Category: Statistics

Front Psychol. 2026 Mar 3;17:1722181. doi: 10.3389/fpsyg.2026.1722181. eCollection 2026.

ABSTRACT

INTRODUCTION: When performing in public, musicians experience varying levels of music performance anxiety (MPA). The degree of MPA is influenced by various internal and external factors and differs between performances. Previous studies have mainly focused on the general disposition of MPA, but comparatively limited attention has been given to the experience of MPA in particular performance situations. In this study, the Performance-related Questionnaire for Musicians (PQM) is introduced and validated. The questionnaire was developed to assess situational MPA, thus filling a gap in standardized questionnaires relating to individual performances.

METHODS: The fourth revised German version of the PQM was tested regarding the reliability of the factor structure and the validity on a sample of 605 musicians. The PQM questionnaire focuses on aspects of situational MPA referring to a just-finished performance. It needs to be completed directly after a performance and considers retrospectively the times before and during the performance, as well as the moment when filling in the questionnaire after the performance. For the analysis, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed. Furthermore, the questionnaire was implemented in a mobile application for the individual acquisition of PQM results across various performances. In a case study, data were analysed from 31 performances of one musician.

RESULTS: A three-dimensional factor structure at the time points before, during, and after the performance showed reliable consistencies in the EFA, and the CFA confirmed the structure with adequate model fit statistics. The three dimensions represent, first, the degree of MPA symptoms (the higher the scale, the more severe the MPA); second, coping with MPA (the higher the scale, the more positive the coping); and third, self-efficacy (the higher the scale, the more positive the self-efficacy). The results of the case study with the mobile application showed individual differences and consistencies in situational MPA between performances.

DISCUSSION: The results show that the PQM is a valid tool for assessing situational MPA. The implementation as a mobile application is described as very practical and supports the use of the PQM for individual self-assessment and feedback.

PMID:41853819 | PMC:PMC12992244 | DOI:10.3389/fpsyg.2026.1722181

Front Psychol. 2026 Mar 3;17:1741344. doi: 10.3389/fpsyg.2026.1741344. eCollection 2026.

ABSTRACT

BACKGROUND: Fear of progression (FoP) is a prevalent psychological issue among stroke patients. Previous studies failing to distinguish characteristics of patient groups with varying FoP levels. Latent profile analysis (LPA) classifies individuals into distinct subgroups via continuous FoP indicators, boosting classification accuracy by accounting for variable uncertainty. Given FoP’s heterogeneity, investigating FoP profiles and their influencing factors in stroke patients is clinically significant for personalized psychological care and improved patient quality of life.

METHODS: A total of 366 stroke patients were selected as study subjects through convenience sampling, and a cross-sectional survey was conducted. FoP was assessed using the Fear of Progression Questionnaire-Short Form (FoP-Q-SF, 2 dimensions, 12 items). Independent variables included demographic characteristics, clinical indicators, the Recurrence Risk Perception Scale for Stroke patients (RRPSS), and the Medical Coping Modes Questionnaire (MCMQ). LPA was performed on the FoP-Q-SF items to identify subgroups. The R3STEP method was used to analyze influencing factors of subgroup membership, and the BCH method was applied to compare differences in distal outcomes across subgroups. Statistical significance was set at p < 0.05.

RESULTS: The study sample had a mean age of 63.93 ± 10.58 years, with 70.5% males and 65.0% first-ever stroke patients. Two latent profiles were identified: Low-FoP Adaptive Type (C1, 48.6%) and High-FoP Sustained Type (C2, 51.4%). The R3STEP showed that age 18-59 years (OR = 0.476, 95%CI = 0.245-0.924, p = 0.028), hypertension comorbidity (OR = 0.402, 95%CI = 0.237-0.683, p = 0.001), higher RRPSS score (OR = 0.971, 95%CI = 0.946-0.995, p = 0.022), MCMQ-confrontation (OR = 0.920, 95%CI = 0.863-0.982, p = 0.011), and MCMQ-avoidance (OR = 0.796, 95%CI = 0.723-0.876, p < 0.001) were significant influencing factors (all p < 0.05). BCH analysis indicated that C2 patients had higher RRPSS score (p < 0.001), higher NIHSS score (p = 0.002) and lower adaptive coping ability than C1.

CONCLUSION: This study revealed significant heterogeneity in FoP among stroke patients. Age, hypertension comorbidity, excessive recurrence risk perception, MCMQ-confrontation, and MCMQ-avoidance were associated with high FoP. Healthcare providers should prioritize identifying high-risk individuals and develop tailored interventions to reduce FoP and improve rehabilitation outcomes.

PMID:41853816 | PMC:PMC12992214 | DOI:10.3389/fpsyg.2026.1741344

Infect Dis Model. 2026 Mar 2;11(3):969-1008. doi: 10.1016/j.idm.2026.01.005. eCollection 2026 Sep.

ABSTRACT

BACKGROUND: Forecasting influenza outbreaks remains a significant challenge due to the complexity of disease transmission and the influence of environmental and behavioral factors. Traditional models based solely on the basic reproduction number $\left(R_0\right)$ often fall short in capturing the full scope of outbreak dynamics.

METHODS: In this study, we employ a seasonally adjusted SEIRT model incorporating stochastic differential equations (SDEs), including Brownian motion and Lévy jump processes, to simulate random and abrupt fluctuations in transmission. A branching process approximation is used to evaluate the probability of an epidemic under the influence of seasonal variability and stochastic perturbations. The model is calibrated using weekly influenza case data from Mexico, with noise components estimated from publicly available CDC [1] and WHO [2] surveillance data.

RESULTS: Simulation results show that the inclusion of stochastic effects and periodic transmission rates significantly enhances the model’s accuracy in reflecting real-world epidemic dynamics. Numerical comparisons between deterministic, Brownian-based, and Lévy-based scenarios reveal that both the initial state of the exposed or infectious subpopulation and the seasonal transmission patterns are critical to determining outbreak probabilities. Results indicate that seasonal transmission rates and stochastic effects significantly alter epidemic probabilities, with Lévy processes capturing abrupt outbreak dynamics more accurately than deterministic models.

CONCLUSIONS: The findings underscore that deterministic models may underestimate epidemic risk when they overlook random and sudden changes in contact rates or disease introduction. The proposed stochastic modeling framework yields a deeper understanding of influenza transmission dynamics by incorporating uncertainty and seasonal variability, thereby supporting more informed and effective public health decision-making.

PMID:41853796 | PMC:PMC12992947 | DOI:10.1016/j.idm.2026.01.005

Infect Dis Model. 2026 Mar 4;11(3):1009-1021. doi: 10.1016/j.idm.2026.03.002. eCollection 2026 Sep.

ABSTRACT

Mpox re-emerged globally in 2022, disproportionately affecting gay, bisexual, and other men who have sex with men (GBMSM). In 2024, Thailand became the first Asian country to detect Clade Ib Mpox, prompting urgent decisions on deploying a limited supply of 3000 vaccine doses. However, evidence on the comparative effectiveness of different vaccine allocation and behavioural strategies in this context remains scarce. We developed a deterministic compartmental model of Mpox transmission among high- and low-risk GBMSM, calibrated to Thailand’s national surveillance data (January 2023-May 2025). The model simulated a range of hypothetical scenarios under a constrained supply of 3000 vaccine doses, distributed either over a short 5-month period or extended across the 28-month epidemic horizon. We evaluated pre-exposure prophylaxis ( $PrEP$ ), post-exposure prophylaxis ( $PEP$ ), dose-sparing regimens, and mixed allocations of the two approaches. Each strategy was examined under alternative rollout timings (early vs. supply-delayed) and in combination with behaviour change, represented as reductions in sexual activity during symptomatic periods. The model reproduced Thailand’s epidemic trajectory. Our simulations suggested that early PrEP rollout would have yielded the greatest reduction in incidence, particularly among high-risk GBMSM. PEP strategies would have had a modest impact overall, though single-dose sparing with delayed rollout (months 5-9) would have been notably effective as the epidemic peak occurred during this period. Mixed PrEP and PEP approaches would have produced intermediate benefits, while behaviour change alone significantly would have lowered transmission. Combining PEP with even modest behavioural changes further enhanced prevention and helped reduce spillover into low-risk groups. Under constrained vaccine supply, dose-sparing and mixed vaccination strategies could improve overall coverage and impact, especially when paired with behavioural changes. Integrating flexible and context-specific vaccination approaches with realistic behavioural modifications offers the best potential for Mpox control in Thailand and similar settings.

PMID:41853794 | PMC:PMC12995482 | DOI:10.1016/j.idm.2026.03.002

Optom Vis Sci. 2026 Jan;103(1):e70027. doi: 10.1002/ovs2.70027.

ABSTRACT

PURPOSE: The aim of this study is to evaluate and quantify model performance for commonly used statistical approaches when using data from both eyes of participants. These models highlight different methods of accounting for interocular correlation.

METHODS: We simulated a continuous outcome variable, a predictor variable measured per-eye (two correlated values per subject – termed bivariate), and a predictor measured once per subject (termed univariate). Both the outcome and the bivariate predictor shared the same correlation level in all simulations. Correlations were varied 0-0.9 in 0.1 steps, with sample sizes of 50, 100, and 150. Two thousand datasets were simulated under each correlation-sample size combination. The datasets were modeled using single-eye, averaged-eye, and assumed-independent two-eye approaches within linear regression, along with a mixed effects model and a generalized estimating equation (GEE).

RESULTS: Mixed effects models, modeling one eye per subject, and averaging eyes within subjects all controlled Type-I error at 0.05 across simulated conditions. GEEs slightly inflated Type-I error, especially with smaller sample sizes. Modeling both eyes independently inflated Type-I error as high as 0.194 in high correlation scenarios. This inflation increased with increasing correlation. For univariate predictors, GEEs, mixed effects modeling and averaging eyes within subjects attained similar power across scenarios. Single-eye modeling resulted in lower power, particularly in low correlation scenarios. For bivariate predictors, mixed effects modeling and GEEs yielded greater power than single-eye or averaged-eye modeling across scenarios.

CONCLUSIONS: Mixed effects models and GEEs out-perform other approaches when the predictor of interest is bivariate and correlated, assuming correlations are similar for the predictor and outcome. For univariate predictors, averaging the outcome across eyes within each subject performs similarly to mixed effects modeling. Treating correlated measurements as independent (such as when using data from both eyes without averaging or factored into a model) inflates Type-I error rates and yields inappropriately high power, especially as correlation increases; this modeling approach leads to inference errors and should be avoided.

PMID:41851051 | DOI:10.1002/ovs2.70027

Alzheimers Dement. 2026 Mar;22(3):e71279. doi: 10.1002/alz.71279.

ABSTRACT

INTRODUCTION: Polygenic risk scores (PRSs) for Alzheimer’s disease (AD) capture an individual’s genetic susceptibility to AD. Although thoroughly studied in older populations, there exists a notable gap in comprehensively exploring the association of AD PRS with early brain development.

METHODS: We examined longitudinal brain magnetic resonance imaging (MRI) data from 348 typically developing children in the RESONANCE cohort. Proportional cerebrospinal fluid (pCSF), white matter (pWM), and gray matter (pGM) volumes were analyzed using functional concurrent regression and Riemannian functional principal component analysis. AD-PRS scores (AD25 and AD54) were computed using genome-wide data.

RESULTS: Higher AD PRS was significantly associated with reduced pCSF during early childhood (ages 2.5 to 5.5 years for AD54). Energy and distance-based tests revealed overall significant differences in brain volume trajectories between moderate and low AD54 risk groups.

DISCUSSION: These findings suggest that genetic risk for late-onset AD is linked to early neurodevelopmental patterns, indicating that AD vulnerability may originate during critical windows of early brain maturation.

PMID:41851041 | DOI:10.1002/alz.71279

J Med Internet Res. 2026 Mar 18;28:e84349. doi: 10.2196/84349.

ABSTRACT

BACKGROUND: Cognitive decline across the mild cognitive impairment (MCI)-dementia continuum is a major driver of loss of independence and growing health- and social-care burden. Immersive technologies, such as virtual reality (VR), augmented reality (AR), and Cave Automatic Virtual Environment (CAVE) systems, are increasingly explored as tools to enhance engagement, personalization, and ecological validity in cognitive rehabilitation.

OBJECTIVE: This systematic review synthesizes current evidence on the usability, therapeutic effects, and implementation challenges of immersive technologies for cognitive rehabilitation in MCI and dementia.

METHODS: A systematic search of Scopus and Web of Science was conducted for peer-reviewed journal articles published between 2021 and 2026. Eligible studies investigated VR, AR, or CAVE interventions targeting cognitive rehabilitation outcomes in MCI and/or dementia and reported measures related to usability or acceptability, or cognitive, functional, or behavioral outcomes. Due to heterogeneity in technologies, intervention content, and outcome measures, findings were synthesized narratively with comparisons across modalities and study designs.

RESULTS: In total, 119 studies met the inclusion criteria. Across immersive VR interventions, signals of benefit were most consistently reported for memory, attention, and executive functioning, with several studies also targeting outcomes with higher ecological relevance (eg, everyday task performance and functional skills). AR approaches primarily support context-aware cueing and task guidance in real-world settings, aiming to strengthen daily functioning and independence. CAVE-based systems were frequently used for spatial navigation and embodied interaction, offering advantages for supervised clinical deployment. Key barriers included cybersickness and comfort issues, interface complexity, and onboarding demands in cognitively impaired users, limited accessibility and standardization of outcome measures, small samples and short follow-up periods, and practical constraints related to cost, space, staffing, and caregiver involvement.

CONCLUSIONS: Immersive VR, AR, and CAVE systems are feasible and often engaging for cognitive rehabilitation in MCI and dementia, with promising therapeutic signals but substantial uncertainty driven by methodological and implementation heterogeneity. Future work should prioritize standardized reporting (intervention components, dose, and adverse events), clinically meaningful outcomes (including functional end points), adequately powered comparative trials, and explicit evaluation of scalability and real-world deployment pathways.

PMID:41851030 | DOI:10.2196/84349

Stat Med. 2026 Mar;45(6-7):e70464. doi: 10.1002/sim.70464.

ABSTRACT

Mediation analysis is a fundamental tool for understanding biological mechanisms through which an exposure exerts its effect on an outcome via intermediate variables, or mediators. However, modern biomedical studies often involve multiple exposures and mediators with complex correlation structures, and may also involve multiple outcomes, as in multi-omics or imaging studies, where existing mediation analyses can suffer from instability and limited interpretability. In this work, we propose Envelope-Based Sparse Partial Least Squares for Mediation Analysis (ESPLSM), which integrates dimension reduction and sparsity enforcement via the sparse envelope model to improve estimation and interpretation of causal effects. We embed the envelope model within the causal mediation framework based on potential outcomes, which allows us to formally define and identify direct and indirect effects and to establish theoretical guarantees, including asymptotic efficiency and selection consistency. Through simulation studies, we show that ESPLSM outperforms existing methods in terms of estimation accuracy, statistical power, and variable selection. Finally, we apply ESPLSM to a cancer cell line dataset to investigate the role of RNA expression in mediating the effect of EGFR mutations on drug responses. Our results provide new insights into the molecular mechanisms underlying targeted cancer therapies. Overall, ESPLSM provides a statistically principled yet practical solution for interpretable and efficient mediation analysis in modern high-dimensional biomedical applications.

PMID:41851029 | DOI:10.1002/sim.70464

DNA Cell Biol. 2026 Mar 18:10445498261433751. doi: 10.1177/10445498261433751. Online ahead of print.

ABSTRACT

Cyclin-dependent kinase 17 (CDK17) is an understudied member of the PCTAIRE family of CDKs, with phosphorylation-guided molecular mechanism being underexplored. In this study, an in-depth mass spectrometry-based phosphoproteomics data integration and harmonization, coupled with replicable statistical analysis, was performed to understand the phosphorylation landscape of CDK17. High-confidence phosphorylation sites of CDK17 were derived from 711 phosphoproteomics profiling studies, where 176 datasets showed differential phosphorylation of CDK17. Among 13 identified phosphorylation sites of CDK17, S180, S137, and S146 were prominently detected in 75% of all the datasets. Notably, sequence conservation of CDK17 (S146, S137, and S180) with CDK16 (S119, S110, and S153) and CDK18 (S98, S89, and S132), respectively, was observed, where CDK16 (S119) is a part of the binding motif for multiple upstream kinases, 14-3-3 protein, and CCNYL1. Furthermore, conserved co-regulatory patterns of other proteins were identified as compared with CDK17 phosphorylation, which revealed 19 upstream kinases, 164 downstream substrates, and several interactors of CDK17, which conserved co-regulatory patterns across diverse biological contexts. Statistical analysis revealed phosphoregulation of CDK17 through other kinases, regulation of CDK17 substrates, protein-protein interactions, and conserved co-differential regulation in multiple datasets. Specifically, this analysis derived through global data integration with a replicable analytical framework lays a groundwork for experimental validation of CDK17 phosphorylation in its functional regulation.

PMID:41851027 | DOI:10.1177/10445498261433751

Future Cardiol. 2026 Mar 18:1-8. doi: 10.1080/14796678.2026.2645005. Online ahead of print.

ABSTRACT

BACKGROUND: Patients with dialysis-dependent chronic kidney disease (CKD) have a high cardiovascular burden, prompting interest in fish oils or long-chain omega-3 polyunsaturated fatty acids (n-3 PUFAs) as potential risk-reducing therapies in this population.

METHODS: We conducted a systematic review and meta-analysis of studies in adults receiving dialysis that assessed associations between n-3 PUFA supplementation, baseline levels, or dietary intake and CV outcomes, or all-cause mortality. Hazard ratios (HRs) were pooled using random-effects models.

RESULTS: Twelve studies met inclusion criteria. In hemodialysis-dependent CKD, fish oil supplementation lowered cardiovascular events by 44% (HR 0.56; 95% CI 0.46-0.68) and myocardial infarction by 48% (HR 0.52; 95% CI 0.34-0.78). Higher baseline n-3 PUFA levels were associated with a 31% reduction in all-cause mortality (HR 0.69; 95% CI 0.54-0.88). Higher dietary n-3 PUFA intake showed a non-significant trend toward lower all-cause mortality (HR 0.92; 95% CI 0.79-1.08).

CONCLUSION: In dialysis-dependent CKD, higher n-3 PUFA exposure through fish oil supplementation or higher baseline levels was associated with fewer cardiovascular events and all-cause mortality. Appropriately dosed n-3 PUFA supplementation represents a promising cardiovascular risk reduction strategy in dialysis-dependent CKD, although confirmatory randomized trials are warranted.

PMID:41851014 | DOI:10.1080/14796678.2026.2645005