Thinking computationally in translational psychiatry. A commentary on Neville et al. (2024).

There is a growing focus on the computational aspects of psychiatric disorders in humans. This idea also is gaining traction in nonhuman animal studies. Commenting on a new comprehensive overview of the benefits of applying this approach in translational research by Neville et al. (Cognitive Affective & Behavioral Neuroscience 1-14, 2024), we discuss the implications for translational model validity within this framework. We argue that thinking computationally in translational psychiatry calls for a change in the way that we evaluate animal models of human psychiatric processes, with a shift in focus towards symptom-producing computations rather than the symptoms themselves. Further, in line with Neville et al.'s adoption of the reinforcement learning framework to model animal behaviour, we illustrate how this approach can be applied beyond simple decision-making paradigms to model more naturalistic behaviours.

[Diagnosis and admission center : Establishment and evaluation of an integrated translational infrastructure for clinical psychiatric research]. / Diagnose- und Aufnahmezentrum : Etablierung und Evaluation einer integrierten translationalen Infrastruktur für die klinisch-psychiatrische Forschung.

The routine in-depth characterization of patients with methods of clinical and scale-based examination, neuropsychology, based on biomaterials, and sensor-based information opens up transformative possibilities on the way to personalized diagnostics, treatment and prevention in psychiatry, psychotherapy, and psychosomatics. Effective integration of the additional temporal and logistical effort into everyday care as well as the acceptance by patients are critical to the success of such an approach but there is little evidence on this to date. We report here on the establishment of the Diagnosis and Admission Center (DAZ) at the Central Institute of Mental Health (ZI) in Mannheim. The DAZ is an outpatient unit upstream of other care structures for clinical and scientific phenotyping across diagnoses as a starting point for data-driven, individualized pathways to further treatment, diagnostics or research. We describe the functions, goals, and implementation of the newly created clinical scientific translational structure, provide an overview of the patient populations it has reached, and provide data on its acceptance. In this context, the close integration with downstream clinical processes enables a better coordinated and demand-oriented allocation. In addition, DAZ enables a faster start of disorder-specific diagnostics and treatment. Since its launch in April 2021 up to the end of 2022, 1021 patients underwent psychiatric evaluation at DAZ during a pilot phase. The patient sample corresponded to a representative sample from standard care and the newly established processes were regarded as helpful by patients. In summary, the DAZ uniquely combines the interests and needs of patient with the collection of scientifically relevant data.

Elevating the field for applying neuroimaging to individual patients in psychiatry.

Although neuroimaging has been widely applied in psychiatry, much of the exuberance in decades past has been tempered by failed replications and a lack of definitive evidence to support the utility of imaging to inform clinical decisions. There are multiple promising ways forward to demonstrate the relevance of neuroimaging for psychiatry at the individual patient level. Ultra-high field magnetic resonance imaging is developing as a sensitive measure of neurometabolic processes of particular relevance that holds promise as a new way to characterize patient abnormalities as well as variability in response to treatment. Neuroimaging may also be particularly suited to the science of brain stimulation interventions in psychiatry given that imaging can both inform brain targeting as well as measure changes in brain circuit communication as a function of how effectively interventions improve symptoms. We argue that a greater focus on individual patient imaging data will pave the way to stronger relevance to clinical care in psychiatry. We also stress the importance of using imaging in symptom-relevant experimental manipulations and how relevance will be best demonstrated by pairing imaging with differential treatment prediction and outcome measurement. The priorities for using brain imaging to inform psychiatry may be shifting, which compels the field to solidify clinical relevance for individual patients over exploratory associations and biomarkers that ultimately fail to replicate.

Brain Imaging in Routine Psychiatric Practice.

Technologies in the 21st century provide increasingly detailed and accurate maps of brain structure and function. So why don't psychiatrists order brain imaging on all our patients? Here we briefly review major neuroimaging methods and some of their findings in psychiatry. As clinicians and neuroimaging researchers, we are eager to bring brain imaging into daily clinical practice. However, to be clinically useful, any test in medicine must demonstrate adequate test statistics, and show proven benefits that outweigh its risks and costs. In 2024, beyond certain limited circumstances, we have no imaging tests that can meet those standards to provide diagnosis or guide treatment. This cold fact explains why for most psychiatric patients, neuroimaging is not currently recommended by professional organizations or the National Institute of Mental Health.

Editorial: Prevention is the best cure - or is it? A cautionary tale.

In large parts of the Western world prevention is considered a necessary, core component of successful youth care practice. Yet, mental health problems in young people do not appear to have declined over the past decades. How to explain this paradox? In this editorial for the Journal of Child Psychology and Psychiatry, several possible explanations are explored, one of which centers around how prevention is being operationalized-primarily, nowadays, as a screen-and-resolve 'troubleshooting' approach, rather than as an approach that supports the development of good health, competence, and resilience.

Structural Racism and Lessons Not Heard: A Rapid Review of the Telepsychiatry Literature During the COVID-19 Public Health Emergency.

Objective: To assess the extent to which articles examining telepsychiatry after the start of the COVID-19 pandemic provided racial and sociodemographic characteristics for people receiving audiovisual (video) versus audio-only telepsychiatry.Data Sources, Study Selection, and Data Extraction: We employed the keyword telepsychiatry and screened all peer-reviewed articles in PubMed published from March 1, 2020, until November 23, 2022, prior to the federal government's announcement of the impending end to the COVID-19 public health emergency. We retrieved and reviewed the full-text articles of 553 results for potential inclusion, of which 266 were original research articles.Results: We found that 106 of 553 articles had any mention of differences between audio-only and audiovisual telepsychiatry. Twenty-nine of 553 articles described potential socioeconomic differences in the distribution of people receiving audio-only versus audiovisual telepsychiatry, and 20 of 553 described potential racial/ethnic differences. Among research articles, most (213/266) did not differentiate between videoconferencing and audio-only/telephone-based telehealth services. A total of 4 research articles provided racial and sociodemographic characteristics of individuals who received audio-only versus audiovisual telepsychiatry services during the COVID-19 pandemic, all of which were conducted in relatively small regional samples that could not be generalized to the US as a whole.Conclusions: Overall, this analysis underscores that empirical data are lacking on racial and sociodemographic distribution of audio-only versus audiovisual telepsychiatry services since the COVID-19 pandemic.Prim Care Companion CNS Disord 2023;25(6):23r03563. Author affiliations are listed at the end of this article.

Alcohol Use Disorder in a University General Hospital: a Four-Year Observational Study of Liaison Psychiatry.

BACKGROUND: Alcohol use disorder is insufficiently treated because it is poorly detected. Improved screening in general hospitals is a major issue in treatment organisation. SUBJECT AND METHOD: Through a retrospective exploratory study based on a review of medical records over four years (2016-19) before the COVID pandemic, we recorded the number of liaison psychiatric referrals for alcohol use disorder and identified two indicators: follow-up care implemented and survival at three years. RESULTS: Subject to the limitations of a retrospective review of medical records, we observed that 136 of 859 referrals concerned an alcohol use disorder. At three years, 25% (34 patients) had died. The causes of death were analysed, which revealed that 65% were directly attributable to alcohol consumption. Ongoing follow-up care was documented for only 17% (15 patients) of the 136 referred patients. Twelve patients who were followed up (80%) were in remission at one year. CONCLUSION: Although the results showed the efficacy of psychiatric follow-up care, the low recruitment of patients receiving regular follow-up care confirmed the problem of access to treatment. Our results support the need for screening and earlier intervention in general hospitals by raising awareness and training all doctors, but also by reflecting on new methods of liaison psychiatry treatment.

Telepsychiatry: The future is already present.

This review paper analyzes the state of knowledge on Telepsychiatry (TP) after the crisis caused by COVID and the resulting need to use new modalities of care. Six essential aspects of TP are addressed: patient's and mental health staff satisfaction, diagnostic reliability, effectiveness of TP interventions, cost-effectiveness in terms of opportunity cost (or efficiency), legal aspects inherent to confidentiality and privacy in particular and the attitude of professionals toward TP. Satisfaction with TP is acceptable among both patients and professionals, the latter being the most reluctant. Diagnostic reliability has been demonstrated, but requires further studies to confirm this reliability in different diagnoses and healthcare settings. The efficacy of TP treatments is not inferior to face-to-face care, as has been proven in specific psychotherapies. Finally, it should be noted that the attitude of the psychiatrist is the most decisive element that limits or facilitates the implementation of TP.

Diagnosing psychiatric disorders from history of present illness using a large-scale linguistic model.

AIM: Recent advances in natural language processing models are expected to provide diagnostic assistance in psychiatry from the history of present illness (HPI). However, existing studies have been limited, with the target diseases including only major diseases, small sample sizes, or no comparison with diagnoses made by psychiatrists to ensure accuracy. Therefore, we formulated an accurate diagnostic model that covers all psychiatric disorders. METHODS: HPIs and diagnoses were extracted from discharge summaries of 2,642 cases at the Nara Medical University Hospital, Japan, from 21 May 2007, to 31 May 31 2021. The diagnoses were classified into 11 classes according to the code from ICD-10 Chapter V. Using UTH-BERT pre-trained on the electronic medical records of the University of Tokyo Hospital, Japan, we predicted the main diagnoses at discharge based on HPIs and compared the concordance rate with the results of psychiatrists. The psychiatrists were divided into two groups: semi-Designated with 3-4 years of experience and Residents with only 2 months of experience. RESULTS: The model's match rate was 74.3%, compared to 71.5% for the semi-Designated psychiatrists and 69.4% for the Residents. If the cases were limited to those correctly answered by the semi-Designated group, the model and the Residents performed at 84.9% and 83.3%, respectively. CONCLUSION: We demonstrated that the model matched the diagnosis predicted from the HPI with a high probability to the principal diagnosis at discharge. Hence, the model can provide diagnostic suggestions in actual clinical practice.

A Review of Telepsychiatry for Pediatric Patients in the Emergency Setting.

PURPOSE OF REVIEW: The purpose of this review is to summarize factors contributing to the current state of pediatric mental health access in ED settings and synthesize the existing literature on the use of telepsychiatry to extend access to care, with particular focus on feasibility and sustainability. RECENT FINDINGS: Children are presenting to emergency departments (EDs) with mental health concerns at an increasing rate, while ED capacity to treat psychiatric needs in children remains insufficient. This growing problem is compounded by decreased access to outpatient care and inpatient psychiatric beds, resulting in exorbitantly long waiting times, or "boarding," of children in crisis. Telepsychiatry has emerged as a strategy to decrease boarding of pediatric patients in ED settings by utilizing remote psychiatric professionals to provide consultation and assessment. Telepsychiatry in ED settings is an effective strategy to increase access to care and decrease length of stay for pediatric patients.

Machine Learning and Pharmacogenomics at the Time of Precision Psychiatry.

Traditional medicine and biomedical sciences are reaching a turning point because of the constantly growing impact and volume of Big Data. Machine Learning (ML) techniques and related algorithms play a central role as diagnostic, prognostic, and decision-making tools in this field. Another promising area becoming part of everyday clinical practice is personalized therapy and pharmacogenomics. Applying ML to pharmacogenomics opens new frontiers to tailored therapeutical strategies to help clinicians choose drugs with the best response and fewer side effects, operating with genetic information and combining it with the clinical profile. This systematic review aims to draw up the state-of-the-art ML applied to pharmacogenomics in psychiatry. Our research yielded fourteen papers; most were published in the last three years. The sample comprises 9,180 patients diagnosed with mood disorders, psychoses, or autism spectrum disorders. Prediction of drug response and prediction of side effects are the most frequently considered domains with the supervised ML technique, which first requires training and then testing. The random forest is the most used algorithm; it comprises several decision trees, reduces the training set's overfitting, and makes precise predictions. ML proved effective and reliable, especially when genetic and biodemographic information were integrated into the algorithm. Even though ML and pharmacogenomics are not part of everyday clinical practice yet, they will gain a unique role in the next future in improving personalized treatments in psychiatry.

THE CURIOUS CASE OF 'PSYCHO-OPHTHALMOLOGY': A NARRATIVE REVIEW OF OPHTHALMOLOGICAL ASPECTS OF PSYCHIATRIC DISORDERS.

Consultation Liaison Psychiatry (CLP) deals with the interface shared between psychiatry and various other disciplines of medicine. The interface shared by psychiatry and ophthalmology is among the lesser discussed ones in the field of CLP, despite the fact that it holds clinical relevance in the evaluation, management and outcomes of both psychiatric and ophthalmological disorders. This narrative review focusses on the ophthalmological aspects of psychiatric disorders, with respect to their manifestations, assessment, and management. Psychiatric disorders, including schizophrenia, affective disorders, 'functional' disorders, and substance use disorders, have numerous ophthalmic manifestations, which can have clinical implications for the patients. Even the psychotropic drugs given for psychiatric disorders can lead to side effects affecting the eye, but these are among the lesser-discussed side effects. Some psychiatric disorders can be investigated using various ophthalmic functions, the assessments ranging from simple physical examination to the use of instruments like a fundoscope, which can be useful for a psychiatrist in their routine practice. Lastly, eye functions can also be used in the treatment of psychiatric conditions, as is seen in eye movement desensitization and reprocessing. This review reiterates the fact that more attention needs to be given to the field of 'psycho-ophthalmology', which holds great promise in the coming days.

Precision Neuroimaging for Localization-Related Psychiatry.

This Viewpoint describes how precision functional mapping may be helpful for associating neuroanatomical regions with specific psychiatric disorders.

Barriers and solutions to the adoption of translational tools for computational psychiatry.

Computational psychiatry is a field aimed at developing formal models of information processing in the human brain, and how alterations in this processing can lead to clinical phenomena. There has been significant progress in the development of tasks and how to model them, presenting an opportunity to incorporate computational psychiatry methodologies into large- scale research projects or into clinical practice. In this viewpoint, we explore some of the barriers to incorporation of computational psychiatry tasks and models into wider mainstream research directions. These barriers include the time required for participants to complete tasks, test-retest reliability, limited ecological validity, as well as practical concerns, such as lack of computational expertise and the expense and large sample sizes traditionally required to validate tasks and models. We then discuss solutions, such as the redesigning of tasks with a view toward feasibility, and the integration of tasks into more ecologically valid and standardized game platforms that can be more easily disseminated. Finally, we provide an example of how one task, the conditioned hallucinations task, might be translated into such a game. It is our hope that interest in the creation of more accessible and feasible computational tasks will help computational methods make more positive impacts on research as well as, eventually, clinical practice.

[The physician's perspective on clinical assessment skills by nurses in psychiatry: A case study]. / Die Sichtweise des ärztlichen Dienstes hinsichtlich des klinischen Assessments durch Pflegefachpersonen in der Psychiatrie.

The physician's perspective on clinical assessment skills by nurses in psychiatry: A case study Abstract: Background: People with a mental and physical illness receive less good somatic care compared to the general population. Patients in psychiatry receive better medical care when nurses have in-depth medical expertise. Therefore, in a psychiatric institution in Switzerland in 2017, the Clinical Assessment and Decision Making (CADM) by nurses was implemented. Aim: The aim of the study was to investigate how physicians and senior psychologists experience the implementation of CADM by nurses in order to derive recommendations on how to optimize the collaboration and promote a sustainable establishment. Methods: An embedded single case study was used, and the data analysis was based on grounded theory strategies by Charmaz. Semi-structured expert interviews (n = 11) and open unstructured observations were conducted in a psychiatric institution in Switzerland. Results: The results showed nine relevant aspects regarding collaboration and CADM by nurses: "Strengths", "Weaknesses", "Risks", "Opportunities", "Expectations", "Challenges", "Benefits", "Competencies of CADM nurses" and "Wishes for the future". Conclusions: The physicians and senior psychologists considered the CADM by nurses as an added value for the interprofessional team and for the patients. Lack of clarity regarding the scope of responsibilities, role definitions and possible applications made the implementation of CADM difficult.

Proactive use of QI methodology in consultation-liaison psychiatry to support the opening of a new COVID+ behavioral health inpatient unit during the omicron surge.

Inpatient consultation-liaison (CL) psychiatry teams routinely facilitate the transfer of medically stable patients in behavioral health crisis from the general hospital to inpatient psychiatric units. The COVID-19 pandemic had a significant impact on this process when inpatient psychiatric units were unable to provide care for patients with asymptomatic COVID-19 infection because of infection control concerns in units unable to accommodate isolation precautions. Similar to other disrupted hospital workflows, these clinical handoffs became more complicated by requiring COVID exposed or COVID+ patients in the midst of behavioral health crisis to quarantine or isolate on general hospital units if not otherwise stable for discharge to the community. To better respond to the growing number of patients isolating in the general hospital during the 2022 Omicron surge, we used quality improvement (QI) methodology to illustrate the need to create a COVID+ unit in the inpatient psychiatric hospital to care for the growing cohort of COVID+ patients in psychiatric crisis who were otherwise unable to access traditional psychiatric hospital care because of their isolation status.

Current Approaches in Computational Psychiatry for the Data-Driven Identification of Brain-Based Subtypes.

The ability of our current psychiatric nosology to accurately delineate clinical populations and inform effective treatment plans has reached a critical point with only moderately successful interventions and high relapse rates. These challenges continue to motivate the search for approaches to better stratify clinical populations into more homogeneous delineations, to better inform diagnosis and disease evaluation, and prescribe and develop more precise treatment plans. The promise of brain-based subtyping based on neuroimaging data is that finding subgroups of individuals with a common biological signature will facilitate the development of biologically grounded, targeted treatments. This review provides a snapshot of the current state of the field in empirical brain-based subtyping studies in child, adolescent, and adult psychiatric populations published between 2019 and March 2022. We found that there is vast methodological exploration and a surprising number of new methods being created for the specific purpose of brain-based subtyping. However, this methodological exploration and advancement is not being met with rigorous validation approaches that assess both reproducibility and clinical utility of the discovered brain-based subtypes. We also found evidence for a collaboration crisis, in which methodological exploration and advancements are not clearly grounded in clinical goals. We propose several steps that we believe are crucial to address these shortcomings in the field. We conclude, and agree with the authors of the reviewed studies, that the discovery of biologically grounded subtypes would be a significant advancement for treatment development in psychiatry.

Evaluation of Telepsychiatry Services Implementation in Medical and Psychiatric Inpatient Settings: A Mixed-Methods Study.

Introduction: Telepsychiatry consultation for rural providers may help address local staffing needs while ensuring timely and appropriate care from behavioral health experts. The purpose of this study was to assess the implementation of a telepsychiatry consultation service within medical and psychiatry inpatient units of hospitals serving predominantly rural areas. Methods: A mixed-methods study with qualitative interviews of site personnel and quantitative assessment of electronic health record data was conducted across 6 facilities in 3 U.S. states between June 2019 and May 2021. We interviewed 15 health care professionals 6 months after telepsychiatry was implemented, and we identified emerging themes related to the inpatient telepsychiatry service implementation and utilization through an inductive qualitative analysis approach. We then applied the themes emerging from this study to existing implementation science theoretical frameworks. Results: Telepsychiatry consultation was utilized for 437 medical inpatient cases and 531 psychiatric inpatient units. Average encounters by site ranged from 1 to 20 per month. The three main domains from the qualitative assessment included the impact on the care process (the partnership between inpatient units and the telehealth hub, and logistical dynamics), the care provider (resource availability in inpatient units and changes in inpatient units' capability), and the patient (impact on patient safety and care). Discussion: Implementation of a telepsychiatry service in the inpatient setting holds the promise of being beneficial to the patient, local hospital, and the rural community. In this study, we found that implementing this telepsychiatry service improved the clinical care processes, while addressing both the providers' and patients' needs.