OBJECTIVE: The COVID-19 pandemic required mental health clinicians globally to transition to the delivery of care via telehealth. This study aimed to gain an understanding of clients\' satisfaction with and attitudes towards telehealth mental health services.
METHODS: Seventy adults who had attended a clinic for mood and anxiety disorders, and participated in at least one telehealth consultation with a psychologist or psychiatrist, completed an anonymous online survey.
RESULTS: The majority of participants (81.5%) reported satisfaction with telehealth mental health care provided during the COVID-19 pandemic. However, satisfaction overall was significantly higher amongst participants who had received both telehealth and face-to-face mental health care, compared to participants who received care via telehealth only. Advantages of telehealth care reported included convenience and increased access to mental health clinicians. However, disadvantages of telehealth care included greater difficulty developing a rapport with a clinician and expressing oneself via telehealth.
CONCLUSIONS: Whilst client satisfaction with telehealth mental health care for mood and anxiety disorders is generally high, clinicians should consider the limitations of telehealth from clients\' perspectives. In particular, strategies to enhance therapeutic connection during telehealth sessions may be needed, and client preferences for mode of delivery should be taken into consideration when possible.

Psychosomatic medicine has been known to play a pivotal role in the management of complex medical cases by providing a bridge between the physical disease and psychological distress. This case study focuses on a 42-year-old Saudi female diagnosed with breast cancer and generalized anxiety disorder. In addition to anxiety, the patient had a history of obsessive-compulsive personality traits, which contributed to her reluctance to undergo mastectomy. Significant challenges and noncompliance with treatment were caused by her unwillingness and inadequate interaction with the medical team. An integrated multidisciplinary strategy including psycho-oncological interventions was necessary because of the complexity of this case. Communication issues were addressed through the concerted efforts of the specialist teams. A comprehensive patient-practitioner understanding was established, which enabled the teams to persuade the patient to undergo surgical intervention. Overcoming her initial resistance, the patient eventually complied with the treatment plan, leading to a successful surgery. Postsurgical evaluations using the Hamilton Anxiety Scale indicated a significant reduction in anxiety levels. This case underscores the critical contribution of psychosomatic medicine to healthcare, especially in challenging situations that demand additional resource allocation, further highlighting the importance of an interdisciplinary approach, efficient communication, and patient-practitioner rapport in healthcare outcomes.

This case report delineates the intricate interplay between psychiatric and oncological pathology in a 72-year-old male diagnosed with low-grade marginal zone B-cell lymphoma and severe psychiatric disturbances, including catatonia. The presentation of severe psychiatric symptoms initially obscured the underlying lymphoma, delaying diagnosis and complicating clinical management. Notably, the lymphoma itself may have precipitated or exacerbated the psychiatric condition, underscoring the potential for oncological diseases to manifest with rapidly progressive dementia and catatonia. A multidisciplinary approach was employed, utilizing electroconvulsive therapy (ECT) for rapid resolution of catatonia, which facilitated significant mental health improvements and clearer delineation of the oncological underpinnings. Concurrently, the patient was treated with rituximab, targeting the lymphoma. This case highlights the critical need for a comprehensive evaluation in patients presenting with psychiatric symptoms, particularly in the elderly, to uncover potential medical causes and illustrates the efficacy of ECT in managing psychiatric conditions that may overshadow or complicate concurrent medical issues.

Early and accurate diagnosis is crucial for effective treatment and improved outcomes, yet identifying psychotic episodes presents significant challenges due to its complex nature and the varied presentation of symptoms among individuals. One of the primary difficulties lies in the underreporting and underdiagnosis of psychosis, compounded by the stigma surrounding mental health and the individuals\' often diminished insight into their condition. Existing efforts leveraging Electronic Health Records (EHRs) to retrospectively identify psychosis typically rely on structured data, such as medical codes and patient demographics, which frequently lack essential information. Addressing these challenges, our study leverages Natural Language Processing (NLP) algorithms to analyze psychiatric admission notes for the diagnosis of psychosis, providing a detailed evaluation of rule-based algorithms, machine learning models, and pre-trained language models. Additionally, the study investigates the effectiveness of employing keywords to streamline extensive note data before training and evaluating the models. Analyzing 4,617 initial psychiatric admission notes (1,196 cases of psychosis versus 3,433 controls) from 2005 to 2019, we discovered that the XGBoost classifier employing Term Frequency-Inverse Document Frequency (TF-IDF) features derived from notes pre-selected by expert-curated keywords, attained the highest performance with an F1 score of 0.8881 (AUROC [95% CI]: 0.9725 [0.9717, 0.9733]). BlueBERT demonstrated comparable efficacy an F1 score of 0.8841 (AUROC [95% CI]: 0.97 [0.9580,0.9820]) on the same set of notes. Both models markedly outperformed traditional International Classification of Diseases (ICD) code-based detection methods from discharge summaries, which had an F1 score of 0.7608, thus improving the margin by 0.12. Furthermore, our findings indicate that keyword pre-selection markedly enhances the performance of both machine learning and pre-trained language models. This study illustrates the potential of NLP techniques to improve psychosis detection within admission notes and aims to serve as a foundational reference for future research on applying NLP for psychosis identification in EHR notes.

Early and accurate diagnosis is crucial for effective treatment and improved outcomes, yet identifying psychotic episodes presents significant challenges due to its complex nature and the varied presentation of symptoms among individuals. One of the primary difficulties lies in the underreporting and underdiagnosis of psychosis, compounded by the stigma surrounding mental health and the individuals\' often diminished insight into their condition. Existing efforts leveraging Electronic Health Records (EHRs) to retrospectively identify psychosis typically rely on structured data, such as medical codes and patient demographics, which frequently lack essential information. Addressing these challenges, our study leverages Natural Language Processing (NLP) algorithms to analyze psychiatric admission notes for the diagnosis of psychosis, providing a detailed evaluation of rule-based algorithms, machine learning models, and pre-trained language models. Additionally, the study investigates the effectiveness of employing keywords to streamline extensive note data before training and evaluating the models. Analyzing 4,617 initial psychiatric admission notes (1,196 cases of psychosis versus 3,433 controls) from 2005 to 2019, we discovered that the XGBoost classifier employing Term Frequency-Inverse Document Frequency (TF-IDF) features derived from notes pre-selected by expert-curated keywords, attained the highest performance with an F1 score of 0.8881 (AUROC [95% CI]: 0.9725 [0.9717, 0.9733]). BlueBERT demonstrated comparable efficacy an F1 score of 0.8841 (AUROC [95% CI]: 0.97 [0.9580, 0.9820]) on the same set of notes. Both models markedly outperformed traditional International Classification of Diseases (ICD) code-based detection methods from discharge summaries, which had an F1 score of 0.7608, thus improving the margin by 0.12. Furthermore, our findings indicate that keyword pre-selection markedly enhances the performance of both machine learning and pre-trained language models. This study illustrates the potential of NLP techniques to improve psychosis detection within admission notes and aims to serve as a foundational reference for future research on applying NLP for psychosis identification in EHR notes.

UNASSIGNED: Frontline staff in psychiatry need to perform at a very high professional level in order to ensure patient and community safety. At the same time they are exposed to high levels of stress and workplace trauma. This may have severe consequences for their professional quality of life. In addition, health care workers in general have higher incidence levels of childhood adversity than the general population. The CRITIC (CRITical Incidents and aggression in Caregivers) Study aims to improve increased understanding of the interaction between personal life history (childhood adversity and benevolence), individual capabilities, exposure to trauma and violence at work and Professional Quality of Life (ProQOL).
UNASSIGNED: The Critic Study is a cross-sectional survey of these aspects in frontline, treatment and administrative staff in clinical and forensic psychiatry. We aim to include 360 participants. Participants will be asked to complete questionnaires on childhood adversity and childhood benevolence (assessing personal life history), professional quality of life, current trauma and violence exposure, current mental health (depression, anxiety and stress), coping, social support, work engagement and resilience. In this study we will examine the moderating role of adverse and benevolent childhood experiences in the association between workplace trauma exposure and professional quality of life. Finally, a theoretical model on the relationships between trauma, stress and coping in the context of professional functioning will be tested using structural equation modelling.
UNASSIGNED: The CRITIC study examines which factors influence the complex relationship between childhood adversity and benevolence, and ProQOL in healthcare workers. It also aims to provide insight into the complex relationship between personal life history, individual characteristics, exposure to trauma and violence at work and ProQOL. The results can be used for designing interventions to increase resilience to trauma and to improve professional quality of life among health care professionals.
UNASSIGNED: The CRITIC study has been approved by the Medical Ethical Committee of the Erasmus Medical Centre, under trial registration number NL73417.078.20.

Auditory hallucinations are sounds that patients perceive as coming from outside of their body. Though the mechanism causing auditory hallucinations is not entirely understood, there is a significant amount of evidence suggesting that auditory hallucinations leave lasting impacts on the brain in the same regions that are involved in auditory processing. Sudden sensorineural hearing loss (SSNHL) is a poorly understood condition in which patients lose their hearing typically in the fifth decade of life. Here we present a case of a 42-year-old female with a history of schizophrenia with auditory hallucinations who experienced SSNHL at age 40. As the patient had no known risk factors for SSNHL, we propose that this patient\'s SSNHL is linked to her history of auditory hallucinations. Through the presentation of this case, we hope to explore the pathogenesis of auditory hallucinations and investigate a potentially bidirectional association between auditory hallucinations and SSNHL. This study calls for further investigation into the impacts of auditory hallucinations on the brain, possible etiologies of SSNHL, and the possibility that auditory hallucinations serve as a risk factor for SSNHL.

In the wake of the COVID-19 pandemic, healthcare systems rapidly embraced technology as a means of providing care while adhering to social distancing protocols. In this brief article, we report on a new telehealth initiative recently implemented in an out-patient psychiatric setting and outline the novel role telehealth may serve in facilitating psychiatric care globally. The uptake of telehealth represents a new and exciting opportunity to increase both access to, and quality of, care for people with mental illness.

Given the ongoing difficulties faced by clinicians and researchers in dealing with neuropsychiatric illnesses, it is becoming more and more evident that there is a need to go beyond traditional disciplinary boundaries. This research consolidates existing material, examining changes in history, the fundamental neurobiological aspects, and the shared clinical manifestations between neurology and psychiatry. This inquiry examines the historical development of neuropsychiatry, focusing on the relationship between early understandings of mental illness and the later division of neurology and psychiatry. The focus is on recent advancements in comprehending the common neurobiological pathways and genetic factors that highlight the merging of these fields. The research highlights the complexities of clinical presentations in neuropsychiatric illnesses by analyzing the overlapping cognitive, affective, and behavioral symptoms. The text critiques the diagnostic issues in traditional frameworks, emphasizing the limitations in differentiating between neurological and psychiatric origins. This has ramifications for achieving correct diagnosis and arranging appropriate treatment. The paper explores developing multidisciplinary care approaches, highlighting successful collaborations between neurologists and psychiatrists. This study examines the difficulties in carrying out a plan and the process of identifying obstacles to combining different elements. It also highlights the urgent need for improved instruction and learning for smooth cooperation. The paper examines the therapeutic implications by investigating pharmacological therapies focusing on shared pathways. It also discusses the difficulties involved in managing neurological and psychiatric diseases that occur together. The study also explores non-pharmacological therapies, such as psychotherapy and rehabilitation methods, as part of a comprehensive treatment approach. Anticipating the future, the report identifies areas where the study could be improved and forecasts the influence of technological improvements on the subject. Suggestions are put out to encourage additional exploration, cooperation, and originality to narrow the divide between neurology and psychiatry, ultimately augmenting our comprehension and treatment of neuropsychiatric illnesses. This real-time synthesis adds to the ongoing discussion, providing valuable insights that align with the ever-changing field of contemporary neuropsychiatric research and therapy.

Objective The objective of this study is to examine the variability in the self-reported fatigue symptom severity in major depressive disorder (MDD) compared to generalized anxiety disorder (GAD). Methods A retrospective chart review was conducted of 100 patients evaluated for fatigue using depression and anxiety questionnaires. The study examined whether ratings of fatigue varied based on whether fatigue was being rated by the patient in the context of MDD vs. when fatigue was being rated by the same patient in the context of GAD. A related-sample Wilcoxon signed-rank test and Mann-Whitney U test were used to compare the median differences between depression and anxiety fatigue scores. The significance level used was 0.05. Results This study found a statistically significant difference in the median difference of the paired depression fatigue and anxiety fatigue scores (depression score - anxiety score) regardless of the order of administration (Wilcoxon signed-rank test statistic = 135.500, p-value =.008, N = 100 paired scores). Conclusion The study\'s conclusions show that although the symptom of fatigue is listed in the Diagnostic Statistical Manual 5 (DSM-5) criteria for MDD as well as GAD, it may be perceived by patients differently based on the context of the syndrome. This emphasizes the importance of considering the context of symptom reporting in patients with MDD and GAD to improve diagnostic methodologies and treatment strategies.