Category: Statistics

Nutrition. 2026 Jul 6;150:113307. doi: 10.1016/j.nut.2026.113307. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the effect of training conducted using simulation- and booklet-based training techniques on breastfeeding self-efficacy, breastfeeding, and breast-related problems.

METHODS: This randomized controlled trial was conducted between July and December 2023 in obstetric outpatient clinics with women receiving antenatal care (control group: 22, booklet-based training group: 22, and simulation-based training group: 22). A total of five interviews with all participants were conducted. The data were collected with a Personal Information Form, the Breastfeeding Self-Efficacy Scale (BSES), and the Breastfeeding Experience Scale (BES). Data analysis was conducted using the SPSS software using descriptive statistics, chi-square, Kruskal Wallis test, and Bonferroni correction test.

RESULTS: In the study, the groups were homogeneous in terms of obstetric and birth-related characteristics (P > 0.05). The total BSES scale scores of the women in the booklet-based and simulation-based groups were higher than those in the control group in the 2nd, 3rd, 4th, and 5th interviews after the training (η² = 0.292; 0.543; 0.640; and 0.682 according to the times). The mean BES scale scores of the women in the booklet-based and simulation-based groups were lower than those of the women in the control group in the 4th and 5th interviews postpartum after the training given (η² = 0.368; 0.508 according to the times).

CONCLUSION: Booklet- and simulation-based breastfeeding training given starting from the antenatal period was effective in increasing breastfeeding self-efficacy, as well as in identifying and solving postpartum problems at an early stage.

PMID:42407201 | DOI:10.1016/j.nut.2026.113307

J Mech Behav Biomed Mater. 2026 Jun 27;182:107529. doi: 10.1016/j.jmbbm.2026.107529. Online ahead of print.

ABSTRACT

BACKGROUND: Virtual patient models require comprehensive knowledge of carotid tissue biomechanics across physiologically relevant deformation states and patient variation. This study aims to characterize the passive biomechanical behavior of the human common carotid artery (CCA) while incorporating the in situ axial pre-stretch, as well as exploring the effect of age, laterality, and sample orientation across CCA samples.

METHODS: Planar biaxial testing was performed on CCA segments from 10 human body donors (50% female; one young adult of 19 years and nine older adults of 78-98 years). A thick-walled Holzapfel-Gasser-Ogden constitutive model was fitted to the data and used to simulate inflation-extension experiments. Simulated inflation experiments incorporated the measured axial pre-stretch. Extension experiments explored the effect of axial stretching at constant pressure of 100 mmHg. Bilateral and regional (anterior-posterior and proximal-distal) differences were statistically compared at 60, 100 and 140 mmHg. Additionally, the effect of age was explored.

RESULTS: Minimal regional and bilateral differences were observed: the loaded inner diameter, circumferential stiffness and reduced axial force were larger in the right than in the left CCA, while axial material stiffness was larger in the left CCA. Circumferential stiffness was larger anteriorly than posteriorly at 60 mmHg. Aged human CCAs visually showed different mechanical behaviors than those from the young donor.

CONCLUSION: This study quantifies the passive mechanical properties of the human CCA under physiological loading conditions. Minimal bilateral and regional differences in mechanical behavior were shown. Samples from the young donor behaved distinctively differently, exemplifying the effect of ageing.

PMID:42407173 | DOI:10.1016/j.jmbbm.2026.107529

Ecotoxicol Environ Saf. 2026 Jul 6;322:120475. doi: 10.1016/j.ecoenv.2026.120475. Online ahead of print.

ABSTRACT

BACKGROUND: Evidence on the independent and interactive associations of green space and air pollution with novel blood lipid biomarkers remains limited. This longitudinal cohort study aimed to examine the independent and interactive associations of green space and air pollution exposure with blood lipid biomarkers.

METHODS: The study included 17,242 adults undergoing health examinations in Shijiazhuang, China (2021-2023). Linear mixed-effects models estimated associations of green space and air pollution exposure with blood lipid biomarkers, including the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and the atherogenic index of plasma (AIP). Interaction terms, restricted cubic splines, and mediation analyses evaluated interaction effects, nonlinear exposure-response relationships, and mediation effects.

RESULTS: Associations with green space were most pronounced within the 500-m buffer. Each one-standard deviation (SD) increase in NDVI was associated with lower NHHR (β = -0.103; 95% CI: -0.114, -0.091) and AIP (β = -0.009; 95% CI: -0.012, -0.006). Among air pollutants, PM₂.₅ showed a stronger positive association with NHHR (β = 0.085 per SD; 95% CI: 0.081, 0.089), whereas PM₁₀ exhibited a stronger association with AIP (β = 0.006 per SD; 95% CI: 0.005, 0.007). Significant interactions were observed between NDVI and multiple air pollutants for both biomarkers (P_interaction < 0.05). Air pollution mixture indices statistically mediated part of the associations between green space exposure and NHHR (13.5%) and AIP (34%).

CONCLUSION: Green space exposure was associated with more favorable lipid biomarkers, whereas air pollution showed adverse associations. Green space is associated with weaker air pollution-related dyslipidemia.

PMID:42407152 | DOI:10.1016/j.ecoenv.2026.120475

Auris Nasus Larynx. 2026 Jul 6;53(4):612-616. doi: 10.1016/j.anl.2026.06.010. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the prevalence of dental-origin pathologies and dentally related anatomical variants in patients with unilateral chronic rhinosinusitis with or without nasal polyposis undergoing surgical treatment and to explore their association with unilateral nasal polyposis.

MATERIALS AND METHODS: This prospective study included 107 patients who underwent endoscopic sinus surgery for medically refractory unilateral chronic rhinosinusitis with or without nasal polyposis treated at our institution between January 2024 and March 2025. Patients with a history of previous sinus surgery or malignant disease were excluded. Detailed current and past dental histories were obtained from all patients. Preoperative paranasal sinus computed tomography and magnetic resonance imaging were evaluated for radiological signs possibly related to odontogenic pathology such as periapical lucency, mucosal thickening, or oroantral fistula as well as for anatomical variants such as dental root protrusion into the maxillary sinus. Intraoperatively, pathological specimens were obtained from all patients for histopathological examination. The data were statistically analyzed.

RESULTS: Of the 107 patients analyzed, 25 (23%) reported a history of dental disease or intervention involving the adjacent tooth. Periapical radiolucency was identified in 67 patients (63%) and oroantral fistulas in seven patients (6%). Seventy-eight patients (73%) demonstrated radiological evidence of mucosal thickening. Among the 78 patients with radiological findings suggestive of odontogenic involvement, the most common histopathological findings were unilateral inflammatory sinonasal polyps in 41 patients (53%) and chronic inflammatory changes consistent with sinusitis in 26 patients (33%). Antrochoanal polyps were identified in four patients (5%). These findings indicate frequent coexistence of odontogenic and inflammatory sinonasal findings in unilateral disease. Exploratory comparative analysis showed no statistically significant difference in the prevalence of odontogenic findings between patients with unilateral nasal polyposis and those with non-polyp pathologies (Fisher’s exact test, p = 0.829).

CONCLUSION: Dental-origin pathologies and related anatomical variants appear to be encountered in patients with unilateral chronic rhinosinusitis. These findings suggest a possible association between odontogenic findings and unilateral sinus disease with or without nasal polyposis. A comprehensive dental evaluation and detailed radiological assessment should be considered as part of the preoperative workup. Furthermore, the observed coexistence of unilateral polyposis and odontogenic findings warrants further investigation to clarify the nature of this association.

PMID:42407144 | DOI:10.1016/j.anl.2026.06.010

Int Dent J. 2026 Jul 6;76(5):109697. doi: 10.1016/j.identj.2026.109697. Online ahead of print.

ABSTRACT

OBJECTIVE: This study aimed to assess the accuracy of intraoral scanning (IOS) for postoperative implant position evaluation in comparison with cone-beam computed tomography (CBCT) across different partially edentulous patterns.

MATERIALS AND METHODS: We retrospectively analysed 172 patients who underwent implant placement between January 2020 and January 2025. Patients were classified into six clinical subgroups according to edentulous configuration. Nonfree-end patterns were defined as tooth-bounded edentulous spaces with remaining teeth on both sides, whereas free-end patterns lacked a distal tooth-supported reference. IOS- and CBCT-derived postoperative implant positions were compared using shoulder and apical deviations, buccolingual, mesiodistal, and vertical components, and angular deviations.

RESULTS: A total of 172 patients with 278 implants were included. The within-group analysis indicated no statistically significant difference between IOS and CBCT measurements in the single tooth and nonfree-end subgroup (Group A). Conversely, the free-end subgroups (Groups B, C, and F) exhibited greater deviations, particularly the unilateral multiple-tooth free-end subgroup (Group C), which demonstrated a significantly different buccal-lingual angular deviation (P < .05). Between-group comparisons confirmed greater discrepancies in free-end than in nonfree-end patterns. Vertical and apical deviations contributed most prominently to subgroup differentiation. The findings from linear discriminant analysis and leave-one-out cross-validation indicated that there was overlap in the deviation performance across edentulous patterns. Nevertheless, vertical displacement, particularly apical deviation, emerged as the most significant indicator for differentiating the characteristic deviations associated with each group.

CONCLUSION: IOS showed better concordance with CBCT in nonfree-end edentulous patterns than in free-end patterns. However, greater variability in free-end cases, particularly in apical and angular measurements, indicates that IOS-based postoperative assessment should be interpreted according to the clinical edentulous pattern. These findings suggest a promising but indication-dependent clinical application of IOS for postoperative implant position assessment.

PMID:42407141 | DOI:10.1016/j.identj.2026.109697

Brief Bioinform. 2026 Jul 3;27(4):bbag368. doi: 10.1093/bib/bbag368.

ABSTRACT

Ferroptosis is a novel form of programmed cell death driven by iron-dependent lipid peroxidation, and can significantly influence the progression of complex diseases such as cancer. Current methods of detecting ferroptosis rely primarily on experimental techniques that are typically low-throughput and costly, limiting their clinical applications. Here we develop an effective statistical method, FerroScore, to quantify ferroptosis by generating a score that integrates the activities of three core pathways-iron, glutathione, and lipid metabolism. This method enables the cross-resolution assessment of ferroptosis and provides mechanistic insights into tumor, immune, and neurodegenerative diseases, thus having potential applications in targeted therapy and drug discovery. When applied to pancreatic cancer transcriptomic data, FerroScore reveals: (i) a U-shaped relationship between ferroptosis and patient survival; (ii) heterogeneous ferroptosis activity across cell types in the tumor microenvironment, with high sensitivity to Macrophages, CD8 Tcm cells, and a population of nCAFs; (iii) the role of ferroptosis-active cells in reshaping the immunosuppressive and pro-metastatic microenvironment through intercellular communication.

PMID:42407120 | DOI:10.1093/bib/bbag368

Brief Bioinform. 2026 Jul 3;27(4):bbag364. doi: 10.1093/bib/bbag364.

ABSTRACT

Accurate identification of causal exposures for multimorbidity can benefit the co-prevention and co-management of multiple-related outcomes. This goal can be conceptually addressed within a multi-outcome Mendelian randomization (MR) framework. However, existing multi-outcome MR methods suffer from restrictions on format and availability of data inputs, fail to account for the potential sample overlap, rely on pre-selected independent instrumental variables (IVs), and are unable to account for horizontal pleiotropy. Here, we propose METEOR, a novel MR method that jointly models one exposure and multiple outcomes to identify both shared and outcome-specific causal exposures. METEOR accounts for sample overlap between exposure and outcomes, allows outcomes from different genome-wide association studies (GWAS) datasets, self-adaptively determines IVs from correlated single-nucleotide polymorphisms, and explicitly models horizontal pleiotropy. Using summary statistics, METEOR infers causal effects under a joint-likelihood framework with a scalable, sampling-based algorithm. Simulations show that METEOR presents well-calibrated $P$-values for both global and single-outcome tests, and achieves average power improvements of 55.33% and 56.50% over five existing MR methods in the global and single tests, respectively. In real data applications, METEOR produces the most accurate causal effect estimates in positive control analyses, reduces false positives by 18.75% in negative control analyses, and highlights that controlling BMI could benefit the co-management of multiple cardiovascular diseases (CVDs) and multiple gastrointestinal (GI) diseases, while controlling blood pressure could benefit the co-management of multimorbidity across CVDs and mental disorders (MDs), as well as across GI diseases and MDs.

PMID:42407119 | DOI:10.1093/bib/bbag364

Rev Esc Enferm USP. 2026 Jul 6;60:e20250511. doi: 10.1590/1980-220X-REEUSP-2025-0511en. eCollection 2026.

ABSTRACT

OBJECTIVE: To analyze the correlation between the intensity of physical symptoms and overall comfort levels in hospitalized cancer patients receiving palliative care.

METHOD: This quantitative, descriptive, and analytical study was conducted with 155 patients admitted to palliative care units at a university hospital. The General Comfort Questionnaire (GCQ) and the Edmonton Symptom Assessment Scale (ESAS) were used. Data were analyzed using descriptive and inferential statistics, employing Pearson’s correlation (p ≤ 0.05).

RESULTS: The ESAS symptom assessment revealed a high symptomatic burden, with anxiety, loss of appetite, and depression standing out as the symptoms with the highest average intensity. A statistically significant negative correlation was found between the intensity of most symptoms and overall comfort, indicating that increased symptom burden was associated with reduced comfort.

CONCLUSION: The increased intensity of physical symptoms is associated with a significant reduction in overall comfort, reinforcing the importance of effective strategies for managing these symptoms in palliative nursing practice.

PMID:42407084 | DOI:10.1590/1980-220X-REEUSP-2025-0511en

J Med Internet Res. 2026 Jul 6;28:e95547. doi: 10.2196/95547.

ABSTRACT

BACKGROUND: Generative artificial intelligence (GenAI) can automate time-intensive tasks and support clinical decision-making in care settings. Nurses require appropriate competencies to ensure that integration of GenAI strengthens care quality and patient safety. However, validated literacy assessment tools remain limited. In particular, instruments tailored to nurses’ role-specific GenAI competencies, including hallucination detection, risk identification, and ethical accountability, are lacking. These gaps highlight the need for a nurse-specific GenAI literacy scale.

OBJECTIVE: This study aimed to develop and psychometrically validate the Generative Artificial Intelligence Literacy Scale for Nurses (GenAILS).

METHODS: We conducted a two-phase, cross-sectional online survey of registered nurses nationwide in Taiwan between June 2025 and October 2025. Phase 1 involved conceptualization and item generation based on a literature review, followed by content appraisal through expert discussion with 6 external reviewers. A 50-item pool was generated. Subsequently, 5 external reviewers evaluated content validity. Items with a content validity index of <0.78 or flagged for revision were revised or deleted. Phase 2 evaluated psychometric properties (item analysis, internal consistency, split-half reliability, and criterion-related validity) and construct validity via exploratory factor analysis (factor loading ≥0.60), followed by confirmatory factor analysis (CFA). The total sample was randomly split into 2 independent subsamples for exploratory factor analysis and CFA.

RESULTS: In phase 1, the initial 50 items underwent expert content validation and were revised to 46 items (scale content validity index based on the average method=0.92). In phase 2, 1313 questionnaires were collected, of which 191 invalid responses were excluded; 1122 valid responses were analyzed. Participants had a mean age of 34.66 (SD 7.8) years. Extreme-group comparison revealed statistically significant differences for each item (P<.001). The final scale comprised 24 items across six dimensions: responsible use, updated competencies, risk identification, fundamental knowledge, critical evaluation, and ethics and law. The cumulative variance explained was 53.1%. The first-order CFA demonstrated excellent model fit: root-mean-square error of approximation=0.035, standardized root-mean-square residual=0.032, comparative fit index=0.99, goodness-of-fit index=0.94, adjusted goodness-of-fit index=0.93, nonnormed fit index=0.99, and parsimony normed fit index=0.84. The second-order CFA demonstrated excellent model fit: root-mean-square error of approximation=0.039, standardized root-mean-square residual=0.040, comparative fit index=0.99, goodness-of-fit index=0.94, adjusted goodness-of-fit index=0.92, nonnormed fit index=0.99, and parsimony normed fit index=0.87. All heterotrait-monotrait ratio values were below 0.85, supporting discriminant validity. The scale was moderately correlated with the Short Form Meta-AI Literacy Scale (r=0.57; P<.001). Reliability was excellent (Cronbach α=0.92; McDonald ω=0.92; split-half reliability=0.81).

CONCLUSIONS: The GenAILS is a concise, nurse-specific self-report instrument with good psychometric properties across 6 clinically relevant domains. It supports needs assessment, targeted training, and intervention evaluation to promote the safe and ethical use of GenAI in nursing.

PMID:42407060 | DOI:10.2196/95547

J Med Internet Res. 2026 Jul 6;28:e93631. doi: 10.2196/93631.

ABSTRACT

BACKGROUND: Most studies examining internet use and health outcomes in older adults rely on cross-sectional designs and binary exposure measures, which are insufficient to capture the multidimensional nature of health-related digital engagement over time. The high collinearity between digital engagement and socioeconomic factors makes it challenging to disentangle independent effects from marker effects. Longitudinal evidence linking health-related digital engagement to incident stroke remains limited.

OBJECTIVE: This study aimed to examine the longitudinal association between a composite Health-Related Digital Engagement Index (HDEI) and incident stroke among community-dwelling older adults, and to quantify the extent to which socioeconomic factors account for this association.

METHODS: This prospective cohort study used data from the National Health and Aging Trends Study, Waves 1-10 (2011-2020). The HDEI (range 0-4) was constructed from 4 health-related internet behaviors assessed at baseline. The primary outcome was incident stroke ascertained by self- or proxy-reported physician diagnosis. Discrete-time hazard models with a complementary log-log link were fitted across 4 nested models, progressively adjusting for demographics, socioeconomic factors, chronic disease burden, functional disability, and social isolation.

RESULTS: Among 5384 participants followed for a median of 5 (IQR 2-9) years, 472 incident stroke events were observed; 81.6% (4395/5384) had an HDEI score of 0, 10.5% (566/5384) had a score of 1, and 7.9% (423/5384) had a score of 2 or higher. In the unadjusted model, each 1-point increase in HDEI was associated with a lower risk of stroke (hazard ratio [HR] 0.76, 95% CI 0.66-0.88; P<.001). After adjustment for age and sex, the association was attenuated but remained statistically significant (HR 0.84, 95% CI 0.72-0.96; P=.01). After further adjustment for race or ethnicity, education, and household income, the association was no longer statistically significant (HR 0.92, 95% CI 0.79-1.06; P=.23); fully adjusted analyses yielded similar results (HR 0.91, 95% CI 0.79-1.05; P=.21). Subgroup patterns observed in demographically adjusted analyses were attenuated after socioeconomic adjustment, and no statistically significant interaction remained in the primary model 3 framework. Sensitivity analyses showed similar patterns of attenuation.

CONCLUSIONS: Greater health-related digital engagement was associated with a lower risk of incident stroke in unadjusted and demographically adjusted models; however, this association was substantially attenuated and was no longer statistically significant after adjustment for socioeconomic factors. These findings are consistent with socioeconomic confounding and suggest that health-related digital engagement may, at least in part, reflect broader socioeconomic advantage among older adults. Future studies should further examine whether digital engagement has an independent role in stroke prevention beyond the socioeconomic and structural determinants of health.

PMID:42407050 | DOI:10.2196/93631