Nevin Manimala

Soc Psychiatry Psychiatr Epidemiol. 2026 Jan 19. doi: 10.1007/s00127-025-03044-6. Online ahead of print.

ABSTRACT

PURPOSE: Physical illness describes long-term physical health conditions such as asthma, diabetes, and epilepsy. Mental or neurodevelopmental disorder (MND) that co-occurs with physical illness in childhood is associated with poorer outcomes for children and their families. There is a need for contemporary estimates of physical-MND burden to inform resource allocation and reduce occurrence. This descriptive study estimated the prevalence of morbidity status and compared prevalence of MNDs among children with or without physical illness.

METHODS: Data come from the 2019 Canadian Health Survey on Children and Youth, a representative cross-sectional study conducted by Statistics Canada. Physical illnesses and MNDs were reported by the person most knowledgeable about the child.

RESULTS: The sample included children aged 5 to 17 years (n = 33,715). In total, 49.5% of children had at least one physical illness and 17.9% had at least one MND. Physical-MND multimorbidity was reported for 9.8% of children. Among children with any physical illness, MNDs were present in 19.9%. Among children with no physical illness, the prevalence of MNDs was 14.1%. Differences in prevalence of MNDs across types of physical illnesses were small in magnitude (h=-0.02 to 0.35).

CONCLUSION: Findings show that childhood physical-MND multimorbidity is common, highlighting the need for screening of MNDs among Canadian children with physical illness. Integrated care models are necessary to comprehensively address the physical and MND health needs of children. These estimates of morbidity snapshot the time immediately prior to the COVID-19 pandemic and have critical utility as baselines for future post-COVID-19 studies.

PMID:41555082 | DOI:10.1007/s00127-025-03044-6

Soc Psychiatry Psychiatr Epidemiol. 2026 Jan 19. doi: 10.1007/s00127-025-03036-6. Online ahead of print.

ABSTRACT

PURPOSE: To estimate how social disparities in child psychiatric symptoms might change following hypothetical interventions targeting sports, outdoor play, and screen time at age 10.

METHODS: We used data from 9,778 children of the Generation R Study, a prospective population-based cohort in Rotterdam, the Netherlands. Social inequality variables included sex, maternal education, and migration background. Primary caregivers filled out the validated Child Behavior Checklist to report on children’s internalizing and externalizing symptoms at the age of 13. The hypothetical interventions (i.e., outdoor play, sports participation, and screen time) were parent-reported at age 10. We used sequential G-estimation to estimate the inequality with and without the hypothetical intervention.

RESULTS: Children with migration backgrounds (46.3%) and low maternal education (53.3%) were associated with relatively more internalizing and externalizing symptoms than peers, with disparities of 0.125 and 0.177 standard deviations, respectively. Girls had more internalizing symptoms (0.106 SD), while boys had more externalizing symptoms (0.154 SD). Increasing sports participation reduced disparities in internalizing symptoms linked to maternal education (β = -0.014; 95% CI: -0.024, -0.003), while outdoor play and screen time interventions showed limited effects. None of the hypothetical interventions led to a statistically significant reduction in social disparities in externalizing symptoms.

CONCLUSIONS: This study underscores the persistence of sex, cultural, and socioeconomic disparities in youth mental health. While sports participation showed a potential effect in reducing disparities in internalizing symptoms, its impact on externalizing symptoms and other interventions was negligible. Future efforts should focus on identifying more effective strategies for addressing these disparities.

PMID:41555079 | DOI:10.1007/s00127-025-03036-6

Environ Monit Assess. 2026 Jan 19;198(2):147. doi: 10.1007/s10661-026-14981-3.

ABSTRACT

Assessing changes in mean sea level (MSL) has become increasingly critical due to the significance of climate changes. Soft computing techniques are now widely used to reduce the time and cost associated with traditional MSL estimation methods. Historical MSL data is frequently used to predict future values, yet the application of soft computing models to analyze climate change’s impact on MSL remains relatively unexplored. This study aims to develop and compare various soft computing techniques for modeling MSL fluctuations using meteorological data. Random forest (RF), support vector regression (SVR), K-nearest neighbors (KNN) regression, deep neural network (DNN), Gaussian process regression (GPR), and stacked ensemble methods are employed in this study. The newly developed models are statistically assessed for their effectiveness in modeling MSL at Damietta station, Egypt. Variables environmental data such as surface water temperature, pressure, air temperature (average air temperature, dewpoint, wet-bulb, and heat index), and humidity and wind attributes (speed and direction) are utilized and evaluated in modeling MSL. The results indicate that RF, KNN, and GP outperformed other proposed models in modeling MSL during both training and testing phases. The developed weighted stacked ensemble model, integrating RF, KNN, and GPR, outperformed the base models with a correlation coefficient (R) of 0.88 and normalized root mean square error (RMSE) of 0.056 m. MSL modeling at the study station was particularly sensitive to variations in water temperature, wind speed and direction, and atmospheric pressure. This methodology serves as a valuable framework for climate-driven MSL forecasting in developing coastal regions lacking long-term tide records, directly contributing to UNESCO’s Ocean Decade Challenge 5 on coastal resilience.

PMID:41555074 | DOI:10.1007/s10661-026-14981-3

Nat Protoc. 2026 Jan 19. doi: 10.1038/s41596-025-01300-2. Online ahead of print.

ABSTRACT

Neural activity data can be associated with behavioral and physiological variables by analyzing their changes in the temporal domain. However, such relationships are often difficult to quantify and test, requiring advanced computational modeling approaches. Here, we provide a protocol for the statistical analysis of brain dynamics and for testing their associations with behavioral, physiological and other non-imaging variables. The protocol is based on an open-source Python package built on a generalization of the hidden Markov model (HMM)-the Gaussian-linear HMM-and supports multiple experimental modalities, including task-based and resting-state studies, often used to explore a wide range of questions in neuroscience and mental health. Our toolbox is available as both a Python library and a graphical interface, so it can be used by researchers with or without programming experience. Statistical inference is performed by using permutation-based methods and structured Monte Carlo resampling, and the framework can easily handle confounding variables, multiple testing corrections and hierarchical relationships within the data, among other features. The package includes tools developed to facilitate the intuitive visualization of statistical results, along with comprehensive documentation and step-by-step tutorials for data interpretation. Overall, the protocol covers the full workflow for the statistical analysis of functional neural data and their temporal dynamics.

PMID:41555071 | DOI:10.1038/s41596-025-01300-2

Int J Colorectal Dis. 2026 Jan 19;41(1):37. doi: 10.1007/s00384-025-05075-6.

ABSTRACT

BACKGROUND: An enhanced recovery protocol (ERP) comprises a series of elements aimed at optimizing and standardizing perioperative care. Therefore, in this study, we aimed to evaluate the safety and feasibility of a modified enhanced recovery after surgery (ERAS) protocol following colorectal surgery in older adults aged ≥ 65 years.

MATERIALS AND METHODS: Patients aged ≥ 65 years who underwent minimally invasive colorectal cancer surgery at a tertiary referral hospital in Taiwan between 2018 and 2022 were reviewed retrospectively. Patients were divided into ERAS and traditional care groups according to the perioperative care strategy. The primary outcome was the short-term complication rate. However, the secondary outcomes were postoperative hospital stay, reoperation, readmission, and 30-day mortality rates.

RESULTS: Overall, 1392 patients were enrolled, including 550 and 842 in the ERAS and traditional care groups, respectively. Demographic characteristics, including comorbidities, perioperative characteristics, and pathological staging, were not statistically significant. The patients’ short-term complication rate was lower in the ERAS group (aged 65-80 years) than in the traditional care group (29 (7.2%) vs. 75 (11.5%), P = 0.026). However, the short-term complication rate did not differ between patients aged > 80 years (24 (16%) vs. 36 (19%), P = 0.438). In addition, the mean postoperative hospital stay was shorter in the ERAS group (7.5 ± 8.9 days vs 9.7 ± 10.0 days, P < 0.001). However, there were no differences in other secondary outcomes, including reoperation, readmission, and 30-day mortality rates.

CONCLUSION: Minimally invasive colorectal cancer surgery within the ERAS program is safe and effective in patients aged 65-80 years.

PMID:41555061 | DOI:10.1007/s00384-025-05075-6

Nat Med. 2026 Jan 19. doi: 10.1038/s41591-025-04176-7. Online ahead of print.

ABSTRACT

Patient-facing large language models (LLMs) hold potential to streamline inefficient transitions from primary to specialist care. We developed the preassessment (PreA), an LLM chatbot co-designed with local stakeholders, to perform the general medical consultations for history-taking, preliminary diagnoses, and test ordering that would normally be performed by primary care providers and to generate referral reports for specialists. PreA was tested in a randomized controlled trial involving 111 specialists from 24 medical disciplines across two health centers, where 2,069 patients (1,141 women; 928 men) were randomly assigned to use PreA independently (PreA-only), use it with staff support (PreA-human), or not use it (No-PreA) before specialist consultation. The trial met its primary end points with the PreA-only group showing significantly reduced physician consultation duration (28.7% reduction; 3.14 ± 2.25 min) compared to the No-PreA group (4.41 ± 2.77 min; P < 0.001), alongside significant improvements in physician-perceived care coordination (mean scores 113.1% increase; 3.69 ± 0.90 versus 1.73 ± 0.95; P < 0.001) and patient-reported communication ease (mean scores 16.0% increase; 3.99 ± 0.62 versus 3.44 ± 0.97; P < 0.001). Equivalent outcomes between the PreA-only and PreA-human groups confirmed the autonomous operation capability. Co-designed PreA outperformed the same model with additional fine-tuning on local dialogues across clinical decision-making domains. Co-design with local stakeholders, compared to passive local data collecting, represents a more effective strategy for deploying LLMs to strengthen health systems and enhance patient-centered care in resource-limited settings. Chinese Clinical Trial Registry identifier: ChiCTR2400094159 .

PMID:41555035 | DOI:10.1038/s41591-025-04176-7

Eur J Obstet Gynecol Reprod Biol. 2026 Jan 14;318:114967. doi: 10.1016/j.ejogrb.2026.114967. Online ahead of print.

ABSTRACT

BACKGROUND: Long-acting reversible contraceptives (LARCs), including subdermal contraceptive implants (SCIs), are widely used and highly effective. General practitioners (GPs) provide most implant services, but little is known about their confidence, awareness of updated guidelines, and approaches to complications in the Irish setting.

AIM: To assess GPs’ experience, confidence, awareness of guidelines, and management of complications related to SCIs.

METHODS: We conducted a prospective quantitative survey of 100 randomly selected GPs in Ireland. A validated 12-item questionnaire was distributed via Qualtrics, with 74 complete responses analysed in SPSS v29.0. Frequency data and chi-square tests with Cramer’s V were used to assess associations between experience, confidence, and guideline awareness.

RESULTS: A total of n = 74 full responses were collected. Results showed that while a majority (94.6 %) have inserted subdermal contraceptive implants, confidence levels varied, with 37.3 % feeling confident in insertion and removal procedures. Notably, 39.2 % were unaware of updated guidelines from January 2020. Statistical analyses revealed significant associations between general practitioners’ reported experience in subdermal contraceptive implant procedures and confidence in these skills (p < 0.001), as well as awareness of guidelines (p = 0.011). General practitioners with greater experience tended to refer complicated cases to specialist services, contrasting with less experienced peers managing cases independently.

CONCLUSION: This study underscores the need for enhanced General Practitioners’ training on subdermal contraceptive implant procedures and guideline updates to optimise service delivery. Given the increasing popularity of subdermal contraceptive implants, addressing these gaps is crucial for ensuring safe and effective contraceptive care in primary care settings.

PMID:41554227 | DOI:10.1016/j.ejogrb.2026.114967

Public Health. 2026 Jan 18;252:106146. doi: 10.1016/j.puhe.2026.106146. Online ahead of print.

ABSTRACT

OBJECTIVES: To protect workers and individuals from second-hand smoke exposure, Japan’s national indoor smoking ban was enforced on April 1, 2020. However, certain exemptions were made for eating and drinking establishments. Local ordinances restricted these exemptions to increase their effectiveness. We aimed to evaluate the 2-year impact of the national ban and local ordinances on indoor smoking policies in eating and drinking establishments over a 2-year period.

STUDY DESIGN: Panel data analysis.

METHODS: From a commercial database of eating and drinking establishments, we used area-level summary data of 320,693 establishments for August 2016 and individual establishment data extracted biannually between January 2020 and December 2022 (n = 329,322 to 403,133). We calculated the category-specific and weighted proportions of smoke-free establishments. We analysed the short-term and trend changes using an interrupted time-series analysis.

RESULTS: The proportion of smoke-free establishments increased after the national ban (+5.7 % points). Local ordinances restricting the exemption for the establishments with non-family employees enhanced the impact of the national ban (+7.8 % points). In December 2022, the proportions of smoke-free establishments were 68.3 % in restaurants, 70.2 % in cafés, 32.8 % in izakaya, and 25.0 % in bars.

CONCLUSIONS: The indoor smoking ban has promoted indoor smoke-free policies in eating and drinking establishments in Japan. However, many establishments, nearly two-thirds of izakaya and bars, remain smoking-allowed, probably owing to exemptions and non-compliance. To effectively reduce second-hand smoke exposure in eating and drinking establishments, it is necessary to minimise exemptions by revising laws or enforcing additional ordinances and promoting compliance with these legislations.

PMID:41554192 | DOI:10.1016/j.puhe.2026.106146

Conscious Cogn. 2026 Jan 18;139:103979. doi: 10.1016/j.concog.2025.103979. Online ahead of print.

ABSTRACT

This study presents the first comprehensive psychometric comparison of Greyson’s (1983) 16-item Near-Death Experience Scale (NDE Scale) and Martial et al.’s (2020) 20-item Near-Death Experience Content Scale (NDE-C) using Rasch modeling and differential item functioning (or response bias) analyses. A total of 705 self-identified “near-death experiencers” (64% women) completed both measures, which were randomly intermingled and rated for experiential relevance. Results confirmed that the two scales measure the same underlying construct of NDE phenomenology, as evidenced by a near-perfect disattenuated Pearson correlation (r = 0.98, p < 0.001). However, Rasch analysis revealed limitations in the category structures of both scales-particularly the NDE-C-and identified psychometric and conceptual weaknesses in its five novel items. Critically, the core Rasch item hierarchy derived from the original NDE Scale was replicated both in this sample and a previously simulated dataset based on the NDE-C’s development research, confirming its long-term structural stability. Based on the present evidence and the principle of parsimony, we recommend the original NDE Scale supported by Rasch scoring and a validated cut-off of 7 (out of 32), as it is conceptually coherent and psychometrically robust, while maintaining historical comparison with previous research. These findings reinforce the value of Rasch modeling for cumulative theory-building and underscore the Rasch NDE hierarchy’s foundational role in operationalizing legitimate near-death experiences.

PMID:41554189 | DOI:10.1016/j.concog.2025.103979

West J Emerg Med. 2025 Dec 19;27(1):25-32. doi: 10.5811/westjem.47392.

ABSTRACT

INTRODUCTION: Free Open Access Medical Education (FOAMed) has emerged as a prominent component of online medical communication, with X (formerly Twitter) serving as an active hub for professional exchange among clinicians. Despite its reach and influence, few longitudinal studies have examined how FOAMed content and engagement patterns evolve over time. In this study we aimed to analyze thematic shifts and user interaction trends in #FOAMed tweets over a five-year period.

METHODS: We conducted a retrospective bibliometric and natural language processing (NLP) study of 6,000 high-engagement, English-language tweets tagged with #FOAMed, posted between January 1, 2020-December 31, 2024. Each month, the 100 tweets were selected from Twitter’s “Top” tab and manually curated. We used latent Dirichlet allocation (LDA) to identify thematic clusters. Hashtag usage and engagement metrics were assessed using descriptive statistics and linear regression.

RESULTS: We identified 10 distinct topics were identified through LDA modeling: point-of-care ultrasound (POCUS) education; neuro-radiology, cardiology-electrocardiogram (ECG); nephrology; and intensive care unit; ultrasound; prehospital/policy; webinars and learning; resuscitation scenarios; pediatric imaging; medical student education; and critical care and publications. Topic prevalence shifted over time: Early tweets focused on COVID-19 and critical care, while later years showed increasing attention to prehospital care, diagnostics, and POCUS. Mean tweet engagement peaked in 2023 (236.9 ± 914.6). Notably, hashtags such as #POCUS and #MedEd showed substantial increases in both usage and engagement, with #MedEd reaching a peak mean engagement of 287.7. In contrast, COVID-19 declined steadily, both in frequency (from 126 tweets in 2020 to just six in 2023) and in engagement (mean: 67.1 → 18.5). Spearman correlation analysis revealed that hashtag count had a weak but statistically significant correlation with engagement (ρ = 0.047, P < .001), suggesting that content quality, rather than volume, was the primary driver of visibility.

CONCLUSION: FOAMed discourse on Twitter/X remains dynamic, responsive to clinical priorities and shaped by peer interaction. Natural language processing and topic modeling are valuable tools to uncover longitudinal trends in digital medical education, reinforcing Twitter/X’s role in informal, real-time learning communities.

PMID:41554176 | DOI:10.5811/westjem.47392