Diagnosis in psychiatry faces familiar challenges. Validity and utility remain elusive, and confusion regarding the fluid and arbitrary border between mental health and illness is increasing. The mainstream strategy has been conservative and iterative, retaining current nosology until something better emerges. However, this has led to stagnation. New conceptual frameworks are urgently required to catalyze a genuine paradigm shift.

We outline candidate strategies that could pave the way for such a paradigm shift. These include the Research Domain Criteria (RDoC), the Hierarchical Taxonomy of Psychopathology (HiTOP), and Clinical Staging, which all promote a blend of dimensional and categorical approaches.

These alternative still heuristic transdiagnostic models provide varying levels of clinical and research utility. RDoC was intended to provide a framework to reorient research beyond the constraints of DSM. HiTOP began as a nosology derived from statistical methods and is now pursuing clinical utility. Clinical Staging aims to both expand the scope and refine the utility of diagnosis by the inclusion of the dimension of timing. None is yet fit for purpose. Yet they are relatively complementary, and it may be possible for them to operate as an ecosystem. Time will tell whether they have the capacity singly or jointly to deliver a paradigm shift.

Several heuristic models have been developed that separately or synergistically build infrastructure to enable new transdiagnostic research to define the structure, development, and mechanisms of mental disorders, to guide treatment and better meet the needs of patients, policymakers, and society.

Pre-diagnostic stages of psychotic illnesses, including ‘clinical high risk’ (CHR), are marked by sleep disturbances. These sleep disturbances appear to represent a key aspect in the etiology and maintenance of psychotic disorders. We aimed to examine the relationship between self-reported sleep dysfunction and attenuated psychotic symptoms (APS) on a day-to-day basis.

Seventy-six CHR young people completed the Experience Sampling Methodology (ESM) component of the European Union Gene-Environment Interaction Study, collected through PsyMate® devices, prompting sleep and symptom questionnaires 10 times daily for 6 days. Bayesian multilevel mixed linear regression analyses were performed on time-variant ESM data using the brms package in R. We investigated the day-to-day associations between sleep and psychotic experiences bidirectionally on an item level. Sleep items included sleep onset latency, fragmentation, and quality. Psychosis items assessed a range of perceptual, cognitive, and bizarre thought content common in the CHR population.

Two of the seven psychosis variables were unidirectionally predicted by previous night's number of awakenings: every unit increase in number of nightly awakenings predicted a 0.27 and 0.28 unit increase in feeling unreal or paranoid the next day, respectively. No other sleep variables credibly predicted next-day psychotic symptoms or vice-versa.

In this study, the relationship between sleep disturbance and APS appears specific to the item in question. However, some APS, including perceptual disturbances, had low levels of endorsement amongst this sample. Nonetheless, these results provide evidence for a unidirectional relationship between sleep and some APS in this population.

The COVID-19 outbreak is a serious global public health issue with wide-ranging negative effects on people’s lives, which is reflected in steadily rising mental health problems. In order to appropriately respond to the increased occurrence of psychiatric illness, protect mental health and strengthen resilience it is necessary to include new technologies, such as extended reality (XR) or socially assistive robots (SAR) in not only psychiatric treatment but also in the prevention of psychiatric diseases. In this context, the use of new technologies offers innovative ways to strengthen resilience, self-efficacy and stress coping skills and plays an important role in improving psychological wellbeing.

Preliminary results from studies at the Clinical Department of Psychiatry and Psychotherapeutic Medicine in Graz, Austria, dealing with new technologies in psychiatry, show new options for psychiatric settings.

Project AMIGA: The aim of this study is to test the effectiveness of a cognitive training session, conducted with the SAR named Pepper. In this randomized controlled trial, the effectiveness of SAR on depressive symptoms and correlates is evaluated in a sample of 60 individuals with major depression. While the intervention group will receive cognitive training with the SAR Pepper, the control group will receive “treatment-as-usual” therapy with a common PC software. Participants will receive 30 minutes of training 2 times per week over a period of 3 weeks.

Project XRes4HEALTH: The aim of this study is to develop an XR resilience training to increase resilience and stress coping mechanisms in healthcare workers. A total of 40 people will be included. To test the effectiveness of the resilience training, 3 XR training sessions of 15 minutes each will be held. A pre-post measurement will test the effectiveness of the training on wellbeing and stress levels as well as the acceptance and satisfaction with the training.

Project AI-REFIT: The overall goal of this study is to explore key information to increase resilience in healthy individuals who are at increased risk for mental health problems. Through a usability study, the artificial intelligence-based prototype app of the resilience training will be tested for acceptance, usability, functionality, and efficiency. During the resilience training, participants are wearing a smartwatch which measures psychophysiological parameters. Conclusions about the success of the therapy can be drawn based on digital data acquisition.

New technologies including XR and SAR support classical psychiatric treatment in the topics of resilience and cognitive training as an add-on therapy in times of reduced availability of healthcare workers.

The rapid development of new technologies holds a lot of potential in the treatment of psychiatric disorders, which is why it is important to scientifically evaluate those innovative tools.

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