BMC Psychiatry最新文献

Background: Among adolescents, symptoms of generalized anxiety disorder (GAD) and social anxiety disorder (SAD) are not only clinically significant but also continuingly increasing. During adolescence, individuals begin to establish distinct, self-determined lifestyle patterns. This study seeks to identify the associations between such lifestyle factors and the prevalence of GAD and SAD symptoms.

Methods: The analyzable sample was based on a cross-sectional, nationally representative survey of Finnish 14-18 year old students from comprehensive schools, general upper secondary schools, and vocational institutions. The sample consisted of 60,252 boys and 71,118 girls, with the mean age of 16.05 years (standard deviation 1.06). Symptoms were identified using the GAD-7 (cutpoint of 10), the Mini-SPIN (cutpoint of 6), and the PHQ-2 (cutpoint of 3). Logistic regression models for both GAD and SAD symptoms were stratified by comorbidity group variables.

Results: GAD symptoms were closely related to excessive internet use and decreased sleep duration among adolescents, regardless of comorbidity with depression or SAD. SAD symptoms were associated with excessive internet use and a lack of intense exercise, independent of comorbid depression or GAD.

Conclusions: The findings underscore the importance of considering lifestyle factors when developing interventions to mitigate GAD and SAD symptoms in adolescents. Interventions and policy recommendations aiming at improving adolescents' health behaviour and mental health should take into account the intertwining of these factors.

Objective: To investigate the prevalence and risk factors of psychological symptoms and quality of life (QoL) in early patients with inflammatory bowel disease (IBD).

Methods: From September 2021 to May 2022, a unified questionnaire was developed to collect clinical data from early patients with IBD from 42 tertiary care hospitals. The influencing factors of psychological symptoms and poor QoL are screened by logistic regression analysis for constructing model in predicting poor QoL. The consistency index, receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration curve, and decision curve analysis (DCA) were used to evaluate the performance of the model.

Results: A total of 939 early patients with IBD were surveyed, Among them, 20.3% exhibited anxiety, 21.7% had depression, 57.3% experienced sleep disturbance, and 41.9% reported poor QoL. The factors influencing psychological symptoms varied between ulcerative colitis (UC) and Crohn's disease (CD) patients. The QoL was primarily affected by disease activity, income level and depression. The AUC value of the model in the training group was 0.781 (95% CI: 0.748-0.814). The calibration diagram of the model closely matched the ideal curve. Compared to other prediction models, our model showed superior predictive capability, with NRI and IDI values of 0.324 (95%CI:0.196-0.4513) and 0.026 (95%CI:0.014-0.038), respectively. DCA indicated that the nomogram model could provide clinical benefits.

Conclusion: Early patients with IBD exhibit a high prevalence of psychological symptoms and poor QoL. The nomogram prediction model we constructed demonstrates high accuracy and performance in predicting QoL in early patients with IBD.

Background: Psychiatry faces a challenge due to the lack of objective biomarkers, as current assessments are based on subjective evaluations. Automated speech analysis shows promise in detecting symptom severity in depressed patients. This project aimed to identify discriminating speech features between patients with major depressive disorder (MDD) and healthy controls (HCs) by examining associations with symptom severity measures.

Methods: Forty-four MDD patients from the Psychiatry Department, University Hospital Aachen, Germany and fifty-two HCs were recruited. Participants described positive and negative life events, which were recorded for analysis. The Beck Depression Inventory (BDI-II) and the Hamilton Rating Scale for Depression gauged depression severity. Transcribed audio recordings underwent feature extraction, including acoustics, speech rate, and content. Machine learning models including speech features and neuropsychological assessments, were used to differentiate between the MDD patients and HCs.

Results: Acoustic variables such as pitch and loudness differed significantly between the MDD patients and HCs (effect sizes 𝜼2 between 0.183 and 0.3, p < 0.001). Furthermore, variables pertaining to temporality, lexical richness, and speech sentiment displayed moderate to high effect sizes (𝜼2 between 0.062 and 0.143, p < 0.02). A support vector machine (SVM) model based on 10 acoustic features showed a high performance (AUC = 0.93) in differentiating between HCs and patients with MDD, comparable to an SVM based on the BDI-II (AUC = 0.99, p = 0.01).

Conclusions: This study identified robust speech features associated with MDD. A machine learning model based on speech features yielded similar results to an established pen-and-paper depression assessment. In the future, these findings may shape voice-based biomarkers, enhancing clinical diagnosis and MDD monitoring.

Background: Compared to the overall population, patients with mental health problems are more likely to experience concurrent physical illnesses, poorer health outcomes, and mortality. Psychotropic medications, which are the pillars in the management of mental health conditions, are associated with adverse effects such as weight gain, an increased level of glucose, and elevated circulating lipid levels, all of which contribute to metabolic disorders. Inadequate health monitoring may led to suboptimal interventions and worsening of these conditions. However, there is a lack of studies assessing routine health monitoring practices for metabolic disorders and their determinants among patients with serious mental illnesses taking psychotropic medications in Ethiopia. This study aimed to evaluate routine health monitoring for metabolic disorders and its determinants in patients with serious mental illnesses on psychotropic medications in Ethiopia.

Method: A hospital based prospective follow-up study was conducted among patients with serious mental illness taking psychotropic medications who attended the outpatient psychiatry department at Debre Markos Comprehensive Specialized Hospital. Eligible participants were selected using a simple random sampling technique. Routine health monitoring was evaluated using guidelines and previous literature. Binary logistic regression was employed to identify the determinants of routine health monitoring, with statistical significance determined by a p-value of less than 0.05 and a 95% confidence interval (CI).

Results: The overall routine health monitoring practice for metabolic disorders was found to be sub-optimal. Vital signs were the most commonly assessed parameters. Key determinants of routine health monitoring included participants aged 45 and above (AOR (95% CI): 2.82 (1.34-5.92), having social insurance (AOR (95% CI): 2.94 (1.86-4.64), availability of laboratory tests at the hospital (AOR (95% CI): 3.46 (2.16-5.55), and reporting of medication-related side effects (AOR (95% CI): 1.96 (1.21-3.17)).

Conclusion: Routine health monitoring for metabolic disorders in patients with serious mental illnesses attending the outpatient psychiatry department was inadequate. Health care providers should give more attention to younger patients, those without health insurance, and who are not reported side effects. These findings provide crucial insights for improving routine health monitoring and promoting better health outcomes.

Background: Men who have sex with men studying in universities (MSM-US) frequently face multiple sexual minority stressors that potentially lead to maladaptive emotional regulations and mental problems. This study compared the prevalence of depression/insomnia between MSM-US and non-MSM male university students (NUS) and hypothesized that the potential differences would be mediated via emotional dysregulation styles (rumination and catastrophizing).

Methods: The study design was a cross-sectional study. NUS were recruited from a university-based survey using cluster sampling in three universities in China from June to October 2018, while MSM-US from the same university-based survey and the other community-based survey using convenience sampling. The effective samples size was 2,531 (292 MSM-US and 2,239 NUS). Structural equation modeling (SEM) was performed.

Results: MSM-US had significantly higher prevalence of both probable depression (55.1% versus 35.7%; OR = 4.85, 95% CI: 3.38-6.94) and moderate-to-severe clinical insomnia (17.3% versus 4.1%; OR = 2.21, 95% CI: 1.73-2.83) than NUS. MSM-US were also more likely than NUS to use emotional dysregulation styles (rumination/catastrophizing), which were correlated with probable depression/insomnia (r = 0.17 to 0.31). In the SEM, the differences in depression/insomnia between MSM-US and NUS were partially mediated by the latent variable of emotional dysregulation (rumination and catastrophizing), with effect sizes of 55.0% for probable depression and 33.6% for insomnia, respectively.

Conclusions: Depression and insomnia were prevalent among male university students in Sichuan, China. Furthermore, MSM-US were at increased risk than NUS for both mental problems; emotional dysregulation partially explained such differences. Future studies are warranted to confirm the findings, develop tailored interventions to address general and MSM-specific stressors and reduce rumination and catastrophizing, and examine whether similar patterns exist in other sexual minority groups.

Background: Exercise is beneficial for persons with schizophrenia; however, high dropout rates limit the impact of interventions. Virtual exercise programs have the potential to improve engagement; however, few intervention studies of virtual programs have been conducted in this population.

Methods: This study examined qualitative data from 15 adults with schizophrenia who participated in a pilot randomized controlled trial of Virtual PACE-Life, a live, video-delivered group walking intervention guided by self-determination theory. Interviews elicited feedback on the intervention, barriers and facilitators to engagement, recommendations for intervention refinement, and preferences for exercise programming modality. Rapid qualitative analysis was used to explore similarities and differences between completers (i.e., those that attended ≥ 50% of virtual walking sessions; n = 9) and non-completers (i.e., those that attended < 50% of virtual walking sessions; n = 6).

Results: Both groups viewed Virtual PACE-Life positively but found the virtual exercise sessions challenging and inadequate for facilitating social interaction. Work obligations impacted completers' attendance whereas technological issues and forgetting impacted non-completers' attendance at virtual walking sessions. Completers preferred virtual exercise programs and non-completers preferred in-person exercise programs.

Conclusions: These findings suggest that future virtual group-based walking programs should prioritize enhancing the social aspect, offering scheduling choices, and regularly assessing the perceived difficulty of exercise sessions. These modifications not only have the potential to improve intervention engagement but they also may increase participant autonomy and relatedness, core components of self-determination theory.

Background: The current study aimed to investigate the performances of clinical scales rated by clinicians and patients as well as cognitive function tests in distinguishing patients with affective and anxiety disorders from healthy controls (HCs).

Methods: We recruited a total of 122 subjects, comprising 24 patients with bipolar disorder (BD), 34 patients with major depressive disorder (MDD), 29 patients with anxiety disorder (AD), and 35 matched HCs. Three clinician-rated scales and five patient-rated scales were used to quantify clinical symptoms, while four cognitive tests were employed to measure cognitive functions in all subjects. Fisher's discriminant analysis (FDA) was employed to distinguish patients from HCs, as well as to discriminate patient sub-groups from each other. In the FDA model, the prior probability of each group was set as 0.5 in the two-group classification and 0.25 in the four-group classification.

Results: The results showed that patient-rated scales achieved higher classification accuracies than clinician-rated scales in identifying MDD and AD from HCs. In contrast, cognitive tests exhibited the lowest accuracy.

Conclusions: These findings suggest that patient-rated scales might improve the classification accuracy for patients with MDD and AD.

Background: The efforts of early psychosis intervention programmes can be impeded by difficulties in maintaining the engagement of service users. As disengagement is often an autonomous decision made by service users, the main aim of this study was to gain insight into the reasons for service user disengagement through qualitative interviews with the service users themselves, and caregivers as proxies or secondary informants.

Methods: Participants recruited for the study were enrolled in the Early Psychosis Intervention Programme in Singapore for at least a year, aged 21 and above, able to communicate in English, and had disengaged for at least three months. The recruitment and interview processes were conducted independently for service user and caregiver participants. Potential participants were invited to a face-to-face semi-structured interview over video call or in-person. Each interview spanned one to two hours, and comprised five phases - icebreaker, exploration of the participant's experience with EPIP before deciding to disengage, discussion of reasons for disengagement, exploration of the post-disengagement experience, and feedback and suggestions for EPIP. Recruitment aimed to conclude after 10-15 participants were interviewed for both service user and caregiver groups, with the expectation that data sufficiency would be reached with no new themes being generated.

Results: Ultimately, 12 service user and 12 caregiver participants were recruited. There were six pairs of service user and caregiver dyads, where the caregivers interviewed were caring for service users also enrolled in the study. Valuable qualitative insights were gathered, including the type of disengagement, medication compliance during disengagement, the decision-making process behind disengaging, and circumstances surrounding re-engagement. A total of five categories each with subthemes were identified from the reasons for service user disengagement - individual factors, stigma, progression, treatment factors, and external factors.

Conclusions: There is a need to narrow down urgent areas of attention, aligning the study themes with established risk factors so that feasible solutions can be developed and appropriate care models can be adopted, to minimise adverse outcomes related to disengagement. It is important to keep an open mind to understand what personal recovery means to the individual service user, so that treatment goals can be better harmonised.

Background: Recent studies have identified a correlation between insulin resistance (IR) and depression. This study aims to explore the correlation between estimated glucose disposal rate (eGDR), a practical and noninvasive measure for assessing IR, and depression in the general population.

Methods: In this population-based cross-sectional study, data from 28,444 adults aged 18 years old or older in the NHANES during the period from 1999 to 2018 were analyzed. The correlation between eGDR and depression was examined through multivariate logistic regression analyses, subgroup analyses, restricted cubic spline, and interaction tests. Furthermore, a mediation analysis was conducted to elucidate the role of the atherogenic index of plasma (AIP) in mediating the effect of eGDR on depression.

Results: Multivariate logistic regression analysis and restricted cubic splines analysis indicated that eGDR can exhibit a linearly correlation with depression (OR = 0.913; 95% CI: 0.875, 0.953). Subjects in eGDR6-8 and eGDR > 8 groups had a decrease risk of depression as 25.4% and 41.5% than those in the eGDR < 4 group. This negative correlation was more pronounced in those with obesity. Mediation analysis indicated that AIP mediated 9.6% of the correlation between eGDR and depression.

Conclusions: eGDR was linear negatively correlated with depression, with AIP playing a mediating role. This study provides a novel perspective on the mechanism connecting IR to depression. Managing IR and monitoring AIP may contribute to alleviating depression.

Backgrounds: Patients with major depressive disorder (MDD) have a high rate of metabolic syndrome (MetS), which could worsen disease progression. One of the most serious progressions in MDD is suicide attempts (SAs). Previous studies have found gender differences in MetS and SAs among MDD patients respectively. Therefore, we aimed to explore gender differences of SAs in first-episode and drug-naïve (FEDN) MDD patients with comorbid MetS.

Methods: 1718 outpatients with FEDN MDD were recruited. Depression, anxiety and psychotic symptoms were evaluated using the Hamilton Depression Scale (HAMD), Hamilton Anxiety Scale (HAMA) and Positive and Negative Syndrome Scale (PANSS) positive subscale, respectively. Blood sugar, blood fat, blood pressure and body mass index (BMI) were measured to evaluate MetS.

Results: 34.4% patients with FEDN MDD were diagnosed as MetS and those subjects with or without MetS differed in the distribution of SAs and gender. In MetS subgroup, 29.5% and 29.7% of male and female subjects had SAs respectively, without significant differences. However, compared with non-suicide attempters, suicide attempters had higher level of blood pressure in female subjects, while there are no differences in any clinical variables in male subjects. Additionally, the influencing factors for SAs differed by gender. The HAMA scores and BMI were variables associated with SAs in male patients while HAMA scores, marital status and systolic blood pressure (SBP) were associated with SAs in female patients. Furthermore, the receiver operating characteristics (ROC) curves, demonstrating the combination all influencing factors by gender, showed good performance and model accuracy.

Conclusions: In FEDN MDD patients with comorbid MetS, there were no gender differences in SAs. However, clinical characteristics and influencing factors of SAs differed in different gender groups.