Tag: pubmed

Online J Public Health Inform. 2026 Aug 7;18:e97291. doi: 10.2196/97291.

ABSTRACT

BACKGROUND: Financial toxicity can contribute to adverse health and care-access outcomes among US veterans, yet scalable methods to identify individuals at elevated risk remain limited. Public health informatics frameworks may enable the translation of patient-reported financial risk signals into streamlined screening, risk stratification, and care-navigation workflows.

OBJECTIVE: This study aimed to examine concept-level indicators of financial literacy and financial toxicity among US veterans and explore how these findings could inform future informatics-enabled screening strategies for identifying subgroups at increased risk of health-related financial strain.

METHODS: We conducted an exploratory cross-sectional survey of 88 US veterans from 2024 to 2025. Financial literacy was assessed using 3 benchmark items from the National Financial Capability Study. Financial toxicity was assessed using items aligned with domains reflected in the Comprehensive Score for Financial Toxicity framework, including difficulty affording care, reduced or quit work, borrowing money or using savings for care, and treatment-adherence impact. Analyses included descriptive statistics, Fisher exact tests, unadjusted logistic regression, and a minimally adjusted sensitivity model for work disruption, controlling for age and education.

RESULTS: Female veterans had lower rates of high financial literacy than male veterans (15/29, 52% vs 48/59, 81%; P=.006) and lower correct-response rates on compound interest (10/29, 35% vs 36/59, 61%; P=.02) and inflation (14/29, 48% vs 43/59, 73%; P=.03). Black veterans had lower correct-response rates than non-Black veterans on inflation (11/24, 46% vs 46/64, 72%; P=.03) and retirement strategy (15/24, 63% vs 56/64, 88%; P=.014), although composite high-literacy rates did not differ significantly by race. In unadjusted models among participants with complete outcome data (n=75), lower financial literacy was directionally associated with higher odds of all 4 financial toxicity outcomes, with the clearest association observed for work disruption (odds ratio 0.56 per 1-point increase in financial literacy score, 95% CI 0.33-0.95; P=.03). Black female veterans reported elevated financial toxicity across multiple domains. Financial support program use was low overall (29%).

CONCLUSIONS: These findings suggest that financial literacy may be a marker of vulnerability to financial toxicity among veterans, but observed associations should be regarded as preliminary and hypothesis-generating. The results identify concept-level financial literacy domains and work disruption as candidate signals for future screening evaluation. Future research should evaluate whether brief screening, financial literacy assessment, and benefit-navigation strategies improve identification, referral, adherence, and downstream financial and health-related outcomes in larger and more representative veteran populations.

PMID:42566768 | DOI:10.2196/97291

Traffic Inj Prev. 2026 Aug 7:1-7. doi: 10.1080/15389588.2026.2694621. Online ahead of print.

ABSTRACT

OBJECTIVE: Driver drowsiness is a critical factor in road accidents. This study aimed to model behavioral indicators of drowsiness using a driving simulator to support noninvasive detection systems.

METHODS: Twenty-four participants completed simulated driving tasks under varying alertness levels. Behavioral metrics including eye-blinking frequency, head movement acceleration, and eye movement variability were recorded. Drowsiness classification was performed using supervised Partial Least Squares Discriminant Analysis (PLS-DA), with the Karolinska Sleepiness Scale as the reference standard. Preprocessing steps included general mean-centering, pairwise mean-centering, and unit variance scaling.

RESULTS: Blink frequency significantly increased with drowsiness, while fluctuations in head movement acceleration and eye movements also rose, indicating reduced alertness. Derived variables such as Corrected Turning Ratio (CTR) showed predictive relevance, whereas angular velocity of head movement was not statistically significant. Model evaluation demonstrated strong performance (ROC AUC = 0.935), with low misclassification rates and acceptable residual normality.

CONCLUSIONS: Behavioral metrics provide practical predictive value for noninvasive drowsiness detection. Although limited by sample size, the model achieved meaningful separation between alertness and drowsiness. Future studies should expand sample size, incorporate additional behavioral indicators, and validate findings externally to strengthen predictive performance.

PMID:42566753 | DOI:10.1080/15389588.2026.2694621

Dev Med Child Neurol. 2026 Aug 7. doi: 10.1111/dmcn.70426. Online ahead of print.

ABSTRACT

AIM: To assess neurodevelopmental and neurological features, including neuroimaging abnormalities, in children with molecularly confirmed hypochondroplasia.

METHOD: A retrospective cohort study of children with molecularly confirmed hypochondroplasia seen at Evelina London Children’s Hospital skeletal dysplasia service was performed. Data collected included referral characteristics, neuroimaging findings, special educational needs, and diagnosed neurodevelopmental disorders. Statistical comparisons with UK population prevalence were performed using χ² testing for educational outcomes and exact binomial testing for neurodevelopmental disorders, with Bonferroni-adjusted p-values reported for multiple comparisons.

RESULTS: Forty-four children (24 females and 20 males; median age 9 years 10 months [interquartile range 6 years 7 months-15 years 7 months]) with molecularly confirmed hypochondroplasia were included. Twenty-five had received brain imaging with hippocampal malrotation (HIMAL) identified in 23 (92%). Among school-aged children, 71% required special educational support and 29% had formal education, health, and care plans (EHCPs), statistically higher than both UK population prevalence and previously reported hypochondroplasia prevalence. Formally diagnosed neurodevelopment disorders affected 20.5% of the cohort. Specific learning disorders remained significantly more common than UK population prevalence estimates after Bonferroni correction, with higher observed autism and attention-deficit/hyperactivity disorder rates also identified.

INTERPRETATION: Hypochondroplasia is associated with a substantial burden of neurodevelopmental and neurological abnormalities, including a high prevalence of HIMAL, which exceeds previous estimates. These findings support the need for clinical guidelines, developmental surveillance, and further research into fibroblast growth factor receptor 3 (FGFR3)-related brain development.

PMID:42566751 | DOI:10.1111/dmcn.70426

J Med Internet Res. 2026 Aug 7;28:e92183. doi: 10.2196/92183.

ABSTRACT

BACKGROUND: Multimodal large language models are increasingly used in radiological diagnosis, but their performance has not been systematically evaluated across volumetric (3D) imaging, real-world clinical versus public teaching cases, and bilingual contexts.

OBJECTIVE: The aim of the study is to develop a bilingual radiology benchmark and characterize the diagnostic performance of state-of-the-art multimodal large language models across input modality, clinical setting (public teaching vs routine clinical), disease rarity, and clinical-history language and to disentangle linguistic from clinical-content effects through a cross-linguistic control experiment.

METHODS: We constructed RadM-Bench, comprising 720 cases evenly distributed across 9 radiological subspecialties: 360 English public teaching cases enriched in rare diseases (RadEdu) and 360 Chinese routine clinical cases (RealClin). In total, 4 proprietary models (GPT-4o, O3, Gemini-2-Flash, and Gemini-2.5-Flash-Thinking) and 6 open-source models (Qwen2.5-VL-72B/7B, InternVL3-78B/8B, Llama-4-Scout-17B-16E, and MedGemma-4B) were evaluated under 4 input conditions: clinical history alone, history with radiologist-selected 2D key images, and history with volumetric data sampled at 2 and 10 frames per second (fps). Each response was scored on a 4-tier 0-3 diagnostic-quality rubric by 2 board-certified radiologists blinded to model identity. Mean scores with bias-corrected and accelerated bootstrap 95% CIs are reported. To disentangle language from clinical content, all 360 RealClin histories were translated into English and re-evaluated, with paired comparisons by Wilcoxon signed-rank tests and Benjamini-Hochberg false-discovery-rate correction.

RESULTS: Mean performance remained below 1.5 on the 0-3 scale for all 10 models on both datasets. Adding radiologist-selected 2D key images to clinical history improved performance in all 10 models (+19.8% to +139.2%). In RealClin at fps=10, all 8 evaluable models scored lower with volumetric input than with the 2D-image baseline (-5.3% to -31.4%); MedGemma-4B and Llama-4-Scout-17B-16E could only be evaluated at fps=2 due to context-window and graphics processing unit-memory constraints. At fps=2, a total of 8 out of 10 models declined (-6.8% to -28.6%), while Qwen2.5-VL-7B and InternVL3-8B showed marginal improvements (+2.4% and +2.1%). Cross-dataset transfer diverged by model category: proprietary models declined from RadEdu to RealClin (eg, O3 with images: 1.14 to 0.79), whereas Chinese-centric open-source models improved (eg, InternVL3-78B: 0.48 to 0.75). The rare-disease premium observed in 9 out of 10 models in RadEdu reversed in RealClin, where common-disease scores exceeded rare-disease scores in 7 out of 10 models under history-only input. Translating RealClin histories into English produced a numerical decrease in mean score for all 10 models, which were statistically significant in 9 out of 10 models after false discovery rate correction, excluding a Chinese-language penalty.

CONCLUSIONS: Within the scope of this benchmark, multimodal inputs improved performance over clinical history alone, but performance gaps remain in volumetric data processing and cross-context generalization, with mean diagnostic performance across the 10 evaluated models remaining below clinically actionable levels on both datasets.

PMID:42566748 | DOI:10.2196/92183

JMIR Form Res. 2026 Aug 7;10:e89837. doi: 10.2196/89837.

ABSTRACT

BACKGROUND: Systematic collection of social determinants of health (SDoH) data remains inconsistent across health care settings, despite its critical impact on patient outcomes. Large language model-powered chatbots offer promise for scalable SDoH data collection, but rigorous, feasible evaluation methods for patient-facing applications are lacking.

OBJECTIVE: This study aimed to describe an efficient, iterative, multidisciplinary approach for developing and evaluating a patient-facing SDoH chatbot using synthetic data and case simulation, with the goal of optimizing both chatbot performance and the evaluation rubric prior to clinical deployment.

METHODS: A 10-criterion evaluation rubric was adapted from established health care AI frameworks and applied to 27 synthetic clinical scenarios representing diverse SDoH profiles. Scenarios were role-played by a licensed clinical social worker, and chatbot-patient interactions were rated by 3 members of the research team that were multidisciplinary experts: a social worker, a nurse practitioner, and a physician. Quantitative analysis used percent agreement and Fleiss κ to characterize chatbot performance and rater consensus, with percent agreement selected due to the high prevalence of ceiling effects in several domains. Qualitative analysis synthesized rater feedback to guide iterative refinement of both chatbot prompts and rubric domains.

RESULTS: Across 27 simulated cases, the chatbot received high proportions of positive ratings for accurate interpretation (agreement=0.98%, 95% CI 0.91-0.99), communication quality, and cultural sensitivity (agreement=0.99%, 95% CI 0.93-1.00), and appropriately adaptive questioning (agreement=0.99%, 95% CI 0.93-1.00). Lower performance was observed in domain focus and completeness (agreement=0.51%, 95% CI 0.40-0.61), completeness of data capture (agreement=0.59%, 95% CI 0.48-0.69; Fleiss κ=0.18), and safety (agreement=0.69%, 95% CI 0.58-0.78; Fleiss κ=-0.04), prompting targeted adaptations. Qualitative feedback highlighted the importance of distinguishing screening from clinical interviewing capabilities and informed the refinement of the rubric, including clarifying the definition of safety to focus on recognition of physical and mental health emergencies.

CONCLUSIONS: This study describes a formative feasibility approach for iterative refinement of a patient-facing SDoH chatbot and its evaluation rubric using synthetic case simulation. Future work will include independent external raters, patient stakeholders, repeated scenario testing, and prospective clinical evaluation.

PMID:42566745 | DOI:10.2196/89837

JMIR Infodemiology. 2026 Aug 7;6:e88849. doi: 10.2196/88849.

ABSTRACT

BACKGROUND: Influenza seasons may be associated with increased anxiety-related expressions on social media. Social media can reflect population-level emotional expression patterns in real time.

OBJECTIVE: The aim of the study is to characterize diurnal and full-season dynamics of anxiety-related language during the 2023-2024 influenza season in China and its association with influenza activity.

METHODS: We retrieved Sina Weibo posts in February 2025 covering September 4, 2023, to April 28, 2024. Posts containing Diagnostic and Statistical Manual of Mental Disorders (DSM)-based anxiety terms were cleaned and deduplicated (N=169,728 → 106,440). We first linked weekly influenza incidence with anxiety-related postings. Then, we plotted diurnal patterns by epidemiologic phase, conducted supplementary within-sample hourly normalization analyses, and modeled longitudinal symptom trajectories using ARIMA (autoregressive integrated moving average) and supplementary ARIMAX (autoregressive integrated moving average with exogenous regressors) time-series models.

RESULTS: Anxiety-related posts closely followed influenza activity, surging during the outbreak and peak phases and remaining elevated even after influenza declined. Initial Spearman correlation analyses showed significant negative associations for irritability (r=-0.413; P=.02) and restlessness or feeling keyed up or on edge (r=-0.396; P=.02). However, supplementary ARIMAX analyses further revealed that being easily fatigued and difficulty concentrating or mind going blank exhibited more stable positive temporal associations with influenza activity after controlling for autocorrelation and lagged effects. Diurnal patterns shifted across stages, showing mild early-evening variation during the outbreak, clear morning peaks with secondary afternoon and evening rises during prevalence and decline, and morning-afternoon concentration in the end stage. Supplementary within-sample hourly normalization analyses showed that the major diurnal structures remained generally stable after normalization. ARIMA time-series analysis revealed that irritability and being easily fatigued consistently dominated the discussions, whereas others remained at relatively low levels. Out-of-sample forecasting based on a chronological 80% training and 20% testing split suggested generally stable short-term trajectories, with being easily fatigued showing a slight increase.

CONCLUSIONS: This study demonstrates how social media can capture diurnal and seasonal fluctuations of anxiety symptoms associated with influenza activity, advancing understanding of affective dynamics in population health.

PMID:42566744 | DOI:10.2196/88849

JCO Glob Oncol. 2026 Aug;12(8):e2500661. doi: 10.1200/GO-25-00661. Epub 2026 Aug 7.

ABSTRACT

PURPOSE: Clinical trial availability often varies between countries, independent of the local burden of disease. We aimed to evaluate the current global availability of prostate cancer clinical trials and the factors affecting it.

METHODS: We searched for clinical trials involving prostate cancer between June 2019 and June 2024 through Clinicaltrials.gov. Noninterventional trials were excluded. Countries were classified according to the World Bank Ranking (WBR) as high-, upper-middle-, lower-middle-, and low-income countries (HICs, UMICs, LMICs, and LICs). Multivariable negative binomial regression was used to evaluate the association between the number of trials and country’s characteristics. Multivariable logistic regression was used to evaluate the association between trial availability and country’s characteristics. In addition, we collected data on sponsorship, funding, intervention, intervention intent, end point selection, trial phase, and cancer stage.

RESULTS: Of the 1,531 trials identified, 1,413 met the eligibility criteria. Most trials were conducted exclusively in HICs (80.4%), included patients with metastatic disease (55.4%), and were sponsored by academia (68.8%). Pharma-funded trials had a higher number of participating countries (mean 2.7 v 1.0, P < .001) and were more likely to include metastatic disease (72.0% v 32.3%, P < .001) and to investigate systemic therapy (76.3% v 29.4%, P < .001). In the multivariable analysis, WBR, gross national income (GNI), and annual health expenditure were all associated with the presence of at least one trial (P < .001). Only GNI was independently associated with the number of trials within a country (P < .001).

CONCLUSION: Prostate cancer trials are disproportionately concentrated in HICs despite a lower burden of disease. Intentional efforts are needed to ensure global representation and long-term benefits for populations historically excluded from research.

PMID:42566737 | DOI:10.1200/GO-25-00661

Physiother Res Int. 2026 Oct;31(4):e70313. doi: 10.1002/pri.70313.

ABSTRACT

BACKGROUND AND PURPOSE: Neck pain is prevalent in postpartum women due to postural stress and muscle dysfunction. Although postural correction exercises are widely used, adding manual therapy techniques such as positional release and Tui-Na may enhance outcomes. However, comparative evidence, particularly using surface electromyography (sEMG), remains limited. This study examined the effects of Tui-Na (TN) versus positional release techniques (PRT) added to postural correction exercises (PCEs) on postpartum neck pain.

METHODS: Sixty women with postpartum neck pain were randomly assigned to three groups for 4 weeks of prescribed treatment. Group A (control) received PCEs, while either PRT or Tui-Na were added to PCEs for Groups B and C, respectively. The primary outcome was neck pain intensity measured by the Visual Analogue Scale (VAS). Secondary outcomes included the Neck Disability Index (NDI) and upper trapezius electromyographic characteristics (normalized root mean square [RMS] and median frequency [MDF]). A two-way repeated-measures MANOVA was used for statistical analysis.

RESULTS: Significant multivariate effects were observed for group effects (F = 4.798, p < 0.001, partial η² = 0.147), time (F = 851.51, p < 0.001, partial η² = 0.968), and group-by-time interaction (F = 3.87, p < 0.001, partial η² = 0.122). Pain intensity was significantly reduced in both groups B (p = 0.035) and C (p = 0.003) when compared to group A. UT-MDF was significantly increased in group C when compared to groups A (p < 0.001) or B (p = 0.02). All groups demonstrated significant within-group improvements in all outcome measures.

DISCUSSION: Both Tui-Na and PRT combined with PCEs improved pain and disability in postpartum women with neck pain. Compared with PRT, Tui-Na demonstrated greater improvements in pain intensity and upper trapezius EMG frequency characteristics. However, these findings should be interpreted cautiously because of the short intervention period and lack of long-term follow-up.

TRIAL REGISTRATION: NCT07261605.

PMID:42566253 | DOI:10.1002/pri.70313

JMIR Res Protoc. 2026 Aug 7;15:e76630. doi: 10.2196/76630.

ABSTRACT

BACKGROUND: Endodontically treated teeth are prone to fractures due to the loss of tooth structure, caries removal, access cavity preparation, and scaling, resulting in compromised strength in the teeth. Posts are used for restoring teeth that have undergone this process, but the role of different fiber posts in resisting fractures in teeth is unclear. Customized carbon fiber posts, customized glass fiber posts, and fiber posts relined with short fiber-reinforced composite (SFRC) are biomechanically efficient. SFRC is used as a relining material around the fiber post to improve adaptation to the root canal.

OBJECTIVE: This study aims to evaluate and compare the fracture resistance of endodontically treated teeth restored with prefabricated carbon fiber posts, customized glass fiber posts, and SFRC-relined fiber posts.

METHODS: In the current in vitro experimental study, the post specimens will be tested on 30 extracted single-rooted human teeth. These will be similar in size. The specimens will go through endodontic treatment and preparation for the post space, after which they will be randomly assigned to groups based on the type of post system: prefabricated carbon fiber posts, customized glass fiber posts, or SFRC-relined fiber posts. These will be cemented using a dual-cured resin cement. The specimens will then be restored using a standardized core build-up and tested for fracture resistance using a universal testing machine. A compressive load will be applied to each specimen at a constant crosshead speed of 1 mm/min until fracture of the specimen occurs. The maximum load at failure will be recorded in newtons. Statistical analysis will be conducted using a 1-way ANOVA.

RESULTS: Institutional ethics approval was granted by the Institutional Ethics Committee of Datta Meghe Institute of Higher Education and Research in January 2025 (DMIHER[DU]/IEC/2025/543). Sample collection and specimen preparation are scheduled to begin in February 2026, with mechanical testing expected to be completed by April 2026. As of April 2025, no specimens had been tested, and data analysis had not commenced. This is a nonfunded in vitro study, and data analysis is anticipated to be completed by May 2026. The results are expected to be submitted for publication by mid-2026.

CONCLUSIONS: This study is expected to generate comparative biomechanical evidence on the fracture resistance of different fiber-based post systems, potentially aiding clinicians in selecting optimal restorative strategies for endodontically treated teeth.

PMID:42566252 | DOI:10.2196/76630

JMIR Res Protoc. 2026 Aug 7;15:e85458. doi: 10.2196/85458.

ABSTRACT

BACKGROUND: Illicit drug use has been rapidly increasing in South Korea, particularly among individuals in their 20s, contributing to a growing burden of substance use disorder (SUD). However, treatment infrastructure remains limited. Nationwide, only a small number of inpatient treatment hospitals are available, and treatment capacity in the Seoul metropolitan area is insufficient to meet growing demand. In addition, community-based addiction services are scarce, creating barriers to continuous care. Digital therapeutics (DTx) have emerged as a promising approach to improve treatment accessibility and continuity of care. In particular, cognitive behavioral therapy (CBT)-based DTx such as RESET-O, developed in the United States and authorized by the US Food and Drug Administration, have demonstrated clinical benefits in supporting addiction recovery. Building on this concept, our team developed D-STOP, a CBT-based DTx intervention designed to support individuals with SUD in the Korean clinical context.

OBJECTIVE: This study aims to evaluate the efficacy of D-STOP as an adjunctive DTx intervention for patients with SUD.

METHODS: This study is a randomized controlled clinical trial designed to evaluate the efficacy of D-STOP in individuals diagnosed with SUD. Following an initial screening assessment, 118 participants meeting the diagnostic criteria will be enrolled. Participants will be recruited from psychiatry departments at addiction treatment and clinical care institutions in Chuncheon, Seoul, Daegu, and Changnyeong, South Korea. During the 12-week intervention period, the experimental group will receive D-STOP in addition to treatment as usual, whereas the control group will receive treatment as usual alone. D-STOP delivers structured CBT-based modules and motivational enhancement interventions through a digital platform. During scheduled study visits, participants will also receive therapeutic feedback from psychiatrists or trained study staff. The primary end point is the abstinence success rate during weeks 9 to 12 of treatment. Logistic regression analysis will be used to estimate treatment effects and evaluate superiority compared with the control group.

RESULTS: The study protocol was approved by the institutional review board of Hallym University Chuncheon Sacred Heart Hospital on April 14, 2025. Funding began on April 1, 2023. Data collection started on August 4, 2025, and is expected to be completed by November 30, 2026. As of March 6, 2026, a total of 65 participants have been enrolled. An interim analysis of the primary efficacy outcome has been conducted based on the data available at the time of analysis; however, statistical significance has not been established due to the limited sample size. The final analysis is expected to be published in April 2027.

CONCLUSIONS: DTx have the potential to expand access to evidence-based addiction treatment in resource-constrained settings. This study will provide clinical evidence on the efficacy and feasibility of D-STOP as a digital treatment support tool for patients with SUD.

PMID:42566248 | DOI:10.2196/85458