Category: Statistics

JMIR Med Inform. 2026 Aug 18;14:e88056. doi: 10.2196/88056.

ABSTRACT

BACKGROUND: Telemedicine may improve access to specialized care, but its use for supervision during critical anesthesia situations remains underexplored. A standardized tele-supervision (TSV) solution for operating rooms (ORs) is lacking.

OBJECTIVE: This study aimed to evaluate a novel telemedical supervision system for critical anesthetic scenarios in a simulated OR environment and compare it to traditional on-site supervision. Specifically, adherence to standard operating procedures (SOPs), the number and modality of senior physician contacts, workload, and user perceptions were assessed.

METHODS: In this randomized controlled simulation study, 16 anesthesiology residents in their first 2 years of training at the Uniklinik Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen (Germany) were randomized using block randomization into 2 groups. The intervention group received remote support exclusively via a TSV system, while the control group used a conventional phone with on-site support. The telemedical system comprised an anesthesia workstation that integrated data from the patient monitor, anesthesia device, and syringe pumps using the Institute of Electrical and Electronics Engineers (IEEE) 11073 Service-Oriented Device Connectivity (SDC) standard and a mobile supervision workstation that enabled the senior physician to monitor multiple ORs and communicate via text, audio, and video. The simulated scenario involved a male patient aged 51 years undergoing an appendectomy who developed an anaphylactic reaction 3 minutes after receiving cefuroxime. Primary outcomes focused on the completion rate of necessary SOP measures. Secondary outcomes included workload, measured using the NASA Task Load Index (NASA-TLX), and participants’ postscenario questionnaire responses. Statistical comparisons were performed using a Welch t test.

RESULTS: All participants in both groups contacted the senior physician at least once. The control group had a mean of 6.44 (SD 4.80) SOP measures supported by the senior physician, whereas the intervention group had a mean of 5.00 (SD 3.06). The mean SOP completion rate was 92.5% (SD 0.04%) in the control group and 91.6% (SD 0.05%) in the intervention group, with no significant difference (t_11.94=0.439; P=.67). NASA-TLX scores revealed that compared to the control group, there was lower mental demand in the TSV group but higher temporal demand. Subjective evaluations indicated mixed preferences regarding on-site support; however, most participants acknowledged the TSV system as a viable alternative when on-site support was not feasible.

CONCLUSIONS: This study demonstrated no statistically significant differences between the groups, indicating similar performance with high adherence to SOPs and comparable clinical decision-making in a simulated high-stakes environment. Despite increased temporal workload, user feedback was positive, underscoring the system’s potential to address staffing shortages and resource limitations. Further research in real clinical settings is needed to optimize usability and validate these findings.

PMID:42612211 | DOI:10.2196/88056

J Med Internet Res. 2026 Aug 18;28:e92764. doi: 10.2196/92764.

ABSTRACT

BACKGROUND: Cognitive decline in older adults imposes a major global burden, with physical inactivity a leading modifiable risk factor for dementia. Digital physical exercise interventions offer scalable alternatives to traditional programs, but comparative effectiveness across cognitive domains remains unclear.

OBJECTIVE: The aim of the study is to compare and rank 4 digital physical exercise interventions-immersive virtual reality exercise (IVR_E), nonimmersive exergame (NI_ExG), remote exercise (RE), and virtual reality exercise combined with cognitive training (VR_EC)-against routine intervention (RI) or nonintervention (NI) on global cognition, executive function, and memory function in older adults aged ≥60 years.

METHODS: Eligible studies were English-language randomized controlled trials evaluating digital physical exercise on any untrained cognitive outcome in older adults. In total, 6 databases (PubMed, Embase, Web of Science, CENTRAL, PsycINFO, and CINAHL) and 2 trial registries were searched from January 2010 to April 2026; reference lists were screened. Screening, data extraction, and risk-of-bias assessment were conducted independently in duplicate using the Cochrane tool. Bayesian network meta-analyses were performed in R, reporting standardized mean differences (SMDs) with 95% CIs and prediction intervals (PIs); surface under the cumulative ranking curve (SUCRA) ranked interventions, and CINeMA (Confidence in Network Meta-Analysis) assessed certainty of evidence, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 and PRISMA-NMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Network Meta-Analyses).

RESULTS: In total, 51 randomized controlled trials (3673 participants) were included. NI_ExG significantly outperformed both NI (SMD 0.51, 95% CI 0.26-0.78; PI -0.03 to 1.07) and RI (SMD 0.32, 95% CI 0.12-0.53; PI -0.20 to 0.86) for global cognition (30 studies); IVR_E also outperformed NI (SMD 0.74, 95% CI 0.11-1.36; PI -0.04 to 1.53) and ranked highest by SUCRA. For executive function (33 studies), only NI_ExG versus NI was significant (SMD 0.39, 95% CI 0.04-0.76; PI -0.48 to 1.29). For memory function (20 studies), RE was significantly superior to both NI (SMD 1.30, 95% CI 0.15-2.44; PI -0.05 to 2.70) and RI (SMD 1.22, 95% CI 0.15-2.28; PI 0.07-2.56), with its PI also excluding the null; VR_EC was significantly inferior to RE (SMD -1.54, 95% CI -2.89 to -0.24; PI -3.09 to -0.07). Cumulative training ≥1000 minutes was associated with more stable memory benefit. Certainty was very low for most comparisons, downgraded for unclear allocation concealment, heterogeneity, and suspected reporting bias in executive function.

CONCLUSIONS: This Bayesian network meta-analysis compares 4 digital physical exercise categories against active and passive controls across 3 cognitive domains. Comparative effectiveness was domain-specific: NI_ExG most consistently benefited global cognition and executive function; RE produced the only statistically robust memory improvement; and IVR_E achieved the highest rankings but requires confirmatory trials. The scalability of RE and NI_ExG makes them practical for older adults in rural and resource-limited settings, providing an evidence base to inform clinical guidelines and digital health investment.

PMID:42612199 | DOI:10.2196/92764

Ann N Y Acad Sci. 2026 Aug;1562(1):e70343. doi: 10.1111/nyas.70343.

ABSTRACT

Individuals with prenatal alcohol exposure (PAE) and fetal alcohol spectrum disorders (FASDs) present a range of neurodevelopmental deficits (e.g., inattention, hyperactivity, and executive dysfunction) which have shown marked overlap with attention-deficit/hyperactivity disorder (ADHD), making differential diagnosis challenging. While rates of comorbidity are high, evidence has suggested there are important distinctions between neurodevelopmental phenotypes. To understand these distinctions, we evaluated whether proposed neurobehavioral disorder associated with prenatal alcohol exposure (ND-PAE) criteria in the appendix of the Diagnostic and Statistical Manual for Mental Disorders (Fifth Edition) can differentiate FASD from ADHD. We conducted systematic searches across three databases (Medline, PsycINFO, PubMed) to identify studies comparing behavioral and cognitive functioning between FASD, ADHD, and healthy controls (HCs). Outcomes indicated FASD individuals have greater magnitude neurodevelopmental deficits than ADHD; however, no differences were found regarding the pattern of deficit because of methodological limitations, such as low I². Moreover, outcomes supported adaptive and neurocognitive (executive functioning) criteria but did not support self-regulation criteria. These findings collectively underscore a need for clinicians to consider the magnitude of deficits presented to facilitate accurate recognition of PAE. Further research characterizing ND-PAE criteria and differences in the magnitude of deficits between disorders may ultimately support more accurate differential diagnosis.

PMID:42612166 | DOI:10.1111/nyas.70343

Nurs Open. 2026 Aug;13(8):e70759. doi: 10.1002/nop2.70759.

ABSTRACT

AIM: To assess intensive care unit (ICU) nurses’ knowledge, attitudes, and practices regarding mechanical ventilator weaning and associated factors in public hospitals in Addis Ababa, Ethiopia.

DESIGN: A hospital-based cross-sectional study.

METHODS: A cross-sectional study was conducted among 275 ICU nurses from 11 public hospitals in Addis Ababa between April and October 2024. Data were collected using a structured self-administered questionnaire. Descriptive statistics and multivariable logistic regression analyses were performed to identify factors associated with knowledge, attitudes, and practices. Statistical significance was set at p < 0.05.

DATA SOURCES: Primary data were collected using a structured questionnaire.

RESULTS: Good knowledge, positive attitudes, and good practices were reported by 56.7%, 94.9%, and 60.7% of nurses, respectively. Higher educational level was associated with positive attitudes and good practices, while more than 2 years of ICU experience was associated with good practice. Nurses aged 31-40 years were less likely to demonstrate good practice.

CONCLUSION: Although most ICU nurses demonstrated positive attitudes toward mechanical ventilator weaning, important knowledge and practice gaps remain. Educational level and ICU experience were associated with ventilator weaning practices. Strengthening nursing education and standardized evidence-based protocols may enhance critical care nursing practice.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Nurse-focused continuing education, competency-based training, and standardized ventilator weaning protocols may strengthen evidence-based nursing practice and support safe patient care in resource-limited ICUs.

IMPACT: This study addresses limited evidence on ICU nurses’ ventilator weaning competencies in resource-limited settings. The findings identify knowledge and practice gaps and associated professional factors. The results may inform nursing education, clinical practice, and policy development in critical care settings.

REPORTING METHOD: Reported according to the STROBE guideline for cross-sectional studies.

PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

PMID:42612164 | DOI:10.1002/nop2.70759

Biotechnol Bioeng. 2026 Aug 18. doi: 10.1002/bit.70351. Online ahead of print.

ABSTRACT

Temperature exerts a critical influence upon coffee fermentation, driving microbial metabolic pathways, acidification kinetics, and post-harvest bean quality. This study presents an integrated computational fluid dynamics (CFD)-experimental validation framework to analyze a temperature-controlled coffee fermentation bioreactor utilizing an external water-jacket system. To establish a computationally efficient engineering design tool, transient CFD simulations were executed utilizing a specialized macro-scale bulk fluid domain. Spatial discretization integrity was verified via a rigorous grid convergence index study, yielding a low numerical uncertainty (GCI₂₁ = 0.47%). Large-scale (25 kg) experimental trials conducted across three distinct thermal boundaries (17°C-20°C, 23°C-26°C, and 32°C-35°C) confirmed excellent thermal control stability, maintaining coefficients of variation below 5% and uniformity indices above 0.95. Macro-scale energy modeling reproduced the mean measured reactor temperature with a mean absolute percentage error (MAPE) of 8.38%, a mean absolute error (MAE) of 2.16°C, and a root mean square error (RMSE) of 2.24°C. It should be emphasized that the experimental validation was limited to the volume-averaged (bulk) reactor temperature at two operating conditions; the predicted spatial temperature distribution and transient flow field were not directly validated. This indicates that a simplified bulk-domain approach can approximate macro-scale thermal performance while avoiding costly multi-phase porous media overhead. Fermentation temperature strongly influenced processing kinetics and physical bean characteristics. Operating at 32°C-35°C maximized physical acceleration, driving a rapid pH reduction (to 4.14 within 12.0 h) and lowering residual mucilage to 11.2%. These effects, together with the significantly faster fermentation duration, were statistically significant (one-way ANOVA, p < 0.001). Conversely, the 23°C-26°C range produced a statistically significant non-monotonic acidification response (p < 0.001); we hypothesize that this reflects a shift in the dominant microbial pathway within the spontaneous mixed culture, although this interpretation was not confirmed by microbiological analysis. Bulk density and bean weight did not differ significantly among treatments (p = 0.25 and p = 0.91, respectively). These findings define a heat-transfer design space for temperature-regulated agricultural bioreactors that balances computational efficiency with physical processing predictability, within the bulk-thermal scope validated here.

PMID:42612163 | DOI:10.1002/bit.70351

Nurs Open. 2026 Aug;13(8):e70756. doi: 10.1002/nop2.70756.

ABSTRACT

AIM: This study aimed to investigate the impact of chronic illness self-care management on negative automatic thoughts among individuals with chronic conditions.

DESIGN: A descriptive cross-sectional design was employed.

METHODS: The study was conducted between January 5 and May 20, 2023, with 439 individuals diagnosed with chronic diseases (including circulatory, nervous and endocrine system disorders) residing in Turkey. Participants were selected utilising a non-probability convenience sampling method. Data were collected entirely through virtual outreach and web-based survey methodologies meticulously structured in accordance with the CHERRIES and STROBE guidelines. Data collection instruments included a Socio-demographic Information Form, the Self-Care Management in Chronic Diseases Scale (SCMCDS) and the Automatic Thoughts Questionnaire (ATQ). Parametric data were analysed using descriptive statistics, independent samples t-tests, one-way ANOVA with Benjamini-Hochberg False Discovery Rate (FDR) correction, Pearson correlation and multiple linear regression analysis.

RESULTS: The mean age of the participants was 49.28 ± 18.53. Total ATQ scores exhibited statistically significant differences based on income status, occupation, mental health status, quality of life, smoking habits and alcohol consumption (p < 0.05). A low-level, statistically significant negative association was identified between the global Negative Automatic Thoughts Scale and the global Chronic Illness Self-Care Management Scale [r(439) = -0.159, p < 0.05]. Multiple linear regression analysis indicated that self-care management sub-dimensions significantly predicted negative automatic thoughts, collectively accounting for 37.9% of the explained variance [F(2, 436) = 134.480, p < 0.05, R² _adj = 0.379]. According to the standardised regression coefficients, social protection (β = -0.597, p < 0.05) and self-protection (β = 0.352, p < 0.05) emerged as the significant predictors within the multivariate model.

CONCLUSION: Enhanced global self-care management substantially diminishes negative automatic thoughts in individuals with chronic conditions, primarily driven by the adaptive capacity of social protection mechanisms. Comprehensive nurse-led counselling programs, specific task-oriented screening tools and targeted cognitive-behavioural interventions should be systematically integrated into primary healthcare services to reduce immediate cognitive distortions, mitigate anxiety-induced hypervigilance and enhance functional self-care behaviours across health networks.

PATIENT OR PUBLIC CONTRIBUTION: Participants voluntarily contributed data regarding their self-care management practices and negative automatic thoughts. Neither the patients nor the public were involved in the study design, conduct, reporting, or dissemination plans.

PMID:42612156 | DOI:10.1002/nop2.70756

JMIR Res Protoc. 2026 Aug 18;15:e93130. doi: 10.2196/93130.

ABSTRACT

BACKGROUND: Frailty and prefrailty are highly prevalent conditions among older adults and are associated with increased functional decline, fall risk, hospitalization, and mortality. Multicomponent supervised exercise programs have demonstrated efficacy in improving physical performance and mitigating frailty, particularly when adapted to older adults’ functional capacity. However, evidence regarding Vivifrail-based interventions for frail and prefrail older adults in Brazil remains limited.

OBJECTIVE: This study aims to evaluate the effects of a 12-week supervised multicomponent exercise program on functional capacity and fall risk among frail and prefrail older adults. Additionally, the study aims to characterize participants according to frailty status, clinical-functional vulnerability, cognitive status, depressive symptoms, physical activity level, muscle mass, fear of falling, and sociodemographic and clinical characteristics at baseline.

METHODS: This study protocol describes a prospective, parallel-group, single-blind randomized controlled trial. Older adults aged 60 years and older who regularly attend activities at the CONVIVER Community Center in Rio Verde, Goiás, Brazil, will be screened and randomized in a 1:1 ratio into either an intervention group or a control group. The intervention group will participate in a supervised multicomponent exercise program based on the Vivifrail model for 12 weeks, whereas the control group will participate in health education workshops focused on healthy aging. The primary outcomes will be functional capacity, assessed using the 6-Minute Walk Test, and fall risk and mobility performance, assessed using the Timed Up and Go Test. Baseline assessments will additionally include frailty status (Edmonton Frailty Scale), Clinical-Functional Vulnerability Index-20, cognitive status (Mini-Mental State Examination), depressive symptoms (Geriatric Depression Scale-15), physical activity level (International Physical Activity Questionnaire), calf circumference, fear of falling (Falls Efficacy Scale-International), and sociodemographic and clinical characteristics.

RESULTS: Recruitment and baseline assessments are planned to occur between July and December 2026 at the CONVIVER Community Center. A total of 70 participants are expected to be enrolled and randomized into the intervention group (n=35) or the control group (n=35). At the time of manuscript submission, participant recruitment had not yet started, and no outcome data had been collected or analyzed. Final results are expected to be published in late 2027.

CONCLUSIONS: This randomized controlled trial protocol describes a supervised multicomponent exercise intervention tailored to frail and prefrail older adults in a Brazilian community setting. If effective, the intervention may represent a feasible, low-cost, and scalable strategy to improve functional capacity and reduce fall risk in vulnerable older populations while supporting evidence-based healthy aging initiatives.

PMID:42612144 | DOI:10.2196/93130

Diabet Med. 2026 Aug 18:e70448. doi: 10.1111/dme.70448. Online ahead of print.

ABSTRACT

AIMS: Telemonitoring in type 2 diabetes (T2D) care has demonstrated positive trends in terms of glycaemic control. However, evidence regarding its impact on patient-reported outcomes, such as general and diabetes-specific quality of life (QoL), remains inconclusive. In particular, the effect of telemonitoring in people with insulin-treated T2D is underexplored. This study aimed to evaluate the effect of telemonitoring on general and diabetes-specific QoL compared with usual care in people with insulin-treated T2D.

METHODS: Participants were randomised (1:1) to telemonitoring or usual care for 3 months. The primary outcomes were changes in the Short Form-12 Health Survey (SF-12) and the DAWN2 Impact of Diabetes Profile (DIDP). Telemonitoring included a continuous glucose monitor (CGM), a connected insulin pen, and an activity tracker. Data were monitored by hospital staff, who also provided regular telephone support. Usual care comprised a blinded connected insulin pen and a blinded CGM during the first and final 20 days, but their data were not monitored. ANCOVA compared groups for normally distributed data, with baseline scores as covariates. The Mann-Whitney U test was applied for non-normally distributed outcomes.

RESULTS: A total of 331 participants were included (telemonitoring: n = 166; usual care: n = 165). No significant between-group differences were found in SF-12 scores for neither the physical (p = 0.102) nor mental component summary score (p = 0.566). The telemonitoring group showed a statistically significant improvement in DIDP compared with usual care (p = 0.015).

CONCLUSIONS: Telemonitoring had no effect on general QoL but led to a statistically significant improvement in diabetes-specific QoL.

PMID:42612137 | DOI:10.1111/dme.70448

JMIR Med Educ. 2026 Aug 18;12:e89411. doi: 10.2196/89411.

ABSTRACT

BACKGROUND: AI is increasingly encountered in clinical care and medical education, but medical students’ attitudes, perceptions, and self-reported familiarity have been assessed using heterogeneous survey instruments, AI referents, and response scales. Prior reviews often combined mixed health profession populations or summarized central estimates without fully showing variation across settings.

OBJECTIVE: This study aimed to synthesize quantitative evidence on medical students’ AI-related attitudes, perceptions, and self-reported familiarity while examining construct harmonization, participant independence, heterogeneity, prediction intervals, risk of bias, and certainty of evidence.

METHODS: We searched PubMed (MEDLINE), Embase, Web of Science, Scopus, PsycINFO, and Cochrane CENTRAL from inception to April 1, 2026; supplementary searches are described in the appendices. Eligible studies enrolled students in MD, MBBS, MBChB, or DO-equivalent medical programs, or reported separable medical student data from mixed samples. Proportion outcomes were harmonized into 9 domains and synthesized using random-effects meta-analysis with Freeman-Tukey double-arcsine transformation, Hartung-Knapp-Sidik-Jonkman-adjusted CIs, and prediction intervals. Subgroup analyses and meta-regressions were exploratory because of multiple testing, ecological confounding, and construct heterogeneity. Risk of bias and certainty were assessed using the Joanna Briggs Institute analytical cross-sectional checklist and the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) framework, respectively.

RESULTS: Ninety-six cross-sectional studies from 37 countries (>45,000 medical students) were included. Summary estimates suggested favorable attitudes but wide between-setting dispersion. Positive attitude toward AI was 76.9% (95% CI 72.2%-81.4%; prediction interval 42.2%-98.3%; I²=98.3%; 44 studies; N=20,806), perceived career benefit was 78.4% (95% CI 69.5%-86.2%; prediction interval 45.3%-98.3%; I²=98.0%; 16 studies; N=9799), and support for curricular integration was 76.6% (95% CI 71.8%-81.1%; prediction interval 47.8%-96.1%; I²=97.2%; 38 studies; N=16,308). Concern about physician replacement was 39.9% (95% CI 33.6%-46.5%; prediction interval 6.6%-80.1%; I²=98.8%; 32 studies; N=16,642), willingness to learn about or adopt AI was 71.5% (95% CI 64.8%-77.8%; prediction interval 37.9%-95.4%; I²=97.7%; 22 studies; N=9199), and ethical concerns were endorsed by 62.8% (95% CI 53.9%-71.3%; prediction interval 21.9%-95.0%; I²=98.8%; 28 studies; N=14,571). Self-reported familiarity or knowledge was 63.3% (95% CI 55.9%-70.3%; prediction interval 7.8%-100.0%; I²=99.5%; 52 studies; N=27,817), and trust in AI-assisted decisions was 50.6% (95% CI 28.5%-72.6%; prediction interval 7.3%-93.3%; I²=98.1%; 8 studies; N=3007). All domains had very low certainty because of cross-sectional self-report designs, frequent use of nonvalidated or adapted instruments, wide prediction intervals, and small study effects in several domains.

CONCLUSIONS: Medical students’ AI-related attitudes and curricular interest appear broadly favorable, but these estimates should not be interpreted as stable global prevalences. This review adds value by restricting the population to medical students, transparently harmonizing nonequivalent constructs, auditing mixed populations and participant independence, and reporting prediction intervals and certainty. Given very low certainty, the findings support locally adapted, exploratory AI-literacy planning and standardized measurement in future studies rather than strong claims about curriculum effectiveness.

PMID:42612090 | DOI:10.2196/89411

JMIR Nurs. 2026 Aug 18;9:e92533. doi: 10.2196/92533.

ABSTRACT

BACKGROUND: Enhancing nursing students’ awareness, attitudes, beliefs, and preparedness toward AI may help improve their health care knowledge and practice.

OBJECTIVE: This study aimed to assess nursing students’ attitudes, perceptions, self-efficacy, barriers, and anxiety, which influence their readiness to adopt AI in nursing practice.

METHODS: This study used a cross-sectional, correlational design. Data were collected from 307 nursing internship students using an 8-part, self-administered questionnaire.

RESULTS: Increased self-efficacy with computers was correlated with decreased barriers to accessing AI technology, lower computer anxiety scale scores (r=-0.27, P<.001 and r=-0.57, P<.001, respectively), and higher perceptions of using AI (r=0.27, P<.001). Meanwhile, nursing students’ readiness to adopt AI in nursing practice was negatively associated with barriers to accessing AI technology (r=-0.20, P<.001) and positively associated with attitudes toward and perceptions of using AI (r=0.32, P<.001 and r=0.14, P=.01, respectively). Increased barriers to accessing AI technology were associated with negative attitudes toward AI and nursing students’ perceptions of using AI (r=-0.34, P<.001 and r=-0.39, P<.001, respectively). A multilayer neural network model identified barriers (relative importance=0.27), attitudes (relative importance=0.16), and perceptions (relative importance=0.15) as the most significant predictors, while self-efficacy (relative importance=0.11) and anxiety (relative importance=0.07) showed smaller contributions, despite nonsignificant bivariate associations with nursing students’ AI readiness. The model demonstrated strong predictive performance, achieving a low relative error of 0.62 in the training set. The stability and generalization ability of the model were supported by the training and testing set results, which yielded a training sum of squares error of 65.93 and a testing sum of squares error of 35.49, showing no signs of overfitting.

CONCLUSIONS: Several contributing factors influenced nursing students’ readiness to embrace AI, with barriers, attitudes, and perceptions emerging as the most consistent, whereas self-efficacy and anxiety may play indirect roles. To improve the adoption of AI among nursing students, such factors should be dealt with in such educational programs; an interrelated adoption of AI in nursing practice is expounded as a more favorable environment.

PMID:42612089 | DOI:10.2196/92533