Tag: pubmed

J Med Internet Res. 2025 Nov 3;27:e79718. doi: 10.2196/79718.

ABSTRACT

BACKGROUND: Consistent wear is essential for valid and reliable actigraphy data. Adherence to actigraphy may be challenging in primary school children due to developmental and design considerations, yet no quantitative synthesis of adherence in this age group exists.

OBJECTIVE: The aim of this study was to provide the first pooled estimate of actigraphy adherence in primary school-aged children and examine the impact of individual, device, and study-specific factors on adherence.

METHODS: We searched seven electronic databases for studies reporting adherence to actigraphy in primary school-aged children. Searches were conducted in Embase, MEDLINE, PsycINFO, Social Policy and Practice via OVID, Education Resources Information Center, British Education Index, and CINAHL via EBSCO using database-specific search strategies conducted between January 2018 and January 24, 2023. Forward and backward citation searches were completed on the Web of Science Core Collection and Google Scholar. Gray literature searches were undertaken in PsycEXTRA and Healthcare Management Information Consortium. Empirical studies reporting quantitative data on adherence to community-based actigraphy in children aged 5-11 years (or if ≥50% of the average age fell within this range) were included. Eligible studies were written in English and could be published or unpublished. Risk of bias was assessed using an 8-item checklist adapted from Berger et al’s actigraphy reporting standards. All included studies were narratively synthesized, and adherence data were pooled in a proportional meta-analysis. Adherence was calculated as the proportion of children meeting wear-time criteria to be included in the analysis compared to the number of children invited to use the device at baseline. Meta-regression was used to examine the impact of individual, device, and study-specific factors on adherence. Prediction intervals were calculated to estimate the range of adherence expected across future studies.

RESULTS: Data were extracted from 235 studies (N=148,161); of these, 135 studies (n=64,541) provided adherence data for proportional meta-analysis. Pooled adherence, measured across 1-140 days, was 81.6% (95% CI 78.7%-84.4%; I2=98.8%). The prediction intervals (42.8%-100%) indicated substantial variability in adherence estimates across studies. Meta-regression suggested that individual characteristics contributed to observed heterogeneity as children with a physical health diagnosis (b=0.236, 95% CI 0.009-0.464; P=.04) and those with neurodevelopmental or mental health diagnosis (b=0.395, 95% CI 0.125-0.665; P=.004) demonstrated higher adherence than undiagnosed children, though these effects were of modest magnitude. No significant effects were found for age, placement, protocol length, protocol deviation, or incentivization. Reporting quality was poor, with only 3.4% of studies satisfying all criteria.

CONCLUSIONS: This review demonstrates generally high actigraphy adherence in primary school-aged children, particularly those with health conditions. However, observed variability indicates that adherence was much lower in some contexts, underscoring that the reported pooled adherence cannot be assumed across future actigraphy applications within this age group. Future research should use standardized adherence reporting and should plan for adherence variability.

PMID:41183377 | DOI:10.2196/79718

Soft Matter. 2025 Nov 3. doi: 10.1039/d5sm00947b. Online ahead of print.

ABSTRACT

Drawing inspiration from the concept of the “primitive path” of a linear chain in melt conditions, we introduce here a numerical protocol which allows us to detect, in an unambiguous manner, the “primitive shapes” of ring polymers in two-dimensional melts. Then, by analysing the conformational properties of these primitive shapes, we demonstrate that they conform to the statistics of two-dimensional branched polymers (or, trees) in the same melt conditions, in agreement with seminal theoretical work by Khokhlov, Nechaev and Rubinstein. Results for polymer dynamics in light of the branched nature of the rings are also presented and discussed.

PMID:41183354 | DOI:10.1039/d5sm00947b

Nanoscale. 2025 Nov 3. doi: 10.1039/d5nr02899j. Online ahead of print.

ABSTRACT

Multiphoton 3D laser printing (MPLP) offers a unique combination of sub-micron resolution, geometrical freedom, and property variability. While this technique opens an extensive parameter space to develop new materials, it poses a significant challenge to disentangle and optimize the interrelated effects of chemical composition, process parameters, and resulting material properties. In this context, data analysis through full factorial analysis (FFA) can serve as a crucial tool for the systematic examination of how multiple factors interact and influence the final material properties of 3D printed microstructures, resulting in the identification of key parameters. In this work we propose a three-step approach, called ‘nano-FFA’, that involves: (1) evaluation of the printability of selected inks via scanning electron microscopy (SEM); (2) characterization of 3D printed structures using nanoindentation and vibrational spectroscopy; and (3) identification of interactions between ink formulation and printing parameters via FFA. Three scenarios have been investigated using the three-step nano-FFA approach: scenario I focuses on the effect of the photoinitiator concentration. Scenario II examines the influence of different photoinitiator species and scenario III evaluates the effect of the crosslinker. Across all scenarios, a significant interaction is observed between ink composition-i.e. photoinitiator concentration, photoinitiator type, and crosslinker-and the laser power (LP) printing parameter. This finding demonstrates that the properties of the final structures can be tailored by precisely selecting these two factors. The results of this study highlight the value of integrating statistical data analysis methods, such as FFA, into 3D printing material optimization toolboxes. Implementation of this new nano-FFA approach can provide a practical method for streamlining ink formulation and process optimization in MPLP, allowing rational ink development over a wide range of applications.

PMID:41183352 | DOI:10.1039/d5nr02899j

Ann Intern Med. 2025 Nov 4. doi: 10.7326/ANNALS-25-00739. Online ahead of print.

ABSTRACT

BACKGROUND: Data extraction is a critical but error-prone and labor-intensive task in evidence synthesis. Unlike other artificial intelligence (AI) technologies, large language models (LLMs) do not require labeled training data for data extraction.

OBJECTIVE: To compare an AI-assisted versus a traditional, human-only data extraction process.

DESIGN: Study within reviews (SWAR) using a prospective, parallel-group comparison with blinded data adjudicators.

SETTING: Workflow validation within 6 ongoing systematic reviews of interventions under real-world conditions.

INTERVENTION: Initial data extraction using an LLM (Claude, versions 2.1, 3.0 Opus, and 3.5 Sonnet) verified by a human reviewer.

MEASUREMENTS: Concordance, time on task, accuracy, sensitivity, positive predictive value, and error analysis.

RESULTS: The 6 systematic reviews in the SWAR yielded 9341 data elements from 63 studies. Concordance between the 2 methods was 77.2% (95% CI, 76.3% to 78.0%). Compared with the reference standard, the AI-assisted approach had an accuracy of 91.0% (CI, 90.4% to 91.6%) and the human-only approach an accuracy of 89.0% (CI, 88.3% to 89.6%). Sensitivities were 89.4% (CI, 88.6% to 90.1%) and 86.5% (CI, 85.7% to 87.3%), respectively, with positive predictive values of 99.2% (CI, 99.0% to 99.4%) and 98.9% (CI, 98.6% to 99.1%). Incorrect data were extracted in 9.0% (CI, 8.4% to 9.6%) of AI-assisted cases and 11.0% (CI, 10.4% to 11.7%) of human-only cases, with corresponding proportions of major errors of 2.5% (CI, 2.2% to 2.8%) versus 2.7% (CI, 2.4% to 3.1%). Missed data items were the most frequent error type in both approaches. The AI-assisted method reduced data extraction time by a median of 41 minutes per study.

LIMITATIONS: Assessing concordance and classifying errors required subjective judgment. Consistently tracking time on task was challenging.

CONCLUSION: Data extraction assisted by AI may offer a viable, more efficient alternative to human-only methods.

PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality and RTI International.

PMID:41183336 | DOI:10.7326/ANNALS-25-00739

JMIR Aging. 2025 Nov 3;8:e80034. doi: 10.2196/80034.

ABSTRACT

BACKGROUND: Measuring and promoting healthy aging at an individual level remains challenging as promoting healthy longevity requires real-time, personalized tools to assess risk and guide interventions in clinical practice.

OBJECTIVE: This study aimed to develop and validate a novel Healthy Longevity Index (HLI) for use in primary care settings in older adults.

METHODS: Using data from the Taiwan Longitudinal Study on Aging (TLSA; n=4470), we developed a nomogram-based HLI incorporating demographics, lifestyle factors, intrinsic capacity (IC) measures, and chronic conditions to predict 4-, 8-, and 12-year disability- and dementia-free survival (absence of physical disability, dementia, or mortality). The HLI was internally validated in a TLSA subset and externally validated in the Japanese National Institute for Longevity Sciences, Longitudinal Study of Aging (NILS-LSA) cohort (n=1090).

RESULTS: The 12-year HLI nomogram demonstrated robust performance, with C-statistics of 0.79 (bootstrapped 95% CI 0.78-0.80) in the TLSA training cohort and 0.77 (bootstrapped 95% CI 0.75-0.79) in the TLSA validation cohort. External validation in the NILS-LSA yielded a C-statistic of 0.71 (bootstrapped 95% CI 0.66-0.76). The HLI effectively stratified participants into risk tertiles, with the highest-risk group showing only 27.8% probability of 12-year disability- and dementia-free survival compared to 87.8% in the lowest-risk group. Key predictors included age, sex, education, and, particularly, IC impairments in locomotion, visual acuity, and cognition-all assessable during routine primary care consultations.

CONCLUSIONS: The HLI provides a practical tool for real-time, personalized assessment of healthy longevity risk in primary care settings. Its design enables providers to deliver person-centered care through targeted interventions and individualized prevention strategies that promote healthy aging across populations, especially in older adults.

PMID:41183329 | DOI:10.2196/80034

JMIR Res Protoc. 2025 Nov 3;14:e76405. doi: 10.2196/76405.

ABSTRACT

BACKGROUND: Heterogeneity in outcome selection and measurement methods has been noted in studies examining the minimization of physical restraint use in adult intensive care units (ICUs). This variability undermines evidence synthesis, limiting the development of evidence-based approaches to minimize restraint use and improve patient outcomes.

OBJECTIVE: This protocol outlines the methods for developing international consensus on core outcomes and standardized measurement approaches for studies focused on physical restraint minimization in adult ICUs.

METHODS: We will follow the Core Outcome Measures in Effectiveness Trials Handbook. Drawing on our previous work, including a scoping review of studies on physical restraint minimization and interviews with family members, we will compile a list of potential outcomes for a 2-round Delphi survey. In round 1, stakeholders will rank outcomes using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) scale. In round 2, they will review the aggregated results for rescoring and refinement. A consensus meeting using the modified nominal group technique will finalize the core outcome set, followed by another meeting to agree on standardized measurement methods.

RESULTS: Research ethics board approval is in progress. Recruitment has not yet begun. Project initiation is anticipated in January 2026, with completion planned for April 2027 and publication of findings is expected by June 2027.

CONCLUSIONS: This study will be the first to establish a core outcome set and a core outcome measurement set for minimizing restraint use in adult ICUs. Standardization will enhance comparability across future studies and support evidence synthesis. The resulting outcome and measurement sets will provide a foundation for high-quality research and guide evidence-based strategies to improve patient safety and care in ICU settings.

TRIAL REGISTRATION: COMET Initiative 3368; https://tinyurl.com/yubfzre9.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/76405.

PMID:41183322 | DOI:10.2196/76405

JMIR Public Health Surveill. 2025 Nov 3;11:e73731. doi: 10.2196/73731.

ABSTRACT

BACKGROUND: Chronic kidney disease and end-stage renal disease are major contributors to the disease burden in low- and middle-income countries, including Indonesia. Despite the expansion of universal health coverage through Badan Penyelenggara Jaminan Sosial (BPJS) Kesehatan, Indonesia’s national health insurance program, disparities in access to hemodialysis persist across different socioeconomic and geographic groups. Understanding these inequities is critical to advancing equitable health care access.

OBJECTIVE: This study aimed to examine disparities in hemodialysis claim patterns as a proxy for access among adult patients with renal failure enrolled in BPJS, focusing on differences by membership type, sex, age, geographic region, urbanicity, and facility ownership.

METHODS: We conducted a cross-sectional analysis of 38,383 anonymized health insurance claims between 2017 and 2022 for patients with renal failure who were aged ≥18 years. The primary outcome was receipt of hemodialysis. We used multivariate logistic regression to estimate adjusted odds ratios (aORs) for receiving hemodialysis across BPJS membership types and other covariates. Subgroup analyses were performed by sex, facility ownership, urbanicity, and geographic region. Robust SEs and probability weights were applied to account for the sample design.

RESULTS: Of the total renal failure claims, 75.6% (29,017/38,383) involved hemodialysis. Compared with individuals in the lowest income group (ie, members subsidized under the national government budget), informal workers (aOR 1.56, 95% CI: 1.34-1.82); P<.001) and members subsidized under the local government budget (aOR 1.31, 95% CI: 1.05-1.63); P=.017) had higher odds of receiving hemodialysis, while formal sector workers had lower odds (aOR 0.81, 95% CI: 0.68-0.98); P=.028). Disparities were more pronounced in rural areas and among women; for example, in rural regions, locally subsidized members had more than twice the odds of receiving hemodialysis compared with nationally subsidized members (aOR 2.40, 95% CI: 1.78-3.23). Men had higher odds than women (aOR 1.17, 95% CI: 1.04-1.32), and younger patients were more likely to receive treatment than older ones. Regional disparities were stark, with patients in Java or Bali having much greater access (aOR 8.30, 95% CI 5.33-12.94) compared with those in eastern Indonesia (Papua, Maluku, and Nusa Tenggara). Patients treated at private facilities (aOR 1.30, 95% CI 1.13-1.50) and in outpatient settings (aOR 3.74, 95% CI 3.36-4.17) were more likely to receive hemodialysis, whereas those in lower-level hospitals or clinics were less likely to access care.

CONCLUSIONS: Substantial disparities in hemodialysis claim patterns (as a proxy for access) exist within Indonesia’s national health insurance system, particularly affecting low-income populations, rural residents, women, and those in less advantaged regions. Policy efforts to enhance health infrastructure, improve service distribution, and reduce geographic and socioeconomic barriers are urgently needed to support equitable access to renal care services and achieve universal health coverage goals.

PMID:41183316 | DOI:10.2196/73731

JMIR Form Res. 2025 Nov 3;9:e80458. doi: 10.2196/80458.

ABSTRACT

BACKGROUND: Stroke has become a global public health problem due to its high incidence, disability, and mortality. In China, TikTok and Bilibili, as mainstream video-sharing platforms, serve as key sources of getting stroke-related information for people, yet their videos’ content quality and reliability remain insufficiently evaluated.

OBJECTIVE: This cross-sectional study aimed to analyze the content and quality of stroke-related videos on Chinese video-sharing platforms.

METHODS: In March 2025, stroke-related videos were retrieved from TikTok and Bilibili using the search term “” (Chinese for stroke). Eligible videos were analyzed for metadata and content indicators. Researchers assessed video quality using validated tools: the Global Quality Scale (GQS), modified DISCERN (mDISCERN), and Patient Education Materials Assessment Tool (PEMAT). Statistical analyses were performed with Python, including descriptive statistics, group comparisons (Kruskal-Wallis tests), and Spearman’s rank correlation to evaluate variable associations, with all P values adjusted for multiple comparisons using the Bonferroni method. A binary classification predictive model was developed using the random forest algorithm, accompanied by feature importance analysis.

RESULTS: Among the stroke-related videos from Bilibili (n=157) and TikTok (n=149), popular science education content predominated (204/306, 66.7%). Bilibili videos were primarily categorized as professional lectures (83/157, 52.9%), while most TikTok videos were popular science education (139/149, 93.3%). TikTok videos demonstrated significantly higher median likes and comments (P<.001) and shorter durations compared to Bilibili (P<.001). No significant differences were observed in median GQS (4) or mDISCERN scores (3) between platforms (P>.05). Videos produced by professional teams exhibited significantly higher GQS and PEMAT-A/V scores than those created by independent content creators (P<.05). Popular science education videos achieved higher PEMAT-A/V actionability scores than professional lectures (P<.001), while videos addressing treatment options scored lowest in GQS (P<.05). Strong positive correlations were identified among user engagement parameters (likes, shares, comments; ρ=0.81-0.90, P<.001), but only weak correlations were found between engagement and quality scores (ρ<0.3). Machine learning modeling (AUC=0.58) identified video duration (importance score: 0.15) and uploader subscriber count (importance score: 0.13) as key predictors of content quality.

CONCLUSIONS: The quality of stroke-related videos on TikTok and Bilibili remains suboptimal. Content uploaded by certified physicians and institutions received higher GQS/mDISCERN scores, confirming that medical authority is a key quality indicator. Our exploratory random-forest model, which used only basic metadata (duration, likes, subscriber count), achieved an area under the curve of 0.58, indicating that surface engagement metrics alone are insufficient to discriminate high- from low-quality material. Consequently, future screening algorithms should incorporate content-based features (eg, captions, medical keywords, visual cues) and creator credentials rather than relying solely on readily available interaction parameters. Multi-platform, larger-scale datasets are warranted to develop clinically useful prediction tools.

PMID:41183313 | DOI:10.2196/80458

J Nurs Educ. 2025 Oct 29:1-4. doi: 10.3928/01484834-20250625-04. Online ahead of print.

ABSTRACT

BACKGROUND: Critical thinking may be enhanced by emotional intelligence (EI) and mindfulness (MF). This study explored the influence of reflective practice and mindful breath and movement exercises on EI and MF among baccalaureate nursing students.

METHOD: Using a mixed-methods design, participants (n = 24) responded to reflective prompts and engaged in mindful breath and movement exercises. Participants completed EI and Mindful Attention Awareness Scale (MAAS) pre- and posttests. A paired-samples t test examined the difference in mean scores. In vivo and focused coding was used for qualitative analysis.

RESULTS: Analysis revealed statistically significant increases in EI (7.5) and MAAS (10.38) mean scores from time 1 to time 2. Qualitative analysis revealed three themes: (1) awareness of self; (2) awareness of other people; and (3) awareness of self-growth.

CONCLUSION: Results suggest that integrating EI-building strategies into nursing curricula may positively influence EI and MF among students. This is important since emotional competencies support nurses’ critical thinking skills in providing safe patient care.

PMID:41183287 | DOI:10.3928/01484834-20250625-04

JMIR Cancer. 2025 Nov 3;11:e70603. doi: 10.2196/70603.

ABSTRACT

BACKGROUND: The growing importance of real-world data (RWD) as a source of evidence for drug effects has led to increased interest in clinical research utilizing secondary use data from electronic medical record systems. Although immune checkpoint inhibitors and targeted therapies have advanced lung cancer treatment, managing complications such as interstitial lung disease (ILD) remains challenging. Early detection and prevention of ILD are crucial for improving patient prognosis and quality of life; however, predictive biomarkers have yet to be established. Therefore, methods to identify ILD risk factors and enable early detection using RWD are needed.

OBJECTIVE: This exploratory study aimed to identify associated factors and prodromal symptoms of ILD onset using clinical data stored in a hospital information system.

METHODS: Clinical data of patients diagnosed with stage IV lung cancer between November 2011 and December 2018 were extracted from the hospital information system of the National Cancer Center Hospital in Japan. A total of 3 patient groups were defined: the ILD Set, based on laboratory test results and radiological records; the ILD-GC Set, which added glucocorticoid treatment to the ILD Set; and the No ILD Set, for patients without ILD. The primary endpoint was the frequency of Japanese words extracted from electronic medical records, specifically from notes in the Problem-Oriented System/Subjective, Objective, Assessment and Plan format. Noun frequencies were compared between the ILD or ILD-GC Sets and the No ILD Set. Free-text data were processed using morphological analysis, and terms were categorized using the Patient Disease Expression Dictionary or the World Health Organization Drug Dictionary. Key terms were extracted from physician and nurse records based on the descending order of ranking differences to identify associated factors and prodromal symptoms.

RESULTS: The analysis included 674 cases (105 in the ILD Set [including 12 in the ILD-GC Set] and 569 in the No ILD Set). Baseline characteristics showed no apparent differences across groups. In the 30 days prior to ILD onset, notable differences in word frequencies per 1000 notes between the ILD-GC Set and No ILD Set were observed in the following term categories: respiratory symptoms (eg, breathlessness, shortness of breath, oxygen), ranging from 170.59 to 46.51; pain or analgesics (eg, Lyrica [pregabalin], soreness, precordial pain, opioids), ranging from 462.88 to 45.16; and appetite-related terms (eg, inappetence, food intake, queasiness, Novamin [prochlorperazine]), ranging from 102.23 to 51.90.

CONCLUSIONS: Terms related to respiratory symptoms, pain or analgesics, and appetite were identified as associated factors for ILD onset in patients with stage IV lung cancer using RWD from acute care institutions for malignant tumors. These findings may support the early detection of ILD and underscore the potential of RWD to generate real-world evidence that informs drug discovery and pharmaceutical development.

PMID:41183283 | DOI:10.2196/70603