BMC Psychiatry最新文献

Background: Adequate sleep and rest are essential for patient recovery; however, lack of sleep has become a common problem faced by Chinese patients during hospital stays. Reduced sleep is often associated with a higher risk of disease progression and is strongly associated with increased hospital stay. However, there is no specific tool in China to assess short-term insomnia caused by hospitalization. This study aimed to translate the Hospital-acquired Insomnia Scale (HAIS) into Chinese, test its applicability to Chinese inpatients through reliability and validity indicators, and investigate the potential influencing factors of hospital-acquired insomnia.

Methods: Psychometric analysis from a sample of 679 hospitalized patients to whom the HAIS questionnaire was applied. The structural validity was assessed by exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), and the content validity of the scale was assessed using the content validity index. Cronbach's alpha coefficient, split-half reliability and test-retest reliability were calculated to evaluate the internal consistency of the scale. Multiple stepwise linear regression analysis was conducted to determine the potential correlates of hospital-acquired insomnia.

Results: EFA supported a four-factor structure with factor loadings for all dimensions greater than 0.40. CFA showed good indicators of model fit. The content validity index of the scale was 0.94. the Cronbach's alpha of the scale was 0.915, the split-half reliability coefficient was 0.819, and the retest reliability was 0.844. Gender, age, total hours of sleep during the night, medical insurance, length of hospital stay, perceived stress level, and perceptions about sleep explained 46.2% of the variance in hospital-acquired insomnia.

Conclusion: The Chinese version of HAIS has good psychometric characteristics and is an effective instrument for evaluating hospital-acquired insomnia. In addition, hospital-acquired insomnia is more common in women, of younger age, less than 5 h of sleep a night, without medical insurance, stressed, and patients with more misconceptions about sleep.

Background: Recurrent depressive disorder (RDD) is mainly manifested as a low mood, negative and pessimistic mood, and often presents suicidal tendencies when severe. This study reports on a patient with RDD who experienced rat poison poisoning occurring tongue biting. The patient's psychiatric symptoms improved after receiving emergency management and subsequent combined medical care.

Case presentation: The patient was a 51-year-old female with RDD complicated with rat poison poisoning. Tongue bite occurred on the third day of hospitalization. She received emergency treatment. Depression, anxiety and suicide risk assessment, safety management and caregiver-health education were conducted on the day of admission and before discharge. At the follow-up after discharge, the risk of suicide was reduced.

Conclusions: Suicide in patients with RDD is characterized by repetition and complexity. The occurrence of clinical cases involving tongue bite after gastric lavage is rare. Suicide assessment and emergency management play an auxiliary role in the treatment of patients with recurrent depressive disorder.

Background: Participation in society and the ability to perform various activities are crucial aspects of everyday functioning. The intertwined relationship between functioning, disability, and health is emphasized in the "International Classification of Functioning, Disability and Health (ICF)" framework. In recent decades, mental health care units have increasingly focused on this aspect. The Practical and Social Functioning scale (PSF) was developed and validated in Norwegian as an easy-to-administer instrument to assess practical and social functioning among patients with serious mental illness in different clinical settings.

Methods: The PSF was developed and revised using data from different Norwegian studies. Data from a total of 562 patients with serious mental illness in different clinical settings were included. The validation process included the evaluation of items into categories by 25 professionals. Development and revision took place in three different stages, and factor analyses were conducted. The quality of the PSF was assessed according to the COSMIN standards for systematic reviews on patient-reported outcome measures.

Results: The final version of the PSF comprises seven subscales, each consisting of four items, resulting in a total of 28 items. These subscales, along with their corresponding items, are loaded onto two factors representing the main dimensions of functioning: activity and participation. Content validity comprises three domains: relevance, comprehensiveness, and comprehensibility. Relevance and comprehensibility were found to be adequate, whereas comprehensiveness was doubtful. Structural validity was adequate, internal consistency was very good, and construct validity was adequate compared to the Global Assessment of Functioning scale. Responsiveness was found to be doubtful in our study with data from an 18-month observation period. Nearly 60% of the items showed a ceiling effect. No items showed a floor effect.

Conclusion: The development and validation of the Norwegian version of the PSF resulted in an instrument consisting of seven subscales and a total of 28 items. The items and subscales assess functioning related to two key factors according to the ICF framework: activity and participation. Our results show that the PSF is an easy-to-administer instrument that may be particularly sensitive for detecting variation among persons with severely impaired functioning.

Trial registration: The study Implementation of Guidelines for the Treatment of Psychoses was registered retrospectively on 31 August 2017 at ClinicalTrials.gov (NCT03271242).

Background: Hoarding disorder (HD) is characterized by a compulsion to collect belongings, and to experience significant distress when parting from them. HD is often misdiagnosed for several reasons. These include patient and family lack of recognition that it is a psychiatric disorder and professionals' lack of relevant expertise with it. This study evaluates the ability of a supervised machine learning (ML) model to match the diagnostic skills of psychiatrists when presented with equivalent information pertinent to symptoms of HD.

Methods: Five hundred online participants were randomly recruited and completed the Hoarding Rating Scale-Self Report (HRS-SR) and the Generalized Anxiety Disorder 7-item (GAD-7) scale. Responses to the questionnaires were read by an ML model. Responses to the HRS-SR were then converted into anonymized, random-equivalent texts. Each of these individual texts was presented in random order to two experienced psychiatrists who were independently asked for a provisional diagnosis - e.g.; the presence or absence of HD. In case of disagreement between the two assessors, a third psychiatrist broke the tie. A decision tree classification model was employed to predict clinical HD using self-report data from two psychological tests, the HRS-SR and GAD-7. The target variable was whether a participant had clinical HD, while the predictive variables were the continuous scores from the HRS-SR and GAD-7 tests. The model's performance was evaluated using a confusion matrix, which compared the observed diagnoses with the predicted diagnoses to assess accuracy.

Results: According to the psychiatrists, approximately 10% of the participants fulfilled DSM-5 diagnostic criteria for HD. 93% of the clinician-identified cases were identified by the ML model based on HRS-SR and GAD-7 scores. A decision tree plot model demonstrated that about 60% of the cases could be detected by the HRS-SR alone while the rest required a combination of HRS-SR and GAD-7 scores. ML evaluation metrics showed satisfactory performance, with a Matthews Correlation Coefficient of 55%; Area Under Curve (AUC), 79%; a Negative Predictive Value of 76%; and a False Negative Rate of 24%.

Conclusions: Study findings strongly suggest that ML can, in the future, play a significant role in the risk assessment of psychiatric disorders prior to face-to-face consultation. By using AI to scan big data questionnaire responses, wait time for seriously ill patients can be substantially cut, and prognoses substantially improved.

Background: Schizophrenia is associated with a high mortality rate due to the high risk of suicide. However, there is still a lack of evidence on the gender-specific risk factors for suicide among people with schizophrenia. In this study, we aimed to measure the sociodemographic and clinical correlates of suicide deaths in different genders among people with schizophrenia.

Methods: Data on patients with schizophrenia from 2013 to 2021 in Guangzhou, China were obtained from the National Information System for Psychosis (NISP), involving a total of 33,080 patients. Cox regression and Fine-Gray models were used to explore the sociodemographic and clinical risk factors for suicide mortality in different genders.

Results: The overall age-standardized mortality rates due to suicide were 133.89 (95% CI: 124.31-143.47) per 100,000 person-years for females and 163.25 (95% CI: 152.92-173.59) per 100,000 person-years for males. To be specific, lack of medical insurance, history of non-treatment, and history of suicidal behavior was associated with a higher risk for suicide mortality for females, while an age of 35-54, being hospitalized once, and the age of onset being > 28 years were linked to lower risk for suicide mortality for males. For both genders, a lower risk for suicide mortality was observed in patients at an older age (≥ 55 years) and with a history of hospitalization more than once, and a higher suicide mortality risk was found in married patients and those residing in rural areas.

Conclusion: The present study found that gender differences should be taken into account in the development of suicide prevention programs for people with schizophrenia, and future research is still required to verify our preliminary results.

Background: Schizophrenia (SCZ) shares high clinical relevance with the immune system, and the potential interactions of psychopharmacological drugs with the immune system are still an overlooked area. Here, we aimed to identify whether the second-generation antipsychotics (SGA) monotherapy or combined therapy of SGA with other psychiatric medications influence the routine blood immunity biomarkers of patients with SCZ.

Methods: Medical records of inpatients with SCZ from January 2019 to June 2023 were retrospectively screened from June 2023 to August 2023. The demographic data and peripheral levels of cytokines (IL-2, IL-4, IL-6, TNF-α, INF-γ, and IL-17 A), lymphocyte subtype proportions (CD3+, CD4+, CD8 + T-cell, and natural killer (NK) cells), and thyroid autoimmune antibodies (thyroid peroxidase antibody (TPOAb), and antithyroglobulin antibody (TGAb)) were collected and analyzed.

Results: 30 drug-naïve patients, 64 SGA monotherapy (20 for first-episode SCZ, 44 for recurrent SCZ) for at least one week, 39 combined therapies for recurrent SCZ (18 with antidepressant, 10 with benzodiazepine, and 11 with mood stabilizer) for at least two weeks, and 23 used to receive SGA monotherapy (had withdrawn for at least two weeks) were included despite specific medication. No difference in cytokines was found between the SGA monotherapy sub-groups (p > 0.05). Of note, SGA monotherapy appeared to induce a down-regulation of IFN-γ in both first (mean [95% confidence interval]: 1.08 [0.14-2.01] vs. 4.60 [2.11-7.08], p = 0.020) and recurrent (1.88 [0.71-3.05] vs. 4.60 [2.11-7.08], p = 0.027) episodes compared to drug-naïve patients. However, the lymphocyte proportions and thyroid autoimmune antibodies remained unchanged after at least two weeks of SGA monotherapy (p > 0.05). In combined therapy groups, results mainly resembled the SGA monotherapy for recurrent SCZ (p > 0.05).

Conclusion: The study demonstrated that SGA monotherapy possibly achieved its comfort role via modulating IFN-γ, and SGA combined therapy showed an overall resemblance to monotherapy.

Objective: Assess the relationship between emotional inhibition, emotional deprivation, failure, vulnerability to harm schema, and severity of symptoms among obsessive-compulsive disorder.

Methods: A descriptive correlational study was conducted on 30 patients with obsessive-compulsive disorder who were recruited to complete the Yale-Brown Obsessive-Compulsive Scale, Young Schema Questionnaire-Long Form.

Results: The results of the study indicate that 66.6% of the 30 subjects exhibited high levels of OCD symptom severity, with a mean score of 33.20 ± 4.67. In terms of early maladaptive schemas, 60% of subjects displayed severe emotional deprivation, 66.7% showed severe emotional inhibition, and 83.3% had severe failure schemas. A strong positive correlation was found between failure schemas and OCD symptoms (r = 0.697, p < 0.001). However, what truly impressed the researchers was the predictive power of the failure schema. It was the only significant predictor of OCD symptoms (Beta = 0.992, p < 0.001), explaining 55.2% of the variance.

Conclusion: The study underscores the crucial influence of early maladaptive schemas on the severity of obsessive-compulsive disorder symptoms in individuals with obsessive-compulsive disorder. It proposes that considering early maladaptive schemas, such as emotional self-awareness, failure, and vulnerability to harm, can aid in gauging the severity of obsessive-compulsive disorder symptoms. Moreover, the study's findings are of significant importance to mental health professionals, researchers, and individuals involved in the treatment and management of obsessive-compulsive disorder, as they provide a deeper understanding of the condition and suggest practical approaches for its management.

Background: Effective preventive interventions for PTSD rely on early identification of individuals at risk for developing PTSD. To establish early post-trauma who are at risk, there is a need for accurate prognostic risk screening instruments for PTSD that can be widely implemented in recently trauma-exposed adults. Achieving such accuracy and generalizability requires external validation of machine learning classification models. The current 2-ASAP cohort study will perform external validation on both full and minimal feature sets of supervised machine learning classification models assessing individual risk to follow an adverse PTSD symptom trajectory over the course of 1 year. We will derive these models from the TraumaTIPS cohort, separately for men and women.

Method: The 2-ASAP longitudinal cohort will include N = 863 adults (N = 436 females, N = 427 males) who were recently exposed to acute civilian trauma. We will include civilian victims of accidents, crime and calamities at Victim Support Netherlands; and who were presented for medical evaluation of (suspected) traumatic injuries by emergency transportation to the emergency department. The baseline assessment within 2 months post-trauma will include self-report questionnaires on demographic, medical and traumatic event characteristics; potential risk and protective factors for PTSD; PTSD symptom severity and other adverse outcomes; and current best-practice PTSD screening instruments. Participants will be followed at 3, 6, 9, and 12 months post-trauma, assessing PTSD symptom severity and other adverse outcomes via self-report questionnaires.

Discussion: The ultimate goal of our study is to improve accurate screening and prevention for PTSD in recently trauma-exposed civilians. To enable future large-scale implementation, we will use self-report data to inform the prognostic models; and we will derive a minimal feature set of the classification models. This can be transformed into a short online screening instrument that is user-friendly for recently trauma-exposed adults to fill in. The eventual short online screening instrument will classify early post-trauma which adults are at risk for developing PTSD. Those at risk can be targeted and may subsequently benefit from preventive interventions, aiming to reduce PTSD and relatedly improve psychological, functional and economic outcomes.

Background: Coordinated specialty care (CSC) programs for first episodes of psychosis are increasingly offered in the United States. A component of CSC programs is active family engagement in treatment, though research on the impact of this engagement is limited. This study examined the characteristics of families engaged compared to families not engaged in treatment, and the impact of family engagement on client participation and medication adherence over the first 6 months of treatment.

Methods: Using data from the Early Psychosis Intervention Network (EPINET) research hub in Minnesota (EPI-MINN), we compared two groups of individuals: clients who had a family member(s) engaged in their treatment vs. clients who did not. Family engagement was defined as any treatment services provided to a family member(s) by CSC clinical staff. The groups were compared on intake demographic variables, duration of untreated psychosis (DUP), hospitalizations, symptom severity, and functioning. A comparison of the total number of treatment visits during the first 6 months of treatment was tested using both nonparametric (Mann Whitney U) and parametric (ANCOVA) tests. Group comparisons on self ratings of "intent to attend visits," "intent to complete the program," and medication adherence were tested with ANCOVA and Chi-Square.

Results: Family-engaged clients were younger, with less years of education, and more often White; clients without family engagement were more often Black. Family engagement was positively associated with increased total number of visits for all interventions with the exceptions of client peer support and case management visits. Family engagement increased clients' self-reported intent to attend visits, though not intention to complete the program, which was moderately to markedly high in both groups. No differences were noted with medication adherence, with high rates of adherence across the entire study sample.

Conclusions: Overall, results of the study support the benefits of family engagement in CSC on client participation, though future research is needed to understand why Black families are less engaged and what treatment adaptations are needed to reduce these racial differences. The results also support the value of CSC programs for medication adherence, a critical factor in symptom reduction and mental health recovery.