Tag: pubmed

Eur Stroke J. 2026 Jun 2;11(6):aakag047. doi: 10.1093/esj/aakag047.

ABSTRACT

INTRODUCTION: Guidelines recommend cognitive screening post-stroke, but there is no consensus on approach. Given the dynamic nature of cognition following stroke, acute screening should both detect prevalent issues (diagnosis) and predict persisting problems (prognosis). We describe the diagnostic and prognostic utility of brief cognitive screening tools.

PATIENTS AND METHODS: Patients were screened on admission with stroke using 12 modified screening tests: 10 and 4 question Abbreviated Mental Test, Cog-4, Clock Drawing test (CDT), Cognitive Impairment Test, informal bedside assessment, General Practitioner Assessment of Cognition, Minicog, Short Form Montreal Cognitive Assessment, Six-Item Screener (SIS), Harmonised Vascular Cognitive Impairment battery and 4-A’s Test. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value were calculated against a Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition adjudicated reference standard of neurocognitive disorders. Test accuracy was compared using area under the receiver operator characteristic curves.

RESULTS: Of 335 patients, 54 (16.1%) had pre-stroke neurocognitive disorder, 79 (23.6%) had 18-month neurocognitive disorder. Ten of 12 screening tests were more specific than sensitive. Informal bedside assessment had highest specificity (96%), but low sensitivity (9%); CDT had highest sensitivity (80%) but low specificity (33%). Negative predictive value ranged from 77% to 87%, PPV ranged from 27% to 54%. Area under the receiver operator characteristic curve ranged 0.53 (informal bedside assessment) to 0.69 (SIS).

DISCUSSION: In the acute setting, where the intention of screening is often to triage those who need further assessment, the pattern of high specificity at the expense of sensitivity is the opposite of what is desired.

CONCLUSION: Brief cognitive screening tools, used in isolation, may not be suitable for assessment in acute stroke settings.

PMID:42302274 | DOI:10.1093/esj/aakag047

Arch Clin Neuropsychol. 2026 May 29;41(5):acag046. doi: 10.1093/arclin/acag046.

ABSTRACT

OBJECTIVE: The study aims to examine the relationship between subjective cognitive complaints (SCC) and objective cognitive performance (OCP) in severe mental disorders, including schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD).

METHOD: Systematic literature searches were conducted using Web of Science and PubMed, including articles published until September 2025. Studies were included if they assessed both SCC and OCP using validated instruments in individuals diagnosed with SCZ, BD, or MDD and were peer-reviewed English research articles. A series of meta-analyses was conducted using random-effects models to examine the associations between SCC and composite OCP scores, as well as the subdomains of objective cognition. Analyses were repeated for each diagnosis.

RESULTS: The sample included 49 articles with 5,007 participants. Our analyses yielded a small but statistically significant correlation between SCC and global OCP (r = -0.145). Domain-wise associations indicated correlations between SCC and OCPs in processing speed, attention/vigilance, working memory, and verbal learning/memory (correlation coefficients ranged from -0.107 to -0.172). In diagnosis-specific analyses, individuals with SCZ showed significant associations in all domains except executive function. In contrast, the associations were restricted to only a few cognitive domains in other disorders, specifically processing speed and working memory in BD, and processing speed and attention/vigilance in MDD.

CONCLUSIONS: Although significant, the strength of these associations was small, suggesting that SCC explains only a limited proportion of the variance in OCP. This suggests that while SCC cannot substitute for objective testing, it provides complementary information that reflects patients’ experiences of cognitive dysfunction.

PMID:42302271 | DOI:10.1093/arclin/acag046

Arch Clin Neuropsychol. 2026 May 29;41(5):acag045. doi: 10.1093/arclin/acag045.

ABSTRACT

OBJECTIVE: Contemporary clinical neuropsychologists primarily provide assessment and consultative services rather than direct intervention. This study examined the extent to which cognitive rehabilitation remains part of contemporary neuropsychological practice and explored reimbursement pathways and perceived barriers to implementation.

METHOD: An anonymous national survey was distributed to members of the National Academy of Neuropsychology through listserv and newsletter announcements. The survey included structured multiple-choice and open-ended questions assessing whether respondents provide cognitive rehabilitation, years of practice, clinical setting, insurance reimbursement patterns, and experiences with insurance denials. Descriptive statistics were used to summarize responses.

RESULTS: Twenty-two respondents completed the survey. Eighteen (81.8%) reported currently providing cognitive rehabilitation services. Reimbursed Current Procedural Terminology (CPT) codes most commonly included 97129/97130 (54.5%) and 96116/96121 (45.5%), with additional endorsement of health and behavior intervention codes (96158/96159) and group therapy codes (97150). Insurance denial experiences were mixed, with most respondents reporting occasional or conditional denials rather than consistent rejection of claims. Respondents also described variability in session limits and billing approaches across practice settings and payer policies.

CONCLUSIONS: Cognitive rehabilitation was reported by a majority of respondents, though service models and reimbursement pathways varied considerably. Given the small, self-selected sample, findings should be interpreted as exploratory rather than representative of broader neuropsychological practice. Larger investigations are needed to clarify training expectations, billing practices, and interdisciplinary collaboration.

PMID:42302270 | DOI:10.1093/arclin/acag045

JMIR Aging. 2026 Jun 16;9:e79797. doi: 10.2196/79797.

ABSTRACT

BACKGROUND: Home telemonitoring programs are increasingly used to support older adults living with chronic conditions such as heart failure (HF). While these interventions show promise for improving health outcomes and reducing care burden, their effectiveness depends largely on how patients and caregivers integrate digital technologies into everyday life and care relationships. However, relatively few studies have examined these experiences using conceptual frameworks that capture both functional and relational dimensions of care.

OBJECTIVE: This study aimed to explore the experiences of older adults and their informal caregivers participating in a home telemonitoring program for HF. Drawing on the Person-Based Approach and the Person-Centered Practice frameworks, we examined how participants engaged with both the technofunctional and relational aspects of the intervention.

METHODS: We conducted a qualitative study involving 34 patients, 28 informal caregivers, and 20 nurses across 3 primary care organizations in Quebec, Canada. The 6-month intervention included 4 connected devices used by patients (smartwatch, Bluetooth-enabled scale, voice-activated tablet, and a smart pill dispenser [xPill; Domedic]) and a mobile app for caregivers, complemented by remote nursing follow-up. Nurses reviewed patient data through a clinical dashboard at least once daily during weekday daytime shifts. Data were collected through semistructured interviews and field notes and analyzed using directed content analysis.

RESULTS: Participants’ experiences revealed both enabling and constraining factors across 2 key dimensions. Technofunctional engagement was shaped by digital literacy, emotional responses to the technology, alignment with daily routines, and access to technical or caregiver support. Relational aspects of care were influenced by perceived professional presence, opportunities for communication and shared decision-making, and the degree of emotional reassurance provided by remote monitoring. While many participants reported increased confidence and a sense of being supported, others experienced frustration, fatigue, or disengagement when the system disrupted routines or when feedback from clinicians was perceived as limited.

CONCLUSIONS: Engagement with home telemonitoring technologies among older adults depends not only on usability but also on the relational context in which these technologies are embedded. Combining technofunctional and relational perspectives provides a more comprehensive understanding of how telemonitoring interventions are experienced and highlights the importance of personalized support, reliable technology, and sustained clinical engagement to promote meaningful adoption.

PMID:42302267 | DOI:10.2196/79797

JMIR Form Res. 2026 Jun 16;10:e89820. doi: 10.2196/89820.

ABSTRACT

BACKGROUND: An estimated 5 to 8 million US children live with a parent who uses cannabis, and most cannabis users report smoking cannabis inside their homes, placing children at risk for cannabis secondhand smoke (cSHS) exposure. Indoor air quality (IAQ) monitoring provides real-time feedback on airborne pollutants and has shown promise in reducing in-home tobacco secondhand smoke exposure, suggesting its potential as an effective harm reduction strategy for cSHS.

OBJECTIVE: This pilot study evaluated the feasibility, acceptability, and preliminary effectiveness of using low-cost, off-the-shelf IAQ monitors to increase caregivers’ awareness of children’s cSHS exposure risk and to change smoking behavior. Secondary aims were to assess participant engagement, perceived usefulness, and household communication regarding in-home cannabis smoking.

METHODS: Between February 2025 and April 2025, 14 adults who smoked cannabis indoors and lived with at least 1 child aged younger than 16 years were recruited primarily via targeted social media advertisements and completed a 3-week trial. Participants received an Awair Element IAQ monitor, printed health education materials, and text messaging prompts for brief surveys. The IAQ monitor continuously measured PM2.5, VOCs, CO₂, temperature, and humidity. Daily surveys captured self-reported PM2.5 readings and recent cannabis use, while baseline and end-of-study assessments evaluated IAQ perceptions, cSHS risk awareness, and in-home smoking behavior. Survey results were summarized via descriptive statistics, and linear mixed-effects models were used to characterize objective IAQ trends. Six additional adult household members provided parallel end-of-study data.

RESULTS: Reported engagement was high, with 85% (11/13) of participants indicating that they reviewed the monitor at least daily. The average number of days in the previous week that a caregiver reported a child being home while cannabis was smoked declined from 4.5 (SD 2.2) at the trial start to 2.8 (SD 2.9) at the end (6/13, 46% had a reduction; 1/13, 8% reported an increase). Furthermore, 62% (8/13) of participants reported that they reduced (4/13, 31%) or thought about changing (4/13, 31%) their smoking habits. Around 62% (8/13) of participants agreed or strongly agreed that IAQ monitoring helped drive conversations about changing indoor smoking rules, while 100% (13/13) reported no IAQ-driven disagreements among household residents regarding in-home smoking rules. A linear mixed-effects model did not indicate a consistent trend in PM2.5 levels across participants over time (β=-0.28; SE 1.13; P=.81), but there was heterogeneity in trends, and those with the largest reductions in PM2.5 over the trial had the largest reduction in reported children’s cSHS exposure.

CONCLUSIONS: In-home IAQ monitoring was feasible and perceived as useful among caregivers who smoked cannabis indoors. Real-time IAQ feedback supported risk awareness, promoted family dialogue, and coincided with reductions in in-home smoking around children. These findings suggest that IAQ feedback may represent a scalable tool for reducing children’s cSHS exposure and merits further testing in larger, controlled trials.

PMID:42302266 | DOI:10.2196/89820

JMIR Aging. 2026 Jun 16;9:e95286. doi: 10.2196/95286.

ABSTRACT

BACKGROUND: Access to geriatric mental health (GMH) care is limited in rural areas. To meet this need, the Veterans Health Administration provides specialty tele-GMH care for aging rural veterans via regional telehealth hubs.

OBJECTIVE: This study aims to create a roadmap describing key phases and determinants underlying the implementation and sustainment of tele-GMH services as part of a qualitative longitudinal evaluation of tele-GMH teams.

METHODS: Semistructured interviews were conducted with clinicians from all 8 tele-GMH teams (n=25) at 3 time points across a 3-year period (October 2021-September 2024). Interview (n=46) data were summarized into key domains using a templated rapid qualitative approach, guided by the Consolidated Framework for Implementation Research (CFIR) 2.0. Further thematic analysis and team discussion elucidated the findings.

RESULTS: We identified key activities and determinants of success in three phases: (1) preimplementation (engaging leaders, securing funding/hiring, and defining services); (2) implementation scale-up and expansion (advertising, addressing challenges, seeking feedback, refining, and growth); and (3) sustainment (maintenance). Activities within each phase were cyclical and iterative (ie, nonlinear). Barriers to implementation included unfamiliarity with local aging resources; facilitators included tailoring strategies and engaging referring clinicians.

CONCLUSIONS: Similar processes emerged across regions in the development and sustainment of tele-GMH services, allowing for the creation of a unified roadmap. Limitations including sampling bias are discussed. Further work could apply and evaluate the utility of the roadmap to guide creation of tele-GMH services in new regions to enhance access to specialty care for aging rural veterans.

PMID:42302264 | DOI:10.2196/95286

JMIR Med Educ. 2026 Jun 16;12:e75516. doi: 10.2196/75516.

ABSTRACT

BACKGROUND: Pretest-posttest designs are widely used to estimate learning gain in studies evaluating educational interventions in medical education. The Weighted Gain Score (WGS) was proposed to reduce bias associated with differences in baseline performance.

OBJECTIVE: This study evaluated the statistical and inferential properties of the WGS by comparing it to Rasch Learning Gain (RLG) across 3 datasets.

METHODS: The WGS implements a weighting coefficient that includes the parameter µ, which linearly rescales the difference between pretest and posttest percentage scores. We examined the effect of varying µ (30, 50, and 70) on learning gain calculations and compared the results with those obtained using RLG. The following three datasets were analyzed: (1) a small illustrative dataset demonstrating the mathematical behavior of the WGS, (2) an empirical dataset from a previous educational evaluation study, and (3) a randomly generated binomial dataset designed to examine the metric under larger sample conditions.

RESULTS: Changing the parameter µ in the WGS affected the magnitude of the calculated learning gains: lower µ-values produced larger gain estimates, whereas higher µ-values produced smaller estimates. Despite these differences in scale, the WGS and RLG correlated strongly in both the empirical dataset (r=0.93; P<.001) and the simulated dataset (r=0.92; P<.001); variation in µ did not alter the inferential results. Both methods identified the same interaction effect in the empirical dataset.

CONCLUSIONS: The WGS produced results highly consistent with those of RLG while requiring substantially lower computational complexity. The metric can be applied to both small and large datasets and allows µ to function as an adjustment coefficient for calibrating learning gain estimates across cohorts without altering inferential conclusions.

PMID:42302261 | DOI:10.2196/75516

J Ultrasound Med. 2026 Jun 16. doi: 10.1002/jum.70337. Online ahead of print.

NO ABSTRACT

PMID:42302255 | DOI:10.1002/jum.70337

JMIR Form Res. 2026 Jun 16;10:e89302. doi: 10.2196/89302.

ABSTRACT

BACKGROUND: Virtual reality (VR) systems are increasingly used in rehabilitation to facilitate motor learning by providing visual feedback. However, few studies have validated the motion tracking accuracy of VR devices compared with gold-standard motion capture systems. In particular, validation evidence for upper-limb reaching with commercially available VR tracking setups remains limited.

OBJECTIVE: This study aimed to evaluate the validity of a custom VR-based rehabilitation system (VRactice) by comparing its motion tracking data with that of a Vicon motion capture system during a goal-directed reaching task in healthy adults.

METHODS: This laboratory-based validation study was conducted at Tokyo Kasei University, Sayama Campus, Japan (August-December 2023). Participants were recruited via posted announcements on campus (convenience sampling) and received a 1000 JPY gift card (US $7.00; JPY 142.79=US $1 as of August 1, 2023). A total of 16 healthy participants (n=6, 37.5% male and n=10, 62.5% female participants; mean age 25.3, SD 4.56 years; all right-handed) performed reaching tasks in a VR environment while being tracked simultaneously by both the VRactice system and a Vicon system. Trackers and reflective markers were attached to the hand and elbow to capture 3D coordinates. Each participant performed 10 reaching trials at a frequency of 1 Hz. Data were upsampled to 100 Hz, synchronized, and normalized to the initial position. Valid cycles were identified, and distance time series from the initial position were extracted for the 500-millisecond interval preceding the peak displacement. For each participant, all valid cycles were pooled, and the coefficient of determination (R2) between VRactice and Vicon trajectories was calculated. Of 160 planned trials (16 participants×10 trials), 4 (2.5%) trials were not recorded; the remaining 156 (97.5%) trials were analyzed without imputation. Statistical significance was evaluated at a 2-sided α level of .05.

RESULTS: Strong agreement between VRactice and Vicon was observed at both the individual and group levels. The R2 ranged from 0.75 to 0.99 across participants, and all comparisons were statistically significant (P<.001). Deviations between the 2 systems remained minimal, confirming that VRactice reliably reproduced the temporal and spatial characteristics of reaching trajectories. At peak displacement, the participant-level mean absolute difference (mean of 10 trials per participant) was 36.5 (SD 29.3) mm (95% CI 20.9-52.1), suggesting spatial agreement that may be acceptable for upper-limb reaching measurements in this experimental context.

CONCLUSIONS: The findings support the validity of VRactice in capturing reaching movements with high spatial accuracy compared with a motion capture system. By providing reliable motion data, VRactice may serve as a useful platform for delivering real-time visual feedback and supporting motor training applications in rehabilitation settings. This study is innovative in that it provides formative validity evidence for a VR-based system that integrates real-time trajectory monitoring with adaptive visual guidance, supporting subsequent clinical implementation and evaluation.

PMID:42302247 | DOI:10.2196/89302

J Chem Inf Model. 2026 Jun 16. doi: 10.1021/acs.jcim.6c00965. Online ahead of print.

ABSTRACT

High-dimensional feature spaces combined with limited sample sizes present substantial challenges for biological prediction tasks. Traditional feature selection methods rely on statistical associations between features and labels, whereas causal feature selection identifies features causally related to the target, improving the interpretability and robustness. Among them, constraint-based methods identify the Markov blanket of the target variable through the conditional independence tests. However, existing constraint-based ensemble strategies are computationally demanding, particularly during the spouse-discovery stage. To address this limitation, we propose EECFS, a novel ensemble causal feature selection algorithm that reduces the computational cost through an efficient spouse discovery strategy. Extensive evaluations on 16 Bayesian network datasets and 17 real-world datasets demonstrate that EECFS achieves improved efficiency while maintaining competitive or superior predictive performance compared with 11 representative methods. Furthermore, we extend causal feature selection to the task of synonymous variant effect prediction and developed CFDPSM. From an initial pool of 23 866 features spanning DNA, RNA, and protein molecular levels, CFDPSM identifies a compact set of 30 Markov blanket features. The experimental results show that it outperforms 13 existing variant effect prediction methods while providing enhanced interpretability.

PMID:42302235 | DOI:10.1021/acs.jcim.6c00965