This study aimed to examine the relationship between attitudes toward love, attachment styles, and personality traits in women who have experienced domestic violence (DV).
The study consisted of 64 women who experienced DV and 64 women without such history. All participants completed a sociodemographic data form and three assessment scales.
Among women who were exposed to violence, attitudes toward altruistic and passionate love were significantly higher (p < 0.001, p = 0.026). In contrast, women who had not experienced violence showed higher levels of friendly and possessive love attitudes (p = 0.010, p < 0.001). Women who experienced violence also exhibited a significant increase in both anxious and avoidant attachment styles (p < 0.001 and p < 0.001), while the emotionally balanced personality trait was significantly lower (p = 0.006). Additionally, positive correlations were found between altruistic love and anxious attachment style and between logical love and anxious attachment style (p = 0.021, r = 0.288; p = 0.033, r = 0.267, respectively). Conversely, negative correlations were observed between altruistic love attitudes and both extraversion and emotional stability (p = 0.038, r = –0.261; p = 0.030, r = –0.271, respectively), between game-playing love attitude and conscientiousness and emotional stability (p = 0.046, r = –0.250; p = 0.027, r = –0.277, respectively), and between passionate love attitude and emotional stability (p = 0.009, r = –0.323). Furthermore, a positive correlation was noted between friendly love attitudes and agreeableness (p = 0.017, r = 0.296).
Individuals with high levels of emotional stability, along with friendly and possessive love attitudes, may be better equipped to cope with violence, while those with anxious and avoidant attachment styles, as well as altruistic and passionate love attitudes, may have difficulty handling such experiences.
Herein, we report on the initial development, progress, and future plans for an autonomous artificial intelligence (AI) system designed to manage major depressive disorder (MDD). The system is a web-based, patient-facing conversational AI that collects medical history, provides presumed diagnosis, recommends treatment, and coordinates care for patients with MDD.
The system includes seven components, five of which are complete and two are in development. The first component is the AI’s knowledgebase, which was constructed using Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression to analyze extensive patient medical histories and identify factors influencing response to antidepressants. The second component is a series of adjustments to the knowledgebase designed to correct algorithm bias in patient subgroups. The third component is a conversational Large Language Model (LLM) that efficiently gathers patients’ medical histories. The fourth component is a dialogue management system that minimizes digressions in the LLM conversations, using a topic network statistically derived from the AI’s own knowledgebase. The fifth component is planned to enable real-time, human-in-the-loop monitoring. The sixth component is an existing analytical, non-generative module that provides and explains treatment advice. The seventh component is planned to coordinate care with clinicians via closed-loop referrals.
In component 1, the AI’s knowledgebase correctly predicted 69.2% to 78.5% of the variation in response to 15 oral antidepressants. Patients treated by AI-concordant clinicians were 17.5% more likely to benefit from their treatment than patients of AI-discordant clinicians. In component 2, the use of the system required adjustments to improve accuracy for predicting the responses of African Americans to four antidepressants and no adjustments were required for the remaining 10 antidepressants. In component 3, the conversational intake efficiently covered 1499 relevant medical history events (including 700 diagnoses, 550 medications, 151 procedures, and 98 prior antidepressant responses). In the fourth component, the dialogue management system was effective in maintaining a long dialogue with many turns in the conversation. In the sixth component, the advice system was able to rely exclusively on pre-set text. An online ad campaign attracted 1536 residents of Virginia to use the advice system. Initially, a focus group of clinicians was skeptical of the value of the advice system and requested more prospective studies before they would implement the system in their clinics. When the system was redesigned to advise patients at home, clinicians were willing to receive referrals from the system and discuss the advice of the system with their patients.
Further research is needed to refine and evaluate the system. We outline our plans for a prospective randomized trial to assess the system’s impact on prescription patterns and patient outcomes.
Depression is a common mental health problem that imposes a significant burden on both individuals and society. Numerous studies have shown that childhood abuse has a long-lasting detrimental effect on mental health, including the development of depression. This study reviews recent studies on the association between childhood abuse and depression, highlighting the robust causal link between childhood abuse and subsequent depression. The strength of this association varies depending on the type of abuse, with emotional abuse showing a particularly strong connection to depression. In addition, this narrative review examines the role of personality in the relationship between childhood abuse and depression. Evidence indicates that personality traits act as both mediators and moderators in this association, with neuroticism being particularly influential. Although available research evidence primarily consists of cross-sectional studies, which cannot determine the temporal sequence of childhood abuse, personality problems, and depression, the interrelations of these three variables provide a more comprehensive understanding of the etiology of depression. These insights lay the foundation for future longitudinal research and inform the development of more targeted preventive and therapeutic interventions in clinical psychiatry.
Postictal delirium (PID) is a significant and often underrecognized adverse effect associated with electroconvulsive therapy (ECT) in geriatric patients. Despite its clinical relevance, the specific risk factors contributing to the development of PID in this vulnerable population remain inadequately understood, which may affect treatment outcomes and patient safety.
In this retrospective study, we analyzed data from 168 elderly patients who underwent ECT between 2009 and 2020 at a general hospital in China. Univariate analyses of sociodemographic and clinical characteristics were performed to identify variables for inclusion in a logistic regression model. Multiple binary logistic regression analysis was performed to determine the relationship between these variables and PID occurrence.
The incidence of PID was 20.8% (35/168) among the study cohort. Univariate analysis revealed statistically significant differences between PID and non-PID groups for lithium (χ2 = 6.67, p = 0.010), quetiapine (χ2 = 4.36, p = 0.037), number of ECT sessions (U = 3065.50, p = 0.003), and response rate (χ2 = 12.86, p < 0.001). Logistic regression analysis demonstrated that lithium (odds ratio (OR) = 5.128; p = 0.009) and quetiapine (OR = 2.562; p = 0.024) were significantly associated with PID.
Our findings indicate that lithium and quetiapine use significantly increase the risk of developing PID, underscoring the need for clinical vigilance. Careful consideration of these medications when planning ECT treatment is recommended to minimize the risk of postictal complications and optimize therapeutic outcomes.
Depression is common among older adults with cataracts and is associated with significant functional impairment. However, the complex interrelationships among different depression symptoms are often overlooked by conventional mood disorders research based on total scores of depression measures. This study examined the interrelationships between different depressive symptoms and quality of life (QoL) in older adults with cataracts based on a national survey. By analyzing the key depressive symptoms related to QoL in this vulnerable population, the study aimed to identify potential critical treatment targets.
In this study, the 10-item Center for Epidemiologic Studies Short Depression Scale and the World Health Organization Quality of Life-brief version were used to measure depressive symptoms and QoL respectively. In the network analysis, Expected Influence was used to identify the central symptoms, and a flow network model was used to examine the symptoms that directly affected QoL.
A total of 1683 participants were included in the analysis. Economic status was the only identified risk factor for depression in older adults with cataracts. The most central symptoms in the depression network were “Feeling blue”, “Everything was an effort”, and “Inability to get going”. The flow network indicated that QoL had the strongest direct connections with “Unhappiness”, “Sleep disturbances” and “Feeling blue”.
Depression was found to be common among older adults with cataracts. To mitigate the negative impact of depression on QoL, psychosocial interventions targeting the most central symptoms and those directly related to QoL should be prioritized.
Depression is a serious mental and emotional disorder and is considered to be the greatest cause of non-fatal disease worldwide. Early life stress (ELS) refers to the exposure of an individual to physical and psychological stress events such as neglect or abuse in early life that has a long-term impact on brain development, thus inducing emotional and cognitive disorders in adulthood. It is the main susceptibility and risk factor for depression. Current clinical treatment is primarily based on Western medicines such as fluoxetine, but there can be serious adverse reactions. Therefore, exploring the biochemical mechanism of ELS-induced disorders and how to intervene effectively and safely to prevent and treat depression has become a significant issue. Traditional Chinese medicine (TCM) has the unique advantages of few adverse reactions and high safety and has great potential for the treatment of depression. Maternal separation (MS) is one of the most important and commonly used models for simulating ELS. Many studies have shown that MS-induced depression involves the regulation of multiple pathways and several studies have shown that TCM improves MS-induced depression. However, there is currently a lack of systematic reviews and summaries of the molecular mechanisms of MS-induced depression and traditional Chinese medical interventions. Therefore, the mechanisms of action and traditional Chinese medical interventions for MS-mediated depression were reviewed by searching recent relevant literature and discussing the limitations of current research. The aim was to provide guidance for follow-up basic research and clinical treatment.
In clinical practice, selective serotonin reuptake inhibitors (SSRIs), a kind of Western medicine, are the primary treatment for depression, a complex mental illness. However, these treatments are associated with significant adverse reactions. With their many benefits and distinctive features, such as all-encompassing intervention and general control through several targets, processes, and pathways, the active components in traditional Chinese medicine (TCM) hold great promise for the treatment of depression. Autophagy plays a crucial role in the pathophysiology of depression, and its regulation has emerged as a potentially crucial management tactic. However, comprehensive evaluations of the link between depression and mitochondrial autophagy, as well as the therapeutic potential of TCM’s active components, remain limited. This review examined recent literature on autophagy and its role in depression, along with studies on the effects of TCM active ingredients. Furthermore, it highlighted the limitations of current research to offer insights to guide future fundamental studies and clinical treatments for depression.
Children’s mental health is significantly influenced by family environments, where multiple risks often coexist, exert unequal impacts, and combine in different configurations that can result in diverse developmental outcomes. This study examines how different configurations of cumulative family risks influence mental health symptoms in Chinese children using a novel person-centered approach.
Data were collected through a large-scale, semester-based comprehensive survey of 34,041 children in Grades 4 to 6 in an economically underdeveloped county-level city in Guangdong, China, during November and December, 2022. Six family risk indicators were examined: incomplete family structure, parent–child separation, financial hardship, low parental education, lack of family intimacy, and family conflict. The Pediatric Symptom Checklist was used to measure children’s mental health outcomes, consisting of internalizing problems, externalizing problems, and attention problems. Crisp-set qualitative comparative analysis was applied to identify specific configurations of family risks associated with different mental health outcomes.
No single risk factor was found necessary or sufficient to explain mental health outcomes; configurations of multiple risks were more predictive. Externalizing and attention symptoms shared one configuration, which also contributed to internalizing symptoms. Additionally, three distinct configurations were uniquely associated with internalizing symptoms. Only lack of family intimacy and family conflict consistently appeared as detrimental across all configurations.
This study reinforces the cumulative risk model and aligns with the concepts of multifinality and equifinality. It emphasizes the importance of monitoring children with coexisting risks and targeted interventions addressing one or two key factors rather than all factors simultaneously. Future research should adopt longitudinal designs and include broader factors.
Obesity and depressive disorders are significant public health concerns, and their association is well-documented. This study investigates the role of inflammatory markers, specifically C-reactive protein (CRP) and neutrophil-to-lymphocyte ratio (NLR), in mediating the relationship between obesity and depressive symptoms.
We utilized data from 37,538 adults from the National Health and Nutrition Examination Survey (NHANES), covering the period from 2005 to March, 2020, pre-pandemic. Depressive symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9), while inflammatory markers were assessed via NLR and CRP levels.
Results indicated a positive correlation between obesity, NLR, and CRP levels, and depressive symptoms. Notably, CRP exhibited a significant mediating effect in the obesity and depressive symptoms link, whereas NLR did not. (NLR: 0.0926%, p = 0.740; CRP: 32%, p < 0.001). Furthermore, the mediating effect of CRP in the male group was significantly higher than in the female group (Men: 57%, p < 0.001; Women: 16%, p = 0.046).
These findings provide new insights into the mechanisms linking obesity and depressive symptoms, especially in men, and may guide future therapeutic strategies.
In bipolar disorder, residual mood symptoms often persist even during the euthymic period, impairing functionality in 30–60% of patients in clinical remission. Addressing residual symptoms is critical as they are linked to reduced functionality and subjective wellbeing. This cross-sectional study aimed to determine the relationship between mindful attention awareness (MASS) and residual symptom severity in bipolar I disorder.
This study included 100 patients with bipolar I disorder (BD-I) in remission, recruited consecutively from outpatient clinics between December, 2019 and March, 2020. The patients were evaluated using the sociodemographic data form, Hamilton Depression Rating Scale (HAM-D), Young Mania Rating Scale (YMRS), and Mindful Attention Awareness Scale (MAAS).
As the MAAS of the patients increases, their depressive symptoms decrease (p < 0.001). As the MAAS of the patients increases, their anxiety symptoms decrease (p < 0.001). No statistically significant relationship was found between the mindful attention awareness of the patients and their manic symptoms (p = 0.161). Two variables (HAM-D and Hamilton Anxiety Rating Scale Scores (HAM-A)) in the multiple linear regression model explain 21.8% of the change in MAAS score.
Residual depressive and anxiety symptoms are predictive of lower MAAS in bipolar I disorder. Incorporating strategies to manage residual mood symptoms and improve mindfulness may enhance functionality and facilitate complete remission. However, given the cross-sectional design and the lack of a control group, causal inferences cannot be made. Further longitudinal and interventional studies are needed to explore the efficacy of mindfulness-based approaches in BD-I and determine whether the observed associations are specific to this disorder.
Problematic internet use (PIU) is a general behavioral addiction and encompasses various syndromes. Previous research found that traumatic events may potentially influence or alter the propensity for PIU. This study aimed to explore the mediating role of fear of missing out (FOMO) and rumination in the influence of post-traumatic stress disorder (PTSD) on PIU among Wenchuan earthquake survivors.
In the fall of 2023, 665 valid participants’ responses were selected in this cross-sectional study. The PTSD Checklist (PCL-C), FOMO Scale, Rumination Scale (RRS), and Generalized Problematic Internet Use Scale 2 (GPIUS2) were used to measure participants’ internet usage and mental state. Description analysis and structural equation model analysis were examined by using SmartPLS.
PTSD positively influenced FOMO (β = 0.315, p < 0.001), rumination (β = 0.279, p = 0.001), and PIU (β = 0.213, p < 0.001). FOMO (β = 0.08, 95% CI (confidence interval) [0.037, 0.144], p = 0.005) and rumination (β = 0.093, 95% CI [0.032, 0.139], p = 0.002) played a mediating role in the influence of PTSD on PIU. Regarding the relationship between PTSD and PIU, direct and indirect effects comprised 45.6% and 54.4%. PTSD had a positively significant effect on PIU by mediating FOMO and rumination to form a chain mediation model (β = 0.081, 95% CI [0.010, 0.039], p = 0.002).
This study investigated online usage and media psychology among survivors of the Wenchuan earthquake in China. FOMO and rumination were found to be important factors influencing the relationship between PTSD and PIU. To prevent or relieve people’s PIU, we propose that medical practitioners and local government intervene on FOMO through effective measures to decrease rumination. The individual differences and specific internet platform usage that influence these psychological variables should also be further investigated in future studies.
The negative impact of obesity on cognitive function (CF) is well-established; nevertheless, no prior studies have explored the link between conicity index and cognitive performance. This research sought to investigate the link between conicity index and cognitive impairment.
Data were obtained from a cross-sectional analysis of the National Health and Nutrition Examination Survey 2011–2014 (NHANES), with CF evaluated by the total scores of three cognitive tests (TCT), the delayed recall test (DRT), the immediate recall test (IRT), the animal fluency test (AFT), and the digit symbol substitution test (DSST). The conicity index was derived from waist circumference, height, and weight. Multiple linear regression, smooth curve fitting, and subgroup interaction analyses were utilized to explore the correlation between conicity index and cognitive performance.
The study included 2752 subjects and the results indicated that increasing conicity index was markedly associated with declining CF. In fully adjusted models, the conicity index was linked to reductions in total cognitive score (β = –16.35, 95% confidence interval (CI): –26.68 to –6.02, p = 0.0019) and DRT (β = –1.52, 95% CI: –2.74 to –0.30, p = 0.0151), IRT (β = –2.93, 95% CI: –5.37 to –0.48, p = 0.0190), AFT (β = –2.03, 95% CI: –4.88 to 0.82, p = 0.1636), and DSST (β = –9.88, 95% CI: –17.11 to –2.65, p = 0.0075) scores. However, the negative association between conicity index and AFT score was not statistically significant.
Lower CF is associated with a higher conicity index. The conicity index is useful for the early detection of cognitive decline.
Information about the level of general personality functioning could provide benefits for tailoring substance use disorder (SUD) treatment. This study examined self-reported personality functioning among patients with SUD compared to the general population, gender specifics, and the psychometric properties of the Czech Level of Personality Functioning Scale-Self Report (LPFS-SR).
Two samples were used in this study. Sample 1 (n = 368) consisted of patients with SUD, while Sample 2 (n = 497) comprised volunteers from the general population. All participants, with an age range of 18–75 years, completed a battery of self-assessment tools, including a demographic form, the Personality Inventory for DSM-5 (PID-5), and the LPFS-SR, administered via a pencil-and-paper method. Internal consistency and several aspects of the validity of the Czech LPFS-SR were examined.
The LPFS-SR showed high internal consistency as estimated by Cronbach’s alpha (α ≥ 0.66) and the high mutual correlation with the PID-5 varied from 0.21 to 0.77. Principal component analysis (PCA) of the four LPFS-SR subscales indicated a single-component structure, accounting for 78.21% of the variance in Sample 1 and 79.20% in Sample 2, supporting previous results regarding the LPFS-SR factorial structure. Furthermore, gender-specific cut-off scores were obtained and are discussed in relation to previous research.
The findings indicate that the Czech LPFS-SR is a valid and reliable tool with acceptable discriminating capacity. It can be used in research and clinical assessments of personality functioning in patients with SUD, particularly when considering gender-specific characteristics.
To analyze the correlation between interleukin-5 (IL-5), eosinophils (EOS), and immunoglobulin A (IgA) levels with schizophrenia, and assess their potential as auxiliary diagnostic markers for schizophrenia.
This study comprised 57 patients with first-episode schizophrenia and 340 patients with recurrent or chronic schizophrenia who were hospitalized at Beijing Huilongguan Hospital from March 2023 to August 2024, and 72 healthy volunteers were recruited as the control group. Fasting venous blood samples were collected from all participants on the second day after admission. For patients with first-episode schizophrenia, a second blood draw was performed after two months of treatment. Simultaneously, the Positive and Negative Symptom Scale (PANSS) was administered to assess the subjects. IL-5 and EOS levels were measured using flow cytometry; IgA levels were measured using immunoturbidimetry. SPSS v.29.0 was used to conduct t-tests, one-way ANOVA, correlation analysis and receiver operating characteristic (ROC) curve analysis.
The first-episode schizophrenia group and the recurrent/chronic schizophrenia group had elevated IL-5 levels relative to healthy controls; however, the increase in EOS levels was specifically observed in the recurrent/chronic schizophrenia group. After treatment, the IL-5 level in the first-episode group was markedly reduced. Correlation analysis revealed that in patients with schizophrenia, IL-5 levels were positively correlated with EOS (r = 0.338, p < 0.001), and EOS levels were positively associated with disease duration (r = 0.171, p < 0.05), the ROC curve analysis revealed that IL-5 had a sensitivity of 52.9%, specificity of 69.4%, and a cut-off value of 2.445 pg/mL for predicting schizophrenia.
In patients with schizophrenia, the elevated levels of IL-5 and EOS appear to be disease-related rather than medication-induced, suggesting their potential involvement in the inflammatory pathogenesis of schizophrenia. Furthermore, IL-5 exhibits greater predictive accuracy for schizophrenia compared to EOS, suggesting that IL-5 may serve as a valuable biomarker for auxiliary diagnosis and stratification analysis in schizophrenia.
Schizophrenia (SCZ) is a common, chronic, severe mental disorder that is often accompanied by dyslipidemia and linked to decreased life expectancy. The prevalence of dyslipidemia among initial-treatment and drug-naïve (ITDN) patients with SCZ and the correlates influencing its occurrence and severity were determined in this study.
Demographic and clinical data including blood pressure, blood cell count, renal function, lipid profile, fasting glucose level, and thyroid function were collected from the 668 patients with ITDN SCZ included in this study. Psychopathology and illness severity were evaluated using the Positive and Negative Symptom Scale and the Clinical Global Impression Scale - Severity of Illness, respectively.
The prevalence of dyslipidemia was 33.53% (224/668) and the influencing factors included higher education attainment (B = 0.43, p = 0.018, odds ratio [OR] = 1.54) and elevated systolic blood pressure (SBP) (B = 0.04, p < 0.001, OR = 1.04), which were predictive factors. Conversely, having a spouse (B = –0.40, p = 0.026, OR = 0.67), higher red blood cell counts (B = –0.77, p < 0.001, OR = 0.47), and higher free tetraiodothyronine (FT4) levels (B = –0.06, p = 0.022, OR = 0.94) were protective factors. Specifically, elevated SBP (B = 0.01, t = 2.71, p = 0.007, 95% confidence interval [CI] = 0.00–0.01) predicted dyslipidemia severity, whereas higher FT4 levels (B = –0.02, t = –2.45, p = 0.015, 95% CI = –0.04–0.00) had a protective effect.
Our study provides valuable insights into the clinical characteristics of dyslipidemia in ITDN SCZ patients. The identified factors influencing dyslipidemia occurrence and severity could serve as potential bioindicators for its prevention and intervention in clinical settings.
Hypothalamic‒pituitary‒adrenal axis response is essential for coping with acute stressors, while maladaptive stress coping may increase the risk of major depressive disorder. We previously demonstrated that behavioral patterns induced by prior psychological stress predict coping levels in response to future stressors. This study investigated whether activating corticotropin-releasing hormone (CRH) and corticosteroid receptors mediates psychological stress-induced coping behavior.
Behavioral responses in mice exhibiting a fear response elicited by exposure to 2,5-dihydro-2,4,5-trimethylthiazoline (TMT), a synthetic component of fox feces, as preceding psychological stress, were assessed by measuring central zone entries in an open-field test. Time spent immobile during the tail suspension test was evaluated as a subsequent aversive stress-coping level. CRH overexpression was induced by adeno-associated virus injection (Hypo-CRH-OE) into the paraventricular hypothalamic nucleus. Dexamethasone (10 μg/kg, s.c.), a glucocorticoid receptor agonist, or fludrocortisone (5 mg/kg, s.c.), a mineralocorticoid receptor agonist was administered 30 min before behavioral tests.
Hypo-CRH-OE mice exhibited significantly higher plasma corticosterone levels than controls, without changes in baseline of locomotor activity or innate fear sensitivity. During TMT exposure, Hypo-CRH-OE mice showed lower central activity in the open-field test, accompanied by longer immobility time in the tail suspension test (TST), disrupting the correlation between these behaviors. A similar disruptive effect was observed in fludrocortisone-treated mice but not in dexamethasone-treated mice. Additionally, fludrocortisone, but not dexamethasone, prolonged immobility during the TST.
Preceding psychological stress-induced behavioral patterns may predict coping levels through mineralocorticoid receptor activations offering a potential target for improving stress resilience and preventing depression.
Physical aggression in schizophrenia patients carries significant societal implications. Previous studies on aggression prediction have primarily focused on hospitalized patients, overlooking specific rural community contexts in China. This study investigated multidimensional predictive factors to develop and validate a predictive model for predicting physical aggression in schizophrenia patients in rural communities in southwestern China.
We used convenience sampling to select 889 confirmed patients with schizophrenia from 22 rural townships recorded by the Pengzhou Mental Health Center from September to November, 2019 for baseline survey. Sixty-two candidate factors were investigated using the Morningness-Eveningness Questionnaire, Multidimensional Fatigue Inventory, and Medication Coherence Rating Scale, and aggression was evaluated using the Modified Overt Aggression Scale during a 3-month follow-up. Logistic regression was used to construct a risk prediction model and the model was validated using the receiver operating characteristic (ROC) curve.
Two variable selection methods, least absolute shrinkage and selection operator and multivariate logistic regression, yielded two models: Model 1 with 27 variables and Model 2 with six variables. Both models demonstrated perfect discrimination, good calibration, and clinical utility. Model 2, with three historical and three modifiable factors, demonstrated greater utility for communities, which included physical aggression against others prior to the first episode of schizophrenia, the Modified Overt Aggression Scale score at first episode onset, mental fatigue, body mass index, experiences of discrimination, and aggression against objects before the first episode. Most predictors were non-specific to schizophrenia.
These findings may help to alleviate the social discrimination and constraints faced by individuals with schizophrenia in rural communities, facilitating the provision of proactive mental health services. Furthermore, our results highlight body mass index, discrimination experiences, and mental fatigue as critical areas for rural community mental health nursing professionals.
No: ChiCTR1800015219. https://www.chictr.org.cn/showproj.html?proj=25941.
The Social Interaction Anxiety Scale-6 (SIAS-6) and Social Phobia Scale-6 (SPS-6) are self-reported measures of social anxiety. The aim of this study was to identify the best model for SIAS-6 and SPS-6 using the newly advanced method of exploratory structural equation modeling (ESEM).
Both confirmatory factor analysis (CFA) and ESEM were utilized to assess the factor structure of the SIAS-6 and SPS-6. Three hundred Korean adults (nfemale = 150, aged: 39.28 ± 10.91 years) participated in an online survey and responded to the SIAS-6 and SPS-6 questionnaires.
The findings showed that the bifactor ESEM and bifactor CFA models were a better fit than the other models. General factors had high loading values and reliability coefficients, whereas specific factors had moderate loading values and reliability coefficients. Additionally, measurement invariance across sexes was established.
This study demonstrated that bifactor models provide a unified perspective on the varying viewpoints regarding the relationship between social interaction and social performance anxiety.
The progressive legalization and widespread use of cannabis has led to its use as a treatment for certain neuropsychiatric disorders. Traditional epidemiological studies suggest that cannabis use has an effect on some neurocognitive aspects. However, it is unclear whether cannabis use is causally related to common neuropsychiatric disorders. The present study was conducted to illustrate the causal relationships of genetically predicted cannabis use with common neuropsychiatric disorders.
We used a two-sample Mendelian randomization method using genome-wide association study (GWAS) summary statistics obtained from publicly available databases on lifetime cannabis use and 10 neuropsychiatric disorders, including multiple sclerosis (MS), Alzheimer’s disease (AD), amyotrophic lateral sclerosis (ALS), autism spectrum disorder (ASD), epilepsy, generalized epilepsy, focal epilepsy, migraine, migraine with aura, migraine without aura, schizophrenia (SCZ), anorexia nervosa (AN), attention-deficit/hyperactivity disorder (ADHD), and Parkinson’s disease (PD) were studied with a two-sample Mendelian randomization method for GWAS summary statistics. The inverse variance weighted (IVW) method was used as the main analysis model.
Our study suggests that lifetime cannabis use is associated with an increased risk of developing PD (odds ratio (OR) = 1.782; 95% CI 1.032–3.075; p = 0.038) and an increased risk of ADHD in female participants (OR = 1.650; 95% CI 1.051–2.590; p = 0.029).
Cannabis intake may cause adverse effects relating to certain neuropsychiatric disorders. Therefore, special attention should be paid to the side effects of addictive drugs during clinical treatment to avoid harmful effects on the brain and neurocognition.
Whether changes in Somatic Symptom Scale-8 (SSS-8) scores adequately reflect subjective improvement in patients with somatic symptoms and related disorders (SSRD) at follow-up is unclear. The minimal clinically important difference (MCID) is a criterion of estimating clinically significant improvement derived from patients’ responses to anchor questions that accurately reflect changes in their condition. This study aimed to clarify the MCID value of the SSS-8 for SSRD.
Patients with SSRD aged 18 to 84 years who attended a university hospital outpatient department in Japan were eligible. The participants were assessed using the SSS-8 for physical symptoms. After approximately 6 months of outpatient treatment, the participants were reassessed using the SSS-8 for physical symptoms. The primary endpoint was the Patient Global Impression of Change score. The secondary endpoint was the physical function items of the Multidimensional Patient Impression of Change questionnaire. These questionnaires were used to define improvements in subjective symptoms as the anchor to estimate the MCID. Receiver operating characteristic analysis was performed based on the anchor questions and the MCID values of the SSS-8 were calculated.
Ninety participants were included. The primary endpoint MCID value for the SSS-8 was –6 points, with an area under the curve (AUC) of 0.87, 65.9% sensitivity, and 93.5% specificity. The secondary endpoint MCID value for the SSS-8 was –6 points, with an AUC of 0.85, 76.5% sensitivity, and 89.3% specificity.
The SSS-8 is a useful indicator for SSRD clinical outcomes. Patients with SSRD may need an SSS-8 score decrease of 6 or more points to notice symptom improvements.
To tailor culturally sensitive interventional strategies for safeguarding adolescents’ mental health, this study investigated the role of perceived parental involvement in predicting depressive symptoms among Chinese adolescents, considering family socioeconomic status (SES).
A cluster convenience sampling method recruited 21,818 participants from 48 middle schools across 29 provinces in China. The perceived parental involvement (PPI) Scale and the Chinese version of the center for epidemiologic studies depression scale (CES-D) assessed parental involvement and depressive symptoms, respectively. Data analysis employed linear mixed-effect models (LMM) and latent profile analysis (LPA).
The results indicated that 35.26% of adolescents exhibited subclinical depressive symptoms. LMM analysis revealed that higher perceived parental involvement scores, particularly emotional involvement, significantly predicted lower CES-D scores (β = –0.45, p < 0.001). LPA identified three distinct family factors profiles, with the “High SES-High PPI” group showing the lowest depression scores.
The findings underscore the protective benefits of perceived parental involvement, especially emotional support, in mitigating depressive symptoms among adolescents. Specifically, adolescents from families with both high SES and high parental involvement exhibited the lowest levels of depressive symptoms, suggesting that interventions should focus on enhancing emotional support and addressing socioeconomic disparities to effectively reduce adolescent depression.
Autism spectrum disorder (ASD) is a multifaceted neurodevelopmental disorder marked by impaired interactions and restricted interests, the pathophysiology of which is not fully understood. The current study explored the potential therapeutic effects of transcranial direct current stimulation (tDCS) on the neurophysiological aspects of ASD, specifically focusing on the brain’s excitatory/inhibitory (E/I) balance and behavioral outcomes, providing scientific guidance for ASD intervention.
Forty-two children with ASD were randomly divided into either an active tDCS or sham tDCS group. Electroencephalography (EEG) recordings were conducted before and after stimulation to assess E/I changesusing EEG markers including α oscillations and the aperiodic exponent, and average spatial phase synchronization (ASPS) analysis and detrended fluctuation analysis (DFA) were performed. Behavioral changes were evaluated using the Autism Behavior Checklist (ABC) and the Social Responsiveness Scale (SRS).
Active tDCS resulted in significant increases in α oscillation power, reductions in α bandwidth, and improvements in γ-band ASPS and DFA values. Furthermore, participants in the active tDCS group exhibited improvements in behavioral scores on the ABC and SRS, with enhancements in social communication, sensory processing, and adaptive behavior. We found no significant changes in the sham group.
These findings suggest that tDCS intervention effectively reduced brain excitability and improved E/I balance and behavioral outcomes in children with ASD. The results warrant further investigation into the efficacy and underlying mechanisms of tDCS for ASD treatment.
No: ChiCTR2400092790, https://www.chictr.org.cn/showproj.html?proj=249950.