Psychiatric Diagnosis Research Articles

Classification of musical hallucinations and the characters along with neural-molecular mechanisms of musical hallucinations associated with psychiatric disorders.

Musical hallucinations (MH) involve the false perception of music in the absence of external stimuli which links with different etiologies. The pathomechanisms of MH encompass various conditions. The etiological classification of MH is of particular importance and offers valuable insights to understand MH, and further to develop the effective treatment of MH. Over the recent decades, more MH cases have been reported, revealing newly identified medical and psychiatric causes of MH. Functional imaging studies reveal that MH activates a wide array of brain regions. An up-to-date analysis on MH, especially on MH comorbid psychiatric conditions is warranted. To propose a new classification of MH; to study the age and gender differences of MH in mental disorders; and neuropathology of MH. Literatures searches were conducted using keywords such as "music hallucination," "music hallucination and mental illness," "music hallucination and gender difference," and "music hallucination and psychiatric disease" in the databases of PubMed, Google Scholar, and Web of Science. MH cases were collected and categorized based on their etiologies. The t-test and ANOVA were employed (P < 0.05) to compare the age differences of MH different etiological groups. Function neuroimaging studies of neural networks regulating MH and their possible molecular mechanisms were discussed. Among the 357 yielded publications, 294 MH cases were collected. The average age of MH cases was 67.9 years, with a predominance of females (66.8% females vs 33.2% males). MH was classified into eight groups based on their etiological mechanisms. Statistical analysis of MH cases indicates varying associations with psychiatric diagnoses. We carried out a more comprehensive review of MH studies. For the first time according to our knowledge, we demonstrated the psychiatric conditions linked and/or associated with MH from statistical, biological and molecular point of view.

Are Psychiatric Nosologies Limiting the Success of Clinical Prediction Models?

This Viewpoint discusses the limitations of clinical prediction models in psychiatric research.

Time Trends in Adolescent Diagnoses of Major Depressive Disorder and Co-occurring Psychiatric Conditions in Electronic Health Records.

Major depressive disorder (MDD) is highly prevalent in youth and generally characterized by psychiatric comorbidities. Secular trends in co-occurring diagnoses remain unclear, especially in healthcare settings. Using large-scale electronic health records data from a major U.S. healthcare system, we examined the prevalence of MDD diagnoses and co-occurring psychiatric conditions during adolescence (12-18 years; N = 133,753) across four generations (birth years spanning 1985 to 2002) and by sex. Then using a phenome-wide association analysis, we explored which of 67 psychiatric conditions were associated with adolescent MDD diagnosis in earlier versus recent generations. Adolescent MDD diagnosis prevalence increased (8.9 to 11.4%) over time. Over 60% with an MDD diagnosis had co-occurring psychiatric diagnoses, especially neurodevelopmental and anxiety disorders. Co-occurring diagnoses generally increased over time, especially for anxiety disorders (14 to 50%) and suicidal behaviors (6 to 23%), across both sexes. Eight comorbidities interacted with generation, showing stronger associations with MDD diagnosis in earlier (e.g., conduct disorder) versus more recent (e.g., suicidal ideation and behaviors) generations. The findings underscore the importance of assessing psychiatric complexity in adolescents diagnosed with MDD, applying transdiagnostic approaches to address co-occurring presentations, and further investigating potential causes for generational increases.

Contextual Considerations for the Neuropsychological Assessment of Pediatric mTBI

AbstractMild traumatic brain injury (mTBI), also known as concussion, is a common injury in the pediatric population. In 2014, children aged 0 to 19 made up 32% (812,000) of the 2.5 million TBI-related emergency department visits in the United States, which does not reflect the much higher number of children with a brain injury who do not present to medical centers (Black &amp; Zablotsky, 2021). Similar to psychiatric diagnoses, a diagnosis of mTBI/concussion is made using clinical features and symptoms that are classified under cognitive, affective, and somatic domains, with none of the symptoms pathognomonic for TBI. Symptoms secondary to a mTBI are time limited and show a typical trajectory, and in a majority of cases, lead to full resolution. When this expected pattern is not observed, contributing comorbid and premorbid factors need to be considered for a thorough understanding of etiology. Accurate psychoeducation and prompt intervention, which begin with early screening (e.g., vulnerabilities, comorbidities, risk factors), are needed to empower the systems that support a child. Although comorbid factors are many and a thorough review is outside the scope of this case series, the three cases presented represent a common constellation of factors (e.g., neurodevelopmental, environmental, and adverse/traumatic experiences) that interplay with contextual factors in a diagnostic workup and treatment planning. This case series will also present relevant literature to briefly introduce various social and cognitive outcomes following mTBI relative to more severe injuries, define aspects that differentiate mTBI from more severe injuries, and discuss the influence of environment and other contextual factors across the severity spectrum.

Artificial intelligence in psychiatric diagnosis: challenges and opportunities in the era of machine learning

The integration of artificial intelligence (AI) into psychiatric diagnosis heralds a new era in mental health care, offering unprecedented opportunities to enhance diagnostic accuracy, personalize treatment, and streamline clinical workflows. A systematic approach was utilized, adhering to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. This literature review explores the current state of AI in psychiatric diagnosis, highlighting key technologies such as machine learning, natural language processing, and deep learning. We discuss the application of these technologies across various psychiatric disorders, including depression, anxiety, and schizophrenia. While AI holds immense promise, significant challenges remain, including issues of data privacy, model bias, and the clinical validation of AI tools. Furthermore, ethical and regulatory considerations must be addressed to ensure responsible implementation. This review also examines the potential future directions of AI in psychiatry, emphasizing the importance of collaboration between AI systems and human clinicians. As the field evolves, AI has the potential to transform psychiatric practice, offering new avenues for early detection, personalized care, and therapeutic monitoring.

Socio-Demographic and Clinical Profile of Admitted Patients for Psychiatric Illness in a Tertiary Care Military Hospital in Bangladesh

Background: Mental health problems are becoming a public health issue in all countries around the world. It’s often ignored and unnoticed by patients, their relatives and society as well. Treatments for all these disorders are as available as efficacious. The purpose of this study was to assess the socio-demographic and clinical profile of admitted patients for psychiatric illness in a tertiary care military hospital. Materials and methods: This hospital based retrospective study was performed by analyzing the medical records of admitted psychiatric patients, carried out in the Department of Psychiatry at Combined Military Hospital (CMH), Chattogram from 01 July 2022 to 31 December 2022. For this purpose, 41admitted patients in psychiatry ward of CMH Chattogram were enrolled in the study. Psychiatric diagnoses of the patients were assigned by the consultant psychiatrist as per International Classification of Diseases (ICD) 10th Revision diagnostic criteria. Statistical analyses were carried out by using the Statistical Package for Social Sciences (SPSS)-version 16. The quantitative observations were indicated by frequencies and percentages. Ethical issues were maintained all through the study. Results: The results showed that more than half of (56.09%) patients were in 19-35 years of age with male preponderance (63.41%) and most of the cases reported from urban area (58.53%). The most common psychiatric morbidity among the patients were major depressive disorder (26.82%) followed by Anxiety disorder (17.07%) and Obsessive- compulsive disorders (17.07%). In this study majority of patients stayed 15-28 days (80.48%) on an average of 21.5 days. Conclusion: Neurotic cases were predominant in psychiatric admission. Results of this study may help in the planning for better mental health service integrated with primary healthcare system of our country. Findings of this study will also act as an eye-opener for psychiatrists regarding a wide range of psychiatric diagnoses as well future research in psychiatric fraternity. IAHS Medical Journal Vol 6(2), December 2023; 19-23

The Clinical Utility of Finding Unexpected Subclinical Spikes Detected by High-Density EEG During Neurodiagnostic Investigations.

This study aimed to analyze the frequency of unexpected subclinical spikes (USCS) in pediatric patients who underwent high-density electroencephalogram (HD-EEG). Of the 4481 successful HD-EEG studies, 18.5% (829) were abnormal, and 49.7% of these abnormal studies showed SCS, of which 64.1% were USCS. USCS were found to be correlated with attention/concentration deficits and executive dysfunction, often accompanied by the dual psychiatric diagnosis of ADHD. MRI revealed abnormal findings in 32.6% of the subjects with USCS, such as abnormal signal or signal hyperintensity in brain parenchyma, temporal or arachnoid cysts, and vascular malformations. Moreover, the USCS group who received neuropsychiatric testing scored lower than the population mean on Full-Scale Intelligence Quotient, Working Memory Index, and Processing Speed Index. This study highlights the potential of USCS as biomarkers that can lead to changes in clinical management and outcomes, provide valuable information about pathophysiological mechanisms, and suggest potential treatment pathways.

People who die by suicide without having attended hospital-based psychiatric care: Who are the ones that do not seek help?

BackgroundLittle is known regarding those who die by suicide without having received help. The aim of this study was to compare those who died by suicide without having attended psychiatric care with controls (a) with a psychiatric diagnosis and (b) from the general population. MethodsCases were all individuals 15+ who lived in Denmark during 2010–2021 and had died by suicide without having attended hospital-based psychiatric care. Cases were matched to controls from the two comparison-groups using a 1:10 ratio and compared using age-and sex-adjusted logistic regression analyses. Geographical variations in psychiatric care utilization were examined. ResultsAmong 7119 individuals who died by suicide, 3474 (48.8 %) had not attended psychiatric care. Compared to controls with a psychiatric diagnosis, cases were more likely to be male (OR, 3.9, 95% CI, 3.6–4.2), older (80+ years: OR, 10.7, 95 % CI, 9.2–12.5), have lost a close relative (OR, 1.8, 95 % CI, 1.3–2.6) or recently retired (OR, 1.4, 95 % CI, 1.0–1.1.8). Compared to controls from the general population, cases were associated with male sex (OR, 4.6, 95 % CI, 4.2–5.0), living alone (OR, 2.3, 95 % CI, 2.2–2.5), unemployment (OR, 2.1, 95 % CI, 1.8–2.5), as well as having lost a close relative (OR, 5.0, 95 % CI, 3.5–7.2) or divorced within the last 1 year (OR, 3.6, 95 % CI, 2.7–4.9). LimitationsCharacteristics and preceding events were limited to available register data. ConclusionsAbout half of all who died by suicide had not attended psychiatric care. Being older, male, or exposed to recent stressors were some of the major markers when compared to controls.

Acute COVID-19 severity markers predict post-COVID new-onset psychiatric disorders: A 2-year cohort study of 34,489 patients.

New-onset psychiatric disorders are frequent after COVID-19. We aim to determine whether acute COVID-19 severity markers can predict post-COVID new-onset psychiatric disorders. We conducted an electronic health records (EHR) cohort study of patients hospitalized for COVID-19 and without any known history of psychiatric disorders. Patients were included between January 2020 and September 2022 in one of the 36 university hospitals of the Assistance Publique - Hôpitaux de Paris. Acute COVID-19 clinical and biological severity markers were recorded during hospitalization for COVID-19. Psychiatric ICD-10 diagnoses were recorded up to 2 years and 9 months after hospitalization for COVID-19. Predictors of post-COVID new-onset psychiatric disorders were identified based on Cox regression models and sensitivity analyses. Predictive scores were built and tested in age- and sex-stratified populations. A total 34,489 patients hospitalized for COVID-19 were included; 3717 patients (10.8%) had at least one post-COVID new-onset psychiatric disorder. Hospital stay >7 days (HR = 1.72, 95%CI [1.59-1.86], p < 0.001), acute delirium (HR = 1.49, 95%CI [1.28-1.74], p < 0.001), elevated monocyte count (HR = 1.14, 95%CI [1.06-1.23], p < 0.001) and elevated plasma CRP (HR = 0.92, 95%CI [0.86-0.99], p = 0.04) independently predicted post-COVID new-onset psychiatric disorders. Sensitivity analyses confirmed hospital stay >7 days, acute delirium, and elevated monocyte count as predictors. Predictive scores based on these variables had good 12-month positive predictive values, up to 7.5 times more accurate than random in women < 65 years. In conclusion, hospital stay >7 days, acute delirium, and elevated monocyte count during acute COVID-19 predict post-COVID new-onset psychiatric disorders.

ESTRATÉGIAS DA ANÁLISE DO COMPORTAMENTO APLICADA PARA DESENVOLVER A INTERAÇÃO SOCIAL EM CRIANÇAS AUTISTAS

Autism Spectrum Disorder (ASD) has evolved from a psychiatric classification to a neurodevelopmental disorder, reflecting advances in scientific understanding and diagnostic approaches. The DSM-5, with its more sensitive criteria, facilitates early identification of ASD, which is crucial for effective interventions. Applied Behavior Analysis (ABA) is a proven approach for enhancing social skills and reducing problematic behaviors in children with ASD. By employing techniques such as positive reinforcement and modeling, ABA fosters individualized communication and social interaction, providing significant benefits for both children and their families. Integrating playful resources and innovative strategies can complement interventions, promoting greater autonomy and self-awareness in autistic children. Ongoing advancements in ASD diagnosis and treatment, combined with scientific innovation, are essential for improving the quality of life for children and their families.

Psychiatric, Neurological, and Somatic Comorbidities in Intermittent Explosive Disorder: a retrospective cohort study of electronic health records.

Intermittent Explosive Disorder (IED) is an understudied psychiatric condition that presents with repeated episodes of impulsive aggression and poorly regulated emotional control, often resulting in interpersonal and societal consequences. Better understanding of comorbidities will allow for enhanced screening, diagnosis, and treatment of patients. To investigate prevalence and associations of IED with psychiatric, neurological, and somatic disorders using real-world data. Matched cohorts of patients with or without IED diagnosis were identified using data from the TriNetX Research Network (until January 31, 2024). Cox proportional hazard models were used to estimate and compare the probabilities of acquiring other diagnoses using patients' available medical records. Analysis of electronic medical records from two patient populations. 30,357 individuals with IED and equal number of demographically matched individuals without IED from the TriNetX Research. IED diagnosis identified through the associated ICD codes. The main outcomes were ICD-10-CM diagnostic categories and root codes for disorders and health conditions in both cohorts. Main measures are total numbers and proportions of patients who had the diagnostic codes, as well as adjusted hazard ratios for IED diagnosis. Although only 0.03% of the total patient population had an IED diagnosis, we found extensive and widespread comorbidities with psychiatric, neurological and somatic conditions. A significant 95.7% of the individuals with IED had another psychiatric diagnosis. All psychiatric sub-categories and 95% of the psychiatric diagnoses were significantly associated with IED, with HRs ranging from 2 to 77. Among neurological conditions, neurodegenerative diseases and epilepsy had the highest HRs, followed by extrapyramidal and movement disorders, cerebral palsy and other paralytic syndromes, and sleep disorders. Notable associations with IED also includes conditions such as obesity, hyperlipidemia, hypertension, and GERD. Our findings illuminate the extensive comorbid relationships between IED and psychiatric, neurological, and somatic disorders. This underscores the necessity for an integrated diagnostic and treatment approach that addresses both the psychological and physical health aspects of IED. Additionally, our work highlights the need for more accurate and inclusive diagnosis of IED in patients with mental disorders.

BrainIB: Interpretable Brain Network-Based Psychiatric Diagnosis With Graph Information Bottleneck.

Developing new diagnostic models based on the underlying biological mechanisms rather than subjective symptoms for psychiatric disorders is an emerging consensus. Recently, machine learning (ML)-based classifiers using functional connectivity (FC) for psychiatric disorders and healthy controls (HCs) are developed to identify brain markers. However, existing ML-based diagnostic models are prone to overfitting (due to insufficient training samples) and perform poorly in new test environments. Furthermore, it is difficult to obtain explainable and reliable brain biomarkers elucidating the underlying diagnostic decisions. These issues hinder their possible clinical applications. In this work, we propose BrainIB, a new graph neural network (GNN) framework to analyze functional magnetic resonance images (fMRI), by leveraging the famed information bottleneck (IB) principle. BrainIB is able to identify the most informative edges in the brain (i.e., subgraph) and generalizes well to unseen data. We evaluate the performance of BrainIB against three baselines and seven state-of-the-art (SOTA) brain network classification methods on three psychiatric datasets and observe that our BrainIB always achieves the highest diagnosis accuracy. It also discovers the subgraph biomarkers that are consistent with clinical and neuroimaging findings. The source code and implementation details of BrainIB are freely available at the GitHub repository (https://github.com/SJYuCNEL/brain-and-Information-Bottleneck).

Clinical Predictors of Mood Disorders and Prevalence of Neuropsychiatric Symptoms in Patients with Systemic Lupus Erythematosus.

Background/Objectives: We aimed to determine the prevalence and clinical correlations of mood disorders in a sample of systemic lupus erythematosus (SLE) patients. Hence, we hypothesized that the prevalence of mood disorders would be lower than reported in the literature and that patients would remain clinically stable and show less damage accrual despite low-dose corticosteroid prescription. Methods: In total, 92 SLE outpatients gave informed consent to participate in this cross-sectional study. Psychiatric and autoimmune clinical data were obtained, and a structured psychiatric interview was performed. The main clinical scales for the assessment of clinical symptomatology were included. To examine the potential relationships of presenting a mood disorder in SLE, clinical correlations and multivariate analyses were performed. Results: Mood disorders were the most prevalent disorder reported by SLE patients (16%), followed by adjustment disorders (5%). A significant proportion of patients presented psychosocial disturbances that did not meet the ICD-10 criteria for psychiatric diagnosis. According to the cut-off criterion for the Montgomery-Åsberg Depression Rating Scale (MADRS), up to 27% of the sample met the clinical criteria for depression. The multivariate analysis revealed a relationship between the presence of a mood disorder with total scores of the MADRS and the Young Mania Rating Scale (YMRS). Conclusions: The prevalence of mood disorders in patients with SLE was lower than previously reported. Although self-report clinical scales are useful for assessing clinical symptomatology, they should not be used in place of a comprehensive standardized interview conducted by a trained mental health specialist. Multidisciplinary teamwork is required for the early identification and therapeutic management of autoimmune patients with neuropsychiatric disorders.

B - 80 The Long-Term Memory Sign in Adults Referred for Neuropsychological Evaluation

Abstract Objective We investigated the clinical utility of the newly described long-term memory (LTM) sign in adults referred for neuropsychological evaluation. Individuals with dementia often report short-term episodic memory decline or no memory decline, but rarely report long-term episodic memory decline. The LTM sign refers to patient self-report of long-term episodic memory decline, that is equivalent to/or greater than, subjective short-term episodic memory decline. Method The LTM sign was endorsed on a pre-visit intake form and established during clinical interview in 568 patients (M age = 63, SD = 14.3) referred for neuropsychological evaluation at a large medical center in the Northwest United States. Results In our sample of 568 patients, 79 (14%) reported the LTM sign. In 79 patients with the LTM sign, 45 were diagnosed with a primary psychiatric disorder (57%), 23 were diagnosed with mild neurocognitive disorder (29%), seven had no cognitive or psychiatric diagnosis (9%), and four had dementia (5%). The LTM sign was most common in those with a history of trauma in childhood or adolescence (52/79, 66%) and substance use disorders (50/79, 63%). Conclusions The LTM sign was rare in dementia, but common in those with a current psychiatric diagnosis. These findings support the literature on episodic memory decline in dementia populations and suggests that encoding of early memories and/or retrieval of old memories is negatively impacted by a current psychiatric disorder, traumatic events in childhood and adolescence, and lifetime history of substance use disorder. The LTM sign is a valuable addition to the clinical interview of neuropsychological patients.

A - 141 The Relationship of Tumor Location and Treatment on Cognition in Long-Term IDH-Mutant Glioma Survivors

Abstract Objective Isocitrate dehydrogenase 1 mutation (IDH-M) denotes a distinct subtype of glioma which has a relatively favorable prognosis but nevertheless requires treatment including surgery, radiation and/or chemotherapy and the tumors inevitably recur. Factors influencing cognition in long-term survivors (LTS) of IDH-M have not been well characterized. We investigated factors affecting cognition in a cohort of well characterized of IDH-M LTS. Method Patients (N = 65; 98.5% Caucasian; 47.7% female; Mage = 47.51; Medu = 16.06) who were at least 3 years post-IDH-M diagnosis who completed neuropsychological assessment in the Neuro-oncology division at Massachusetts General Hospital were included. Tests of processing speed, working memory, episodic memory, and executive function were analyzed along with tumor, treatment, and individual difference factors relevant to cognition. Exploratory analyses were conducted to generate hypotheses regarding factors of interest. Results Tumor hemisphere affected delayed recall of word list learning Z-score (F = 4.00; p = 0.024; left = −1.41; right = −0.59). Tumor lobe affected visual learning (F = 3.11; p = 0.054; frontal = −0.594; temporal = −0.807; parietal = −1.983). There were no effects of treatment type (photon vs proton radiation; single vs multi-agent chemotherapy), presence of seizures, psychiatric diagnosis, tumor subtype (oligodendroglioma/astrocytoma), grade (2,3,4) or disease duration (Mean = 9.5y; min = 3y; max = 28.8y) on cognition. Conclusions In this heavily treated group of IDH-M glioma LTS referred for neuropsychological evaluation, typical lateralizing/localizing cognitive deficits were revealed. However, simple dichotomies may fail to capture relevant contributors to cognitive impairment. Integration with individual factors including premorbid cognition, radiation dosimetry and brain network connectivity may be necessary to predict cognitive trajectories and outcomes.

B - 22 Self-Reported Traumatic Brain Injury and its Biopsychosocial Risk Factors in Siblings of Individuals with Neurodevelopmental Conditions

Abstract Objective Siblings of individuals with neurodevelopmental conditions (NDCs) are situated within a complex system of transdiagnostic risk and resilience factors for poor psychosocial, cognitive and behavioral outcomes. Many such factors experienced by NDC siblings overlap with risk for traumatic brain injury (TBI) and correlate with poorer recovery trajectories. Method With data from an online self-report survey, the present study used Bayesian analyses to characterize and compare TBI and biopsychosocial risk factors amongst 632 siblings (207 NDC, 425 controls; mean age 20.54 years, range 10–30, 78.48% female), and examine correlations between clinical, biological, and social determinant of health variables. Results NDC siblings had a higher self-reported lifetime history of TBI compared to controls (14.98% versus 6.35%), with most NDC siblings reporting more than one TBI, and at an earlier mean age. TBI history was associated with psychiatric diagnoses and subclinical NDC features, including hyperactivity and impulsivity, inattention, conduct problems, and autistic traits. Family and structural factors related to TBI included poorer parent–child relationship, NDC diagnoses of autism or fetal alcohol spectrum disorder, minority ethnicity and lower income. Conclusions Findings have important clinical and policy implications for health literacy, TBI education and screening, development of prevention and intervention strategies, and implementation of family support to target social and structural determinants of health impacting NDC sibling wellbeing.

B - 107 Is the Flynn Effect Present in a Veteran Outpatient Clinic Sample?

Abstract Objective The Flynn Effect refers to improvement in cognitive scores over time due to advancements in education quality, nutrition, and socioenvironmental variables. Recent studies suggest cognitive scores may plateau or decline over time. Characterization of cohort effects in cognitive performance has implications for normative group selection and identification of brain illness. This study examines cognitive performances of veterans using older and newer versions of normative data to determine if a Flynn effect is present. Method Veterans (N = 189) who passed TOMM and completed the Trail-Making Test (TMT), Animal Naming, and California Verbal Learning Test-II (CVLT-II) were selected for inclusion. The sample was 81% male, racially diverse (49% White/Caucasian, 31% Black/African American, 16% Hispanic/Latino, 4% other), and diagnostically diverse (13% no diagnosis, 33% cognitive disorder, 54% psychiatric diagnosis). Normative scores were calculated from CVLT-II/CVLT-3 manuals for Trial 1, Trial 5, and LDFR; ADC Uniform Data Sets (UDS) were used for TMT-A/B and Animals. Wilcoxon matched-pairs signed rank tests examined differences in z-scores across older and newer normative data. Results Median z-scores were significantly lower using updated UDS norms for TMT-A (z = −11.60, p &amp;lt; 0.001), TMT-B (z = −10.41, p &amp;lt; 0.001), and Animals (z = −11.76, p &amp;lt; 0.001), while CVLT Trial 1 z-scores were significantly higher using CVLT-3 norms (z = 11.24, p &amp;lt; 0.001). CVLT Trial 5 and LDFR medians did not differ. Conclusion Findings demonstrate the need to examine cohort differences in normative reference groups to ensure accurate detection of brain illness. Furthermore, the Flynn Effect may not apply uniformly across domains within a period.

A - 143 Organic Psychiatric Disorders Due to Frontal Lobe Neoplasms

Abstract Objective This current study seeks to explore the presentation of psychiatric disorders as a preliminary symptom in individuals who suffer from frontal lobe neoplasms. Data Selection The primary sources of information for this literature review were Google Scholar, PubMed, ScienceDirect, and the National Institute of Health (NIH). Search terms included frontal lobe tumors/neoplasms, primary brain tumors, psychiatric/psychological, acquired disorders, and pseudo-depression/mania. This search was limited to articles published in English from January 2014 to December 2023. Inclusion criteria were studies that focused on frontal lobe tumors and psychiatric manifestations as a result of illness. Exclusion criteria were studies older than nine years or studies that explored traits of psychiatric illness (i.e., aggression) as opposed to a psychiatric diagnosis. Data Synthesis Frontal lobe neoplasms, accounting for a significant percentage of PTBs, have been found to impact the psychological well-being of patients, leading to a range of psychiatric manifestations that may appear before physiological symptoms. These include mood disorders (i.e., depression, manic episodes), psychotic episodes, and personality disorders. Due to the complexities of the frontal lobe, these manifestations are not linearly linked to frontal lobe lesions. Conclusion This study’s findings advocate for a multidisciplinary approach to treatment, emphasizing the need for neuropsychological evaluations pre- and post-tumor resection. It calls for heightened awareness among clinicians to consider organic causes behind psychiatric presentations, especially in atypical cases or when traditional treatments fail. Ultimately, this research contributes to a deeper understanding of the neuropsychiatric consequences of frontal lobe neoplasms and paves the way for more targeted and effective interventions.

Influenza and COVID-19 Vaccine Uptake Among Individuals With Versus Without Diagnosed Psychiatric Disorders.

The authors sought to examine influenza and COVID-19 vaccine uptake among individuals diagnosed as having psychiatric disorders compared with those without such diagnoses and to examine variations in vaccine uptake by sociodemographic and clinical characteristics. The study was conducted in the Kaiser Permanente Georgia, Washington, and Southern California health care systems. Individuals with psychiatric conditions had at least one diagnosis of any psychiatric disorder during a 12-month study period; individuals in the control group had no psychiatric disorder diagnoses during this period, and the two groups were matched on age and sex. Bivariate analyses were conducted with Pearson chi-square tests; multivariate analyses were used to calculate the odds of receiving an influenza vaccine (N=1,307,202 individuals) or COVID-19 vaccine (N=1,380,894 individuals) and were controlled for selected covariates. After controlling for relevant confounders, the authors found that having a diagnosis of any psychiatric illness was associated with significantly increased odds of receiving an influenza vaccine (OR=1.18; 95% CI=1.17-1.19, p<0.001), compared with no diagnosis of a psychiatric disorder. Having any psychiatric illness was associated with decreased odds of receiving a COVID-19 vaccine (OR=0.97; 95% CI=0.96-0.98, p<0.001), after the analysis was controlled for the same covariates. The findings provide evidence that people with mental health conditions were more likely to receive an influenza vaccine but were less likely to receive a COVID-19 vaccine, compared with individuals without such conditions. However, the vaccination rates observed for individuals with and without diagnosed psychiatric conditions were below national benchmarks, suggesting room for improving vaccine uptake in both patient populations.

Mental disorders in adults from Ribeirão Preto, Brazil: a cross-sectional analysis of two birth cohorts

BackgroundIn Brazil, the prevalence of mental disorders is heterogeneous, with most studies conducted in large cities with high population density. This study aimed to assess the prevalence of mental disorders and psychiatric comorbidities among young adults (22–23 years old) and adults (37–38 years old) from Ribeirão Preto, a city located in the Northeast of the São Paulo state, with approximately 700,000 inhabitants, and to explore associations with sociodemographic variables, suicide risk, and health service usage. Second, we aimed to evaluate the performance of the Self-Report Questionnaire (SRQ-20) as a screening tool for mental disorders to be applied to the local population.MethodsParticipants from the 1978/1979 and 1994 Ribeirão Preto birth cohorts were evaluated using the Mini International Neuropsychiatric Interview (MINI) and the SRQ-20 at mean ages of 22–23, and 37–38 years, respectively.ResultsOur sample comprised 1,769 individuals from the 1978/1979 cohort and 1,037 from the 1994 cohort. The prevalence of mental disorders ranged from 28.6% (1978/79) to 31% (1994), with frequent comorbid diagnoses (42.7% and 43.3%, respectively). Men and women had a similar prevalence of mental disorders in the younger cohort, while women had a higher prevalence in the older cohort. Low educational attainment was associated with higher rates of diagnosis. In both cohorts, alcohol and other psychoactive substance use was higher among those with a psychiatric diagnosis. Although those with a psychiatric diagnosis were less satisfied with their own health, only one-fifth had seen a mental health professional in the previous year. A psychiatric diagnosis increased the suicide risk by 5.6 to 9.1 times. Regarding the SRQ-20, the best cutoff points were 5/6 for men and 7/8 for women, with satisfactory performance.ConclusionsThe prevalence and comorbidity of mental disorders were high in both cohorts and comparable to those in larger Brazilian cities. However, few individuals with a diagnosis had sought specialized care. These data suggest that the mental health gap is still significant in Brazil.