Psychiatric Diagnosis Research Articles

Trends in Mental Disorders in Children and Adolescents Receiving Treatment in the State Mental Health System

To examine recent trends in clinical diagnoses of children and adolescents receiving treatment in publicly funded mental health treatment services in the United States. Data on children and adolescents (≤17 years) receiving treatment from publicly funded mental health treatment services recorded in Mental Health Client-Level Data 2013-2021 (total number of records= 13,684,154) were used to examine temporal trends in the proportion of different child and adolescent psychiatric disorders. Trends were examined overall and in age, sex, racial/ethnic, and service strata focusing on community-based programs. The analyses revealed increases in the proportion of anxiety disorders from 9.6% in 2013 to 19.2% in 2021 (adjusted odds ratio [AOR] 2.17, 95% CI 1.85-2.55, p< .001), trauma- and stressor-related disorders from 22.7% to 27.4% (AOR 1.31, 95% CI 1.09-1.57, p= .004), and depressive disorders from 13.4% to 17.0% (AOR 1.20, 95% CI 1.03-1.41, p= .04). During this same period, the proportion of bipolar disorders declined almost 8-fold from 10.0% to 1.3% (AOR 0.07, 95% CI 0.06-0.09, p< .001). The proportion of conduct disorder and oppositional defiant disorder also declined from 9.7% to 4.4% (AOR 0.42, 95% CI 0.32-0.55, p< .001) and from 11.1% to 7.8% (AOR 0.79, 95% CI 0.65-0.98, p= .03), respectively. Trends varied across sex, age, and racial/ethnic strata. The composition of childhood psychiatric diagnoses in patients within publicly funded mental health treatment settings changed over the past decade. While some of the trends may reflect changes in diagnostic practices of clinicians, increases in anxiety and depressive disorders parallel trends in the prevalence of these conditions in the general population and highlight a growing need for identifying and treating these conditions in this age group.

Quality of Life Among Breast Cancer Patients in Mures County, Romania: A Cross-Sectional Study.

Background and aim Psychiatric pathology does not always start on its own but may be conditioned or triggered by a comorbidity with a high impact on the human psyche. When there are comorbidities, psychiatric pathology can occur due to the high diagnostic burden. Our study aims to find out if there is a correlation between the diagnosis of breast cancer and its severity,and psychiatric symptoms such as depressive mood, atypical anxiety, or even autolytic ideation that directly influence the quality of life of patients. Materials and methods The study is a prospective, cross-sectional, single-center study carried out between December 2023 and June 2024 at the Mureș County Clinical Hospital in Romania. The sample population had to be at least 18 years old and had to bediagnosed with breast cancer recently.We applied two tests, WHODAS 2 (World Health Organization's Disability Assessment Schedule 2.0) and level 1 (level 1 of cross-sectional measurements of symptoms), to be able to measure and aid assessment of mental health domains that are important across psychiatric diagnoses and also the degree of disability triggered by breast cancer. The statistical analysis included descriptive statistics and interferential statistics. Statistical tests, such as Shapiro-Wilk, Kruskal-Wallis, and Mann-Whitney U tests with Bonferroni correctiontests, were used.The p-value was set to 0.05 with a confidence interval (CI) of 95%. Results The study included 120 women diagnosed with breast cancer, with a mean age of 56.64 ± 9.46 years. Regarding the severity of the diagnosis, 44 women (36.66%) had non-invasive cancer, 58 (48.33%) had invasive cancer, and 18 (15%) had metastases.There was a statistically significant difference between three of the five selected level 1 domains across cancer types.The WHODAS 2.0 disability scores showed a significant difference between groups (p < 0.001). Subjects with non-invasive cancer had the lowest WHODAS 2.0 score, followed by the invasive group, while metastases had the highest score. Conclusions Following the application of the two tests, level 1 and WHODAS 2.0, to our group of subjects, statistically significant differences were observed between the three categories of subjects. The degree of disability and the occurrence of psychological symptoms differed according to the severity of breast cancer. Adapting to the status of an oncological patient entails multiple changes from a psycho-emotional, social, occupational, and professional point of view. Although the most recent medications prolong survival, a holistic approach that considers psychological aspects can improve patients' long-term results.

Association of psychiatric and substance use disorders with cannabis use and cannabis use disorder during early pregnancy in northern California.

To estimate the strength of association between psychiatric disorders and substance use disorders (SUD), and cannabis use and cannabis use disorder (CUD)during early pregnancy. Observational study. Kaiser Permanente Northern California, USA. 299 496 pregnancies from 227 555 individuals screened for cannabis use by self-report and a urine toxicology test at entrance to prenatal care in Kaiser Permanente Northern California during January 2011-December 2021 (excepting year 2020). The sample was 62.5% non-White, with a mean (standard deviation) age of 31.1 (5.5) years; 6.8% used cannabis; 0.2% had a CUD. Exposure variables included electronic health record-based psychiatric diagnoses of attention deficit hyperactivity, anxiety, bipolar, depressive, personality, posttraumatic stress and psychotic disorders; and alcohol, opioid, stimulant and tobacco use disorders, during the two years prior to pregnancy up to the day before the prenatal substance use screening date. Outcome variables were any cannabis use, frequency of self-reported cannabis use and CUD during early pregnancy. Psychiatric disorder prevalence ranged from 0.2% (psychotic) to 14.3% (anxiety), and SUD ranged from 0.3% (stimulant/opioid) to 3.8% (tobacco). Psychiatric disorders were associated with cannabis use and CUD, with the strongest association for any use found for bipolar disorder (adjusted odds ratio [aOR] = 2.83; 95% confidence interval [CI] = 2.53-3.17) and the strongest association for CUD found for psychotic disorders (aOR = 10.01, 95% CI = 6.52-15.37). SUDs were associated with cannabis use and CUD, with the strongest association for any use found for tobacco use disorder (aOR = 4.03, 95% CI = 3.82-4.24) and the strongest association for CUD found for stimulant use disorder (aOR = 21.99, 95% CI = 16.53-29.26). Anxiety, bipolar, depressive disorders and tobacco use disorder were associated with greater odds of daily than monthly or less cannabis use. Psychiatric disorders and substance use disorders appear to be associated with elevated odds of any and frequent cannabis use as well as cannabis use disorder during early pregnancy. In most cases, the associations with cannabis outcomes were stronger for substance use disorders than other psychiatric disorders.

Further validation of the Parent-Reported ADHD Symptom Infrequency Scale (PRASIS) in parents of children with oppositional defiant disorder and anxiety

ABSTRACT This study aimed to validate a novel parent-report measure of ADHD symptom inflation, the Parent-Reported ADHD Symptom Infrequency Scale (PRASIS), in a clinical sample. The PRASIS is composed of an Infrequency subscale and an ADHD subscale. Online participants were assigned to one of three groups: mothers of children with diagnosed ADHD (n = 110), mothers of children with diagnosed ODD and/or anxiety (n = 116), and mothers of children without ADHD, ODD, or anxiety. The third group was then randomized to either receive instructions to complete the questionnaire honestly (controls, n = 164) or to complete the questionnaire as if they were trying to convince a provider that their child has ADHD (simulators, n = 141). Results indicated good to excellent internal consistency (INF α = .83, ADHD Total α = .93); strong convergent validity of the PRASIS ADHD scale with the ADHD Rating Scale-5 (r(529) = .85, p < .001); excellent group discrimination of the PRASIS Infrequency scale and the PRASIS ADHD scale (η2 = 0.38–0.42); and specificity of 86.7, sensitivity of 67.4%, and an AUC of .86 for the Infrequency scale. Overall, these outcomes supported the utility of the PRASIS in samples including mothers of children with psychiatric diagnoses of ODD and/or anxiety.

Associations of Post-Traumatic Stress Disorder and Objective Subtle Cognitive Difficulties in Cognitively Unimpaired Older Veterans.

Psychiatric conditions such as post-traumatic stress disorder (PTSD) and depression have a two-fold increased dementia risk in Veterans. Prior work has shown that psychiatric factors can both impact cognitive functioning and be early symptoms associated with Alzheimer's disease (AD). Objectively defined subtle cognitive difficulties (Obj-SCD) has been associated with cognitive decline and AD biomarkers. However, Obj-SCD has not yet been investigated in the context of psychiatric disorders. A total of 179 cognitively unimpaired Veterans (50-92years old) underwent a comprehensive neuropsychological evaluation at VA San Diego and a retrospective medical record review. Chi-squared tests compared rates of psychiatric diagnoses in Veterans with and without Obj-SCD. About 21% of the sample was classified as Obj-SCD. Relative to cognitively unimpaired Veterans, Veterans classified as Obj-SCD had higher rates of PTSD, but not higher rates of other psychiatric conditions (e.g., depression). The PTSD findings appear to be driven by measures of cognitive efficiency. Elevated rates of PTSD, but not other psychiatric conditions, were observed among Veterans with Obj-SCD. The prevalence and type of subtle cognitive difficulties associated with PTSD in older Veterans demonstrates a need, and informs potential targets, for intervention. Further work is needed to determine mechanisms of subtle cognitive difficulties in older Veterans with PTSD.

Epidemiological study on seroprevalence of syphilis in patients with mental diseases.

The objective of this study was to investigate the seroprevalence of syphilis and its possible influencing factors in patients with mental illness. A total of 24,414 patients with mental illness from 2019 to 2021 were included. Serum syphilis antibody test results and available demographic data were collected. Chi-square test and regression analysis were used to analyze the data. The seroprevalence of syphilis was 0.59% (95% CI 0.49-0.69%) in patients with mental illness in the study area. There were significant differences in the seroprevalence of syphilis in age, marital status, occupation, urban region, and mental disease classification. The seroprevalence of syphilis increased with age (p < 0.01). The seroprevalence of syphilis was higher in patients with "Nonorganic sleep disorders" and "Reaction to severe stress, and adjustment disorders". Adjusted logistic regression analysis showed that the seroprevalence of syphilis in patients with mental illness was associated with age, region, and psychiatric classification. Older age group was a risk factor for syphilis seropositivity. Compared with schizophrenia, "bipolar affective disorder" (OR = 1.707, 95% CI: 1.017-2.864, p = 0.043) and "severe stress response and adjustment disorders"(R = 4.912, 95% CI: 1.138-21.204, p = 0.033) were risk factors for syphilis antibody positivity. The patients with "nonorganic sleep disorders" and "reaction to severe stress, and adjustment disorders" had a high seroprevalence of syphilis. Age and psychosis types became the influencing factors of the positive rate of serum syphilis antibody in patients with mental illness.

PERFORMANCE COMPARISON OF MACHINE LEARNING MODELS TO REDUCE MISDIAGNOSIS RATES IN PSYCHIATRIC DISORDER USING EEG DATASET

This paper aims at comparing the suitability of three machine learning models: LightGBM, CatBoost, and Logistic Regression, to lower misdiagnosis rates for psychiatric disorders. Misdiagnosis in mental health may mean improper treatment and, hence, poor outcomes for patients. Our research aims to determine the most accurate predictive model for mental health condition diagnosis that will lead to improved clinical outcomes. We trained and tested these models on an EEG dataset with patient records that have psychiatric diagnoses labeled. For all the models, evaluation and comparison are made using key performance metrics such as Accuracy, Precision, Recall, and F1-Score. Through the use of these methods, it was shown that LightGBM performed better than CatBoost and Logistic Regression, having achieved higher accuracy and F1 scores, indicating more power to make a difference among different psychiatric disorders. These results suggest that machine learning techniques, especially LightGBM, can greatly increase diagnostic accuracy and reduce misdiagnosis in psychiatric contextual systems. Keywords Machine Learning, Psychiatric Disorder, LightGBM, CatBoost, Logistic Regression.

Prevalence of Developmental, Psychiatric, and Neurologic Conditions in Older Siblings of Children with and without Autism Spectrum Disorder: Study to Explore Early Development.

This study evaluated developmental, psychiatric, and neurologic conditions among older siblings of children with and without autism spectrum disorder (ASD) to understand the extent of familial clustering of these diagnoses. Using data from the Study to Explore Early Development, a large multi-site case-control study, the analyses included 2,963 children aged 2-5 years with ASD, other developmental disabilities (DD group), and a population-based control group (POP). Percentages of index children with older siblings with select developmental, psychiatric, and neurologic conditions were estimated and compared across index child study groups using chi-square tests and multivariable modified Poisson regression. In adjusted analyses, children in the ASD group were significantly more likely than children in the POP group to have one or more older siblings with ASD, developmental delay, attention-deficit/hyperactivity disorder, intellectual disability, sensory integration disorder (SID), speech/language delays, or a psychiatric diagnosis (adjusted prevalence ratio [aPR] range: 1.4-3.7). Children in the DD group were significantly more likely than children in the POP group to have an older sibling with most of the aforementioned conditions, except for intellectual disability and psychiatric diagnosis (aPR range: 1.4-2.2). Children in the ASD group were significantly more likely than children in the DD group to have one or more older siblings with ASD, developmental delay, SID, or a psychiatric diagnosis (aPR range: 1.4-1.9). These findings suggest that developmental disorders cluster in families. Increased monitoring and screening for ASD and other DDs may be warranted when an older sibling has a DD diagnosis or symptoms.

Diagnostic accuracy of large language models in psychiatry

IntroductionMedical decision-making is crucial for effective treatment, especially in psychiatry where diagnosis often relies on subjective patient reports and a lack of high-specificity symptoms. Artificial intelligence (AI), particularly Large Language Models (LLMs) like GPT, has emerged as a promising tool to enhance diagnostic accuracy in psychiatry. This comparative study explores the diagnostic capabilities of several AI models, including Aya, GPT-3.5, GPT-4, GPT-3.5 clinical assistant (CA), Nemotron, and Nemotron CA, using clinical cases from the DSM-5. MethodsWe curated 20 clinical cases from the DSM-5 Clinical Cases book, covering a wide range of psychiatric diagnoses. Four advanced AI models (GPT-3.5 Turbo, GPT-4, Aya, Nemotron) were tested using prompts to elicit detailed diagnoses and reasoning. The models' performances were evaluated based on accuracy and quality of reasoning, with additional analysis using the Retrieval Augmented Generation (RAG) methodology for models accessing the DSM-5 text. ResultsThe AI models showed varied diagnostic accuracy, with GPT-3.5 and GPT-4 performing notably better than Aya and Nemotron in terms of both accuracy and reasoning quality. While models struggled with specific disorders such as cyclothymic and disruptive mood dysregulation disorders, others excelled, particularly in diagnosing psychotic and bipolar disorders. Statistical analysis highlighted significant differences in accuracy and reasoning, emphasizing the superiority of the GPT models. DiscussionThe application of AI in psychiatry offers potential improvements in diagnostic accuracy. The superior performance of the GPT models can be attributed to their advanced natural language processing capabilities and extensive training on diverse text data, enabling more effective interpretation of psychiatric language. However, models like Aya and Nemotron showed limitations in reasoning, indicating a need for further refinement in their training and application. ConclusionAI holds significant promise for enhancing psychiatric diagnostics, with certain models demonstrating high potential in interpreting complex clinical descriptions accurately. Future research should focus on expanding the dataset and integrating multimodal data to further enhance the diagnostic capabilities of AI in psychiatry.

A Transdiagnostic, Hierarchical Taxonomy of Psychopathology Following Traumatic Brain Injury (HiTOP-TBI).

Psychopathology, including depression, anxiety, and post-traumatic stress, is a significant yet inadequately addressed feature of moderate-severe traumatic brain injury (TBI). Progress in understanding and treating post-TBI psychopathology may be hindered by limitations associated with conventional diagnostic approaches, specifically the Diagnostic and Statistical Manual of Mental Disorders (DSM) and International Classification of Diseases (ICD). The Hierarchical Taxonomy of Psychopathology (HiTOP) offers a promising, transdiagnostic alternative to psychiatric classification that may more effectively capture the experiences of individuals with TBI. However, HiTOP lacks validation in the TBI population. To address this gap, we administered a comprehensive questionnaire battery, including 56 scales assessing homogeneous symptom components and maladaptive traits within HiTOP, to 410 individuals with moderate-severe TBI. We evaluated the reliability and unidimensionality of each scale and revised those with psychometric problems. Using a top-down, exploratory latent variable approach (bass-ackwards modeling), we subsequently constructed a hierarchical model of psychopathological dimensions tailored to TBI. The results showed that, relative to norms, participants with moderate-severe TBI experienced greater problems in the established HiTOP internalizing and detachment spectra, but fewer problems with thought disorder and antagonism. Fourteen of the 56 scales demonstrated psychometric problems, which often appeared reflective of the TBI experience and associated disability. The Hierarchical Taxonomy of Psychopathology Following Traumatic Brain Injury (HiTOP-TBI) model encompassed broad internalizing and externalizing spectra, splitting into seven narrower dimensions: Detachment, Dysregulated Negative Emotionality, Somatic Symptoms, Compensatory and Phobic Reactions, Self-Harm and Psychoticism, Rigid Constraint, and Harmful Substance Use. This study presents the most comprehensive empirical classification of psychopathology after TBI to date. It introduces a novel, TBI-specific transdiagnostic questionnaire battery and model, which addresses the limitations of conventional DSM and ICD diagnoses. The empirical structure of psychopathology after TBI largely aligned with the established HiTOP model (e.g., a detachment spectrum). However, these constructs need to be interpreted in relation to the unique experiences associated with TBI (e.g., considering the injury's impact on the person's social functioning). By overcoming the limitations of conventional diagnostic approaches, the HiTOP-TBI model has the potential to accelerate our understanding of the causes, correlates, consequences, and treatment of psychopathology after TBI.

From Names to Objects: A Pseudo-Biological Justification of Psychiatric Classifications

From Names to Objects: A Pseudo-Biological Justification of Psychiatric Classifications

Glucagon-like peptide agonists for weight management in antipsychotic-induced weight gain: A systematic review and meta-analysis.

Managing body weight in patients with antipsychotic-induced weight gain (AIWG) is challenging. Besides lifestyle interventions, pharmacological interventions may contribute to weight loss. This systematic review and meta-analysis evaluated the effect on weight loss and adverse effects of glucagon-like peptide-1 (GLP-1) agonists in patients with AIWG. Following PRISMA guidelines, we performed a meta-analysis of blinded and open-label randomised controlled trials (RCTs), non-randomised controlled trials and cohort studies that evaluated treatment with GLP-1 in patients with AIWG, regardless of psychiatric diagnosis. PubMed, Embase, PsycINFO and Cochrane Library databases were searched. Primary outcome measures were changes in body weight and BMI. Secondary outcomes were changes in adverse effects and severity of psychopathology due to GLP-1 agonists. Only data for exenatide and liraglutide could be included, that is, five RCTs and one cohort study. For exenatide the mean weight loss was -2.48 kg (95% Confidence Interval (CI) -5.12 to +0.64; p = 0.07), for liraglutide the mean weight loss was -4.70 kg (95% CI -4.85 to -4.56; p < 0.001). The mean change in BMI was -0.82 (95% CI -1.56 to -0.09; p = 0.03) in the exenatide groups and -1.52 (95% CI -1.83 to -1.22; p < 0.001) in the liraglutide groups. Exenatide and liraglutide did not adversely affect psychopathology. The most common adverse events were nausea, vomiting, and diarrhoea. The GLP-1 agonists exenatide and liraglutide are promising drugs for inducing weight loss in patients with AIWG. The adverse effects are acceptable, and the addition of GLP-1 does not increase the severity of psychopathology. However, more research is needed.

Sex-stratified analyses of comorbidities associated with an inpatient delirium diagnosis using real world data.

Delirium is a detrimental mental condition often seen in older, hospitalized patients and is currently hard to predict. In this study, we leverage electronic health records (EHR) to identify 7,492 UCSF patients and 19,417 UC health system patients with an inpatient delirium diagnosis and the same number of control patients without delirium. We found significant associations between comorbidities or laboratory values and an inpatient delirium diagnosis, including metabolic abnormalities and psychiatric diagnoses. Some associations were sex-specific, including dementia subtypes and infections. We further explored the associations with anemia and bipolar disorder by conducting longitudinal analyses from the time of first diagnosis to development of delirium, demonstrating a significant relationship across time. Finally, we show that an inpatient delirium diagnosis leads to increased risk of mortality. These results demonstrate the powerful application of the EHR to shed insights into prior diagnoses and laboratory values that could help predict development of inpatient delirium and the importance of sex when making these assessments.

Breast Conserving Therapy Preserves Sexual Well-Being More Than Postmastectomy Breast Reconstruction: Trends, Factors, and Interventions.

Up to 85% of breast cancer patients report sexual health concerns, but their concerns are not adequately addressed by providers. Sexual dysfunction among breast cancer patients remains understudied. We aimed to investigate the impact of breast-conserving therapy (BCT) and postmastectomy breast reconstruction (PMBR) on the sexual health of breast cancer patients and frequency of sexual medicine consultation in postoperative care. We conducted a retrospective analysis of patients who underwent BCT or PMBR and completed the Sexual Well-being of the BREAST-Q BCT and Reconstruction modules from January 2010 to October 2022. We compared Sexual Well-being scores between BCT and PMBR patients overtime up to 5-years postoperatively, delineated associated demographic and clinical factors with Sexual Well-being, and evaluated the frequency of sexual medicine consultations. Of 15,857 patients, 8,510 (53.7%) underwent BCT and 7,347 (46.3%) underwent PMBR. PMBR patients had significantly lower Sexual Well-being scores than BCT patients from preoperative to 5-year postoperative. Regression analyses showed that PMBR patients scored 7.6 points lower at 1-year than BCT patients. Separated marital status, higher body mass index, cardiovascular disease, hyperlipidemia, psychiatric diagnosis, and neoadjuvant chemotherapy were associated with significantly lower Sexual Well-being. 299 (3.5%) of BCT and 400 (5.4%) of PMBR patients received sexual medicine consultations. Sexual health concerns must be considered in breast cancer care, particularly among patients who undergo PMBR. Although many patients experience sexual dysfunction, most do not receive a sexual medicine consultation, suggesting an opportunity for providers to improve breast cancer patients' sexual health.

Categorization challenges in research on organ donation after euthanasia: Determining somatic or psychiatric origins of suffering

This perspective article discusses the classification challenges encountered in organ donation after euthanasia (ODE) among individuals with psychiatric disorders, as highlighted in our recent case series. In cases involving &amp;ldquo;somatic symptoms and related disorders,&amp;rdquo; somatic symptoms are connected to excessive thoughts, feelings, and behaviors, causing distress or dysfunction. Conditions such as tinnitus and chronic pain often co-occur with psychiatric disorders. The recent Dutch guideline on ODE eliminated the requirement to distinguish between somatic and psychiatric causes of suffering. This updated guideline encourages a holistic approach to patient care, emphasizing the importance of addressing patients&amp;rsquo; overall suffering rather than specific categorizations. To avoid errors in classification, categorization in research on ODE should recognize the overlap between somatic and psychiatric diagnoses, thereby eliminating the risk of misclassification, avoiding the stigmatization of patients, and optimizing future treatment options.

Опыт изучения интернализированных расстройств у детей и подростков в зарубежных исследованиях

&lt;p style="text-align: justify;"&gt;This paper reviews the experiences of researchers from Western and Eastern countries, including the USA, Germany, Canada, the United Kingdom, China, and others, in studying internalized disorders in children and adolescents. The diversity of countries with different public health systems in the review broadened the perspective on a diagnostic paradigm based on the transdiagnostic model of mental disorder classification. The paper examines various approaches to conceptualizing internalizing disorders in overseas research. It introduces the concept of "internalized disorders" and contrasts it with "externalized disorders", with a focus on the symptoms, diagnosis, and interventions for internalized disorders in childhood and adolescence. It also presents data on the epidemiology and aetiology of internalized disorders, analyzing their prevalence in populations, which vary by age, gender, and region of residence. The paper also includes a discussion on the comorbidity of internalized disorders in children and adolescents. This scope of information provides a comprehensive understanding of the essence of "internalized disorders" and their key characteristics, creating a foundation for developing effective diagnostic and therapeutic strategies in national psychological practice.&lt;/p&gt;

Inpatient Equivalent Home Treatment of Gerontopsychiatric Patients (ieht-g) in a Major German City - An Observational Study

Patient characterization and evaluation of gerontopsychiatric inpatient equivalent treatment (IEHT-G) in a large German city. Collection of sociodemographic and clinical data, as well as assessment of clinical severity (CGI), health and social functioning (HoNOS-D) and autonomous performance of activities of daily living (IADL) at the beginning and end of IEHT-G. 53 subjects (age: MW=74.81; 77.4% women) were analyzed. Main psychiatric diagnoses were affective disorders (n=25), schizophrenia and schizotypal disorders (n=20). 12 patients (22.64%) had a cognitive disorder. The CGI, HoNOS-D and IADL showed a significant improvement over the treatment period (paired t-test, p<0.001). In an urban gerontopsychiatric population, IEHT-G can be implemented well. Symptom severity, social functioning and autonomy improved significantly.

Examining the association of familial and social stress, trauma, and support on mood, anxiety, and behavioral symptoms and diagnoses in youth at risk for bipolar disorder and controls

IntroductionYouth with a family history of bipolar disorder (At-Risk) have a higher risk of developing psychiatric disorders and experiencing environmental stressors than youth without such family history (Control). We studied the differential associations of familial and environmental factors on developing psychiatric diagnoses and symptoms, in At-Risk and Control youth. MethodsAt-Risk and Control youth (N = 466, ages 9–22) were systematically assessed for severity of symptoms, psychiatric diagnoses, and self-reported measures of stress and social support. We tested the association of family history and measures of stress or support with symptom severity and diagnoses. ResultsAt-Risk youth had higher symptom severity scores and were more frequently diagnosed with psychiatric disorders (all p values < 0.001). When predicting mood symptom severity, family history had an interaction effect with stressful life events (p < 0.001) and number of distinct traumatic events (p = 0.001). In multivariate models, At-Risk status predicted anxiety disorders (OR = 2.7, CI 1.3–5.4, p = 0.005) and anxiety severity (Coefficient = 0.4, CI 0.2–0.7, p < 0.001) but not mood or behavioral disorder diagnoses or severity. LimitationsMeasures of stress and social support were based on self-report. Not all participants had passed through the period of risk for developing the outcomes under study and the follow up period was variable. We could not fully study the differential impact of physical or sexual abuse due to low frequency of occurrence in controls. ConclusionAt-Risk youth exhibit more severe mood symptoms compared to Controls when exposed to similar levels of stress or trauma. At-Risk youth are also more prone to develop anxiety which may be a precursor for bipolar disorder.

Assessing the impact of elexacaftor/tezacaftor/ivacaftor on anxiety & depression symptom scores in adults with Cystic Fibrosis

The mental health effects of elexacaftor/tezacaftor/ivacaftor (ETI) on adults with CF are still uncertain with mixed findings from published studies. To systematically investigate the impact of ETI on symptoms of anxiety and depression in adults with CF, Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire (PHQ-9) scores were evaluated at baseline, 6 months, and 12 months post-ETI. Overall, GAD-7 and PHQ-9 scores improved at 6 months post-ETI, with a greater proportion of individuals experiencing a clinically significant improvement (vs. worsening) of their symptoms, which was sustained at 12 months. Factors influencing mental health outcomes included pre-existing psychiatric diagnoses and psychiatric medication use. In conclusion, although there was overall improvement in anxiety and depression symptoms post-ETI, approximately 10 % of individuals experienced clinically significant worsening.

Impact of comorbid subthreshold depressive symptoms on cancer-related fatigue and complications in adults with leukemia.

Patients not only experience symptoms caused by cancer but also suffer from the accompanying psychological pain. Therefore, these patients do not have high quality of life. According to the World Health Organization, the incidence of leukemia in China in 2020 was 5.1/100000, the mortality rate was 3.3/100000, and the prevalence rate was 16.7/100000. Therefore, it is important to examine the influence of comorbid subthreshold depressive symptoms on leukemia patients. To determine the impact of comorbid subthreshold depressive symptoms on cancer-related fatigue and complications in leukemia patients, thereby providing a basis for early diagnosis and treatment in clinical practice. A questionnaire survey was conducted among leukemia patients admitted to a tertiary hospital in Xi'an, Shaanxi Province, China, from August 2022 to December 2023. Patients with a score > 16 on the Chinese Classification of Mental Disorders (CCMD-3) and a Hamilton Depression Rating Scale score of 8-17 were classified as the subthreshold depressive group (n = 95), while 100 leukemia patients admitted during the same period were classified as the control group. Data were collected using Epidata 3.1 software, and comparisons were made between the two groups regarding general clinical data, the Piper Fatigue Scale (PFS), the Pittsburgh Sleep Quality Index (PSQI), the Numeric Rating Scale for pain assessment, laboratory indicators, and the occurrence of complications. In this survey, 120 leukemia patients with depression were preliminarily screened, 95 patients with subthreshold depression were ultimately selected as the subthreshold depression group, and 100 leukemia patients admitted during the same period were enrolled as the normal group. Comparison of basic clinical data between the two groups revealed no significant differences in age, sex, body mass index, cognitive function, or comorbidity with other chronic diseases. However, there were statistically significant differences in the use of radiotherapy and regular exercise between the two groups (P < 0.05). Comparisons of scales and laboratory indicators revealed no significant differences in albumin or PSQI scores between the two groups, but there were statistically significant differences in pain scores, PSQI scores, PFS scores, hemoglobin levels, and C-reactive protein levels (P < 0.05). Spearman's correlation analysis indicated that cancer-related fatigue was correlated with age, hemoglobin levels, C-reactive protein levels, pain, and regular exercise among leukemia patients with subthreshold depression. Multivariate regression analysis revealed that advanced age, combined radiotherapy, pain, and low hemoglobin levels were risk factors for cancer-related fatigue in leukemia patients with comorbid subthreshold depression, while regular exercise was a protective factor against cancer-related fatigue. Follow-up comparisons revealed a significantly lower overall incidence of complications in the control group (4%) than in the depressive group (24.21%; P < 0.001). Leukemia patients with comorbid subthreshold depressive symptoms experience more severe cancer-related fatigue and a higher incidence of complications. These findings may be related to advanced age, combined radiotherapy, pain, and low hemoglobin levels, while regular exercise may effectively alleviate symptoms.