FNAB) improves diagnostic adequacy and facilitates ancillary molecular testing. In this prospective, multireader study, the authors evaluated the feasibility of using whole-slide images (WSIs) for ROSE to determine specimen adequacy and preliminary categorization (according to The Bethesda System for Reporting Thyroid Cytopathology [Bethesda]) of image-guided thyroid FNABs compared with conventional light-microscopic (LM) examination of the same specimens in a referral cancer center.

METHODS: The authors evaluated 98 ultrasound-guided thyroid FNAB cases. Smears were stained with Papanicolaou and Diff-Quik and were scanned at ×20 magnification using a Leica Aperio CS2 scanner. Five cytopathologists evaluated specimen adequacy and Bethesda categorization using WSI followed by LM assessment after a 2-week washout. Intraobserver and interobserver agreements were calculated using Cohen and Fleiss kappa (κ) statistics. Scan time, interpretation time, and the need for ×40 magnification or z stacking were recorded.

RESULTS: In total, 463 slides were scanned, with mean scan time of 5.48 minutes. WSI quality was acceptable in most cases. Z stacking and ×40 magnification were requested in 23% and 14% of reviews, respectively. Intrareader agreement between WSI and LM examination was excellent (κ = 0.86-0.95). Inter-reader agreement was moderate for both WSI (κ = 0.48) and LM examination (κ = 0.56). Concordance was highest for Bethesda categories I and VI and lowest for categories III-V. Interpretation with WSI took significantly longer than with LM examination (p < .0001).

CONCLUSIONS: WSI is a feasible alternative to LM examination for ROSE of thyroid FNABs, with high intrareader agreement and comparable inter-reader agreement. The limited need for high magnification and z stacking supports its practical utility.

PMID:40889104 | DOI:10.1002/cncy.70046

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Morphological and Functional Outcomes in the Long-Term Natural Course of Peripapillary Pachychoroid Syndrome

Ophthalmol Ther. 2025 Sep 1. doi: 10.1007/s40123-025-01226-8. Online ahead of print.

ABSTRACT

INTRODUCTION: This study investigated the long-term natural history of peripapillary pachychoroid syndrome (PPS), analyzing both morphological and functional outcomes.

METHODS: This retrospective study included 24 eyes from 14 participants diagnosed with PPS. No interventions were administered. Baseline and follow-up assessments comprised best-corrected visual acuity (BCVA), measured on the LogMAR scale, inner nasal (IN) and outer nasal (ON) macular thickness measured using the ETDRS (Early Treatment Diabetic Retinopathy Study) subfields. To account for repeated measures and the hierarchical structure of eyes nested within participants, and to appropriately handle incomplete longitudinal data, linear mixed-effects models were utilized for all statistical analyses.

RESULTS: The mean age was 74 ± 7 years, and 71% of patients had bilateral PPS. All patients had peripapillary atrophy at baseline. The mean baseline BCVA was 0.05 and showed only small variations over time. ON macular thickness showed a significant decrease at 2 years (Δ = – 36.9 µm, p = 0.034), whereas IN macular thickness decreased significantly at both 2 years (Δ = – 40.75 µm, p = 0.023) and 3 years (Δ = – 39.97 µm, p = 0.042). One-quarter of participants developed a serous pigment epithelium detachment with subretinal fluid, suggesting an overlapping PPS/CSC (central serous chorioretinopathy) phenotype.

CONCLUSIONS: Peripapillary atrophy appears to be an important anatomical predisposition for PPS. Waxing and waning of intraretinal fluid were observed during the natural course of PPS, with a significant reduction at 2 years. Most patients remained asymptomatic and maintained stable BCVA throughout long-term follow-up, indicating a generally favorable prognosis in the absence of intervention.

PMID:40889090 | DOI:10.1007/s40123-025-01226-8

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International Trends in Opioid Prescribing by Age and Sex from 2001 to 2019: An Observational Study Using Population-Based Databases from 18 Countries and One Special Administrative Region

CNS Drugs. 2025 Sep 1. doi: 10.1007/s40263-025-01215-2. Online ahead of print.

ABSTRACT

OBJECTIVE: To characterize multinational trends and patterns of opioid analgesic prescribing by sex and age.

DESIGN, SETTING, AND PARTICIPANTS: We studied opioid analgesic prescribing from 2001 to 2019 with common protocol using population-based databases from eighteen countries and one special administrative region.

MAIN OUTCOME MEASURES: We measured opioid prescribing by geographical region, sex and age, estimating annual prevalent, incident, and nonincident opioid prescribing per 100 population with a 95% confidence interval (CI) and meta-analyzed the multinational and regional opioid prescribing with a random-effects model. Time trends were reported through average annual absolute changes, estimated using linear mixed models. We further explored the effect of sex and age on prevalent opioid prescribing in the multivariable analysis.

RESULTS: Over 248 million individuals were included. Pooled multinational opioid prescribing prevalence was 9.0% amongst included countries/regions. Opioid prescribing prevalence in 2015 ranged from 2.7% in Japan to 19.7% in Iceland. Average annual absolute changes in opioid prescribing prevalence per year ranged from – 1.53% (95% CI – 2.06, – 1.00; United States Medicaid) to + 1.24% (95% CI 1.02, 1.46; South Korea). Pooled multinational incident opioid prescribing (4.9%; 95% CI 4.1, 5.9) was higher than pooled multinational nonincident opioid prescribing (3.7%; 95% CI 2.9, 4.8). The female sex and older age were associated with higher opioid prescribing. Main limitations of this study include the absence of data from study duration or individuals not covered by the data sources and the lack of information on medication adherence and indication.

CONCLUSIONS: Opioid prescribing remains unbalanced across geographical regions; however, results suggest a tendency to convergence across countries/regions. Differences in opioid prescribing by sex and age were identified.

PMID:40889082 | DOI:10.1007/s40263-025-01215-2