Category: Statistics

JMIR Aging. 2026 Apr 24;9:e81927. doi: 10.2196/81927.

ABSTRACT

BACKGROUND: Smartphones have become deeply embedded in daily life, supporting a range of social and practical activities. Individuals with dementia can potentially use smartphones to compensate for cognitive decline and maintain independence. However, while smartphones are widely studied in controlled research settings, little is known about how individuals with dementia spontaneously use them in everyday life. Understanding usage patterns and their potential link to social participation could inform strategies to support smartphone use in their social and practical daily activities.

OBJECTIVE: This study aimed to identify factors associated with spontaneous smartphone use, describe usage patterns, and examine whether smartphone use is associated with participation in social activities.

METHODS: In 2024, we conducted a cross-sectional survey among community-dwelling individuals with mild to moderate dementia from 17 medical facilities in Tokyo. Structured questionnaires were completed by the participants, their families, and attending physicians. Participation in social activities was assessed using the “Spending Time with Others” subscale of the Social Functioning in Dementia (SF-DEM) scale. Factors associated with smartphone use were analyzed using multinomial logistic regression. Associations with participation in social activities were assessed via hierarchical linear regression.

RESULTS: Among 151 participants with a mean age of 82.9 (SD 6.6) years, 43 (29%) participants were regular smartphone users. Smartphone use was negatively associated with older age (odds ratio [OR] 0.41, 95% CI 0.21-0.80) and positively associated with longer education (OR 1.82, 95% CI 1.00-3.30), living alone (OR 3.17, 95% CI 1.08-9.31), and better cognitive function (OR 2.14, 95% CI 1.24-3.69). Common uses included calling, texting, taking photos and videos, and checking the news and weather. Smartphone users reported marginally more frequent participation in social activities than nonusers did (b=1.41, 95% CI -0.01 to 2.83), particularly visiting the homes of friends or family (b=0.43, 95% CI 0.08-0.78) and shopping together (b=0.49, 95% CI 0.15-0.83).

CONCLUSIONS: Despite their limited use at the time of this writing, commercial-based smartphones have the potential to support participation in social activities among individuals with dementia. Targeted support may help bridge the gap between this usage and the broader capabilities of these devices, enhancing their role in sustaining meaningful social participation.

PMID:42030556 | DOI:10.2196/81927

Prim Care Companion CNS Disord. 2026 Apr 23;28(2):25m04149. doi: 10.4088/PCC.25m04149.

ABSTRACT

Objective: Collaborative care models (CoCMs) are modalities for treating mental health conditions in primary care. One such iteration of CoCM, antidepressant monitoring (ADM), is a pharmacologic treatment modality for the management of depression and anxiety. ADM programs have established efficacy, yet little is known about ideal patient selection or approaches related to program retention. The objective of this study was to address this need by examining predictors of referral from a CoCM ADM program to higher levels of psychiatric services.

Methods: A retrospective cohort analysis was conducted on individuals enrolled in the Tampa Veterans’ Affairs ADM program over 18 months (from June 4, 2018, through December 4, 2019). Data collected included information related to referral to a higher level of service, as well as baseline information and covariates of interest. Primary analysis was conducted utilizing a multivariable logistic regression model to evaluate whether baseline characteristics were associated with differences in referral rates to higher-level services.

Results: A total of 757 veterans were included in the analyses, with 131 (17.31%) referred on to a higher level of service for specialty psychiatric care. Multivariable modeling showed the following covariates to be associated with higher rates of referral to specialty psychiatric services: baseline 9-item Patient Health Questionnaire scores, sleep issues at the time of enrollment, alcohol use disorder, and cannabis use disorder.

Conclusions: Results show low rates of referral overall but identify a number of baseline characteristics associated with higher referral rates to specialty psychiatric services. Further research is needed, including prospective work and studies examining proactive interventions to limit required referrals to specialty mental health services.

Prim Care Companion CNS Disord 2026;28(2):25m04149.

Author affiliations are listed at the end of this article.

PMID:42030552 | DOI:10.4088/PCC.25m04149

Neurology. 2026 May 12;106(9):e214803. doi: 10.1212/WNL.0000000000214803. Epub 2026 Apr 24.

ABSTRACT

BACKGROUND AND OBJECTIVES: Cerebral small vessel disease (SVD) is the most common vascular contributor to dementia. SVD markers often coexist, contributing to difficulty assessing their independent contributions to cognitive domains. MRI-visible perivascular spaces (PVSs) are an emerging SVD marker visualized by MRI. We previously showed that basal ganglia PVSs cross-sectionally contribute to worse cognition, independent of other SVD markers. To further characterize the clinical relevance of PVS, we studied its role as a unique SVD marker of longitudinal cognitive decline.

METHODS: Participants without stroke or dementia were included in the Vanderbilt Memory and Aging Project, a longitudinal observational cohort study based in Nashville, TN. Participants completed 3T MRI at study entry to measure SVD burden (PVS volume fraction, white matter hyperintensities volume, lacune counts, and cerebral microbleeds counts). PVS volumes were segmented using a deep learning algorithm. Participants underwent comprehensive serial neuropsychological testing over an 11-year follow-up period (mean follow-up = 4.9 ± 3.1 years). Each SVD marker was related to longitudinal neuropsychological performances using a linear mixed-effects model adjusting for age, sex, race/ethnicity, education, baseline cognitive status, apolipoprotein E-ε4 presence, Framingham Stroke Risk Profile, and intracranial volume. Head-to-head comparisons simultaneously tested multiple statistically significant SVD markers.

RESULTS: Among participants (n = 750, age 68 ± 9 years, 52% female), higher basal ganglia PVS burden at baseline was associated with worse longitudinal performances in Boston Naming Test (β = -29.63; 95% CI -56.66 to -2.60), Animal Naming (β = -33.09; 95% CI -65.66 to -0.51), Wechsler Adult Intelligence Scale IV Coding (β = -86.36; 95% CI -150.9 to -21.82), executive function composite (β = -9.51; 95% CI -14.33 to -4.68), Hooper Visual Organization Test (β = -26.06; 95% CI -50.53 to -1.59), and episodic memory composite (β = -7.05; 95% CI -11.9 to -2.21). In head-to-head comparisons, basal ganglia PVS remained independent associations with executive function composite (β = -7.47; 95% CI -12.84 to -2.10) and Hooper Visual Organization Test (β = -22.11; 95% CI -42.38 to -1.85).

DISCUSSION: Basal ganglia PVS burden independently contributes to worse longitudinal executive function and visuospatial skills independent of other SVD markers, highlighting PVS as an emerging marker of domain-specific cognitive decline in aging. Although causation cannot be established, findings further support PVS as a vascular contributor to deep brain structure damage underlying cognitive decline over time.

PMID:42030516 | DOI:10.1212/WNL.0000000000214803

JMIR Form Res. 2026 Apr 24;10:e77255. doi: 10.2196/77255.

ABSTRACT

BACKGROUND: Breast cancer-related lymphedema is the most prevalent postoperative complication among breast cancer survivors. Although mobile health tools are increasingly used for patient education, evidence supporting their efficacy in lymphedema prevention remains limited.

OBJECTIVE: This study aimed to evaluate the effectiveness of a WeChat-based intervention grounded in the common-sense model (CSM) in improving preventive behaviors, modifying illness perceptions, and reducing lymphedema incidence among breast cancer survivors and to validate the targets of the intervention.

METHODS: This study used a quasi-experimental design. Participants (N=192) were recruited from the breast cancer department of a cancer hospital in Guangzhou, China. The control group (n=98) received routine care. The intervention group (n=94) participated in a 3-month CSM-guided WeChat mini-program (“Nantian e-Care”) delivering tailored educational articles, exercise tutorials, arm circumference monitoring, and real-time nurse consultations. Outcomes, including preventive behaviors, illness perceptions, and lymphedema incidence, were assessed 1, 3, and 6 months post surgery. Generalized estimating equations were used for the analysis.

RESULTS: The intervention group exhibited significant improvements in lifestyle adjustments (Wald χ22=6.9, P=.03) and physical exercise adherence (Wald χ22=6.9, P=.03) compared with the control group. Illness perception, including identity (Wald χ23=8.1, P=.04), timeline cyclical (Wald χ23=8.5, P=.04), personal control (Wald χ23=9.3, P=.03), illness coherence (Wald χ23=29.8, P<.001), and behavioral (Wald χ23=19.5, P<.001) and physical factors (Wald χ23=24.1, P<.001) were markedly enhanced. Mechanistically, skin care improvements were driven by intervention effects, personal control, illness coherence, and behavioral attribution. Lifestyle changes were correlated with intervention and illness coherence. Adherence to physical exercise was not statistically significantly affected by the intervention, although a trend was observed. Critically, the intervention group demonstrated a lower incidence of lymphedema at 6 months (7.50% vs 16.48%, χ21=3.9, P=.048).

CONCLUSIONS: The CSM-guided WeChat intervention effectively promoted preventive behaviors, optimized illness perceptions, and reduced lymphedema risk. These findings underscore the value of integrating theory-driven mobile health tools into postoperative care and highlight scalable strategies for chronic disease management in resource-limited settings.

PMID:42030512 | DOI:10.2196/77255

JCO Oncol Pract. 2026 Apr 24:OP2501161. doi: 10.1200/OP-25-01161. Online ahead of print.

ABSTRACT

PURPOSE: 177Lu-PSMA-617 (LuPSMA) is an approved prostate-specific membrane antigen (PSMA)-targeted radiopharmaceutical therapy for men with metastatic castration-resistant prostate cancer (mCRPC). Older patients, particularly octogenarians, represent a substantial proportion of men with mCRPC but have been traditionally underrepresented in key registrational trials of LuPSMA.

METHODS: This retrospective multi-institutional study evaluated patients age 80 years and older with mCRPC after chemotherapy treated with ≥1 cycle of LuPSMA from August 2022 to December 2024. Clinical and demographic data were abstracted from electronic medical records. Outcomes included prostate specific antigen (PSA) response (PSA50 and PSA90), progression-free survival (PFS), overall survival (OS), and toxicities. Kaplan-Meier methods estimated PFS/OS; descriptive statistics summarized baseline and safety data.

RESULTS: Ninety-five patients (median age, 83 years) were included, of whom 36 (38%) and 21 (22%) had a history of cardiac disease or chronic kidney disease, respectively. Median follow-up was 24.1 months (IQR, 6.7-28.1). Patients received a median of five cycles of LuPSMA. Fifty-two (57%) and 21 (23%) patients achieved a PSA50 and PSA90, respectively. Median PFS and OS were 7.3 months (95% CI, 6.4 to 8.7) and 13.5 months (95% CI, 9.7 to 18.8), respectively. Grade ≥3 hematologic toxicities included anemia (n = 19; 20%) and thrombocytopenia (n = 4, 4%); grade ≥3 acute kidney injury occurred in one patient. Fourteen (15%) patients had dose delays, seven (7%) required reductions, and 10 (11%) discontinued therapy due to toxicity. Thirty-seven patients (39%) were hospitalized during therapy, with intensive care unit-level care required in two patients (2%), and there was one treatment-related death.

CONCLUSION: LuPSMA had comparable outcomes in octogenarians with mCRPC to patients on registrational trials, although 2/5 of patients required hospitalization during therapy. These findings support the feasibility and efficacy of LuPSMA in well-selected older men with mCRPC and suggest a role for closer monitoring of older patients.

PMID:42030508 | DOI:10.1200/OP-25-01161

JMIR Med Inform. 2026 Apr 24;14:e83127. doi: 10.2196/83127.

ABSTRACT

BACKGROUND: Artificial intelligence-augmented electrocardiogram (AI-ECG) models for detecting left ventricular systolic dysfunction (LVSD) often exhibit degraded performance in patients with comorbidities.

OBJECTIVE: This study aimed to introduce and validate a recalibration method using longitudinal patient data to enhance prediction accuracy and simulate its clinical utility for ongoing monitoring.

METHODS: We conducted a multicenter, retrospective cohort study using data from 2 hospitals in Korea. A dataset of paired transthoracic echocardiograms (TTEs) and electrocardiograms (ECGs) matched within a 2-week interval was constructed, separating pairs into baseline (first for each patient) and follow-up assessments. In addition to conventional supervised learning, we developed a patient-wise recalibration strategy that incorporated historical left ventricular ejection fraction measurements and prior AI-ECG outputs to adjust for future predictions, thus empirically mitigating confounding effects. Pretraining was also implemented to enhance the model’s performance.

RESULTS: The recalibrated 12-lead DeepECG LVSD model achieved an area under the receiver operating curve of 0.956 (95% CI 0.946-0.965) for internal validation and 0.940 (95% CI 0.936-0.945) for external validation of follow-up TTE-ECG pairs. The uncalibrated 12-lead DeepECG LVSD model also showed modest performance, with an area under the receiver operating curve of 0.953 (95% CI 0.941-0.965) in the internal validation and 0.947 (95% CI 0.943-0.951) in the external validation when tested on baseline TTE-ECG pairs. Recalibration yielded statistically significant improvements in the 12-lead DeepECG LVSD models (P<.001), with enhanced and more balanced performance across all clinical subgroups.

CONCLUSIONS: Patient-wise recalibration improved accuracy and consistency across various comorbidities by mitigating performance degradation and bias. This broadens the application of AI-ECG for LVSD detection from low-risk screening to high-risk longitudinal monitoring.

PMID:42030497 | DOI:10.2196/83127

Int J Methods Psychiatr Res. 2026 Jun;35(2):e70074. doi: 10.1002/mpr.70074.

ABSTRACT

OBJECTIVES: To develop a statistical method that uncovers clinically meaningful differences between active psychiatric treatments, even when traditional rating scales fail to do so.

METHODS: We introduce Supervised Varimax (SV), a novel algorithm that transforms individual items from clinical rating scales into a small set of optimized outcomes that maximally differentiate treatments. SV was applied to data from two large, multi-center, randomized controlled trials: CATIE (schizophrenia) and STAR*D (treatment-resistant depression).

RESULTS: SV identified significant differential treatment effects that were not evident in the original analyses. In CATIE Phase I, olanzapine was more effective than quetiapine and ziprasidone for hostility, and perphenazine outperformed ziprasidone for emotional dysregulation. In Level 2 of STAR*D, bupropion augmentation was more effective than buspirone augmentation for patients with increased appetite. These findings were validated using post-hoc permutation testing and matched to clinical subgroups using simple, symptom-based rules.

CONCLUSIONS: SV enables precision psychiatry by optimizing outcome definitions to enhance treatment differentiation in RCTs. This approach provides interpretable, clinically actionable insights using existing trial data, without requiring complex predictive modeling or additional biomarkers.

TRIAL REGISTRATION: CATIE (NCT00014001), STAR*D (NCT00021528).

PMID:42030496 | DOI:10.1002/mpr.70074

Trends Psychiatry Psychother. 2026 Apr 24. doi: 10.47626/2237-6089-2025-1228. Online ahead of print.

ABSTRACT

OBJECTIVE: The constant access to online content has raised concerns worldwide. Excessive engagement with digital platforms can contribute to significant mental health challenges, including increased levels of depression, anxiety, and stress. This phenomenon is related to impairments in neuroanatomical areas leading to adverse outcomes. The study aimed to analyze the associations between internet addiction (IA), depression, anxiety, stress, and a diversity of sociodemographic variables, including gender, social media use, employment status, sleep, and physical activity patterns.

METHODS: A sample of 618 adolescents and young adults in southern Brazil was analyzed (mean age: 23.34). Participants filled an online form and statistical analysis was conducted.

RESULTS: The results show that depression, anxiety, and stress levels were higher in women (p < 0.001), whereas IAT scores did not reach statistical significance, despite being higher in women (p = .06). Those who are employed may have lower levels of IA; poor sleep habits are associated with higher internet addiction and social media use is associated with poorer mental health and IA (p < 0.001).

CONCLUSION: Mental health support and internet use limits should be offered to the general population in terms of prevention and treatment of these conditions.

PMID:42030494 | DOI:10.47626/2237-6089-2025-1228

JMIR Res Protoc. 2026 Apr 24;15:e87902. doi: 10.2196/87902.

ABSTRACT

BACKGROUND: School health policies and practices are key components of health promotion for children and adolescents and play a central role in shaping healthy school environments, reducing health inequities, and fostering intersectoral collaboration between education and health systems. Despite their relevance, systematic and comparable assessments of how these policies and practices are implemented across different national contexts remain limited, particularly in low- and middle-income countries. Internationally comparable data are essential to identify strengths, gaps, and priorities for investment in school health.

OBJECTIVE: The aim of this study is to describe the protocol of a mixed methods study evaluating and comparing school health policies and practices in Brazil and Portugal.

METHODS: An explanatory sequential mixed methods design (QUAN → qual → [qual] → [qual]) will be adopted. The quantitative phase (phase I) consists of a cross-sectional survey conducted with school administrators using the Global School Health Policies and Practices Survey, which assesses multiple domains of school health policies, coordination, services, and practices. Quantitative findings will inform the subsequent qualitative phases. Phase II involves semistructured interviews with school principals or head teachers to explore institutional decision-making and policy implementation. Phase III includes interviews with school nurses to examine health service organization, intersectoral collaboration, and professional practices. Phase IV comprises participatory research with adolescents using the photovoice technique to capture youths’ perspectives on school health environments and practices. The study will be conducted in elementary and secondary schools and related health services in selected cities in Brazil and Portugal. Data integration will occur sequentially through connected analyses and joint displays, enabling the development of meta-inferences that link quantitative patterns with qualitative explanations.

RESULTS: The study has secured funding from 2 funding agencies, with project activities initiated in 2025. Quantitative data collection and analysis began in October 2025 in the city of Cuiabá, Brazil. The expansion of data collection to additional Brazilian and Portuguese cities is planned for the first half of 2026. The qualitative phases, including interviews and photovoice activities, are scheduled to take place throughout 2026. The final integrated mixed methods analysis and manuscript preparation are planned for 2027, with dissemination of findings through peer-reviewed journals and national and international scientific conferences by the end of the project cycle.

CONCLUSIONS: This study is expected to generate context-sensitive and comparative evidence to support intersectoral actions and inform the development and strengthening of school health promotion policies and practices in different national settings.

PMID:42030489 | DOI:10.2196/87902

J Psychosoc Nurs Ment Health Serv. 2026 Apr 28:1-13. doi: 10.3928/02793695-20260420-02. Online ahead of print.

ABSTRACT

PURPOSE: To examine the effect of metacognitive beliefs and cognitive insight on subjective perception of recovery in individuals with schizophrenia.

METHOD: Participants in the current descriptive cross-sectional and correlational study comprised 133 individuals with schizophrenia being treated in the psychiatry clinic of a training and research hospital in Türkiye. Data were collected using a Personal Information Form, Metacognition Questionnaire-30 (MCQ-30), Beck Cognitive Insight Scale (BCIS), and Subjective Recovery Assessment Scale (SubRAS). Descriptive statistics, bivariate analysis, and hierarchical regression analysis were used to analyze the data.

RESULTS: Participants’ MCQ-30, BCIS, and SubRAS scores were 84.45 (SD = 9.90), -0.15 (SD = 5.12), and 57.78 (SD = 15.26), respectively. Metacognitive beliefs were a predictor of subjective perception of recovery (β = -0.179, p = .034). The meta-cognition score explained 10.1% of the total variance associated with subjective perception of recovery (adjusted R² = 0.101).

CONCLUSION: Results of the current study can guide psychiatric-mental health nurses to develop specific interventions and programs to support subjective recovery in individuals with schizophrenia and improve their mental health outcomes.

PMID:42030479 | DOI:10.3928/02793695-20260420-02