Tag: pubmed

J Autism Dev Disord. 2026 May 22. doi: 10.1007/s10803-026-07347-8. Online ahead of print.

ABSTRACT

PURPOSE: This study investigated the risk of ASD and ADHD in children who have survived hypoxic-ischemic encephalopathy (HIE), one of the common conditions during birth resulting in neonatal brain injury.

METHODS: A population-based cohort study analyzed electronic medical records of term infants with HIE born in public hospital in Hong Kong from 1st January 2004 to 31st December 2018 with followed-up until 31st Dec 2024. The association of HIE with ADHD and ASD was examined using log-binomial regression models adjusting sequentially for age, sex, and socioeconomic status (SES).

RESULTS: A total of 533,230 children were included of which 349 cases had a diagnosis of HIE. Compared to children without history of HIE, the RR of ADHD in children with HIE was 1.94 (CI 1.40-2.68, p < 0.001) in the unadjusted model, 1.83 (CI 1.32, 2.52, p < 0.001) when adjusting for age & sex, and 1.84 (CI 1.34, 2.55, p < 0.001) when adjusting for age, sex and socioeconomic status (SES). The relationship between ASD and HIE did not reach statistical significance, RR = 1.58 (p = 0.08, CI 0.93, 2.68) adjusted for age, sex and SES. A significant interaction effect was found between HIE and the age of mothers, the RR of ADHD was 4.25 (CI 2.14, 8.46) in mothers under 24 years of age.

CONCLUSION: Children with HIE, especially those born to younger mothers, were associated with elevated risk of ADHD. The relationship between ASD and HIE remained inconclusive, suggesting the need for further research to clarify this potential association.

PMID:42171963 | DOI:10.1007/s10803-026-07347-8

J Cross Cult Gerontol. 2026 May 22;41(2):31. doi: 10.1007/s10823-026-09580-1.

ABSTRACT

Perceived barriers and motivational factors may influence the adherence of older adults to physical exercise. Considering these variables, this study investigated the association between barriers and motivation for physical exercise among older adults. This cross-sectional study included 225 older adults engaged in physical exercise at private gyms, senior fitness centers, and sports centers in Maringá, Paraná, Brazil. The Exercise Motivation Inventory (EMI-2) and the Questionnaire on Barriers to Physical Activity Practice in Older Adults (QBPAFI) were used. Statistical analyses included descriptive statistics, Pearson’s correlation, multiple regression, and cluster analysis. Results indicated that older adults attending sports centers reported higher perceptions of physical, social, and belief-related barriers, as well as lower motivation for physical condition and social recognition, compared to those from gyms and Senior Fitness Academies (p < 0.05). Regression analyses revealed that higher weekly exercise duration was the strongest predictor of motivation, and higher frequency was associated with lower belief-related barriers. Women reported more external barriers, while men were more motivated by competition (p < 0.05). Cluster analysis revealed two distinct profiles: Cluster 1 (“low motivation and moderate perception of barriers,” n = 78) and Cluster 2 (“high motivation and low perception of barriers,” n = 147). Individuals in Cluster 2 reported more weekly exercise hours (p = 0.002), suggesting that higher motivation and lower perceived barriers are linked to greater adherence. Social and motivational barriers negatively affect adherence, while belief-related barriers may serve as incentives for disease prevention.

PMID:42171951 | DOI:10.1007/s10823-026-09580-1

Behav Res Methods. 2026 May 22;58(6):169. doi: 10.3758/s13428-026-03036-7.

ABSTRACT

Count data in the psychological and health sciences are often characterized by an excess of zero values, a feature known as zero inflation. While traditional zero-inflated models, such as the zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB), were developed to handle such data, they present challenges for applied researchers. Standard count models can produce biased estimates, and the dual-parameter output of traditional zero-inflated models provides conditional effects for a latent-at-risk subpopulation, complicating interpretation and often failing to answer research questions about the entire population directly. To address these limitations, marginalized zero-inflated (mZI) models directly estimate the population-averaged effect, yielding a single, interpretable coefficient for each predictor’s overall effect. However, the adoption of mZI models has been hindered by the lack of an accessible software package. The current study has two objectives: first, it provides a tutorial on the theory, estimation, and interpretation of marginalized zero-inflated models. Second, it introduces mzim, a new R package designed to make both marginalized zero-inflated Poisson (mZIP) and Negative Binomial (mZINB) models readily accessible. Using an empirical example on self-reported youth abuse experiences, we demonstrate a complete workflow with the mzim package and compare the results from the mZINB model to traditional approaches, highlighting the practical benefits of the marginalized framework for applied researchers.

PMID:42171937 | DOI:10.3758/s13428-026-03036-7

Discov Ment Health. 2026 May 22. doi: 10.1007/s44192-026-00449-w. Online ahead of print.

ABSTRACT

INTRODUCTION: Mental health problems are increasingly prevalent among school-aged children and adolescents, underscoring the need for teacher-inclusive mental health interventions.

OBJECTIVES: To examine the association between sociodemographic and socioemotional factors and resilience among teachers, prior to their participation in a school-based intervention aimed at strengthening socioemotional competencies.

METHODS: A cross-sectional analytical study was conducted among 693 teachers from 56 public schools in Amazonas, Boyacá, and Vaupés, Colombia. Teachers completed standardized instruments including the Connor-Davidson Resilience Scale (CD-RISC), Compassion Scale (ECOM), and Prosocial Personality Battery (PSB), along with mental health screeners for anxiety (HARS), depression (Whooley), and PTSD (PCL-C). Descriptive statistics, bivariate analyses, and multivariate linear regressions were used to assess associations between socioemotional factors and resilience scores.

RESULTS: The mean age was 47.13 years (SD = 9.91); most were female (65.95%). Median resilience score was 76 (IQR = 69-86). Teachers from Vaupés showed higher resilience, while those from Boyacá had lower scores. Higher compassion (ECOM: β = 0.23; 95% CI: 0.10-0.36) and prosociality scores (PSB: β = 0.43; 95% CI: 0.31-0.54) were independently associated with increased resilience. Conversely, higher anxiety levels (HARS: β = -0.22; 95% CI: -0.39 to – 0.06) and a positive depression screen (Whooley: β = -2.46; 95% CI: -5.18 to 0.25) were associated with lower resilience scores. Age and sex were not independently associated with resilience in the adjusted model.

CONCLUSIONS: Mental health programs in school settings should prioritize teacher well-being as a central component for promoting student mental health outcomes. Findings underscore the relevance of addressing socioemotional skills and resilience in educators, particularly in contexts affected by armed conflict.

PMID:42171929 | DOI:10.1007/s44192-026-00449-w

Adv Health Sci Educ Theory Pract. 2026 May 22. doi: 10.1007/s10459-026-10547-7. Online ahead of print.

ABSTRACT

Artificial intelligence tools such as ChatGPT offer new opportunities to support medical students’ learning through interactive questioning and instantaneous feedback. However, while ChatGPT may facilitate learning engagement through its accessibility, ChatGPT’s potential to foster higher-order thinking and sustained engagement remains underexplored. This study explored how ChatGPT-facilitated questioning relates to medical students’ cognitive engagement and motivation in a first-year foundational science module, integrating Self-Determination Theory, Expectancy-Value Theory, and Bloom’s Taxonomy as learning frameworks. A study was conducted among medical students pursuing a cardiovascular physiology course. Students generated course-related questions and used ChatGPT to obtain answers, which were subsequently evaluated by instructors. 31 student questions were independently coded by two reviewers according to Bloom’s cognitive domains. Perceived autonomy, competence, relatedness, interest/enjoyment, and task value were collected using validated Self-Determination and Expectancy-Value Theory-based tools. Student-generated questions were coded according to Bloom’s cognitive domains, and open-ended feedback on the strengths and limitations of ChatGPT was synthesised through conventional content analysis. Survey results indicated higher perceived autonomy, competence, and task value among ChatGPT users compared with non-users, although differences were not statistically significant. Most student-generated questions also reflected lower to intermediate cognitive levels – ‘Understand’ (41.9%), and ‘Apply’ (45.2%), with few reaching ‘Analyse’. Qualitative insights highlighted ChatGPT’s efficiency, accessibility, and cognitive support, alongside concerns regarding accuracy, superficial engagement, and limited interpersonal interactions. Integrated results suggest that ChatGPT may support self-directed motivation and learning but does not consistently facilitate higher-order thinking and social relatedness without instructor mediation. ChatGPT may offer benefits for medical education by supporting autonomy and perceived usefulness. However, motivation alone is insufficient to promote higher-order thinking. ChatGPT should be facilitated by educators to transform artificial intelligence use from information retrieval into reflective, dialogic inquiry. Integrating ChatGPT within collaborative learning may strengthen analytical reasoning and relational engagement in early medical training.

PMID:42171923 | DOI:10.1007/s10459-026-10547-7

Genet Med. 2027 Jan 22:101943. doi: 10.1016/j.gim.2026.101943. Online ahead of print.

ABSTRACT

PURPOSE: The G6PD missense variant rs1050828 (NP_000393.4:p.Val98Met) is common in African and African American populations. It lowers HbA1c levels independent of glycemia, increasing the risk of underdiagnosis or delayed diagnosis of diabetes. We aimed to develop polyphenotypic scores (PPS) using routinely collected phenotypes to identify likely carriers.

METHODS: Using data from 31,083 African or African American participants in the All of Us Research Program (AoU), we developed sex-specific PPS through multi-stage variable selection. We validated the PPS in independent African or African American individuals from AoU (N = 8,846), BioMe Biobank (N = 8,839), and UK Biobank (N = 6,811), and evaluated their utility among individuals without diagnosed diabetes.

RESULTS: The PPS achieved an area under the receiver operating characteristic curve ranging from 0.7614 to 0.8686 in identifying male hemizygotes and from 0.7378 to 0.8654 identifying female homozygotes. Among individuals without diagnosed diabetes and with HbA1c <6.5%, PPS-based screening reduced the number needed to screen for identifying male hemizygotes by 65-90% and female homozygotes by 80-90%, compared to random screening.

CONCLUSION: The PPS may help identify likely rs1050828 carriers in African and African American populations, supporting prioritization for confirmatory testing or alternative diagnostic approaches for diabetes.

PMID:42170804 | DOI:10.1016/j.gim.2026.101943

Twin Res Hum Genet. 2026 May 22:1-12. doi: 10.1017/thg.2026.10070. Online ahead of print.

ABSTRACT

Record linkage projects provide powerful opportunities to enrich cohort data with administrative and clinical information from national registries. The Netherlands Twin Register (NTR) is a large population-based twin-family cohort with longitudinal data collection that has established multiple record linkage initiatives to expand research on genetic and environmental determinants of health, disease, behaviour, development, and fertility. In this article we summarize and discuss NTR record linkage projects. Clinical and pathology registries have provided essential data on chorionicity, reproductive history, neonatal thyroid function, and cancer diagnoses, facilitating studies on prenatal environment, disease heritability, and polygenic risk prediction for diseases. Linkage with health insurance data has enabled validation of medication use and health research. Collaborations with Statistics Netherlands allow linkage to nationwide population-based data via secure infrastructures such as Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI), supporting genomewide association studies of, for example, healthcare expenditure. Finally, linkage to environmental exposure datasets has permitted exposomewide analyses of health and wellbeing. Together, these projects illustrate the feasibility, scientific value, and challenges of record linkage in the Dutch context, highlighting its role in advancing twin research, genetic epidemiology, and population health studies.

PMID:42170785 | DOI:10.1017/thg.2026.10070

Health Soc Care Deliv Res. 2026 May;14(15):1-91. doi: 10.3310/XYRV6485.

ABSTRACT

BACKGROUND: In 2019, the NHS App was launched as a ‘digital front door’ to England’s National Health Service, aiming to improve access to primary care, enhance patient experience, save time in general practitioner practices and promote self-care.

AIMS AND OBJECTIVES: This project aimed to identify and understand the use and acceptability of the NHS App, to measure the extent to which it improved patient experience and influences health service access, and to understand patterns of early take-up and participation.

METHODS: Qualitative work explored experiences and views on the acceptability of the app through 60 hours of observation in general practices, document analysis (approximately 100 documents), and 62 interviews and four focus groups with patients, carers, members of the public and staff across five general practices, as well as commissioners and policy-makers. Our theoretical approach used the Non-adoption, Abandonment, Scale-up, Spread and Sustainability framework. Quantitative work examined the impact of the NHS App on the usage of primary and secondary care, using routinely collected data. Firstly, using monthly NHS App user data at general practice level in England, descriptive statistics and time series analysis explored monthly NHS App use from January 2019 to May 2021. Secondly, data on the sociodemographic characteristics of the general practitioner-registered population and their healthcare needs at the general practitioner level were used as covariates to explore inequalities in app usage. Finally, NHS App usage data were also compared with measures of patient experience of care and care access extracted from the General Practitioner Patient Survey database.

RESULTS: The qualitative analysis guided by the Non-adoption, Abandonment, Scale-up, Spread and Sustainability framework illustrated the multiple layers of complexity when introducing a constantly shifting technology into a challenging environment such as English general practice, during and after a period of considerable societal turbulence caused by the COVID-19 pandemic. Quantitative work showed there was strong adoption of the NHS App even before the onset of the pandemic, although the introduction of the COVID-19 Pass feature was linked to a fourfold increase in downloads. Analyses by sociodemographic data found higher usage in less-deprived and less ethnically diverse practices, with a generally younger population. There were 25% lower registrations in the most deprived practices (p < 0.001), and 44% more registrations in the largest-sized practices (p < 0.001). Registration rates were 36% higher in practices, with the highest proportion of registered White patients (p < 0.001), 23% higher in practices with the largest proportion of 15- to 34-year-olds (p < 0.001) and 2% lower in practices with highest proportion of people with long-term care needs (p < 0.001). Analyses by patient subgroup and by patient experience of care showed mixed findings.

LIMITATIONS: There was no opportunity to evaluate the app or the app functionality in an experimental design. The technology itself, and the context, was changing during the study, which added challenges and complexity. The quantitative analyses used aggregated data rather than individual-level linked data.

CONCLUSIONS: The NHS App was introduced into a complex and changing landscape. It has achieved strong uptake, with the COVID-19 Pass feature increasing adoption substantially. Overall uptake and use have followed an inverse deprivation gradient, influenced in particular by age, ethnicity and healthcare needs. Different functions of the NHS App have been used to different extents, and with different patterns over time.

FUTURE WORK: Further evaluation as the healthcare landscape and the functions of the NHS App evolve is warranted, including longitudinal studies using person-level data and further work on inequalities in access and use.

STUDY REGISTRATION: This study is registered as ISRCTN72729780.

FUNDING: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref.: NIHR128285) and is published in full in Health and Social Care Delivery Research; Vol. 14, No. 15. See the NIHR Funding and Awards website for further award information.

PMID:42170774 | DOI:10.3310/XYRV6485

Colorectal Dis. 2026 May;28(5):e70491. doi: 10.1111/codi.70491.

ABSTRACT

BACKGROUND: Magnetic resonance imaging (MRI) is central to staging and treatment planning in rectal cancer, particularly in identifying candidates for neoadjuvant therapy. Prognostic MRI features such as tumour depth (mrT), extramural venous invasion (EMVI) and tumour deposits (TDs) are increasingly recognised as markers of systemic risk, yet their reporting in randomised controlled trials (RCTs) remains unclear. This systematic review aimed to evaluate the reporting frequency, consistency and integration of pre-treatment MRI prognostic variables in RCTs assessing neoadjuvant treatment for rectal cancer.

METHODS: A systematic search was conducted across MEDLINE, EMBASE, Web of Science and CENTRAL from 01 January 2005 to 18 November 2025. RCTs evaluating neoadjuvant strategies in adult patients with resectable rectal cancer were included. Two reviewers independently extracted data on MRI variables, protocol details and trial design. PRISMA guidelines were followed.

RESULTS: Of 1,283 screened studies, 34 RCTs met inclusion criteria. All studies reported mrT, and 33 (97%) included nodal staging (mrN). mrEMVI was reported in only 10 trials (29.4%), and mrT substage was reported in 5 studies (14.7%). MRI protocols were inconsistently described, with only 5 trials specifying acquisition parameters. Only 10 studies incorporated EMVI into risk stratification frameworks. Four trials did not mandate MRI for baseline staging.

CONCLUSION: Despite MRI’s critical role in rectal cancer management, key prognostic features such as EMVI/TDs and mrT substage are underreported. This omission risks poor risk stratification, trial imbalance and misinformed clinical guidance. Standardisation of MRI reporting is urgently needed to enhance trial validity and optimise personalised treatment strategies.

PMID:42170773 | DOI:10.1111/codi.70491

Biomark Med. 2026 May 22:1-7. doi: 10.1080/17520363.2026.2654370. Online ahead of print.

ABSTRACT

AIMS: To evaluate whether cytokine profiles combined with lymphocyte count could predict infection risk in lymphoma patients undergoing chemotherapy.

PATIENTS & METHODS: This retrospective study included 110 patients with pathologically confirmed lymphoma treated at Xiangtan Central Hospital between January 2022 and December 2023. Peripheral blood samples were collected before chemotherapy to determine lymphocyte count and serum cytokine levels (IFN-γ, TNF-α, IL-6, IL-8, IL-10) using ELISA. Statistical analyses included ROC curve and Kaplan-Meier survival analysis to assess predictive accuracy and treatment outcomes.

RESULTS: Sixty-five patients (59.1%) developed infections, including bacterial, fungal, and viral types. Infected patients exhibited significantly lower lymphocyte counts and decreased cytokine levels. A combination of ≥3 decreased cytokines with low lymphocyte count provided stronger predictive power for infection than single indicators.

CONCLUSION: Reduced cytokine levels together with lymphopenia are strong predictors of infection in lymphoma patients receiving chemotherapy. Immune monitoring of cytokine-lymphocyte patterns may facilitate early identification of high-risk individuals and improve infection prevention and treatment strategies.

PMID:42170771 | DOI:10.1080/17520363.2026.2654370