Tag: statistics

Patient Educ Couns. 2025 Nov 23;143:109431. doi: 10.1016/j.pec.2025.109431. Online ahead of print.

ABSTRACT

PURPOSE: The growing prevalence of cancer and of the responsibilities of primary informal caregivers calls for exploring the burden of caregivers. Communication with providers has become a major responsibility of caregivers increasing their burden. Despite the harmful consequences of caregiver burden (CB), little is known regarding mitigators of CB. The perceived high quality of communication with providers may be a mitigator of CB which is yet to be tested. Therefore, this study tests the association of episodic listening behaviors of providers and CB among caregivers of cancer patients. We hypothesize that constructive listening behaviors of nurses will shape the extent of CB.

METHODS: In this cross-sectional study, hospitalized oncology patients gave their consent to approach their informal primary caregivers and requested their consent to participate by completing anonymous questionnaires. Study variables included the Zarit Burden Interview and the abbreviated Constructive and Destructive Listening questionnaires. Statistical analyses used Pearson correlations and multivariable linear regression.

RESULTS: The sample comprised 80 primary caregivers of cancer patients. 65 % were women, 65 % were religious, and the average age was 51 years. Mean CB was 27.21 (SD-16.39). CB was positively associated with destructive listening (r = 0.400, p = 0.000) and negatively associated with constructive listening (r = -0.223, p = 0.000). Multivariable linear regression identified destructive listening as a significant antecedent (β = 0.265; t = 2.007; p = 0.049), explaining 14.7 % of the variance in CB (R² = 0.0192; MS = 568.147; df = 6; F = 2.7; p = < 0.002).

CONCLUSIONS: Although episodic listening is a key component of nursing ethics and fundamental to relationships with patients, caregivers of cancer patients may be ignored. To reduce CB, nurses should eradicate destructive listening and promote constructive listening forging higher quality communication with patients. Insights may guide future research and paths to reduce CB.

PMID:41308256 | DOI:10.1016/j.pec.2025.109431

Biomed Phys Eng Express. 2025 Nov 27. doi: 10.1088/2057-1976/ae250e. Online ahead of print.

ABSTRACT

The study of inter-beat intervals (IBI) and systolic blood pressure (SBP) fluctuations is of public health importance. Here we obtain insights about their underlying dynamics by means of an innovative study of the distribution of their rank-ordered registers, provided by fits to the Discrete Generalized Beta Distribution (DGBD), for healthy subjects and patients with end-stage renal disease (ESRD), under an active standing maneuver. SBP and IBI non-invasive time series were recorded during supine position followed by active standing for nine ESRD patients and eighteen age-matched healthy subjects. Once the data were rank ordered, the three parameter DGBD function was fitted through the Levenberg-Marquardt non-linear algorithm. Taking into consideration the statistical interpretations of the parameters, the quantitative exploration of their dependence with regard to the cases examined and changes in body position provided new insights: i) Evidence for the presence of regulatory mechanisms that preserve the tail symmetry of the IBI distributions in healthy subjects, which are not evident in ESRD patients; ii) The identification of a more pronounced weight of low-magnitude fluctuations at active standing in the SBP time series, manifested as a broader statistical dispersion of blood pressure values; iii) A quantitative determination of a more undermined SBP regulation in ESRD. Overall, a better understanding of the statistical behavior of IBI and SBP time series is achieved by means of the DGBD function. Through the variation of its parameters, the DGBD approach has the potential to become a marker for assessing or even predicting the impairment of cardiovascular control mechanisms.&#xD.

PMID:41308208 | DOI:10.1088/2057-1976/ae250e

Biomed Phys Eng Express. 2025 Nov 27. doi: 10.1088/2057-1976/ae250f. Online ahead of print.

ABSTRACT

Photoplethysmography (PPG) is widely used in wearable health monitors for tracking fundamental physiological parameters (e.g., heart rate and blood oxygen saturation) and advancing applications requiring high-quality signals-such as blood pressure assessment and cardiac arrhythmia detection. However, motion artifacts and environmental noise significantly degrade the accuracy of PPG-derived physiological measurements, potentially causing false alarms or delayed diagnoses in longitudinal monitoring cohorts. While signal quality assessment (SQA) provides an effective solution, existing methods show insufficient robustness in ambulatory scenarios. This study concentrates on PPG signal quality detection and proposes a robust SQA algorithm for wearable devices under unrestricted daily activities. PPG and acceleration signals were acquired from 54 participants using a self-made physiological monitoring headband during daily activities, segmented into 35712 non-overlapping 5-second epochs. Each epoch was annotated with: (1) PPG signal quality levels (good: 10817; moderate: 14788; poor: 10107), and (2) activity states classified as stationary, light, moderate, or vigorous-intensity. The dataset was stratified into training (80%) and testing (20%) subsets to maintain proportional representation. Fourteen discriminative features were extracted from four domains: morphological characteristics, time-frequency distributions, physiological parameter estimation accuracy, and statistical properties of signal dynamics. Four machine learning algorithms were employed to train models for SQA. The random forest (95.6%) achieved the highest accuracy on the test set, but no significant differences (p=0.471) compared to support vector machine (95.4%), naive Bayes (94.1%), and BP neural network (95.1%). Additionally, the classification accuracy showed no statistically significant variations (p=0.648) across light (95.3%), moderate (97.6%), and vigorous activity (100%) when compared to sedentary (95.8%). All features exhibited significant differences (p<0.05) across high/moderate/poor quality segments in all pairwise comparisons.The results indicate that the proposed feature set achieves robust SQA, maintaining consistently high classification accuracy across all activity intensities. This performance stability enables real-time implementation in wearable devices.

PMID:41308204 | DOI:10.1088/2057-1976/ae250f

JMIR Serious Games. 2025 Nov 27;13:e71593. doi: 10.2196/71593.

ABSTRACT

BACKGROUND: Staff working in residential care homes (RCHs) have played a significant role in preventing the spread of infection among residents, visitors, and staff. Providing continuous professional training to the staff is essential. Current infection control training mostly rests on short educational talks or one-to-one reminders in the RCHs. A blended mode of online interactive games and face-to-face consultations was now proposed as a new way to conduct infection control training in the RCHs.

OBJECTIVE: This study aims to assess the efficacy of the Blended Gaming COVID-19 Training System (BGCTS) on infection control practices and self-reported knowledge, attitude, and practices of standard precautions among health care workers in RCHs.

METHODS: A 2-arm, single-blinded, parallel cluster randomized controlled trial was designed, and 30 RCHs were recruited and randomized into an intervention group to receive the BGCTS and a control group to receive usual care on infection control training. Due to the COVID-19 pandemic and infected cases in the homes, 17 RCHs refused or delayed the on-site observations. The BGCTS intervention, developed based on “The COVID-19 Risk Communication Package for Healthcare Facilities” of the World Health Organization, consists of two parts: (1) an eHealth mode of a 120-minute web-based training system covering 8 topics, delivered in short-clip videos and games, and (2) two 30-minute face-to-face interactive sessions for concept clarification. The 2 infection control practices, “use of gloves and personal protective equipment (PPE) and performing respiratory hygiene” and “hand rub,” were assessed by on-site unobtrusive observations, and self-reported infection control practices and knowledge and attitude toward infection control were measured via online survey post intervention.

RESULTS: A total of 212 staff from 13 RCHs were involved in the analysis, with 7 RCHs from the intervention group (n=114) and 6 RCHs from the control group (n=98). A significantly greater increase in the proportions of proper use of gloves and PPE and respiratory hygiene performance (β=.195, 95% CI 0.046-0.344; P=.02) and properly performed hand rub (β=.068, 95% CI 0.005-0.132; P=.04) was observed in the intervention group. The changes in the self-reported outcomes were not statistically significant.

CONCLUSIONS: BGCTS improved RCH staff’s performance in 2 infection control practices by objective measurement, “gloves and PPE use and performance in respiratory hygiene” and “hand rub.” BGCTS was shown to be an effective training, although it was a 2-week intervention. The BGCTS did not perform better than infection control briefing sessions in self-reported infection control knowledge, attitude, and practices. This electronic-based infection control training with 2 intensive interactive sessions has good potential to be adopted as regular training in RCHs.

TRIAL REGISTRATION: Clinicaltrials.gov NCT04783025; http://clinicaltrials.gov/ct2/show/NCT04783025.

PMID:41308187 | DOI:10.2196/71593

Percept Mot Skills. 2025 Nov 27:315125251395108. doi: 10.1177/00315125251395108. Online ahead of print.

ABSTRACT

Visual perception is crucial for successfully executing motor skills in interceptive sports like baseball. Understanding the contribution of visual skills (VS) to baseball performance is essential for talent selection and development. Some evidence suggests that performance on visual tests is predictive of batting performance, though these findings are not consistently replicated across studies. Therefore, the aim of this study is to associate a broad spectrum of visual performance indicators with a set of batting performance variables in highly trained baseball players by combining different methodological approaches used in previous studies. Forty-five highly trained male baseball players from the same club, aged between 15 and 19 years old (mean = 17.25), underwent a thorough battery of visual tests under standardized conditions. Twenty-one variables of VS were collected and associated with ten performance indicators, including game statistics, players’ ranking, age, years of practice, and position. Frequentist correlations and t-tests revealed that 17 out of the 210 associations (8.09%) reached our unadjusted threshold level and thus indicated a positive and statistically significant association. Bayesian analyses identified 34 associations (16.19%) that supported a positive association between VS and performance indicators, but only two of them (0.95%) revealed a moderate level of evidence in favor of the positive association. Therefore, this study provides limited support to the hypothesis that performance on visual tests predicts batting performance. The homogeneity of the sample and potential non-linear relations between visual and batting performance may account for these findings.

PMID:41308178 | DOI:10.1177/00315125251395108

Interdiscip Cardiovasc Thorac Surg. 2025 Nov 27:ivaf281. doi: 10.1093/icvts/ivaf281. Online ahead of print.

ABSTRACT

OBJECTIVES: Increased aortic angulation (AA) is anatomically challenging during transcatheter aortic valve implantation (TAVI) and may affect procedural outcomes. This study evaluates the clinical and procedural impact of aortic angulation in contemporary TAVI procedures.

METHODS: This retrospective single-center observational study included 509 consecutive patients undergoing transfemoral TAVI between January 2021 and December 2024. Primary end-point was device success according to VARC-3 criteria. Secondary end-points included technical success, early safety at 30 days, procedural time, fluoroscopy time, contrast volume, paravalvular regurgitation (PVR) and permanent pacemaker implantation (PPI). Multivariable logistic and linear regression models were used to assess the association between aortic angulation (in degrees) and clinical outcomes. ROC and spline regression analyses were used to evaluate potential threshold effects.

RESULTS: Device success at discharge was achieved in 89.4% (455/509) of patients, technical success in 96.3% (490/509), and early safety at 30 days in 75.6% (385/509). Aortic angulation did not significantly influence device success (aOR: 0.974, 95% CI: 0.938-1.012, p = 0.175), technical success (aOR 1.034; 95% CI 0.980-1.091; P = 0.22), or early safety (aOR: 0.994, 95% CI: 0.968-1.020, p = 0.633). Similarly, no association was observed between aortic angulation and PPI (aOR 1.016; 95% CI 0.984-1.050; P = 0.34) and PVR. However, aortic angulation significantly correlated with increased fluoroscopy times (coefficient: 0.073, SE: 0.026; P = 0.006) and greater contrast usage (coefficient: 0.406, SE: 0.194; P = 0.037).

CONCLUSIONS: While higher aortic angulation increased procedural imaging demand, it did not adversely affect device performance or clinical safety outcomes after TAVI. Importantly, outcomes remained consistent across prosthesis types.

PMID:41308164 | DOI:10.1093/icvts/ivaf281

Science. 2025 Nov 27;390(6776):883-884. doi: 10.1126/science.aec7388. Epub 2025 Nov 27.

ABSTRACT

Changing algorithms with artificial intelligence tools can influence partisan animosity.

PMID:41308160 | DOI:10.1126/science.aec7388

Brief Bioinform. 2025 Nov 1;26(6):bbaf633. doi: 10.1093/bib/bbaf633.

ABSTRACT

Inflammatory bowel disease (IBD) is a hereditary and chronic inflammatory condition affecting the gastrointestinal tract, with two main subphenotypes: Crohn’s disease (CD) and ulcerative colitis (UC). Most IBD-related genetic associations are limited to independent subphenotypes and ancestral populations, and the heritability remains largely unexplained, prompting us to conduct the large-scale multi-trait genome-wide association study (GWAS) meta-analysis that incorporates both subphenotypes and diverse ancestral populations to reveal novel susceptibility loci through the substantially enhanced genetic discovery power. We initially identified IBD statistical association signals at 84 (12 novels) independent index loci by two-stage multi-trait analysis of GWAS and increased the number to 165 (29 novels) in cross-ancestry meta-analysis. Subtype-specific analysis revealed distinct genetic architectures for CD and UC. Leveraging multi-omics datasets, we performed a comprehensive functional post-GWAS annotation. Several therapeutic targets were identified by a multi-stage prioritization strategy, including JAK2, STAT3, IL18R1, IFNG, and CCL2, highlighting systemic immune regulation in IBD treatment. In the inflammatory injury model, we determined that increased GNA12 expression may disrupt the intestinal barrier. Cross-trait analyses and multi-omics Mendelian randomization showed potential causalities with immune-mediated diseases, cytokines, cell traits, and microorganisms. This study yields novel insights into the molecular etiology of IBD and reveals potential immunotherapy targets and pathways for medication.

PMID:41308126 | DOI:10.1093/bib/bbaf633

Health Promot Int. 2025 Oct 30;40(6):daaf206. doi: 10.1093/heapro/daaf206.

ABSTRACT

Given that news media play key roles in shaping public and policy responses to food poverty and insecurity, this study analysed how newspapers frame these issues across the island of Ireland, comparing coverage between jurisdictions (Republic of Ireland and Northern Ireland) and newspaper types (national versus regional/local). Using LexisNexis and Irish Newspaper Archives, we searched for articles containing ‘food poverty’ or ‘food insecurity’ published between January 2018 and January 2023. We used Entman’s framing theory to code articles for problem definitions, causal interpretations, solutions, moral evaluations, and social actors. Analysis of 80 articles from 14 newspapers revealed coverage peaked during school holiday periods (December and Summer), reinforcing episodic attention to ‘holiday hunger’. Although structural causes appeared in 66% of articles-including inadequate income, living costs, and welfare failures-proposed solutions were predominantly charitable (79%) rather than structural (39%), with food banks cited most frequently. National newspapers more frequently discussed structural causes and policy solutions, while regional publications focused on charitable responses. Articles predominantly featured voices from charities (88%) and government officials (50%), while only 10% incorporated voices from those experiencing food poverty and insecurity. This disconnect between acknowledged structural causes and proposed charitable solutions perpetuates normalization of food poverty and insecurity, obscuring state responsibility for ensuring the right to adequate food. Such framing impedes recognition that this issue in wealthy nations results from political choices requiring systemic reform, not charitable intervention.

PMID:41308116 | DOI:10.1093/heapro/daaf206

IEEE Trans Image Process. 2025 Nov 27;PP. doi: 10.1109/TIP.2025.3635025. Online ahead of print.

ABSTRACT

Deep neural networks pre-trained on ImageNet have demonstrated remarkable transferability for developing effective full-reference image quality assessment (FR-IQA) models. However, existing approaches typically demand pixel-level alignment between reference and distorted images-a requirement that poses significant challenges in practical scenarios involving natural photography and texture similarity evaluation. To address this limitation, we propose a novel FR-IQA model leveraging deep statistical similarity derived from pre-trained features without relying on spatial co-location of these features or requiring fine-tuning with mean opinion scores. Specifically, we employ distance correlation, a potent yet relatively underexplored statistical measure, to quantify similarity between reference and distorted images within a deep feature space. The distance correlation is computed via the ratio of the distance covariance to the product of their respective distance standard deviations, for which we derive a closed-form solution using the inner product of deep double-centered distance matrices. Extensive experimental evaluations across diverse IQA benchmarks demonstrate the superiority and robustness of the proposed model. Furthermore, we demonstrate the utility of our model for optimizing texture synthesis and neural style transfer tasks, achieving state-of-the-art performance in both quantitative measures and qualitative assessments. The implementation is publicly available at https://github.com/h4nwei/DeepDC.

PMID:41308106 | DOI:10.1109/TIP.2025.3635025