Psychiatric Diagnosis Research Articles (Page 1)

Patients on immune checkpoint therapy (ICT) are at risk for neuropsychiatric events due to the use of steroids in managing immune-related adverse effects. We aimed to characterize neuropsychiatric events after the initial administration of high-dose steroids following early ICT. We performed a retrospective, single-institution cohort study for those on ICT between 6/1/2017 and 6/1/2022 during the 6months after the initial administration of high-dose steroids (≥ 40mg/d of prednisone or equivalent glucocorticoid dose) within 7months from ICT compared with control patients receiving ICTs but not receiving steroids in this timeframe. The steroid group consisted of single (≤ 1month) and extended (> 1month) exposure based on prescriptions. Neuropsychiatric events by proxy measures (new psychiatric diagnoses and psychiatric medications) were compared between groups using 2-sided t-tests and chi-square tests. Multinomial logistic regression models were used to determine group differences in neuropsychiatric events while adjusting for predefined covariates. A total of 13,465 patients were analyzed, with 3080 and 10,385 patients in the steroid and control groups, respectively. New psychiatric diagnoses were more frequent in the steroid group compared with controls (11% for single exposure and 15% for extended vs 2.5% for controls) for 1 new diagnosis. The extended steroid group had more new antipsychotic prescriptions (6.3% for single exposure and 11% for extended vs 9%, p < 0.001) and intravenous/intramuscular haloperidol or chlorpromazine use (2.8% for single exposure and 5.5% for extended vs 2.1%, p < 0.001). Extended high-dose steroid use during early ICT was associated with an increased frequency of neuropsychiatric events, highlighting the need to educate patients and medical staff about this risk and to monitor neuropsychiatric events for early recognition and intervention in this population.

Psychodermatology addresses the interaction between cutaneous disease and psychological conditions. The Coping Clinic at Boston Medical Center (BMC) provides interdisciplinary psychodermatology care where pediatric patients see a dermatologist and a psychologist in the same visit. This study's purpose was to preliminarily assess the scope and impact of collaborative care between pediatric dermatology and psychology. A retrospective chart review of 50 patients (94 charts) examined the reasons for referral, dermatologic and psychiatric diagnoses, treatment recommendations, and interventions made in the Coping Clinic from 2018-2023. Of the 50 patients seen, 62% (31/50) were female and 38% (19/50) were male, with a mean age of 13.2 years. The most common dermatologic diagnoses were atopic dermatitis (32%; 16/50) and acne vulgaris (30%; 15/50). Excluding those diagnosed with adjustment disorder, 72% (36/50) of patients received new psychological diagnoses at Coping Clinic, the most common being anxiety (34%; 17/50) and depression (12%; 6/50). Sixty-four percent (32/50) of patients were referred to therapy after being seen in Coping Clinic, and 28.1% (9/32) met with a mental health provider at least once. As documented in the psychologist's notes, 80% (12/15) of patients had signs of improved mood at their follow-up visits. All Coping Clinic patients received new psychological assessments and plans or a referral to Behavioral Health along with continuity in dermatology care. While we cannot prove from this chart review that improvement in mood was specifically related to attending Coping Clinic, these results demonstrate the feasibility of interdisciplinary pediatric psychodermatology care in an urban safety-net hospital.

Most adult mental health conditions begin in early childhood and adolescence, the most common being anxiety and behavioral disorders. Early intervention can improve outcomes and may reduce the risk of developing a clinical disorder in the future. However, children may not have the communication or understanding to share their symptoms with those around them, leaving pediatric primary care providers responsible for identifying concerning signs. This paper reviews both general symptoms that suggest possible mental health conditions as well as specific correlations between symptoms and psychiatric diagnoses. A literature search utilizing PubMed identified nine relevant articles that were supplemented with additional sources. The findings found that impaired coordination or balance, weakness, paralysis or loss of sensation, seizure-like activity, blindness, double vision, deafness, or one severe symptom, typically pain, were general signs that may indicate a psychiatric illness. More specific associations were also identified. For instance, children who report somatic complaints and school refusal have been linked to anxiety; in addition, reported stress, anger, and worries about family alcohol and drug use have been linked to depression, among many others. Awareness of the somatic and social concerns presented by children to primary care can reduce the delay from the onset of symptoms to diagnosis, leading to earlier identification, treatment, and improved outcomes. Early intervention may delay or prevent symptoms from developing into a diagnosable psychiatric disorder and/or may reduce the severity of symptoms in a child who already has a psychiatric condition.

One of the main causes of the global disease burden is psychiatric disorders. However, due to the complex relationships between genetic, epigenetic, environmental, and neurological factors, diagnosing and treating these conditions remains challenging. Precision psychiatry, driven by multi-omics and artificial intelligence (AI), offers a novel approach to understanding mental health conditions and developing personalized treatments. This review examines the contributions of genome integration, transcriptomics, epigenomics, proteomics, metabolomics, and microbiome studies to psychiatric research and diagnosis. The area has changed as a result of recent developments in AI, particularly in machine learning and deep learning, combined with information from patient-reported outcomes, electronic health records, and neuroimaging. AI models facilitate the creation of customized treatment regimens, enhance pharmacogenomic predictions, and aid in the identification of biomarkers. Furthermore, the interpretability issues of these models are addressed by the emergence of explainable AI (XAI), which facilitates more transparent healthcare choices. The broad clinical application of precision psychiatry is, however, hindered by several challenges, including the difficulty in integrating multi-omics data, ethical concerns about the use of AI in mental health, and the need for thorough validation across diverse populations. Computational biologists, neuroscientists, psychiatrists, and clinicians from other disciplines must collaborate to address these challenges and develop scalable, reliable, and ethically sound frameworks for precision medicine in psychiatry. This study lays the groundwork for future research and clinical practice by highlighting the potential for integrating AI and multi-omics technology to revolutionize psychiatric care. Precision psychiatry can transition from a trial-and-error method to a tailored and predictive one by utilizing sophisticated computational tools, ultimately improving patient outcomes and mental health treatment. This study is among the first comprehensive efforts to explore the integration of multi-omics and AI, especially XAI, within the context of precision psychiatry, establishing a translational model for tailored mental health treatment. Received: 25 April 2025 | Revised: 5 August 2025 | Accepted: 17 October 2025 Conflicts of InterestThe authors declare that they have no conflicts of interest to this work. Data Availability StatementThe data supporting the findings of this study are available upon request from the corresponding author. Author Contribution StatementOluwafikayo Seun Adeyemi-Benson: Conceptualization, Methodology, Software, Validation, Writing – original draft, Writing – review &amp; editing.

Aims The Alcohol Use Disorders Identification Test (AUDIT) is a widely used screening instrument for harmful alcohol use. Comorbidity between alcohol use disorders and other mental disorders is common, but there is a shortage of studies investigating AUDIT’s diagnostic accuracy in young adult psychiatric patients. The aim of this study was to examine AUDIT’s diagnostic accuracy and psychometric properties in young adult psychiatric outpatients. Methods In data from two samples of young adults (18–25 years) from general psychiatric outpatient clinics in Sweden, recruited in 2002–2003 (n = 197) and 2012–2016 (n = 283) psychiatric diagnoses were assessed using the Structured Clinical Interview for DSM-IV, axis I disorders, clinical version (SCID-I-CV) or the Mini International Neuropsychiatric Interview (MINI 6.0). Internal consistency of AUDIT, sensitivity, specificity, positive and negative predictive values (PPV and NPV), receiver operator characteristic (ROC) curves, and area under the curve (AUC) were calculated. Results The internal consistency of AUDIT was acceptable (Cronbach’s alpha = 0.76). For the samples combined the optimal cut-off was 10, sensitivity 87% and specificity 82%, PPV 0.28 and NPV 0.99. For Sample 2002–2003, the optimal cut-off point was nine For Sample 2012–2016, the optimal cut-off point was 10. ROC curves are presented, with an AUC of 0.88 (95% CI= 0.81–0.95) for both samples combined, 81.1% for Sample 2002–2003 (95% CI = 0.63–0.99) and an AUC of 90.6% for Sample 2012–2016 (95% Cl = 0.85–0.96). Conclusion The full version of AUDIT is a reliable and valid screening instrument for alcohol use disorders, as shown in two samples of young adult psychiatric outpatients.

Background: Cannabis is one of the most widely used psychoactive substances worldwide and has been linked to various psychiatric disorders. Despite its traditional use in Nepal, data on cannabis use among psychiatric outpatients are limited. This study aimed to find out the patterns of cannabis use and to determine its associated socio-demographic factors and comorbid psychiatric disorders among psychiatric outpatients attending a tertiary care teaching hospital in Eastern Nepal. Methods and materials: A hospital-based cross-sectional study was conducted among 500 psychiatric outpatients at BPKIHS, Dharan. Socio-demographic data were collected using a semi-structured proforma. Cannabis use was assessed with the Cannabis Use Disorders Identification Test–Revised (CUDIT-R), and psychiatric diagnoses were made using ICD-10 criteria. Associations between cannabis use and socio-demographic and psychiatric variables were analyzed using Chi-square and Fisher’s exact tests Results: Ever cannabis use was reported by 38(7.6%) patients and 25(5%) patients were current users. Hazardous use and possible cannabis use disorder were observed in 8 patients (1.6%), and 15 patients (3%) respectively. Lifetime cannabis dependence was present in 16 (3.2%) patients. Cannabis use was significantly associated with young age 16–25 years (p&lt;0.01), male gender (p=0.01), unmarried status (p=0.01), and occupation (p=0.01). Most common comorbidities among cannabis users included nicotine dependence (p=0.001), alcohol use (p=0.001), opioid use (p=0.001), mania (p=0.001) and obsessive-compulsive disorder (OCD) (p=0.043). Conclusion: Routine screening for cannabis uses in psychiatric outpatient settings is recommended for holistic management of psychiatric patients with high-risk socio-demographic profile.

This article critically examines the diagnostic criteria for Major Depressive Disorder as presented in the DSM-5-TR, with a particular focus on the symptoms of ‘depressed mood’ and ‘psychomotor agitation or retardation’. While existing literature in both humanistic psychology and phenomenological psychopathology has highlighted the limitations of the Diagnostic and Statistical Manual of Mental Disorders (DSM) symptom-based and externalist model, this article contributes to the discussion by grounding its critique in first-person accounts and by analysing how the aforementioned symptoms, as conceptualised in the DSM, flatten and obscure the lived experience of depression. It argues that the symptom of ‘depressed mood’ is conceptually circular and diagnostically imprecise, while ‘psychomotor agitation or retardation’, insofar as it is diagnosed based on being ‘observable by others’, fails to capture the phenomenological nuances of the experience, such as the loss of volition. Such limitations point to the need for an approach that takes seriously the lived, first-person dimensions of depression, rather than reducing the experience to externally verifiable signs. In this regard, by advancing a symptom-specific critique grounded in phenomenology, this article calls for a more person-centred approach to psychiatric diagnosis, one that considers the role of first-person experience. Finally, this article reflects on the implications of a person-centred approach for the evaluation of psychotropic medication, especially with regard to experiential phenomena such as depersonalisation and derealisation.

Huntington's disease is a progressive neurodegenerative disorder characterized by motor, cognitive, and behavioral symptoms. While psychiatric comorbidity is common and may influence disease outcomes, there is a lack of data on its prevalence and impact in Portugal. This study aimed to analyze the frequency and impact of a diagnosis of psychiatric comorbidities among Huntington's disease hospitalized patients in Portugal. A retrospective observational study was conducted using administrative data from Portuguese public hospitals within the National Health Service between 2000 and 2016. All hospitalization episodes of patients with a diagnosis of Huntington's disease (International Classification of Diseases, Ninth Revision, Clinical Modification code 333.4) were analyzed. Comorbid psychiatric diagnoses registered as primary or secondary diagnoses were identified and defined using the Clinical Classification Software codes 650-670. Age at admission, length of hospital stay, admission type, in-hospital mortality, and estimated hospital charges were analyzed according to psychiatric comorbidity categories and adjusting for age and sex. A total of 1667 hospitalizations with a diagnosis of Huntington's disease occurred between 2000 and 2016, of which 28.97% had a psychiatric comorbidity. These patients were more likely to be younger (adjusted odds ratio = 1.32, 95% confidence interval 1.07 - 1.64; p = 0.011) and to have longer hospitalizations (adjusted odds ratio = 1.88, 95% confidence interval 1.52 - 2.34; p < 0.001) than those with no psychiatric comorbidity. No association was found between psychiatric comorbidity in general and in-hospital mortality, admission type or hospitalization costs. An upward trend was observed in Huntington's disease admissions and the percentage of those with psychiatric comorbidity over the study period. Psychiatric comorbidity in Huntington's disease was associated with younger age at admission and longer hospitalizations. These results highlight the importance of psychiatric care in the management of these patients. Early screening and intervention could improve outcomes and optimize healthcare resource allocation.

Pregnancy and postpartum are times of increased risk for a variety of mental health problems. Historically, these symptoms have been conceptualized via ostensibly distinct, consensus-based diagnostic categories. However, applying an empirically based, dimensional approach to psychiatric classification may significantly advance understanding of common and specific risk factors during this highly dynamic period. In the present study, we used exploratory psychometric methods to examine the structure of psychopathology symptoms from the "bottom-up" or using symptom-level co-occurrence to derive common factors in a sample of individuals (N = 347) across earlier pregnancy (M = 17.4 weeks gestation), later pregnancy (M = 34.6 weeks gestation), and postpartum (M = 25.3 weeks postpartum). We examined changes (or invariance) in symptom structure longitudinally. Results demonstrated a hierarchical structure of symptoms including a robust broad distress factor at the highest level, followed by replicable internalizing and externalizing factors. The best lower-order solutions included eight to nine factors at each timepoint. Across earlier to later pregnancy and postpartum, psychopathology structure showed both significant invariance and nuanced changes, indicating that perinatal symptom factors are largely robust, while the structure of select subfactors (e.g., low mood, general anxiety) differs slightly across time. Consistent pregnancy anxiety, traumatic stress, somatic problems, detachment, anger-antagonism, and inattention-hyperactivity factors emerged across timepoints. Factors relating to positive affect, low mood, general anxiety, and social anxiety were structured similarly although not identically across time. These longitudinal trends in psychopathology structure have important implications for empirically based psychopathology classification in this critical developmental phase. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

The burden of early onset psychosis: Diagnostic complexity, high comorbidity, and poor functioning in patients and their relatives.

The phenotypic and genetic relationship between adolescent mental health and time spent on social media, gaming, and TV.

Association between hyperemesis gravidarum and depression: a national register-based controlled study in Finland.

The effectiveness and safety of Chinese herbal Jieyu Anshen Decoction monotherapy or in combination with Western medicine for mental disorders: A systematic review and meta-analysis of randomized controlled trials.

This study aimed to compare rates of psychiatric and neurologic diagnoses on emergency department (ED) visit records of adults with versus without intellectual and developmental disabilities (IDDs). This cross-sectional study used the 2019 Nationwide Emergency Department Sample of U.S. hospital ED visit discharges. Validated codes were used to compare psychiatric and neurologic diagnoses of patients ages ≥18 with versus without diagnosed IDDs. Diagnosed psychiatric and neurologic conditions included depression, anxiety, schizophrenia or psychosis, suicidality, seizure, dementia, and sleep disorder. The analysis identified 558,408 and 112,593,527 (nationally weighted) ED visits by adults with and without IDDs, respectively. Compared with the general population, adults with IDDs were twice as likely to have a mental disorder as the principal visit diagnosis, with higher probabilities of principal visit suicidality (1.6 times higher), neurologic disorder (5.6 times higher), and seizure (8.1 times higher) diagnoses. Compared with the general population, adults with intellectual disability were nearly twice as likely to have a dementia diagnosis, and patients with Down's syndrome were six times likelier to have a dementia diagnosis. More than one in five ED visit records of patients ages 50-54 with Down's syndrome included a dementia diagnosis; the dementia diagnosis rate for such patients ages ≥70 was 2.7 times higher than that of the general population. Adult ED patients with IDDs were more likely than those without IDDs to have co-occurring mental and neurologic disorders. Findings underscore the need to provide neuropsychiatric services across the lifespan to address the distinctive care needs of individuals with IDDs.

This study aimed to assess the prevalence and profile of psychiatric comorbidity among geriatric kidney transplantation candidates and to identify associated demographic and clinical factors. To our knowledge, this is the first study to investigate psychiatric comorbidity in geriatric kidney transplant candidates specifically. This medical record-based, descriptive cross-sectional study included patients aged ≥ 65 years with end-stage renal disease (ESRD) who were referred for psychiatric evaluation as part of the kidney transplant candidacy process at a university hospital between January 2016 and June 2024. Psychiatric diagnoses were determined based on DSM-5 criteria through a review of psychiatric consultation records. Patients were grouped based on the presence or absence of current psychiatric disorders, and univariate analyses were conducted to identify associated factors. A total of 205 patients (mean age 68.4 ± 3.4 years; 65.9% male) were evaluated. Psychiatric disorders were present in 15.1% of the sample. Anxiety and depression were the most common. Psychiatric comorbidity was significantly associated with female gender (p = 0.002), unmarried status (p = 0.033), prior psychiatric history (p < 0.001), and history of graft rejection (p = 0.020). No associations were found with dialysis duration, education, or employment status. Psychiatric disorders are common in geriatric ESRD patients evaluated for kidney transplantation. Psychiatric comorbidity was significantly associated with female gender, unmarried status, prior psychiatric history, and previous graft rejection. Routine psychiatric assessment and interdisciplinary care may improve outcomes in this vulnerable population.

Early pregnancy depressive symptoms and severe maternal morbidity.

Neighborhood experience and hoarding disorder.

New-onset psychiatric diagnoses, including suicidal ideation and suicide attempts, are more common among hidradenitis suppurativa patients compared to the general population: A propensity score-matched retrospective cohort-study of 43,707 patients utilizing the TriNetX research network.

Structural connectomic signatures of childhood maltreatment across affective and psychotic disorders.

Association between adverse childhood experiences and combat-related PTSD among Israeli conscripts referred for pre-enlistment mental health evaluations.