Search results
Found 18357 matches for
Call up the (cognitive) reserves: how adult socialisation and education influences cognition in the UK Biobank.
INTRODUCTION: Dementia involves the loss of memory and degradation of cognitive function. Crucially, the onset of dementia may be prevented by identifying and modifying relevant risk factors years before disease onset in midlife. Commonly described modifiable risk factors include social isolation and educational attainment. Here, we aim to understand the relationships between adult activities and their effects on cognition related to mid-life aging in terms of where and how people live. METHODS: We analysed data from the UK Biobank (N = 502,165, Mage = 56.53, SDage = 8.09, 54.40% female). In particular, our path analysis investigated the associations between years of education in childhood, education later in life, social activities in adulthood, built environment (i.e., coastal distance and percentage of greenspace), socioeconomic status (i.e., Townsend deprivation index), and cognitive functions (i.e., memory, executive function, and abstract reasoning). RESULTS: Adult education and social activities predict better cognition. Being deprived predicts attendance in adult education classes, but fewer social activities and poorer cognition. Moreover, living in areas with less greenspace and being further away from coastlines predict attendance in adult education classes; however, only greenspace predicts participation in social activities. Finally, less greenspace and further coastal distance support abstract reasoning, whereas further coastal distance predicts poorer executive function. CONCLUSION: We demonstrate the potential utility of adult education and social activities which may offset the detrimental effects of deprivation. Accordingly, we argue for improved access to adult social programs in deprived/underserviced areas in the United Kingdom.
Engagement and attrition in digital mental health: current challenges and potential solutions.
In digital mental health engagement rates are consistently low, which may limit its effects. Using an international multidisciplinary consensus method, including lived experience expertise and a systematic review, we identified three key challenges: (i) lack of agreed metrics for engagement; (ii) lack of evidence on how better engagement improves outcomes; (iii) lack of standards for user involvement. Three potential solutions encompassed: (i) standardisation of frameworks for reporting engagement metrics and optimal doses of digital tools, (ii) measuring engagement with more precise reporting of outcomes, including potential harms; (iii) defining standards of user involvement (including appropriate diversity, and clinician as well as user input). Digital interventions have real potential in meeting the shortfall in service provision for mental health, but this will require focus on high quality research studies of the underlying mechanisms of engagement and optimal outcomes. Our findings identify and highlight the next best steps in this process.
Economic evaluation of caregiver interventions for children with developmental disabilities: A scoping review.
Globally, families with children with developmental disabilities (DDs) experience challenges, including social isolation, stigma, and poverty, especially in low-income settings in Africa. Most children with DDs in Africa remain unidentified and receive no formal support. Caregiver interventions focusing on education and training for the carers/parents have been shown to be adaptable and low intensity in implementation, although the economic evidence is limited. This review aimed to describe the evidence and methodological aspects of economic evaluations for caregiver interventions for DDs. The Arksey and O'Malley framework was applied. Seven electronic databases, grey literature and cited references were systematically searched to identify eligible studies. published from 1993 to 2023. We assessed the quality of the included studies using the Drummond checklist. Data were systematically extracted, tabulated, and qualitatively synthesised using inductive thematic analysis. From 7811 articles, twenty studies all in high-income countries were included, and focused on caregiver interventions for autism spectrum disorder (n = 7), attention deficit hyperactivity disorder (ADHD) (n = 6), disruptive behaviour and behaviour problems with ADHD (n = 5), intellectual disabilities (n = 1) and language delay (n = 1). Economic evaluation analyses included cost effectiveness (n = 11), costing (n = 3), cost utility (n = 2), cost consequence (n = 1) cost benefit (n = 1), and combined analyses (n = 2). Nine studies reported the interventions as cost effective and five studies reported the intervention to be cost saving. The main methodological challenges were related to costing, outcome measurement in children and the appropriate time horizon for modelling. Caregiver interventions demonstrate cost-effectiveness, with the available evidence supporting the adoption of the interventions as a promising avenue to strengthen access and reduce the associated healthcare costs. The identified key methodological challenges highlighted further research areas. Prioritizing more economic evaluation studies in this area would inform decision-making on efficient resource allocation, promote inclusivity and equitable access to services for children with DDs.
In Children, N-Methyl-D-Aspartate Receptor Antibody Encephalitis Incidence Exceeds That of Japanese Encephalitis in Vietnam.
BACKGROUND: The recognition of autoimmune causes of encephalitis has led to epidemiological shifts in the worldwide characteristics of encephalitis. N-methyl-D-aspartate receptor (NMDAR) antibody encephalitis leads to well-established complex neuropsychiatric manifestations. In low- and middle-income countries, including Vietnam, its relative incidence, especially in children, is unknown and most neurologists currently consider infectious encephalitis prior to autoimmune etiologies. METHODS: The study was prospectively conducted at Children's Hospital 1 in Ho Chi Minh City between March 2020 and December 2022. Any child admitted to the Department of Infectious Diseases and Neurology fulfilling the case definition of encephalitis was eligible to participate. Cerebrospinal fluid samples were collected alongside meta-clinical data for analysis. RESULTS: We recruited 164 children with a clinical diagnosis of encephalitis. Etiologies were determined as NMDAR antibody encephalitis in 23 of 164 cases (14.0%), Japanese encephalitis virus in 14 of 164 (8.5%), and herpes simplex virus in 4 of 164 (2.4%). Clinical categorizations suggested idiopathic viral encephalitis in another 71 (43.3%), and autoimmune encephalitis of unknown origin in the remaining 52. Factors including demographics, specific clinical features, cerebrospinal fluid and electroencephalogram findings, and length of hospital stay were significantly different between NMDAR antibody encephalitis and Japanese encephalitis. CONCLUSIONS: At a tertiary children's hospital in Vietnam, the prevalence of NMDAR antibody encephalitis exceeds that of Japanese encephalitis, the most common infectious encephalitis cause in Southeast Asia. NMDAR antibody encephalitis is associated with long hospital stay and poor outcomes. These findings should change pediatric diagnostics, to earlier consider autoimmune treatments in this clinical setting.
Genomic risk prediction for type 2 diabetes in Australian individuals aged 70 years and older.
AIMS: The utility of a polygenic score (PGS) for type 2 diabetes (T2D) has been demonstrated in the general adult population. However, while previous studies have included older adults within broader age ranges, the performance of PGS specifically in older individuals aged ≥70 years remains unclear. We aimed to evaluate the predictive utility of a PGS in an older cohort. MATERIALS AND METHODS: We derived a PGS in 12 174 Australian participants aged ≥70 years from the ASPREE trial, with a median follow-up of 4.6 years. T2D was defined by self-report, commencement of glucose-lowering medication, or a fasting plasma glucose of ≥7.0 mmol/L. Multivariable logistic and Cox models examined associations between the PGS and baseline and incident T2D, adjusting for clinical risk factors. Risk prediction was evaluated using area under the curve (AUC), C-index, and net reclassification improvement (NRI). RESULTS: At baseline, 1150 (9.4%) participants had prevalent T2D. During follow-up, an additional 590 (4.8%) developed incident T2D. Per standard deviation, the PGS was significantly associated with baseline (odds ratio: 2.39 [95% CI: 2.19-2.61]) and incident (hazard ratio: 1.55 [1.40-1.71]) T2D. The PGS improved prediction over the clinical risk factors, increasing the AUC from 0.70 to 0.79, and C-index from 0.67 to 0.71 (both p
Tacrolimus monitoring in renal transplantation: A comparison between high-performance liquid chromatography and immunoassay
It is recommended that specific methods of tacrolimus monitoring rather than immunoassays, which overestimate tacrolimus levels, should be used in transplant recipients. Direct comparison of these techniques, however, has not been conducted in renal transplantation. In this study, 40 renal transplant recipients with tacrolimus monitoring by microparticle enzyme immunoassay (MEIA; target trough level 10 to 15 ng/mL) were compared with 40 patients monitored by high-performance liquid chromatography with tandem mass spectrometry (HPLC-MS; target trough level 8 to 13 ng/mL). All patients received anti CD25 antibody induction and mycophenolate mofetil in a steroid-sparing protocol. No differences were seen between MEIA and HPLC-MS groups in patient demographics. All patients were followed for 6 months. Patient survival was 100% in both groups; graft survival was 100% in the MEIA group and 97.5% in the HPLC-MS group. The groups did not differ in the number of dose changes required in the first 6 months or in the number of patients displaying tacrolimus levels within target range at 3 and 6 months. Delayed graft function occurred in 14 patients in the MEIA group and 12 patients in the HPLC-MS group (P = NS). Biopsy-proven acute rejection occurred in four patients in the MEIA group and one patient in the HPLC-MS group (P
Exploring early childhood development programming in Kenya’s arid and semi-arid lands
Background: Promoting high-quality early childhood development (ECD) is vital for individuals’ physical and social well-being and yields significant societal returns. However, children in marginalised regions like Kenya’s arid and semi-arid lands (ASALs) face significant barriers to accessing quality ECD services. Aim: This study aimed to document existing ECD services in Kenya’s ASAL areas, including their availability, types and key characteristics; identify gaps in their provision and propose solutions to enhance access and quality. Setting: This qualitative study was conducted in 10 ASAL counties in Kenya. Methods: Using purposive and snowball sampling techniques, 103 key informants, including pre-primary teachers, parents, healthcare workers, religious leaders and county ECD coordinators, were interviewed. The interviews were audio-recorded, transcribed verbatim and analysed thematically. Results: The study found that while diverse ECD programmes exist in ASAL regions, their quality and effectiveness are hindered by challenges such as inadequate funding, insecurity, extreme weather events, food insecurity, poor infrastructure, inadequate healthcare access and limited early learning opportunities. Recommendations include increasing ECD funding, improving healthcare, enhancing early learning opportunities, promoting livelihood diversification and addressing security and food insecurity. Conclusion: Despite investments in ECD programmes, significant challenges persist, underscoring the need to provide children with high-quality services that foster nurturing care and mitigate risks to their development. This study highlights the urgency of adopting a multi-sectoral approach to strengthen ECD programmes and services in Kenya’s ASAL. Contribution: This article contributes to the scarce literature on ECD programming in Kenya’s ASALs by documenting existing ECD services, identifying critical gaps in their provision and offering actionable recommendations to address barriers to programme quality and effectiveness.
The cognitive neuroscience of ketamine in major depression.
Ketamine's potential as a rapid-acting antidepressant was first identified in 2000, despite its long-standing use as an anesthetic agent. Clinically, ketamine alleviates depressive symptoms, including the difficult to treat symptom of anhedonia, within hours, with the effects of a single dose lasting for days. Since then, research has focused on uncovering the mechanisms underlying its rapid antidepressant effects in both humans and animal models. While its molecular and cellular effects have been extensively characterized, its impact on cognitive and neuropsychological mechanisms - potential mediators of its clinical efficacy - remains an area of ongoing investigation. Preclinical studies suggest that ketamine rapidly influences the lateral habenula (involved in punishment processing) and fronto-striatal (reward) systems, reverses negative affective biases in established memories, and promotes long-term stress resilience. Translating these findings to human models is crucial, and emerging evidence suggests that ketamine engages similar mechanisms in healthy volunteer and patient groups. However, its clinical application is constrained by acute side effects and an unknown long-term safety profile. Further research into ketamine's mechanisms of action will be essential to inform the development of novel, safer, and more accessible rapid-acting antidepressants.
Commentary: The wars within – uncomfortable truths about the bullying of girls in conflict-affected societies
This commentary reflects on a timely and methodologically significant study by Silwal et al., which investigates bullying victimization among adolescents in conflict-affected Eastern Ukraine. Conducted in a context of fragility, social fragmentation, and resource scarcity, the study offers vital insights into how war and its aftermath shape adolescent experiences. It reveals higher rates of bullying in conflict-affected regions, with girls disproportionately targeted—an uncomfortable finding that challenges conventional gender patterns in bullying. Drawing on emerging evidence, the commentary considers the role of desensitization, emotional regulation, and digital exposure in shaping youth aggression. It also highlights the need to address the structural stressors facing adolescents in both post-conflict and post-migration contexts, particularly within disrupted school systems. In response, the commentary calls for integrated and context-responsive interventions that strengthen emotional and social competencies without reinforcing stigma. It further urges researchers and policymakers to acknowledge the politicized nature of post-migration violence discourse and to maintain commitment to nuanced and context-sensitive analysis. The findings underscore that bullying in such settings is a social indicator of wider systemic pressures—an expression of the hidden wars adolescents carry in their daily lives and into their schools.
Nonequilibrium brain dynamics elicited as the origin of perturbative complexity.
Assessing someone's level of consciousness is a complex matter, and attempts have been made to aid clinicians in these assessments through metrics based on neuroimaging data. Many studies have empirically investigated measures related to the complexity elicited after the brain is stimulated to quantify the level of consciousness across different states. Here we hypothesized that the level of non-equilibrium dynamics of the unperturbed brain already contains the information needed to know how the system will react to an external stimulus. We created personalized whole-brain models fitted to resting state fMRI data recorded in participants in altered states of consciousness (e.g., deep sleep, disorders of consciousness) to infer the effective connections underlying their brain dynamics. We then measured the out-of-equilibrium nature of the unperturbed brain by evaluating the level of asymmetry of the inferred connectivity, the time irreversibility in each model and compared this with the elicited complexity generated after in silico perturbations, using a simulated fMRI-based version of the Perturbational Complexity Index, a measure that has been shown to distinguish different levels of consciousness in in vivo settings. Crucially, we found that states of consciousness involving lower arousal and/or lower awareness had a lower level of asymmetry in their effective connectivities, a lower level of irreversibility in their simulated dynamics, and a lower complexity compared to control subjects. We show that the asymmetry in the underlying connections drives the nonequilibrium state of the system and in turn the differences in complexity as a response to the external stimuli.
The arrow of time in Parkinson's disease
Background: Parkinson's disease (PD) is a system-level disorder that implicates brain network dynamics across multiple scales. Detecting the ‘arrow of time’, or temporal reversibility of the brain's information processing flow enables quantification of equilibrium in the brain and inferences on the hierarchical organization. Therefore we aimed to explore disturbances in resting-state equilibrium levels as well as changes in the hierarchical organization due to PD. Methods: Structural and functional MRI of 29 PD patients and 19 healthy controls were acquired and analyzed. Empirical non-reversibility was computed as the distance between time-shifted forward- and artificially-reversed time series. Levels of equilibrium were subsequently assessed globally and within two cortico-subcortical motor networks implicated in PD. Moreover, whole-brain generative computational models consisting of 1051 Hopf oscillators were constructed to evaluate effective connectivities and alterations of the functional hierarchical organization. Results: We found that PD is characterized by disrupted equilibrium regimes, marked by distinct effective connectivity patterns, particularly within the motor networks. Additionally, we observed a flatter hierarchical organization in PD, with the cerebellum and thalamus exerting increased influence. Conclusion: The arrow of time methodology effectively identifies distinct and informative characteristics of PD. Our analyses suggest that PD shifts the brain towards less efficient, non-equilibrium dynamics that impair intrinsic flexibility and disrupt motor coordination. Thus, these findings not only provide insight into widespread system alterations in PD that could serve as potential biomarkers, but also lay the groundwork for next-generation stimulation techniques aimed at restoring balance in the Parkinsonian brain.
Non-local Schrödinger diffusion model reveals mechanisms of critical brain dynamics
Time-efficient computation is essential for survival. It has been proposed that this is made possible through the principle of criticality amplified by the rare long-range connections found in the brain's unique anatomical structure, which together provide the necessary non-local, distributed computation. Here, we directly tested this hypothesis by building a non-local, diffusion whole-brain model using the mathematical structure of Schrödinger's equation to capture non-local/long-range brain dynamics. We tested this non-local diffusion model against a conventional state-of-the-art local diffusion model in large-scale empirical neuroimaging data from over 1,000 healthy human participants and found the non-local model performed significantly better at capturing the brain dynamics. Overall, these results demonstrate that the non-locality of Schrödinger's equation is excellent for revealing the necessary non-local (but non-quantum) properties of the human brain.
Moral psychological exploration of the asymmetry effect in AI-assisted euthanasia decisions
A recurring discrepancy in attitudes toward decisions made by human versus artificial agents, termed the Human-Robot moral judgment asymmetry, has been documented in moral psychology of AI. Across a wide range of contexts, AI agents are subject to greater moral scrutiny than humans for the same actions and decisions. In eight experiments (total N = 5837), we investigated whether the asymmetry effect arises in end-of-life care contexts and explored the mechanisms underlying this effect. Our studies documented reduced approval of an AI doctor's decision to withdraw life support relative to a human doctor (Studies 1a and 1b). This effect persisted regardless of whether the AI assumed a recommender role or made the final medical decision (Studies 2a and 2b and 3), but, importantly, disappeared under two conditions: when doctors kept on rather than withdraw life support (Studies 1a, 1b and 3), and when they carried out active euthanasia (e.g., providing a lethal injection or removing a respirator on the patient's demand) rather than passive euthanasia (Study 4). These findings highlight two contextual factors–the level of automation and the patient's autonomy–that influence the presence of the asymmetry effect, neither of which is not predicted by existing theories. Finally, we found that the asymmetry effect was partly explained by perceptions of AI incompetence (Study 5) and limited explainability (Study 6). As the role of AI in medicine continues to expand, our findings help to outline the conditions under which stakeholders disfavor AI over human doctors in clinical settings.