Actas espanolas de psiquiatria最新文献

Background: Measuring adolescents' and youths' perception of their Cyber-Self can enhance the understanding of how digital technology influences identity formation. While psychological literature offers numerous measures of the self, there is a notable lack of studies addressing the measurement of the Cyber-Self. This study aims to evaluate the reliability, factorial- and criterion-related validity, and measurement invariance of the Cyber-Self Scale (CSS) across age and gender among the youth and adolescents in Saudi Arabia.

Methods: The Cyber Relationship Motives (CRM) and E-Emotional Questionnaire (EEQ) were administered to students at Umm Al-Qura University (N = 335), aged 17-31 years (39.7% male, 60.3% female; mean (M) = 21.75, standard deviation (SD) = 2.17).

Results: The results indicated significant positive correlations between the sub-components of the CRM and EEQ. One item was selected based on two criteria: the highest correlation with other items and the highest correlation with the general factor. A total of 12 items were identified as the final form of the CSS, which demonstrated acceptable internal consistency for both male and female participants. Confirmatory factor analysis (CFA) revealed that the CSS model fit the data well, with all 12 items meeting the fit criteria for chi-square and root mean square error of approximation (RMSEA).

Conclusion: The Arabic version of the CSS is sufficiently reliable and valid for use among Arabic-speaking adolescents and youth. Further research is recommended to examine its measurement invariance over extended periods.

Background: Neural stem cells (NSCs) disrupt with aging, contributing to neurodegeneration. Ginsenoside Rg1 (Rg1), a compound found in Ginseng, is known for its anti-aging effects; however, its role in the progression of aging NSCs remains unclear. Therefore, this investigation explored the impact of Rg1 on the growth and maturation of aging NSC and elucidated its underlying molecular mechanisms.

Methods: Initially, mouse models of brain aging were successfully established using D-galactose (D-gal) injection. Mice received Rg1 treatment along with D-gal administration. Brain tissues and NSCs were isolated and analyzed for pathological changes, gene expression, and cellular function. In vitro, experiments used aging NSCs treated with Rg1 to assess cell viability, proliferation, differentiation, and senescence markers.

Results: D-gal triggered aging-related pathological alterations in mouse brains, elevated acetylcholinesterase levels, upregulated senescence genes, and inhibited NSC proliferation (p < 0.05). However, Rg1 treatment mitigated D-gal-induced effects, delayed brain aging, and improved NSC function. In vitro, Rg1 significantly increased cell viability, promoted NSC proliferation and differentiation, reduced senescent neurons, and downregulated p53 and p21 genes (p < 0.05).

Conclusions: Rg1 demonstrates anti-aging properties in D-gal-induced mouse brain aging, promoting the proliferation and differentiation of NSCs, and downregulating the p53-p21 signaling pathway.

Parkinson's disease (PD) is a degenerative disease of the central nervous system primarily affecting middle-aged and elderly individuals, significantly compromising their quality of life. Neuroinflammation is now recognized as a key feature in the pathogenesis of PD. This study reviews recent advances in the identification of potential biomarkers associated with neuroinflammation in PD and their significance for therapeutic strategies. These findings suggest that inflammatory factors play a pivotal role in PD treatment, and interventions involving anti-inflammatory drugs, physical exercise, and dietary modifications have shown promising results in mitigating disease progression.

Background: In emergency warning nursing, the pre-alert system significantly influences the biochemical markers and clinical outcomes of patients with Acute Stress Disorder. Therefore, this study applies hierarchical analysis to explore the impact of early warning nursing on crucial indicators such as C-reactive protein (CRP), procalcitonin (PCT), tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and assess their clinical efficacy.

Methods: The study selected patients with acute stress disorder who were hospitalized in Southwest Hospital of Chongqing from December 2021 to December 2022, and collected data from 250 patients. Through PSM score matching, 170 patients were finally scored and grouped, 85 patients in each group, which were divided into routine group and stratified analysis group. The changes in serum inflammatory markers, psychological resilience, and post-traumatic growth were compared between the two experimental groups on day 1 of admission and after 14 days of intervention.

Result: After one day of admission, there was no significant difference in the serum factor levels, psychological resilience, and post-traumatic growth among the participants (p > 0.05). However, after 14 days of intervention, patients in the hierarchical analysis group showed better outcomes in serum inflammatory markers such as C-reactive protein, procalcitonin, tumor necrosis factor-alpha, and interleukin-6 compared to the conventional group (p < 0.05). The hierarchical analysis group had higher psychological resilience scores regarding strength, optimism, and resilience compared to the conventional group (p < 0.05). Furthermore, the hierarchical analysis group showed higher post-traumatic growth scores regarding mental changes, personal strength, appreciation of life, interpersonal relationship, and new possibilities relative to the conventional group (p < 0.05).

Conclusion: Analytic Hierarchy Process (AHP)-based emergency warning nursing can help improve the serum inflammatory factor levels, strengthen psychological resilience, and enhance post-traumatic growth levels in patients with Acute Stress Disorder.

Background: Accurate diagnosis and classification of Alzheimer's disease (AD) are crucial for effective treatment and management. Traditional diagnostic models, largely based on binary classification systems, fail to adequately capture the complexities and variations across different stages and subtypes of AD, limiting their clinical utility.

Methods: We developed a deep learning model integrating a dot-product attention mechanism and an innovative labeling system to enhance the diagnosis and classification of AD subtypes and severity levels. This model processed various clinical and demographic data, emphasizing the most relevant features for AD diagnosis. The approach emphasized precision in identifying disease subtypes and predicting their severity through advanced computational techniques that mimic expert clinical decision-making.

Results: Comparative tests against a baseline fully connected neural network demonstrated that our proposed model significantly improved diagnostic accuracy. Our model achieved an accuracy of 83.1% for identifying AD subtypes, compared to 72.9% by the baseline. In severity prediction, our model reached an accuracy of 83.3%, outperforming the baseline (73.5%).

Conclusions: The incorporation of a dot-product attention mechanism and a tailored labeling system in our model significantly enhances the accuracy of diagnosing and classifying AD. This improvement highlights the potential of the model to support personalized treatment strategies and advance precision medicine in neurodegenerative diseases.

Background: Efforts to improve psychiatry training must incorporate residents' assessment of their training. This study sought to collect the opinion of residents about the program that has been in force in Spain since 2008, until the current transition to a new plan.

Methods: The authors conducted an online survey of psychiatry residents in Spain, asking about their formative and working conditions. Based on previous research and the national training programme, it was distributed electronically to resident representatives of the National Board of Psychiatry. This descriptive, cross-sectional study used a mixed-methods (quantitative and qualitative) approach, following standard procedures for data analysis.

Results: A total of 109 residents from 67 training units responded to the survey. The average score for satisfaction with their training was 6.84 (standard deviation (SE) = 2.4; the maximum possible score was 10). Psychotherapy was considered the area with the greatest need for improvement, while the rotations that participants would most like to be extended were child psychiatry and addictions. It was reported that rotation durations established by the national programme were not fulfilled in 38.5% of cases, while the required direct supervision for first-year residents was not fulfilled in 77.1% of cases. Regarding working conditions, 47.7% of the residents reported that they exceeded the maximum working time established by European law.

Conclusions: Psychiatry residents in Spain perceive certain areas of their training as deficient, especially those related to psychotherapy and clinical supervision, and they consider that their working time is excessive. The approval of the new training programme opens up an interesting opportunity for improvement.

Background: Alcohol Use Disorders (AUD), affective disorders, and personality disorders are among the most prevalent mental health conditions observed in individuals exhibiting suicidal behavior, encompassing both completed and attempted suicides. A robust association between AUD and suicidal behavior has been established through retrospective and prospective cohort studies. Research on the relationship between alcohol consumption and self-harm has predominantly focused on Western and high-income countries, whereas approximately one-third of the global population, including half of the world's countries, lacks accessible suicide data. This study aims to present an updated review of empirical evidence regarding the risk of suicide associated with AUD in both developed and developing nations.

Methods: We identified published meta-analyses, reviews, systematic reviews, randomized controlled trials, clinical studies, clinical trials, controlled clinical trials, observational studies, and case reports written in English and published between January 2004 and June 2024. Our search yielded a total of 312 papers. After reviewing titles and abstracts, 232 articles were excluded from the initial records. Following full-text review of the remaining 80 articles, a qualitative synthesis was conducted, highlighting the most representative 41 papers for inclusion in this overview.

Results: Our analysis indicates that alcohol abuse is a significant risk factor for all forms of suicidal behavior. Alcohol consumption functions as both a predisposing and precipitating factor, contributing to maladaptive behaviors in both developing and developed countries. The clinical condition is exacerbated by alcohol use, which in turn increases the risk of suicide.

Conclusions: Further research is essential to develop targeted psychological and pharmacological interventions aimed at preventing and treating these conditions, with the goal of reducing the risk of suicidal behavior associated with AUD. In developing countries, integrating public health and clinical strategies is crucial for effectively addressing suicide prevention.

Objective: To explore the relationship between Career Decision-Making Self-Efficacy and maladjustment among psychiatric nursing students.

Method: The results of baseline data, Mental Health Knowledge Questionnaire, Career Decision-Making Self-Efficacy scale and Clinical Practice Maladjustment Questionnaire of psychiatric nursing students from January 2022 to August 2023 were obtained from our hospital, and the correlation of scores was examined through Pearson correlation analysis. The factors affecting psychiatric nursing students' maladjustment were analyzed through logistic regression analysis.

Results: A total of 286 psychiatric nursing students were included in this study. The total score of all students of Mental Health Law Knowledge Questionnaire score was 21.30 ± 5.28, the total score of Career Decision-Making Self-Efficacy scale was 132.90 ± 13.36 and the total score of Clinical Practice Maladjustment Questionnaire was 102.85 ± 9.81. Positive correlations were found among the Mental Health Knowledge Questionnaire score and the Career Decision-Making Self-Efficacy scale and Clinical Practice Maladjustment Questionnaire (r = 0.550, 0.602, p < 0.05). Similarly, a positive correlation was found between the Career Decision-Making Self-Efficacy scale and Clinical Practice Maladjustment Questionnaire (r = 0.639, p < 0.05). Personality, school performance, Mental Health Knowledge Questionnaire score and Career Decision-Making Self-Efficacy Scale score were the main factors affecting clinical practice inadaptability of psychiatric nursing students, and the odds ratio (OR) values were higher than 1.

Conclusion: Psychiatric nursing students experienced maladjustment during clinical practice, and Career Decision-Making Self-Efficacy was the main influencing factor.

This editorial explores the dynamic psychiatric research field by focusing on interdisciplinary approaches to understand the complexity of mental disorders by placing particular emphasis on schizophrenia. It highlights the need to integrate findings from diverse scientific disciplines, such as neuroscience, computational modeling and genomics, to unravel the multifaceted nature of these conditions. The potential of interdisciplinary research to transform our knowledge and the treatment of psychiatric disorders is underscored by moving beyond traditional models and developing more nuanced frameworks to more effectively address these complexities. Thus by combining perspectives from different fields, significant advancements are expected in the diagnosis, treatment and prevention of mental disorders like schizophrenia, and will open new research and clinical practice avenues in psychiatry.

Background: Diagnosing psychiatric disorders following craniocerebral trauma primarily depends on clinical symptoms and neuropsychological evaluation, which can be subjective and limited. This study aimed to investigate the diagnostic value of serum matrix metalloproteinase-9 (MMP-9), S100 calcium-binding protein β (S100-β), and glial fibrillary acidic protein (GFAP) in post-traumatic mental disorders.

Methods: A retrospective analysis was conducted on 108 patients with craniocerebral trauma admitted to Wenzhou Hospital of Integrated Traditional Chinese and Western Medicine between January 2021 and December 2023. Patients were categorized into a post-traumatic mental disorder group (n = 68) and a simple craniocerebral trauma group (n = 40) according to whether they had mental disorders. Serum MMP-9, S100-β, and GFAP levels were measured using enzyme-linked immunosorbent assay (ELISA) and compared between the two groups. Logistic multivariate regression identified risk factors for post-traumatic mental disorders, while receiver operating characteristic (ROC) curve analysis assessed the predictive value of the biomarkers. Spearman correlation analysis examined the relationship between serum biomarkers and the presence of post-traumatic mental disorders.

Results: Serum levels of MMP-9, S100-β, and GFAP were significantly elevated in the post-traumatic mental disorder group compared to the simple traumatic brain injury group (p < 0.001). Logistic regression revealed that craniocerebral injury severity, family satisfaction, and serum levels of S100-β and GFAP were significant risk factors for post-traumatic mental disorders (p < 0.05). The areas under the ROC curve for MMP-9, S100-β, and GFAP were 0.768, 0.937, and 0.904, respectively. Spearman correlation analysis showed that serum MMP-9, S100-β and GFAP were significantly positively correlated with the incidence of post-traumatic mental disorders (p < 0.001).

Conclusion: The levels of MMP-9, S100-β and GFAP were abnormal in the serum of patients with craniocerebral trauma. These biomarkers hold significant diagnostic value in patients with post-traumatic stress disorder.