Nevin Manimala

J Eval Clin Pract. 2026 Aug;32(5):e70520. doi: 10.1111/jep.70520.

ABSTRACT

OBJECTIVE: This study addresses the common misconception that larger sample sizes inevitably produce smaller P-values and higher statistical power, using Monte Carlo simulations to examine the effect of sample size under scenarios with and without a true effect.

METHODS: Monte Carlo simulations were performed with 1000 iterations for each of 11 sample sizes per group (n = 5-800). Two scenarios were simulated: (1) both groups drawn from the same normal distribution (μ = 4.5, σ = 0.5; null hypothesis H₀ true), and (2) groups drawn from different normal distributions (μ₁ = 4.5, σ = 0.5; μ₂ = 4.4, σ = 0.5; alternative hypothesis H₁ true). For each iteration, the absolute mean difference (|X̅₁ – X̅₂|), standard error (S_e), t-test p-value and the proportion of significant results (p < 0.05) were calculated. This proportion was interpreted as the Type I error rate or statistical power, depending on the scenario.

RESULTS: When a true effect existed, increasing sample size led to a marked rise in statistical power, with the proportion of significant results increasing from 5.4% to 98.1%. In contrast, when no true effect existed, p-values remained uniformly distributed across all sample sizes, and the frequency of p < 0.05 consistently approximated the nominal 5% significance level. Importantly, increasing sample size under the null hypothesis did not increase the likelihood of detecting significance.

CONCLUSION: Larger sample sizes do not create statistical significance in the absence of a true effect; they only enhance the detection of effects that genuinely exist. Study design and statistical interpretation should therefore be guided by effect size and clinical relevance rather than by sample size alone.

PMID:42472374 | DOI:10.1111/jep.70520

Lancet Reg Health Am. 2026 Jul 10;61:101542. doi: 10.1016/j.lana.2026.101542. eCollection 2026 Sep.

ABSTRACT

BACKGROUND: Individuals with psychosis face persistent barriers to care. Peru’s recent mental health reform expanded services nationwide but coincided with the COVID-19 pandemic. We hypothesized that service utilization among individuals with psychosis would increase between 2018 and 2024, particularly in underserved regions.

METHODS: We analyzed outpatient morbidity data from the Peruvian National Superintendence of Health (2018-2024). Sex was available as binary male/female coding; gender identity and race/ethnicity data were not available. Service utilization was compared across three groups: psychosis, non-psychotic mental disorders, and general medical conditions. We examined changes in access (rate ratios, rate differences), the impact of the pandemic (interrupted time series), and decentralization trends (Poisson regression), separately for each disorder group.

FINDINGS: In 2024 compared with 2018, monthly service utilization per 100,000 declined for psychosis (28.2 in 2018-19.2 in 2024; rate ratio 0.68), rose for non-psychotic mental disorders (225.2 in 2018-304.6 in 2024; 1.35), and slightly fell for general medical conditions (12,688.1 in 2018-12,370.4 in 2024; 0.97). The pandemic caused a comparable immediate drop in service utilization, with rates falling to 37.9%, 37.0%, and 35.3% of expected levels for the three groups in March 2020, followed by gradual monthly increases (psychosis 1.3%, non-psychotic mental disorders 2.6%, general medical conditions 2.2%). A shift from tertiary to primary and regional facilities was seen for both mental disorder groups, but greater utilization in underserved regions was observed only for non-psychotic mental disorders.

INTERPRETATION: Despite nationwide expansion of mental health services, individuals with psychosis did not experience higher service use. The pandemic’s impact was acute and enduring for this group. Findings underscore the need to examine reasons for this stagnation in service utilization and evaluate the acceptability and appropriateness of Peru’s current service model for psychosis.

FUNDING: Canadian Institutes of Health Research, Canada Research Chairs program.

PMID:42472313 | PMC:PMC13380218 | DOI:10.1016/j.lana.2026.101542

EClinicalMedicine. 2026 Jul 9;97:104047. doi: 10.1016/j.eclinm.2026.104047. eCollection 2026 Jul.

ABSTRACT

BACKGROUND: Psychosocial oncology (PSO) is essential to comprehensive cancer care, yet access and delivery remain inconsistent and inadequate globally. This study mapped patient- and provider-reported experiences of barriers shaping PSO access globally.

METHODS: Cross-sectional, web-based surveys were administered separately to adults with a self-reported cancer diagnosis and to oncology healthcare providers (HCPs) in five languages between November 12, 2024 and April 25, 2025. Descriptive statistics and multivariable logistic regressions examined associations between sociodemographic and clinical factors with PSO access, perceptions, and delivery.

FINDINGS: The final sample included 200 patients from 16 countries and 237 HCPs from 38 countries. Among patients, 85.0% rated PSO care as highly important, with 81.0% considering it as important as biomedical care, yet 63.5% reported receiving no PSO care. Among HCPs, 53.2% indicated PSO is not routinely provided at their institutions. Mental health stigma and cultural norms affecting comfort discussing emotional concerns were commonly reported barriers, reported by 57.0% and 64.0% of patients, respectively, and 52.7% and 74.3% of HCPs. Workforce and training gaps were substantial, with 66.6% of HCPs reporting insufficient specialized staff, and 42.1% reporting no formal training in PSO. Investment in PSO research was perceived as low, with 60.3% of HCPs estimating that <10% of national cancer research funding was allocated to PSO and 69.6% viewing overall research support as insufficient.

INTERPRETATION: Patients and providers emphasized the importance of PSO; however, PSO was reported to be under-delivered worldwide due to stigma, cultural factors, workforce and training limitations, and insufficient research investment. System-level strategies are needed to address these challenges and close the global PSO care gap.

FUNDING: This study was supported by a seed grant from the Global Institute of Psychosocial, Palliative and End-of-Life Care (GIPPEC), Toronto, Canada.

PMID:42472281 | PMC:PMC13380114 | DOI:10.1016/j.eclinm.2026.104047

JCPP Adv. 2026 Jul 18:e70148. doi: 10.1002/jcv2.70148. Online ahead of print.

ABSTRACT

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) and language/reading difficulties frequently co-occur. The extent of shared genetic architecture remains incompletely defined. We investigated genome-wide overlap between ADHD and four core skills: word reading, nonword reading, spelling, and phoneme awareness.

METHODS: We integrated genome-wide association study (GWAS) summary statistics from the Psychiatric Genomics Consortium for ADHD (38,691 cases; 186,843 controls) and from the GenLang Consortium for language-related traits (n = 13,633-33,959). We performed linkage disequilibrium score regression (LDSC) to estimate genetic correlations and stratified LDSC to identify enriched genomic annotations. Cross-trait meta-analyses were conducted using MTAG and CPASSOC to identify cross-trait association signals. Mendelian randomization (MR) was applied to assess potential directional relationships.

RESULTS: Genome-wide genetic correlations were negative and significant between ADHD and each reading- and language-related trait (word reading rg = -0.35, p = 1.35 × 10^-16; nonword reading rg = -0.28, p = 2.15 × 10^-9; spelling rg = -0.38, p = 1.03 × 10^-15; phoneme awareness rg = -0.28, p = 2.64 × 10^-6). Partitioned heritability analysis using S-LDSC showed significant enrichment after Benjamini-Hochberg false discovery rate correction (BH-FDR), concentrated in conserved or constrained annotations such as Genomic Evolutionary Rate Profiling and phastCons. Cross-trait analyses (MTAG and CPASSOC) identified loci associated with ADHD and each skill, 6 for word reading, 7 for spelling, 7 for phoneme awareness, and 4 suggestive loci for nonword reading (dual-method p < 5 × 10^-6); several map near neurodevelopmental genes including DCC, MEF2C, and ST3GAL3. Bidirectional MR findings were consistent with a potential directional contribution of ADHD genetic liability to poorer reading/language performance, with no clear evidence supporting the reverse direction under standard MR assumptions.

CONCLUSION: ADHD and language/reading abilities share a substantial polygenic overlap with convergent signals in neuronal regulatory annotations. These genome-wide findings support a transdiagnostic framework linking attention and literacy-related skills, while indicating that causal and clinical interpretations should remain cautious given the modest effect sizes and limited variance captured by current GWAS resources.

PMID:42472273 | PMC:PMC13379746 | DOI:10.1002/jcv2.70148

J Oral Biol Craniofac Res. 2026 Jul-Aug;16(4):101494. doi: 10.1016/j.jobcr.2026.101494. Epub 2026 Jul 11.

ABSTRACT

INTRODUCTION: Temporomandibular joint (TMJ) is a complex synovial joint commonly affected by temporomandibular disorders (TMDs), with disc displacement being the most prevalent subtype. Magnetic resonance imaging (MRI) is the gold standard for TMJ evaluation, offering superior soft tissue contrast and non-invasive assessment of disc position and morphology.

AIM AND OBJECTIVES: To evaluate the diagnostic value of MRI in the preclinical detection of TMJ disc displacement, determine the prevalence of unilateral and bilateral displacement patterns and compare disc position and TMJ anatomical variables between normal and abnormal disc positions in the closed-mouth position.

METHODOLOGY: This retrospective cross-sectional study analyzed 214 MRI scans of patients aged 13-70 years using high-quality sagittal closed-mouth TMJ sections. Disc thickness, Disc area and Articular eminence inclination (AEI) were assessed by a TMD-trained specialist. Descriptive statistics, Chi-square and Mann-Whitney U tests were applied, with significance set at p < 0.05.

RESULTS: After excluding poor-quality scans, 214 participants (428 TMJs; mean age 45.8 years; 61.2% male) were analyzed. Abnormal disc position was present in 61.7% of TMJs, mainly anterior displacement (57.5%) and was associated with increased disc thickness, reduced disc area and flatter AEI (p < 0.001). Symptomatic individuals exhibited thicker discs and reduced AEI (p < 0.05), with no gender differences. Abnormal disc position showed a significant association with TMJ symptoms (p = 0.049).

CONCLUSION: MRI can characterize TMJ disc position and morphology on closed-mouth sagittal sections and frequently identified anterior displacement even in asymptomatic individuals, highlighting its value in early and preclinical diagnosis.

PMID:42472270 | PMC:PMC13380457 | DOI:10.1016/j.jobcr.2026.101494

Drug Alcohol Depend Rep. 2026 Jun 22;20:100459. doi: 10.1016/j.dadr.2026.100459. eCollection 2026 Sep.

ABSTRACT

BACKGROUND: Cardiovascular disease (CVD) risk prediction tools have not been developed or validated for adults who use nonmedical stimulants (cocaine or methamphetamine), despite substantially elevated event rates and pathophysiologically distinct risk profiles in this population. Accurate estimation of absolute risk is needed to support individualized clinical decision-making.

METHODS: We developed a 3-year CVD risk prediction model using a cohort of 6940 adults aged 18-79 with documented stimulant use, identified from electronic health record (EHR) data of a large academic hospital system spanning 2016-2024. Type of stimulants used was a candidate predictor, alongside demographic characteristics, cigarette smoking status, systolic blood pressure, and baseline cardiovascular medications. Variable selection used least absolute shrinkage and selection operator (LASSO) with 10-fold cross-validation, followed by unpenalized logistic regression on selected variables. Model performance was assessed using discrimination and calibration metrics; bootstrap internal validation estimated and corrected for optimism in apparent performance.

RESULTS: LASSO selected 8 predictors: age, sex, Black race, Hispanic ethnicity, current cigarette smoking, cocaine-only use, any cardiovascular medication use, and systolic blood pressure. Calibration was excellent. Observed and predicted 3-year event rates were 29.6% and 30.1%, respectively (observed/expected [O/E] ratio 0.985, calibration slope 1.000, integrated calibration index [ICI] 0.008). Performance was maintained after optimism correction: O/E ratio 0.988, calibration slope 0.992, ICI 0.010. The apparent C-statistic was 0.730 (95% CI 0.717-0.743); the optimism-corrected C-statistic was 0.728. For illustration, a 45-year-old Black adult with cocaine use, current cigarette smoking, and systolic blood pressure of 130 mmHg has an estimated 3-year CVD risk of approximately 27.7%; the same profile with methamphetamine use yields approximately 22.1%.

CONCLUSIONS: A CVD risk prediction model tailored to individuals with stimulant use accurately estimated absolute 3-year CVD risk, with excellent calibration and clinically meaningful risk stratification. These findings establish proof of concept for a stimulant-specific CVD risk prediction tool. External validation and implementation studies are needed before clinical deployment.

PMID:42472268 | PMC:PMC13380514 | DOI:10.1016/j.dadr.2026.100459

Adv Radiat Oncol. 2026 May 30;11(11):102086. doi: 10.1016/j.adro.2026.102086. eCollection 2026 Nov.

ABSTRACT

PURPOSE: Intraoperative radiation therapy (IORT) with electrons is associated with higher rates of ipsilateral breast tumor recurrence in early-stage breast cancer than whole-breast external beam radiation therapy (EBRT). Although limited randomized and retrospective data suggest that this approach may suit a subset of patients, its role remains uncertain. This study aimed to compare oncological outcomes between technically optimal IORT with electrons and whole-breast EBRT in suitable patients with breast cancer.

METHODS AND MATERIALS: In this single-center retrospective cohort study, patients were grouped by radiation treatment: IORT with electrons or whole-breast EBRT. Endpoints included disease-free survival (DFS), local control, and breast cancer-specific survival (BCSS).

RESULTS: From January 2011 to December 2021, 204 eligible patients were reviewed (IORT, 74; EBRT, 130). The median follow-up was 5.1 years. The 5-year DFS rates were 95.61% for IORT and 98.08% for EBRT (log-rank P = .02). The 5-year local control rates were 98.46% for IORT and 100% (no event) for EBRT (log-rank P = .07). The 5-year BCSS rates were comparable: 98.61% for IORT and 100% (no event) for EBRT (log-rank P = .23). On univariable analysis for DFS, receipt of systemic treatment was a statistically significant protective factor (hazard ratio, 0.09; 95% CI, 0.01-0.74). Receipt of whole-breast EBRT was associated with a reduced risk of events, although this did not reach statistical significance (hazard ratio, 0.12; 95% CI, 0.02-1.01).

CONCLUSIONS: IORT with electrons was associated with a modest but statistically significant reduction in 5-year DFS in appropriately selected patients compared with whole-breast EBRT, whereas BCSS remained comparable between groups. Therefore, electron-based IORT should be approached with caution and reserved for patients who prioritize treatment convenience.

PMID:42472265 | PMC:PMC13380423 | DOI:10.1016/j.adro.2026.102086

Patient Prefer Adherence. 2026 Jul 14;20:619080. doi: 10.2147/PPA.S619080. eCollection 2026.

ABSTRACT

PURPOSE: This cross-sectional study aimed to investigate factors influencing healthcare-seeking delays among Chinese residents using the Andersen Model of Total Patient Delay and the Behavioral Model of Health Services Use.

METHODS: A self-designed questionnaire was developed by integrating the two theoretical frameworks. A cross-sectional survey was conducted from July to September 2022 among Chinese residents aged 16 years and older. Stratified sampling was employed across three economic development strata, with trained investigators conducting face-to-face interviews using a standardized electronic questionnaire. Descriptive statistics, one-way ANOVA, and multiple linear regression were used to analyze delay patterns and influencing factors.

RESULTS: The study included 580 participants, with 312 (53.79%) experienced healthcare-seeking delays. The total delay was 5.63 (± 11.95) days. Age, interpersonal manner, and social networks showed significant positive associations with total delay (p < 0.05). Female gender, inadequate communication, and self-medication were associated with longer delays.

CONCLUSION: The findings suggest that targeted interventions-including priority care pathways for at-risk groups, public education on appropriate care-seeking, and patient-centered facility design-may help reduce healthcare-seeking delays.

PMID:42472261 | PMC:PMC13380277 | DOI:10.2147/PPA.S619080

Curr Res Food Sci. 2026 Jul 7;13:101492. doi: 10.1016/j.crfs.2026.101492. eCollection 2026.

ABSTRACT

Human milk (HM) provides essential nutrients for infant growth and development. When own mother’s milk is unavailable, donor human milk (DHM) is used and typically pasteurized, which may alter protein integrity. This study presents the use of external cavity-quantum cascade laser (EC-QCL) mid-infrared spectroscopy, as a rapid, non-destructive technique, to quantify both individual and total proteins in 276 HM and DHM samples. The method showed high accuracy (≥84% explained variance) and strong correlation with reference techniques. Pasteurization significantly reduced α-lactalbumin (24%) and lactoferrin (14%), while casein and total protein declined slightly (3%). Protein levels decreased notably during early lactation, then stabilized. In the cohort of the present study, no statistically significant differences in protein content were observed between preterm and term milk. EC-QCL spectroscopy also differentiated raw and pasteurized DHM. These results support EC-QCL as a reliable tool for clinical use and quality control, with implications for improving processing methods to preserve the nutritional and immunological integrity of DHM.

PMID:42472244 | PMC:PMC13380451 | DOI:10.1016/j.crfs.2026.101492

Brain Behav Immun Health. 2026 Jul 6;56:101299. doi: 10.1016/j.bbih.2026.101299. eCollection 2026 Oct.

ABSTRACT

INTRODUCTION: Myalgic Encephalomyelitis (ME)/Chronic Fatigue Syndrome (CFS) is a debilitating condition characterized by severe fatigue and post-exertional malaise (PEM). Reported neuropsychophysiological abnormalities suggest ME/CFS is multifactorial, but current knowledge remains fragmented. This study protocol outlines a multimodal investigation designed to (1) compare neuropsychophysiological mechanisms between ME/CFS patients and healthy participants, (2) test an integrative model of ME/CFS, (3) identify neuropsychophysiological subgroups within the patient population, and (4) identify predictors of symptom response during rehabilitation.

METHODS AND ANALYSIS: This study will enroll 115 ME/CFS patients and 55 healthy participants. Groups will be comparable in age, sex, and education level, with a larger patient sample enabling subgroup and longitudinal analyses. A cross-sectional assessment at baseline will be carried out in both groups. Patients will then be evaluated longitudinally throughout a standardized cognitive-behavioral therapy rehabilitation program delivered as routine care. Baseline measures include systemic inflammation and general health biomarkers, measures of autonomic and central nervous system function, neuroinflammation (magnetic resonance spectroscopy, [¹⁸F]DPA714 PET in a subsample), serum short-chain fatty acid levels, gut microbiota composition and function, and neuroendocrine and self-reported responses to psychosocial stress. Fatigue severity (physical and cognitive) and PEM will be assessed through validated questionnaires, ecological momentary assessment, and laboratory tasks. These will be re-evaluated during therapy, and all non-neuroimaging measures will be repeated after the rehabilitation program. Statistical analyses will comprise multivariate analysis of variance, general linear models, classification algorithms, structural equation models, least absolute shrinkage selection operator principal component regression (LASSO-PCR), cluster analysis and latent class growth analysis (LCGA).

PMID:42472232 | PMC:PMC13380062 | DOI:10.1016/j.bbih.2026.101299