BMC Psychiatry最新文献

{"title":"Effects of community-based rehabilitation on caregivers of people with schizophrenia in Ethiopia in the RISE trial.","authors":"Lotte G Dijkstra, Helen A Weiss, Rahel Birhane, Girmay Medhin, Mary de Silva, Charlotte Hanlon, Abebaw Fekadu, Laura Asher","doi":"10.1186/s12888-025-06651-4","DOIUrl":"10.1186/s12888-025-06651-4","url":null,"abstract":"<p><strong>Background: </strong>Schizophrenia is a severe mental health condition with high impact on those affected and their families. Community-based rehabilitation (CBR) is a recommended treatment component for schizophrenia in low- and middle-income countries (LMIC), as it seeks to address complex social, health and economic needs. There is little evidence on the effects of CBR on caregivers of people with schizophrenia. RISE, conducted in Ethiopia, was the first randomised controlled trial of CBR for schizophrenia in a low-income country. In this paper, we extend our previous examination of caregiver impact by (1) investigating the impact of CBR on caregiver stigma and burden, (2) assessing effect modification of outcomes, and (3) determining predictors of caregiver outcomes at 12 months.</p><p><strong>Methods: </strong>Data are from the cluster-randomised controlled RISE trial, which investigated CBR and facility-based care versus facility-based care alone among 166 people with schizophrenia and 166 linked caregivers in 48 sub-districts in Ethiopia. We analyse the effect of CBR on caregiver stigma, unemployment and burden measured with the WHO Family Interview Schedule-Impact at 6 and 12 months; and caregiver depression, reduction in work due to caregiving and caregiver burden measured with the Involvement Evaluation Questionnaire at 6 months. Logistic and linear regression models adjusted for clustering by sub-district and health centre were used for binary and continuous outcomes respectively. Effect modification by caregiver sex, age, baseline of the outcome, and baseline disability were assessed. Baseline factors associated with caregiver outcomes across the whole cohort at 12 months were investigated using hierarchal regression modelling.</p><p><strong>Results: </strong>Data were available for 112 caregivers at 6 months (67%), and 149 caregivers at 12 months (90%). There was evidence that CBR was associated with greater tendency to reduce work due to caregiving at 6 months (OR:2.40, 95%CI:1.06-5.45). No evidence of an intervention effect was found on unemployment, depression, stigma or other aspects of caregiver burden. There was no evidence for effect modification. Higher baseline disability was independently associated with greater caregiving burden at 12 months (β:0.26, 95%CI:0.14-0.37).</p><p><strong>Conclusions: </strong>There appeared to be no positive intervention effect of CBR on caregiver stigma, unemployment and burden in this analysis. Improving the outcomes of caregivers of people with schizophrenia in LMIC requires interventions and research addressing the needs of caregivers, for instance by integrating social and livelihoods interventions.</p><p><strong>Trial registration: </strong>Clinical Trials.gov Identifier NCT02160249. Registered on 3 June 2014.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"231"},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11899427/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143603777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinician differences in attitudes and perceptions on the use of long-acting injectable antipsychotic agents in treating patients with schizophrenia: results from the US DECIDE survey.","authors":"Dawn Velligan, Gregory D Salinas, Emily Belcher, Kelli R Franzenburg, Mark Suett, Stephen Thompson, Rolf T Hansen","doi":"10.1186/s12888-025-06565-1","DOIUrl":"10.1186/s12888-025-06565-1","url":null,"abstract":"<p><strong>Background: </strong>Long-acting injectable antipsychotics (LAIs) reduce relapses in schizophrenia; however, most clinicians reserve LAIs for nonadherence with oral antipsychotics (OAs) or severe disease.</p><p><strong>Methods: </strong>US psychiatric clinicians were surveyed regarding their schizophrenia management practices and use of LAIs. Respondents were grouped by LAI use (high [≥ 31% of patients using LAIs], low [≤ 14% using LAIs]; mid not analyzed) and mindset based on their response to \"Which of the following best fits the current way you view your use of [LAIs] for your patients with schizophrenia?\"</p><p><strong>Results: </strong>Respondents (n = 380) were distributed across LAI use (106 high, 130 low) and mindset (123 early-use, 88 severity-reserved, 113 adherence-reserved, 56 LAI-hesitant) subgroups. Across subgroups, clinicians estimated that OA nonadherence was lower for patients in their practice (21-52%) than for patients nationwide (50-56%). Compared with other subgroups, greater proportions with high LAI use or an early-use mindset were confident in key aspects of LAI treatment like dosing, managing side effects, and access (67-74% high LAI use, 59-70% early-use vs. 11-57% other subgroups; P < .05 each), agreed it was \"worth [their] time to resolve issues with the insurance company\" (42%, 45% vs. 16-30%; P < .05 each), and were optimistic they would be able to do so (23%, 20% vs. 2-11%; P < .05 each). Clinicians with high LAI use estimated the proportion of patients who initially accept LAIs to be higher (mean, 56%) than clinicians with low LAI use (45%, P < .01); there were no differences among mindsets (49-54%). Clinicians with high LAI use or early-use mindset were more likely to \"use any means necessary to ensure that a patient is on an LAI\" than clinicians in other subgroups (44% high LAI use, 51% early-use vs. 5-22% other subgroups; P < .01 each) or had used guardianship to assist with treatment (70%, 69% vs. 32-56%; P < .05 each).</p><p><strong>Conclusions: </strong>These results indicate that multiple factors (e.g., environmental/demographic factors, access, attitudes, motivation, knowledge/confidence) combine to influence LAI use, and highlight the need to tailor educational materials aimed at improving patient outcomes through increased LAI use.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"232"},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11899160/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143603772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Admission and goodbye letters from adolescents with anorexia nervosa in a day hospital.","authors":"Sarah Pinto, Lisa Minier, France Hirot, Pauline Drecq, Nathalie Godart, Caroline Huas","doi":"10.1186/s12888-025-06647-0","DOIUrl":"10.1186/s12888-025-06647-0","url":null,"abstract":"<p><strong>Background: </strong>Care providers working with adolescents with anorexia nervosa (AN) encounter difficulties inherent in the illness (denial, ambivalence) and those related to the fact that it is most often the parents who bring adolescents to care units. Our aim was to study attitudes towards care among adolescents with AN treated in a specialised day hospital using an analysis of letters written before and after treatment.</p><p><strong>Methods: </strong>Adolescents (12-20 years old) treated for AN in a specialised day hospital, providing multidisciplinary care while enabling a return to schooling inside the facility were included. We analysed 50 admission letters and 23 goodbye letters using general inductive analysis. A mirror analysis was conducted.</p><p><strong>Results: </strong>In the admission letters, symptoms, calls for help, and reports on the adolescents' care trajectories were central themes. Among the categories noted in both the admission and the goodbye letters, some were similar, some mirrored others and a few differed.</p><p><strong>Conclusions: </strong>This study highlights how ambivalence and motivations towards care, recovery and illness all interact. It also shows the evolution of the adolescents' positions via their narratives on their experience of care, the constraints involved and its benefits for them. The results are discussed in a care perspective.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"221"},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11900417/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143603762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Individual and integrated indexes of inflammation predicting the risks of mental disorders - statistical analysis and artificial neural network.","authors":"Shu-Min Huang, Fu-Hsing Wu, Kai-Jie Ma, Jong-Yi Wang","doi":"10.1186/s12888-025-06652-3","DOIUrl":"10.1186/s12888-025-06652-3","url":null,"abstract":"<p><strong>Objective: </strong>The prevalence of mental illness in Taiwan increased. Identifying and mitigating risk factors for mental illness is essential. Inflammation may be a risk factor for mental illness; however, the predictive power of inflammation test values is unclear. Artificial intelligence can predict the risk of disease. This study was the first to conduct risk prediction based on the combination of individual inflammation test values.</p><p><strong>Methods: </strong>A retrospective longitudinal design was adopted to analyze data obtained from a medical center. Patients were enrolled if they had received blood tests for inflammation. Propensity score matching was employed for within-group comparisons. A total of 231,306 patients were enrolled. A deep neural network model was employed to establish a predictive model.</p><p><strong>Results: </strong>Among inflammation markers, high-sensitivity C-reactive protein concentrations were associated with the greatest risk of mental illness (37.45%), followed by the combination of individual inflammation test values (32.21%). The more abnormal a participant's inflammation values were, the higher the risk of mental illness (aHR = 1.301, p <.001). Specifically, high-sensitivity C-reactive protein concentration was the most indicative marker for predicting mental illness. Inflammation markers exhibited certain correlations with the type of mental illness. When the same variables were considered, statistical analysis and the deep neural network had similar results. After feature extraction was incorporated, the performance of the deep neural network model improved (excellent, area under the curve = 0.9162) and could effectively predict the risk of mental illness.</p><p><strong>Conclusion: </strong>Inflammation values could predict the risk of developing mental illnesses in general and the risk of developing certain types of mental illness.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"226"},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11900596/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143603786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the nature and dynamics of self-affirmation in non-depressed and subclinically depressed Indian adults: a thematic analysis.","authors":"Gyanesh Kumar Tiwari, Priyanka Parihar, Ajit Kumar Singh, Amit Kumar Macorya, Anurag Shukla, Archana Singh, Archna Choudhary, Ashutosh Pandey","doi":"10.1186/s12888-024-06364-0","DOIUrl":"10.1186/s12888-024-06364-0","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Self-affirmation, a crucial concept that promotes self-esteem and individual development amidst life challenges, has proven therapeutic, preventative, and enhancing benefits. However, there is limited understanding regarding its frequency among individuals experiencing subclinical depression. This research aimed to understand the dynamics of self-affirmation, threats, and self-resources in both healthy (non-depressed) and subclinically depressed Indian adults.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Using a qualitative research design, forty-three individuals aged 20-30 years (18 healthy, 25 subclinically depressed individuals) were selected based on depression measurement. The data were collected through a semistructured interview. The interviews were audiotaped, transcribed verbatim and analysed using the thematic analysis method.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Five themes were identified for subclinically depressed: social and relational threats, the tendency to magnify threats, negative cognitions and thoughts, denial/avoidance of threats, and poor awareness of self-resources. Five themes were also identified for healthy adults: explicit awareness of threats, common humanity, early responses to threats, adversity as an opportunity and easy availability of positive cognitions. Thus, the two groups differed significantly in their type, nature, and genesis of self-affirmation. For subclinically depressed, the major threats were related to health, financial conditions, employment, and relationships. These threats were positively and adaptively present in healthy adults. The subclinically depressed participants suffered from maladaptive tendencies and insufficient self-resources, while the healthy participants used positive self-resources and positive cognitions in dealing with the threats.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This study highlights the significant differences in self-affirmation processes between subclinically depressed and healthy adults. This finding supports the theoretical understanding that subclinical depression is associated with maladaptive cognitive patterns and a lack of self-resources. These findings underscore the importance of cognitive-behavioural frameworks that emphasize the role of positive self-affirmation and self-resources in mental health and highlight the need for targeted interventions that can strengthen these domains in subclinically depressed individuals. Therapeutic interventions for subclinical depression should focus on improving self-affirmation practices, increasing awareness of self-resources, and attenuating negative cognitive tendencies. Practitioners should consider integrating strategies that promote positive cognitions and proactive threat management. Additionally, preventative mental health programs could benefit from incorporating modules that strengthen self-affirmation and self-resource awareness of one's resources to build resilience in the general population, parti","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"224"},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11900383/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143603479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mediation by elevated prolactin in the relationship between childhood trauma and first-episode drug-naïve schizophrenia.","authors":"Yuqian Pan, Leijun Li, Xiaowei Xia, Zhinan Li, Jiamin Dai, Junyan Wu, Tong Liu, Ming Chen, Junxiao Ma, Yanxi Liu, Ziyi Zhang, Qingni Shen, Sichu Tao, Zixin Deng, Shimao Kang, Kexin Zhang, Xiaobing Zou, Jihui Wang, Qinling Wei","doi":"10.1186/s12888-025-06629-2","DOIUrl":"10.1186/s12888-025-06629-2","url":null,"abstract":"<p><strong>Background: </strong>The elevated prolactin levels in first-episode drug-naïve (FEDN) schizophrenia patients may correlate with long-term stress caused by childhood trauma. This study aimed to assess the relationship between elevated prolactin levels and childhood trauma in FEDN schizophrenia patients, while also considering sex differences.</p><p><strong>Methods: </strong>Utilizing a cross-sectional design, the study involved 88 FEDN schizophrenia patients and 76 healthy controls (HCs). Evaluations encompassed measuring prolactin levels in peripheral blood and assessing mental health using the Positive and Negative Syndrome Scale (PANSS), the Childhood Trauma Questionnaire - Short Form (CTQ-SF), as well as evaluating resilience with the Connor-Davidson Resilience Scale (CD-RISC), perceived social support with the Perceived Social Support Scale (PSSS), and demographic characteristics to control for confounding factors. A mediation model was constructed using the RMediation package of the R software.</p><p><strong>Methods: </strong>The results suggested prolactin levels in FEDN schizophrenia patients were higher than in HCs(t=-9.938, p = 0.000). Group classification (HCs vs. FEDN schizophrenia patients) (t = 9.291, p = 0.000) and sex (t = 3.282, p = 0.001) were influential factors for prolactin levels. Elevated prolactin(OR = 1.007, p = 0.000), along with higher scores for childhood emotional(OR = 1.469, p = 0.006)andsexual abuse(OR = 1.592, p = 0.018) and lower social support(OR = 0.946, p = 0.026), were associated with the onset of schizophrenia. Positive correlations were found between prolactin levels and childhood emotional (r = 0.268, p = 0.002) /sexual abuse(r = 0.264, p = 0.002), with no sex differences. No significant relationship was observed between prolactin levels and PANSS scores. Mediation analysis revealed that childhood emotional abuse (95% CI: [0.059 ~ 0.293]) and sexual abuse (95% CI: [0.086 ~ 0.439]) had significant indirect effects on schizophrenia, mediated by elevated prolactin levels.</p><p><strong>Conclusion: </strong>These findings suggest that childhood trauma may be associated with the onset of schizophrenia by influencing prolactin levels, highlighting the complex interplay between hormonal disruptions and early-life stress in the development of schizophrenia.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"223"},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11900333/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143603731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using network analysis to identify central symptoms of depression and anxiety in different profiles of infertility patients.","authors":"Fang Liu, Wei Qiao, Wenju Han, Xueming Fan, Yingbo Chen, Ruonan Lu, Yujie Zhai, Tianci Pan, Xiuxia Yuan, Xueqin Song, Dongqing Zhang","doi":"10.1186/s12888-025-06637-2","DOIUrl":"10.1186/s12888-025-06637-2","url":null,"abstract":"<p><strong>Background: </strong>Depression and anxiety were not only common but also with serious consequence in infertility patients. The current study endeavors to define distinct depression and anxiety profiles of infertility patients and identify central symptoms within different profiles to facilitate targeted interventions.</p><p><strong>Method: </strong>The research employed K-means Clustering to delineate the depression and anxiety profiles, followed by a repetition of the analysis using Latent Class Analysis (LCA). Furthermore, network analysis was utilized to identify central symptoms within the various profiles.</p><p><strong>Result: </strong>K‑means Clustering identified Cluster 1 (16.15%), Cluster 2 (37.08%) and Cluster 3 (46.77%), while LCA yielded the low-risk group (47.23%), the mild-risk group (34.46%) and the high-risk group (18.31%). A majority of patients in the three clusters were predominantly in a single LCA-derived patient class (88.38-100%). Network analysis revealed that connections within each symptom in PHQ-9 and GAD-7 were stronger than those between symptoms. Furthermore, PHQ 2 (\"sad mood\"), GAD 1 (\"nervousness\") and GAD 2 (\"uncontrollable worry\") were identified as the central symptoms in Cluster 1 GAD 3 (\"excessive worry\"), GAD 2 (\"uncontrollable worry\") and GAD 5 (\"restlessness\") emerged as the central symptoms in Cluster 2) Additionally, PHQ 4 (\"fatigue\"), GAD 6 (\"irritability\") and GAD 3 (\"excessive worry\") were identified as the central symptoms in Cluster 3.</p><p><strong>Conclusions: </strong>We defined three distinct depression and anxiety profiles among infertility patients and pinpointed central symptoms within each profile. These findings underscore the importance of directing research towards those central symptoms within each profile in order to develop targeted intervention strategies.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"229"},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11899931/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143603482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Develop and validate machine learning models to predict the risk of depressive symptoms in older adults with cognitive impairment.","authors":"Enguang Li, Fangzhu Ai, Qingyan Tian, Haocheng Yang, Ping Tang, Botang Guo","doi":"10.1186/s12888-025-06657-y","DOIUrl":"10.1186/s12888-025-06657-y","url":null,"abstract":"<p><strong>Background: </strong>Cognitive impairment and depressive symptoms are prevalent and closely interrelated mental health issues in the elderly. Traditional methods for identifying depressive symptoms in this population often lack effectiveness. Machine learning provides a promising alternative for developing predictive models that can facilitate early identification and intervention.</p><p><strong>Methods: </strong>This study utilized data from 945 participants aged 60 years and older with cognitive impairment, sourced from National Health and Nutrition Examination Surveys (2011-2014). Depressive symptoms were assessed using the Patient Health Questionnaire-9. Lasso regression was applied for feature selection, ensuring consistency across models. Several machine learning models, including XGBoost, Logistic Regression, Random Forest, and SVM, were trained and evaluated. Model performance was assessed using accuracy, precision, recall, F1 score, and AUC.</p><p><strong>Results: </strong>The incidence of depressive symptoms in older adults with cognitive impairment was 14.07%. Key predictors identified by lasso included general health, memory difficulties, and age, among others. Notably, general health emerged as a novel and significant predictor in this population, underscoring the interplay between physical and mental health. XGBoost was the best model for comprehensively comparing discrimination, calibration, and clinical utility.</p><p><strong>Conclusions: </strong>Machine learning models, particularly XGBoost, effectively predict depressive symptoms in cognitively impaired older adults. The findings highlight the importance of physical, cognitive, and social factors in depressive symptoms risk. These models have the potential to assist in early screening and intervention, improving patient outcomes. Future research should explore ways to enhance model generalizability, including the use of clinically diagnosed depressive symptoms data and alternative feature selection approaches.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"219"},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11895390/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143603774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of factors influencing contact in the 686 Program for patients with a first-time diagnosis of severe mental disorders in Hainan Province from 2018 to 2022.","authors":"Xin Zuo, Jianhe Hong, Di Liang, Wenting Cao, Qiqing Liang, Yumei Liu","doi":"10.1186/s12888-025-06627-4","DOIUrl":"10.1186/s12888-025-06627-4","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The 686 Program in China primarily aims to provide certain health and policy services to individuals with severe mental disorders within the community. As of 2020, a total of 6.43 million patients were registered nationwide under this program. However, there remains a disparity between the actual number of patients covered by the program and the total number of individuals with mental disorders. Factors influencing the engagement in 686 Program among individuals with severe mental disorders remain underexplored in current research.This study aims to understand the barriers and facilitators to program contact, offers implications for the development of targeted interventions for people with severe mental disorders, enabling the creation of more tailored and impactful strategies to enhance the 686 Program's effectiveness and reach.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;We aimed to explore the influencing factors associated with the registration and management of the 686 Program in a clinical sample of inpatients with severe mental disorders.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Method: &lt;/strong&gt;This study employed a cross-sectional study design. Demographic information, behavioral characteristics, and clinical information of inpatients firstly diagnosed with severe mental disorders from 2018 to 2022 were retrieved from the Hainan Provincial Anning Hospital information system, subsequently, registration and management data were matched using resident ID numbers within the 686 Program information system to effectively align independent and dependent variables. Binary logistic regression analysis was utilized to investigate the factors influencing the registration and management of the 686 Program among the first confirmed patients with severe mental disorders.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Between 2018 and 2022, Hainan Provincial Anning Hospital had 3,008 individuals who were first diagnosed with severe mental disorders. Among them, 1135 (37.73%) did not register for 686 Program, and 1873 (62.67%) had registered the 686 Program, of which 82 (4.38%) were unwilling to accept management. Multivariable analysis revealed that older age(OR = 1.010, 95% CI: 1.002-1.019), local (OR = 1.356, 95% CI: 1.014-1.814), longer disease duration (OR = 1.031, 95% CI: 1.015-1.047), total number of hospitalizations (from initial diagnosis onward) &gt; 1 time (OR = 1.362, 95% CI: 1.135-1.635; OR = 3.287, 95% CI: 2.579-4.189) and smoking(OR = 1.383, 95% CI: 1.081-1.769) were associated with a higher likelihood of registering for the 686 Program. Conversely, being ethnic minorities (OR = 0.707, 95% CI: 0.500-0.998), individuals with a middle school education and above(OR = 0.477, 95% CI: 0.276-0.823; OR = 0.357, 95% CI: 0.204-0.623), and those diagnosed with bipolar disorder (OR = 0.459, 95% CI: 0.357-0.590) were less inclined to register for the 686 Program. Furthermore, local resident status (OR = 2.455, 95%CI: 1.212-4.970) and being married (OR = 1.909, 95%CI:1.023-3","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"233"},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11899841/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143603764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distribution characteristics of mental disorders in community health service center: based on outpatient data from 2014-2022 in Shanghai, China.","authors":"Jie Qian, Hanzhi Zhang, Aizhen Guo, Qiangqiang Fu, Jianwei Shi, Hua Jin, Dehua Yu","doi":"10.1186/s12888-025-06656-z","DOIUrl":"10.1186/s12888-025-06656-z","url":null,"abstract":"<p><strong>Background: </strong>The prevalence of mental disorders is gradually increasing in China. As the Chinese government fully implements the tiered diagnosis and treatment system, community health service centers will take on an increased role in the diagnosis and treatment of mental disorders. However, Chinese general practitioners currently have limited expertise in mental health. The health administration is still exploring which areas should be the focus of training for general practitioners in their capability to handle mental disorders.</p><p><strong>Objective: </strong>To understand the types and characteristics of mental disorders, which can provide direction and evidence for improving the diagnosis and treatment capabilities of mental disorders in community mental health services in China.</p><p><strong>Methods: </strong>The data of outpatient visits of all community health service centers in Shanghai were extracted from the outpatient and emergency information system platform of primary care institutions during 2014 to 2020. All of the diagnoses of mental disorders were classified and counted according to the ICD-10 code. Mental disorders were analyzed by the specific types, gender, age group and regions.</p><p><strong>Results: </strong>From 2014 to 2022, the proportion of patients with mental disorders in community health. Service centers in Shanghai has been increasing year by year, from 0.8% to 2.8%. The most common diagnostic category was F40-48: \"Neurotic, stress-related and somatoform disorders\", accounting for 50.9% of all mental disorders. Neurotic disorders, Non-organic sleep disorders and depressive episodes were the top three mental disorders. In the children and adolescents group aged 0-18 years, the most common diagnosis category was F80-F89: \"Disorders of psychological development\", accounting for 68.6% of the total number of children and adolescents with mental disorders in community health service centers. In the adult group, the Nonorganic sleep disorders and dementia gradually increased with age, while neurotic disorders and depressive episodes decreased after peaking at age the group 60 to 79.</p><p><strong>Conclusions: </strong>In China, an increasing number of patients with mental disorders are seeking medical attention at community health service centers, while the knowledge and skills of general practitioners on mental disorders were still insufficient. Neurotic disorders, insomnia, depression as well as Disorders of psychological development in children and adolescents need to be studied more and paid attention to by general practitioners.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"216"},"PeriodicalIF":3.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11892172/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143596177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}