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BACKGROUND: Social anxiety symptoms are common and harmful psychological illness in college students. Although some studies have illustrated that physical activity could reduce social anxiety symptoms, the specific mechanism is still unclear. Based on theoretical studies on resilience and sleep, this study constructed a serial mediation model to explore whether they mediate between physical activity and social anxiety symptoms among college students. METHODS: This study surveyed 9,530 college students from three colleges in China to explore the mediating effect of physical activity and sleep problems between physical activity and social anxiety symptoms. Participants were investigated with the International Physical Activity Questionnaire, Connor-Davidson Resilience Scale, Sleep-related problems, and the Social Interaction Anxiety Scale and the Social Phobia Scale. Correlations between variables were analysed using Pearson correlation analysis and mediation analyses were performed using SPSS PROCESS macro 3.3 software. RESULT: The study found that physical activity was negatively associated with social anxiety symptoms and sleep problems, but positively with psychological resilience. After controlling for sociodemographic variables, physical activity can not only indirectly alleviate social anxiety symptoms through the separate mediation of psychological resilience and sleep problems, but also through the serial mediation of psychological resilience and sleep problems. CONCLUSION: These results suggest that improving physical activity levels could reduce social anxiety scores by increasing psychological resilience and sleep quality. This is of great reference significance for the prevention and intervention of college students' mental health.
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Ansiedad , Ejercicio Físico , Resiliencia Psicológica , Trastornos del Sueño-Vigilia , Estudiantes , Humanos , Estudiantes/psicología , Estudiantes/estadística & datos numéricos , Masculino , Femenino , China , Adulto Joven , Universidades , Ejercicio Físico/psicología , Ansiedad/psicología , Ansiedad/epidemiología , Trastornos del Sueño-Vigilia/psicología , Adulto , Adolescente , Encuestas y CuestionariosRESUMEN
The Boolean satisfiability (SAT) problem exhibits different structural features in various domains. Neural network models can be used as more generalized algorithms that can be learned to solve specific problems based on different domain data than traditional rule-based approaches. How to accurately identify these structural features is crucial for neural networks to solve the SAT problem. Currently, learning-based SAT solvers, whether they are end-to-end models or enhancements to traditional heuristic algorithms, have achieved significant progress. In this article, we propose TG-SAT, an end-to-end framework based on Transformer and gated recurrent neural network (GRU) for predicting the satisfiability of SAT problems. TG-SAT can learn the structural features of SAT problems in a weakly supervised environment. To capture the structural information of the SAT problem, we encodes a SAT problem as an undirected graph and integrates GRU into the Transformer structure to update the node embeddings. By computing cross-attention scores between literals and clauses, a weighted representation of nodes is obtained. The model is eventually trained as a classifier to predict the satisfiability of the SAT problem. Experimental results demonstrate that TG-SAT achieves a 2%-5% improvement in accuracy on random 3-SAT problems compared to NeuroSAT. It also outperforms in SR(N), especially in handling more complex SAT problems, where our model achieves higher prediction accuracy.
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INTRODUCTION: Haemophilia A (HA) is a congenital bleeding disorder caused by a deficiency/absence of factor VIII (FVIII) and characterised by frequent, acute and prolonged spontaneous or traumatic bleeding events, often leading to haemophilic arthropathy and progressive joint deterioration. HA severity is characterized by endogenous FVIII activity: mild (> 5-40%), moderate (1-5%), or severe (< 1%). HA poses a substantial clinical and socioeconomic burden on people with HA (PWHA), their caregivers, and society. This analysis evaluates clinical and patient-centric outcomes of a cohort of individuals with non-inhibitor HA sampled from France, Germany, Italy, Spain, and the UK in the 'Cost of Haemophilia in Europe: A Socioeconomic Survey II' (CHESS II) study. METHODS: CHESS II was a cross-sectional burden-of-illness study collecting clinical and socioeconomic data on adult (≥ 18 years) individuals with haemophilia A or B of any severity with or without inhibitors from eight European countries. Descriptive analyses were conducted examining physician-reported demographics, clinical and health resource utilisation information. PWHA-reported health-related quality of life (HRQoL) using the EQ-5D-5L and Work Productivity and Activity Impairment (WPAI) were also examined. Outcomes were stratified by HA severity and reported at country level. RESULTS: Demographics and clinical characteristics of the cohort (N = 880) were generally consistent across countries. Individuals with severe HA experienced more frequent bleeding events and joint disease despite broad use of factor replacement therapy long-term prophylaxis. A minority of those with mild or moderate HA also experienced such challenges. HRQoL and workforce participation diminished, and chronic pain increased, with increasing HA severity. CONCLUSION: This analysis provides up-to-date insights on the impact of HA across five European countries. Increasing HA severity was generally associated with worse clinical outcomes, HRQoL and workforce participation. These findings suggest a place for continued evidence-based tailored treatment and clinical management approaches in addressing the residual burden of HA.
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This study examined health information technology-related incidents to characterise system issues as a basis for improvement in Swedish clinical practice. Incident reports were collected through interviews together with retrospectively collected incidents from voluntary incident databases, which were analysed using deductive and inductive approaches. Most themes pertained to system issues, such as functionality, design, and integration. Identified system issues were dominated by technical factors (74%), while human factors accounted for 26%. Over half of the incidents (55%) impacted on staff or the organisation, and the rest on patients - patient inconvenience (25%) and patient harm (20%). The findings indicate that it is vital to choose and commission suitable systems, design out "error-prone" features, ensure contingency plans are in place, implement clinical decision-support systems, and respond to incidents on time. Such strategies would improve the health information technology systems and Swedish clinical practice.
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Informática Médica , Suecia , Humanos , Informática Médica/métodos , Estudios Retrospectivos , Errores Médicos/prevención & control , Errores Médicos/estadística & datos numéricos , Seguridad del Paciente/normas , Seguridad del Paciente/estadística & datos numéricos , Entrevistas como Asunto/métodos , Gestión de Riesgos/métodosRESUMEN
A neural network model is constructed to solve convex quadratic multi-objective programming problem (CQMPP). The CQMPP is first converted into an equivalent single-objective convex quadratic programming problem by the mean of the weighted sum method, where the Pareto optimal solution (POS) are given by diversifying values of weights. Then, for given various values weights, multiple projection neural networks are employded to search for Pareto optimal solutions. Based on employing Lyapunov theory, the proposed neural network approach is established to be stable in the sense of Lyapunov and it is globally convergent to an exact optimal solution of the single-objective problem. The simulation results also show that the presented model is feasible and efficient.
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This research aims to summarize and discuss issues related to psychiatric drugs by using the classification system of the Pharmaceutical Care Network Europe (PCNE) and to provide a reference for the development and direction of clinical pharmacists' work in the future. Psychiatric patients who were hospitalized in our hospital from Janurary 2023 to December 2023 were enrolled. Drug-related problems (DRPs) were evaluated using the PCNE classification system (version 9.0). The types, causes, intervention plans, acceptance of intervention plans, and statuses of DRPs were analyzed. A total of 362 patients were included, covering 405 DRP cases, with an average DRP of 1.12 for each patient. All 405 DRP cases underwent interventions, with a success rate of 83.46%. The main categories of related drugs were psychotropic drugs (70.37%), anti-infective drugs (8.89%), and cardiovascular system drugs (5.19%). The main DRPs were possible adverse drug events (21.24%), poor treatment effects (69.14%), and unnecessary medication treatment (9.63%). The main causes of DRPs were inappropriate drug selection (18.52%), inappropriate combinations of drugs (16.05%), and excessive drug dosage (13.58%). The PCNE classification system helps clinical pharmacists improve their ability to identify and solve DRPs faced by psychiatric departments, improve pharmaceutical care efficiency, and ensure rational drug use.
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PURPOSE: The aim was to evaluate the effectiveness of a problem-solving intervention with workplace involvement (PSI-WPI) added to care as usual (CAU) in reducing sickness absence days among employees with common mental disorders compared to CAU alone in Swedish primary health care on a monthly basis over 18-months follow-up. METHODS: We conducted a cluster-randomised controlled trial including 197 employees blinded to allocation (85 PSI-WPI and 112 CAU). As sickness absence data was skewed and over-dispersed, generalised estimating equations was used to enable a comparison between the intervention and control group for each month of the follow-up period. RESULTS: The median number of sickness absence days over the 18-month follow-up was 78 days, inter-quartile range (IQR) 18-196 for employees receiving PSI-WPI and 64 days, IQR 18-161 for employees receiving CAU. The time x group generalised estimating equations analysis showed no statistically significant difference in sickness absence days per month. CONCLUSION: The addition of a PSI-WPI to CAU was not more effective in reducing sickness absence days. This may be explained by the primary health care context, lack of specialisation in occupational health and the Swedish social insurance system with specific time limits. TRIAL REGISTRATION: The trial was registered at ClinicalTrials.gov, identifier: NCT03346395 on January 12th, 2018.
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Theory predicts that nonlinear summation of synaptic potentials within dendrites allows neurons to perform linearly non-separable computations (LNSCs). Using Boolean analysis approaches, we predicted that both supralinear and sublinear synaptic summation could allow single neurons to implement a type of LNSC, the feature binding problem (FBP), which does not require inhibition contrary to the exclusive-or function (XOR). Notably, sublinear dendritic operations enable LNSCs when scattered synaptic activation generates increased somatic spike output. However, experimental demonstrations of scatter-sensitive neuronal computations have not yet been described. Using glutamate uncaging onto cerebellar molecular layer interneurons, we show that scattered synaptic-like activation of dendrites evoked larger compound EPSPs than clustered synaptic activation, generating a higher output spiking probability. Moreover, we also demonstrate that single interneurons can indeed implement the FBP. Using a biophysical model to explore the conditions in which a neuron might be expected to implement the FBP, we establish that sublinear summation is necessary but not sufficient. Other parameters such as the relative sublinearity, the EPSP size, depolarization amplitude relative to action potential threshold, and voltage fluctuations all influence whether the FBP can be performed. Since sublinear synaptic summation is a property of passive dendrites, we expect that many different neuron types can implement LNSCs.
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Dendritas , Interneuronas , Modelos Neurológicos , Dendritas/fisiología , Animales , Interneuronas/fisiología , Potenciales de Acción/fisiología , Potenciales Postsinápticos Excitadores/fisiología , Sinapsis/fisiología , Cerebelo/fisiología , Cerebelo/citología , Neuronas/fisiología , RatonesRESUMEN
Background: The Oslo Sports Trauma Research Center Questionnaire on Health Problems (OSTRC-H) is a proven surveillance method to register acute injury, overuse injury, or illness in athletes. However, it has not yet been translated into Malay. Purpose: To translate, culturally adapt, and validate the OSTRC-H into Malay using internationally established guidelines. Study Design: Cohort study (diagnosis); Level of evidence, 3. Methods: The Malay translation of the OSTRC-H (OSTRC-H.M) was distributed to 54 elite (ie, professional) and recreational athletes. Face validity, content validity, and construct validity were assessed for the validity measurement properties, while test-retest and internal consistency were used for reliability measurement properties. Results: The content validity index was satisfactory at 0.93. The OSTRC-H.M showed good internal consistency, with a Cronbach α value of .84. Confirmatory factor analysis showed a good model for construct validity, with values of 0.99 and 0.04 for comparative fit index and root mean square error of approximation, respectively. Per-item intraclass correlation coefficients (ICCs) for test-retest reliability ranged from 0.55 to 0.80. The overall test-retest reliability of the questionnaire was good (ICC, 0.8; 95% CI, 0.63-0.88; P < .001). Conclusion: The OSTRC-H.M was found to be valid and reliable and therefore acceptable for application among Malay-speaking athletes.
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Introduction: Families with multiple and complex problems often deal with multiple professionals and organizations for support. Integrated social care supposedly prevents the fragmentation of care that often occurs.We identified facilitators and barriers experienced by families receiving integrated social care and by the professionals who provide it. Method: We performed a scoping review following Arksey and O'Malley's framework, using the following databases: PsycINFO, Web of Science Core Collection, Psychology and Behavioral Sciences Collection, CINAHL, PubMed, and Medline. Furthermore, conducted a thematic analysis. The results were divided into facilitators and barriers of integrated social care. Results: We identified 278 studies and finally included sixteen in our scoping review. We identified facilitators, including: linking formal care with informal networks, promoting collaboration among professionals e.g., working in pairs, and professionals autonomy. We identified barriers, including: time constraints, tasks outside professionals' expertise, along with resistance to integrated collaboration among organizations. These findings can enhance the advancement of social integrated care as a promising approach to support families facing multiple and complex problems. Conclusion: To empower families, integrated social care requires a systematic approach based on trust. It involves coordinated care, shared decision-making, informal networks and the participation of all family members, including children.
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How did specific useful protein sequences arise from simpler molecules at the origin of life? This seemingly needle-in-a-haystack problem has remarkably close resemblance to the old Protein Folding Problem, for which the solution is now known from statistical physics. Based on the logic that Origins must have come only after there was an operative evolution mechanism-which selects on phenotype, not genotype-we give a perspective that proteins and their folding processes are likely to have been the primary driver of the early stages of the origin of life.
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Origen de la Vida , Pliegue de Proteína , Proteínas , Proteínas/química , Evolución MolecularRESUMEN
OBJECTIVE: The current study was a systematic review and meta-analysis of cognitive behavioral treatment (CBT) for problem gambling and gambling disorder and whether it produced different outcomes than minimal or no treatment controls on three putative change mechanisms: 1) gambling cognitions, 2) coping, and 3) self-efficacy. METHOD: Studies were identified from five bibliographic databases (i.e., Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Embase, PsycINFO, and PubMed). Included studies were randomized controlled trials of CBT that included posttreatment data on putative mechanisms. Between-group Hedges's g effect sizes were calculated to examine outcomes of CBT relative to minimal or no treatment control on gambling cognitions, coping, and self-efficacy at posttreatment. Risk of bias was determined using the Cochrane Risk of Bias tool. RESULTS: Fifteen studies, representing 1,536 participants, were eligible for analysis. Participants in CBT had more favorable gambling cognitions (g = -0.41), coping behaviors (g = 0.27), and self-efficacy (g = 1.12) at posttreatment than minimal or no treatment control. CONCLUSIONS: Results of the current study provided preliminary support for the effectiveness of CBT on three putative mechanisms of change among individuals experiencing problem gambling and gambling disorder. Although the results were promising, there was significant heterogeneity in the magnitude of effect sizes for all three outcomes, and outcomes were not consistently assessed with psychometrically established assessment tools.
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[Purpose] A method for evaluating integrated interpretation skills, which is an important educational goal in clinical practice, is yet to be established. This study examined the interrater reliability of a problem-solving model that was developed as a novel assessment method. [Participants and Methods] Three students created problem-solving models using fictitious case data. Ten clinical practice supervisors with at least 3â years of experience were asked to score the models, and the intraclass correlation coefficient (2, 1) was calculated. [Results] The intraclass correlation coefficient was 0.88, which indicates a good result. [Conclusion] Good interrater reliability was obtained using the problem-solving model, which suggests that this model may be used to assess integrated interpretation skills in clinical practice.
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Gambling type involvement, both in terms of participation (engagement in specific gambling types) and diversity (how many gambling types an individual engages in), is a key feature to address in gambling self-report measures, but such systematic measurement procedures are scarce. The aim of this study was to test the psychometric performance of the gambling type assessment in the recently developed Gambling Disorder Identification Test (GDIT), in terms of test-retest reliability, convergent validity, and patterns of gambling diversity, among help-seeking and general population gambling samples (total n = 603). Overall, online gambling was more commonly reported as problematic than land-based gambling. Retest reliability varied for specific gambling types (ICC range 0.32-0.64, rtet range 0.66-0.85). In terms of gambling participation, online gambling showed stronger correlations with GDIT total score (i.e., symptom severity) than land-based gambling, where Slots showed the strongest correlation (r = 0.52), followed by Casino table games (r = 0.25), Sports and Horse betting (r = 0.16 and r = 0.14, respectively), and Poker (r = 0.14). Lotteries showed no correlation with GDIT total score (r=-0,01). For Slots gambling, all gambling diversity levels (including Slots as a single gambling type) were on average associated with the highest diagnostic severity level (GDIT total score > 30; severe gambling disorder). Finally, explorative configural frequency analysis identified typical and antitypical gambling diversity patterns. The result from the current study corroborates findings that engagement in specific gambling types matter, and that such features should be included in gambling measurement. We conclude that the GDIT is a reliable and valid measure for systematic assessment of gambling type involvement. The GDIT can be used to assess gambling participation and diversity, as part of a broad measurement setup for problem gambling and gambling disorder.
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Given a family of linear constraints and a linear objective function one can consider whether to apply a Linear Programming (LP) algorithm or use a Linear Superiorization (LinSup) algorithm on this data. In the LP methodology one aims at finding a point that fulfills the constraints and has the minimal value of the objective function over these constraints. The Linear Superiorization approach considers the same data as linear programming problems but instead of attempting to solve those with linear optimization methods it employs perturbation resilient feasibility-seeking algorithms and steers them toward feasible points with reduced (not necessarily minimal) objective function values. Previous studies compared LP and LinSup in terms of their respective outputs and the resources they use. In this paper we investigate these two approaches in terms of their sensitivity to condition numbers of the system of linear constraints. Condition numbers are a measure for the impact of deviations in the input data on the output of a problem and, in particular, they describe the factor of error propagation when given wrong or erroneous data. Therefore, the ability of LP and LinSup to cope with increased condition numbers, thus with ill-posed problems, is an important matter to consider which was not studied until now. We investigate experimentally the advantages and disadvantages of both LP and LinSup on examplary problems of linear programming with multiple condition numbers and different problem dimensions.
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Prior research has identified a host of factors that increase the likelihood that an individual will develop problem gambling, clinically diagnosed as Gambling Disorder (GD), most of which would be identified by criminologists as "strains" under the framework of General Strain Theory (GST). This study utilizes propositions from GST to determine whether strain from another person's gambling may be related to why people develop GD and whether gender is a moderating factor in this relationship. Secondary data is analyzed to assess levels of strain individuals experience from another person's gambling behavior, its relationship to the individual's risk of Gambling Disorder, and the role gender plays in this relationship. Findings demonstrate a relationship between the strain from the perceived problem gambling of someone with a close relationship and having a gambling disorder. Experiencing strain from a spouse/partner who is perceived as a problem gambler has the strongest correlation with an individual also having Gambling Disorder. Considering gender as a moderating factor, this effect was stronger on men than women, calling into question the strong belief that it is primarily women who gamble to escape problems.
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Collaborative methods for learning such as team-based learning, case-based learning, and problem-based learning have become leading methods for active learning within the field of health professions education. Critical thinking and exposure to diverse perspectives within a group are highlighted as important benefits of team-based learning. However, without consideration of the potential socioemotional, behavioral, and team dynamic challenges associated with this format of learning, the tenets which support a welcoming learning community can begin to deteriorate. In this essay, authors highlight the core concepts of growth mindset, psychological safety, and culturally responsive pedagogy within a framework of 1) what learners should know and 2) what educators can do, to co-create an inclusive collaborative learning experience.
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The inappropriate use of electronic devices can affect the psychological and physical health of children and adolescents. Therefore, it is essential to accompany them and promote media literacy to ensure a healthy and responsible use of technology. On occasions that depend on a multifactorial complex, the inappropriate use of networks can trigger problematic consumption and seriously affect the lives of young people. In 2022, the World Health Organization recognized, through ICD-11, the addiction to video games and used the term "problematic use" for the Internet and social networks. This article attempts to update professionals on new trends in the consumption of social networks, video games, and online gambling platforms and their consequences on the psychophysical well-being of children and adolescents.
El uso inapropiado de dispositivos electrónicos puede afectar la salud psicofísica de niños y adolescentes. Por ello, es fundamental acompañarlos y fomentar la alfabetización mediática para garantizar un uso saludable y responsable de la tecnología. En ocasiones que dependen de un complejo multifactorial, el uso inadecuado de las redes puede desencadenar consumos problemáticos y afectar gravemente la vida de los jóvenes. En 2022, la Organización Mundial de la Salud reconoció, a través del CIE 11, la adicción a los videojuegos y utilizó el término "uso problemático" para internet y redes sociales. Este artículo intenta actualizar a los profesionales sobre las nuevas tendencias en el consumo de las redes sociales, los videojuegos, las plataformas de apuestas en línea y sus consecuencias en el bienestar psicofísico de los niños y adolescentes.
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Emotional health represents a significant burden on the mental health of university students. Adapting to a new learning environment and facing increased academic pressure make this period particularly vulnerable for their emotional health and well-being. The objective of the study was to analyse the prevalence of emotional and behavioural problems in university students and their association with lifestyle habits, and mental and physical health indicators. A cross-sectional study was conducted on a sample of 1268 students (23.65 ± 7.84 years) from a university in northern Spain during November 2020 and March 2021. An online questionnaire was administered, comprising the self-report Strengths and Difficulties questionnaire, the Trait Meta-Mood Scale, the Rosenberg Self-Esteem Scale, the Satisfaction with Life Scale, the Perceived Stress Scale, the SENTIA-Brief Scale, the KIDMED questionnaire, the International Physical Activity Questionnaire-Short Form, the Alcohol Use Disorders Identification Test, and the Compulsive Internet Use Scale. 27.60% of students exhibited some form of emotional and behavioural problem. Students who did not present emotional and behavioural problems showed lower perceived stress, reduced suicidal behaviour and emotional intelligence deficits, as well as lower alcohol consumption and compulsive internet use (p < 0.001). Additionally, they reported higher engagement in physical activity and greater adherence to the Mediterranean diet (p < 0.001). The study shows that emotional and behavioural problems are recurring among university students, and given that modifiable psychosocial and lifestyle factors are associated with these issues, it underscores the need to develop multidisciplinary intervention strategies.
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Controllable Pareto front learning (CPFL) approximates the Pareto optimal solution set and then locates a non-dominated point with respect to a given reference vector. However, decision-maker objectives were limited to a constraint region in practice, so instead of training on the entire decision space, we only trained on the constraint region. Controllable Pareto front learning with Split Feasibility Constraints (SFC) is a way to find the best Pareto solutions to a split multi-objective optimization problem that meets certain constraints. In the previous study, CPFL used a Hypernetwork model comprising multi-layer perceptron (Hyper-MLP) blocks. Transformer can be more effective than previous architectures on numerous modern deep learning tasks in certain situations due to their distinctive advantages. Therefore, we have developed a hyper-transformer (Hyper-Trans) model for CPFL with SFC. We use the theory of universal approximation for the sequence-to-sequence function to show that the Hyper-Trans model makes MED errors smaller in computational experiments than the Hyper-MLP model.