The Anomalous Effect of COVID-19 Pandemic Restrictions on the Duration of Untreated Psychosis (DUP).

We investigated the impact of COVID-19 restrictions on the duration of untreated psychosis (DUP). First-episode psychosis admissions (n=101) to STEP Clinic in Connecticut showed DUP reduction (p=.0015) in the pandemic, with the median reducing from 208 days during the pre-pandemic to 56 days in the early pandemic period and subsequently increasing to 154 days (p=.0281). Time from psychosis onset to anti-psychotic prescription decreased significantly in the pandemic (p=.0183), with the median falling from 117 to 35 days. This cohort study demonstrates an association between greater pandemic restrictions and marked DUP reduction and provides insights for future early detection efforts.

Over 30 years of STEP: The Pittsburgh experience with first-episode psychosis.

AIMS: For over 30 years, combined research and treatment settings in the US have been critical to conceptualizing care for first-episode psychosis (FEP). Here we describe an early example of such a context, the Services for the Treatment of Early Psychosis (STEP) clinic, which is affiliated with the University of Pittsburgh. METHODS: We describe STEP's historical roots and establishment in the early 1990s; STEP's research and treatment contributions, alongside its growth and ongoing leadership. RESULTS: Research-based clinics, like STEP, preceded and helped pave the way for the Recovery After an Initial Schizophrenia Episode project in the US and the ensuing Coordinated Specialty Care (CSC) approach, now widely adopted in the US. Early clinic-based research at STEP helped establish protocols for psychopharmacology, the relevance of effective early treatment, including psychosocial approaches, and highlighted disparities in treatment outcomes across race/ethnicity. Multidisciplinary collaboration and dialogue with consumers contributed to early treatment, combining psychosocial and pharmacological approaches. STEP adopted CSC and is situated within a bi-state Learning Health System. STEP has retained a relatively unique 5-year treatment model and exists within continuum of care ideally suited to studying psychotic illness and treatment outcomes. CONCLUSIONS: STEP remains the largest academic FEP clinic in Pennsylvania. Academic FEP clinics like STEP will have a critical role within Learning Health Systems nationally to model participatory approaches, sustain early intervention treatment quality and ongoing treatment developments.

Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis.

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals.

Posterior Cerebellar Resting-State Functional Hypoconnectivity: A Neural Marker of Schizophrenia Across Different Stages of Treatment Response.

BACKGROUND: Identifying stable and consistent resting-state functional connectivity patterns across illness trajectories has the potential to be considered fundamental to the pathophysiology of schizophrenia. We aimed to identify consistent resting-state functional connectivity patterns across heterogeneous schizophrenia groups defined based on treatment response. METHODS: In phase 1, we used a cross-sectional case-control design to characterize and compare stable independent component networks from resting-state functional magnetic resonance imaging scans of antipsychotic-naïve participants with first-episode schizophrenia (n = 54) and healthy participants (n = 43); we also examined associations with symptoms, cognition, and disability. In phase 2, we examined the stability (and replicability) of our phase 1 results in 4 groups (N = 105) representing a cross-sequential gradation of schizophrenia based on treatment response: risperidone responders, clozapine responders, clozapine nonresponders, and clozapine nonresponders following electroconvulsive therapy. Hypothesis-free whole-brain within- and between-network connectivity were examined. RESULTS: Phase 1 identified posterior and anterior cerebellar hypoconnectivity and limbic hyperconnectivity in schizophrenia at a familywise error rate-corrected cluster significance threshold of p < .01. These network aberrations had unique associations with positive symptoms, cognition, and disability. During phase 2, we replicated the phase 1 results while comparing each of the 4 schizophrenia groups to the healthy participants. The participants in 2 longitudinal subdatasets did not demonstrate a significant change in these network aberrations following risperidone or electroconvulsive therapy. Posterior cerebellar hypoconnectivity (with thalamus and cingulate) emerged as the most consistent finding; it was replicated across different stages of treatment response (Cohen's d range -0.95 to -1.44), reproduced using different preprocessing techniques, and not confounded by educational attainment. CONCLUSIONS: Posterior cerebellar-thalamo-cingulate hypoconnectivity is a consistent and stable state-independent neural marker of schizophrenia.

First episode psychosis caregiver perspectives on motivational interviewing for loved ones training: A qualitative study.

BACKGROUND: Past research has found that family involvement in psychosis treatment leads to better patient outcomes. Thus, caregiver communication skills training can be a viable approach to reducing caregiver stress and increasing self-efficacy and communication. AIM: The purpose of this qualitative study was to describe family caregivers' perceptions of changes in themselves and their family member with psychosis following their participation in Motivational Interviewing in Loved Ones (MILO), a brief four to five-hour psychoeducational intervention for caregivers. METHODS: Sixty-three participants in the MILO trials provided written qualitative responses to the prompt, "Since learning the ideas and techniques in this course, what is the most significant change you noticed in yourself, your family, or your relationships?" Responses were collected immediately following MILO participation and 12 weeks later. Qualitative themes were identified through an iterative consensus process. RESULTS: Most participants reported positive changes in multiple domains of their lives. Major themes included: (1) Changes in Self, (2) Changes in Relationships, (3) Changes in Mindset, (4) Use of MILO Skills, and (5) Challenges. CONCLUSION: Qualitative results support and add context to the previously reported quantitative results from this study. MILO is a promising family intervention that positively influenced family environment and communication in pilot trials. Adaptations of MILO for families outside of a highly educated North American context should be considered.

Symptom contributors to quality of life in schizophrenia: Exploratory factor and network analyses.

Individuals with schizophrenia and other associated disorders experience significant disturbance to their quality of life (QoL) due to a multitude of co-occurring symptoms. Popular evidence-based practices (EBPs) devote significant effort to reduce positive symptomatology in order to prevent relapse, while emerging research posits that other symptoms (cognitive deficits, negative and affective symptoms) are more indicative of QoL disturbance. This study sought to examine the impact of symptom constructs on QoL and attempt to infer directionality of influence via network analysis. A total of 102 recovery phase adult outpatients with schizophrenia spectrum disorders were assessed on positive, negative, and affective symptomatology, in addition to QoL and cognitive abilities. Exploratory factor analysis and network analysis were performed to identify associations and infer directed influence between symptom constructs, and a directed acyclic graph was constructed to observe associations between symptom domains and QoL. Factor analysis results indicated that individual measures align with their respective symptom constructs. Strong factor correlations were found between QoL and the negative and affective symptom constructs, with weaker associations found between positive symptoms and cognition. Visualization of the network structure illustrated QoL as the central cluster of the network, and examination of the weighted edges found the strongest connectivity between QoL, negative symptomatology, and affective symptoms. More severe negative and affective symptoms were most directly linked with poorer QoL and may prove to be integral in attaining positive outcomes in schizophrenia treatment. Incorporation of psychosocial treatments in addition to pharmacotherapy may prove effective in targeting negative and affective symptoms.

Role of Early Psychosis Detection in the Relationship Between Personal Income and Duration of Untreated Psychosis.

OBJECTIVE: Prolonged duration of untreated psychosis (DUP) predicts poor outcomes of first-episode psychosis (FEP) and is often linked to low socioeconomic status (SES). The authors sought to determine whether patients' personal income, used as a proxy for SES, predicts length of DUP and whether personal income influences the effect of an early psychosis detection campaign-called Mindmap-on DUP reduction. METHODS: Data were drawn from a trial that compared the effectiveness of early detection in reducing DUP across the catchment area of an FEP service (N=147 participants) compared with an FEP service with no early detection (N=75 participants). Hierarchical regression was used to determine whether personal income predicted DUP when analyses controlled for effects of age, race, and exposure to early psychosis detection. A group × personal income interaction term was used to assess whether the DUP difference between the early detection and control groups differed by personal income. RESULTS: Lower personal income was significantly associated with younger age, fewer years of education, Black race, and longer DUP. Personal income predicted DUP beyond the effects of age, race, and early psychosis detection. Although Mindmap significantly reduced DUP across all income levels, this effect was smaller for participants reporting lower personal income. CONCLUSIONS: Patients' personal income may be an important indicator of disparity in access to specialty care clinics across a wide range of settings. Early detection efforts should measure and target personal income and other SES indicators to improve access for all individuals who may benefit from FEP services.

Know thyself (Jnana Yoga): Psychotherapeutic insights from the east.

Humans have asked themselves the question "who am I" from ancient times. Vedic, upanishadic and buddhist philosophers have pointed out over millennia the illusive nature of the individual self, and posit either a no-self, or a universal Self. Vedantic scholars also posit the illusory nature of the universe (Maya) and suggest that the only reality is the knower (Brahman), a view resonating with modern concepts in quantum theory. On the other hand, western philosophers, notably influenced by the Cartesian dualism, have pursued an individualist view of the self. Recent psychological literature is convergent with eastern views and emphasizes the importance of understanding the self, metacognition and mindful practices to understand the mind and its afflictions. Several recent western psychotherapeutic models resonate with, and may have been motivated, at least in part, by ancient eastern philosophy and spiritual practices. More work is needed to develop and implement psychotherapeutic approaches using eastern insights, and to empirically test their effectiveness.

Assessing social cognition in patients with schizophrenia and healthy controls using the reading the mind in the eyes test (RMET): a systematic review and meta-regression.

The reading the mind in the eyes test (RMET) - which assesses the theory of mind component of social cognition - is often used to compare social cognition between patients with schizophrenia and healthy controls. There is, however, no systematic review integrating the results of these studies. We identified 198 studies published before July 2020 that administered RMET to patients with schizophrenia or healthy controls from three English-language and two Chinese-language databases. These studies included 41 separate samples of patients with schizophrenia (total n = 1836) and 197 separate samples of healthy controls (total n = 23 675). The pooled RMET score was 19.76 (95% CI 18.91-20.60) in patients and 25.53 (95% CI 25.19-25.87) in controls (z = 12.41, p < 0.001). After excluding small-sample outlier studies, this difference in RMET performance was greater in studies using non-English v. English versions of RMET (Chi [Q] = 8.54, p < 0.001). Meta-regression analyses found a negative association of age with RMET score and a positive association of years of schooling with RMET score in both patients and controls. A secondary meta-analysis using a spline construction of 180 healthy control samples identified a non-monotonic relationship between age and RMET score - RMET scores increased with age before 31 and decreased with age after 31. These results indicate that patients with schizophrenia have substantial deficits in theory of mind compared with healthy controls, supporting the construct validity of RMET as a measure of social cognition. The different results for English versus non-English versions of RMET and the non-monotonic relationship between age and RMET score highlight the importance of the language of administration of RMET and the possibility that the relationship of aging with theory of mind is different from the relationship of aging with other types of cognitive functioning.

Medical and Psychiatric Care Preceding the First Psychotic Disorder Diagnosis.

BACKGROUND: Individuals with psychotic symptoms experience substantial morbidity and have shortened life expectancies; early treatment may mitigate the worst effects. Understanding care preceding a first psychotic disorder diagnosis is critical to inform early detection and intervention. STUDY DESIGN: In this observational cohort study using comprehensive information from the Massachusetts All-Payer Claims Database, we identified the first psychotic disorder diagnosis in 2016, excluding those with historical psychotic disorder diagnoses in the prior 48 months among those continuous enrollment data. We reviewed visits, medications, and hospitalizations 2012-2016. We used logistic regression to examine characteristics associated with pre-diagnosis antipsychotic use. STUDY RESULTS: There were 2505 individuals aged 15-35 years (146 per 100 000 similarly aged individuals in the database) with a new psychotic disorder diagnosis in 2016. Most (97%) had at least one outpatient visit in the preceding 48 months; 89% had a prior mental health diagnosis unrelated to psychosis (eg, anxiety [60%], depression [60%]). Many received psychotropic medications (77%), including antipsychotic medications (46%), and 68% had a visit for injury or trauma during the preceding 48 months. Characteristics associated with filling an antipsychotic medication before the psychotic disorder diagnosis included male sex and Medicaid insurance at psychosis diagnosis. CONCLUSIONS: In this insured population of Massachusetts residents with a new psychotic disorder diagnosis, nearly all had some healthcare utilization, visits for injury or trauma were common, and nearly half filled an antipsychotic medication in the preceding 48 months. These patterns of care could represent either pre-disease signals, delays, or both in receiving a formal diagnosis.

Development of the PSYCHS: Positive SYmptoms and Diagnostic Criteria for the CAARMS Harmonized with the SIPS.

AIM: To harmonize two ascertainment and severity rating instruments commonly used for the clinical high risk syndrome for psychosis (CHR-P): the Structured Interview for Psychosis-risk Syndromes (SIPS) and the Comprehensive Assessment of At-Risk Mental States (CAARMS). METHODS: The initial workshop is described in the companion report from Addington et al. After the workshop, lead experts for each instrument continued harmonizing attenuated positive symptoms and criteria for psychosis and CHR-P through an intensive series of joint videoconferences. RESULTS: Full harmonization was achieved for attenuated positive symptom ratings and psychosis criteria, and modest harmonization for CHR-P criteria. The semi-structured interview, named Positive SYmptoms and Diagnostic Criteria for the CAARMS Harmonized with the SIPS (PSYCHS), generates CHR-P criteria and severity scores for both CAARMS and SIPS. CONCLUSIONS: Using the PSYCHS for CHR-P ascertainment, conversion determination, and attenuated positive symptom severity rating will help in comparing findings across studies and in meta-analyses.

Neuroscience in pictures:1. History of psychiatric neuroscience.

Our understanding of the brain basis of mental illness has evolved over three and half millennia. Early insights into the role of the brain in relation to the mind faded during the middle ages as mental illness became the province of religion, spirituality, and philosophy. Psychiatry became a medical discipline again as medical and scientific thinking evolved during the 17th century. However, progress in neuroscience and astute clinical observations were punctuated by setbacks due to lingering dualism, reductionistic thinking, and dogma. Accelerating neuroscience discoveries and methodological innovations are beginning to bring neuroscience and psychiatry closer than ever as we begin the 21st century, This pictorial article seeks to briefly highlight this journey for an early trainee in psychiatry and related professions in mind.

Double dissociation between P300 components and task switch error type in healthy but not psychosis participants.

Event-related potentials (ERPs) during oddball tasks and the behavioral performance on the Penn Conditional Exclusion Task (PCET) measure context-appropriate responding: P300 ERPs to oddball targets reflect detection of input changes and context updating in working memory, and PCET performance indexes detection, adherence, and maintenance of mental set changes. More specifically, PCET variables quantify cognitive functions including inductive reasoning (set 1 completion), mental flexibility (perseverative errors), and working memory maintenance (regressive errors). Past research showed that both P300 ERPs and PCET performance are disrupted in psychosis. This study probed the possible neural correlates of 3 PCET abnormalities that occur in participants with psychosis via the overlapping cognitive demands of the two study paradigms. In a two-tiered analysis, psychosis (n = 492) and healthy participants (n = 244) were first divided based on completion of set 1 - which measures subjects' ability to use inductive reasoning to arrive at the correct set. Results showed that participants who failed set 1 produced lower parietal P300, independent of clinical status. In the second tier of analysis, a double dissociation was found among healthy set 1 completers: frontal P300 amplitudes were negatively associated with perseverative errors, and parietal P300 was negatively associated with regressive errors. In contrast, psychosis participants showed global P300 reductions regardless of PCET performance. From this we conclude that in psychosis, overall activations evoked by the oddball task are reduced while the cognitive functions required by PCET are still somewhat supported, showing some level of independence or compensatory physiology in psychosis between neural activities underlying the two tasks.

Potential Role of Smartphone Technology in Advancing Work on Neurological Soft Signs with a Focus on Schizophrenia.

LEARNING OBJECTIVE AFTER PARTICIPATING IN THIS CME ACTIVITY, THE PSYCHIATRIST SHOULD BE BETTER ABLE TO: • Outline and Identify potential benefits of using neurological soft signs (NSS) as biomarkers of schizophrenia. ABSTRACT: Since the late 1960s, NSS have been a focus of study across psychiatric illnesses, including depression, bipolar disorder, and schizophrenia in particular. Utilizing these subtle neurological impairments as biomarkers of illness has numerous benefits; NSS offer a direct connection between clinical presentation and neurological functioning, and assessments are cost-effective. However, incongruent measurement scales, confounding variables, and rating system subjectivity have hindered the advancement and scalability of NSS research and clinical implementation. This article provides a brief overview of the literature on NSS as related to schizophrenia, and proposes utilizing smartphone sensing technology to create standardized NSS assessments with objective scoring. Incorporating digital phenotyping into NSS assessment offers the potential to make measurement more scalable, accessible, and directly comparable across locations, cultures, and demographics. We conducted a narrative search in PubMed and APA PsycInfo using the following keywords: neurological soft signs, schizophrenia spectrum disorders, and psychotic illnesses. No date limitations were used. There is no other direct work on NSS and new smartphone methods like digital phenotyping; though, there is related work in neurology. Harnessing advances in smartphone technology could provide greater insight into and further our understanding of specific aspects of the NSS field. For instance, it could help us distinguish trait vs. state markers and better understand how distinct groups of signs may reflect different aspects of psychiatric illness and neurological impairment. In addition, such technology can help advance research on the capabilities of NSS as an effective diagnostic tool.

Clinical characterization and differentiation of B-SNIP psychosis Biotypes: Algorithmic Diagnostics for Efficient Prescription of Treatments (ADEPT)-1.

Clinically defined psychosis diagnoses are neurobiologically heterogeneous. The B-SNIP consortium identified and validated more neurobiologically homogeneous psychosis Biotypes using an extensive battery of neurocognitive and psychophysiological laboratory measures. However, typically the first step in any diagnostic evaluation is the clinical interview. In this project, we evaluated if psychosis Biotypes have clinical characteristics that can support their differentiation in addition to obtaining laboratory testing. Clinical interview data from 1907 individuals with a psychosis Biotype were used to create a diagnostic algorithm. The features were 58 ratings from standard clinical scales. Extremely randomized tree algorithms were used to evaluate sensitivity, specificity, and overall classification success. Biotype classification accuracy peaked at 91 % with the use of 57 items on average. A reduced feature set of 28 items, though, also showed 81 % classification accuracy. Using this reduced item set, we found that only 10-11 items achieved a one-vs-all (Biotype-1 or not, Biotype-2 or not, Biotype-3 or not) area under the sensitivity-specificity curve of .78 to .81. The top clinical characteristics for differentiating psychosis Biotypes, in order of importance, were (i) difficulty in abstract thinking, (ii) multiple indicators of social functioning, (iii) conceptual disorganization, (iv) severity of hallucinations, (v) stereotyped thinking, (vi) suspiciousness, (vii) unusual thought content, (viii) lack of spontaneous speech, and (ix) severity of delusions. These features were remarkably different from those that differentiated DSM psychosis diagnoses. This low-burden adaptive algorithm achieved reasonable classification accuracy and will support Biotype-specific etiological and treatment investigations even in under-resourced clinical and research environments.

Supervised machine learning classification of psychosis biotypes based on brain structure: findings from the Bipolar-Schizophrenia network for intermediate phenotypes (B-SNIP).

Traditional diagnostic formulations of psychotic disorders have low correspondence with underlying disease neurobiology. This has led to a growing interest in using brain-based biomarkers to capture biologically-informed psychosis constructs. Building upon our prior work on the B-SNIP Psychosis Biotypes, we aimed to examine whether structural MRI (an independent biomarker not used in the Biotype development) can effectively classify the Biotypes. Whole brain voxel-wise grey matter density (GMD) maps from T1-weighted images were used to train and test (using repeated randomized train/test splits) binary L2-penalized logistic regression models to discriminate psychosis cases (n = 557) from healthy controls (CON, n = 251). A total of six models were evaluated across two psychosis categorization schemes: (i) three Biotypes (B1, B2, B3) and (ii) three DSM diagnoses (schizophrenia (SZ), schizoaffective (SAD) and bipolar (BD) disorders). Above-chance classification accuracies were observed in all Biotype (B1 = 0.70, B2 = 0.65, and B3 = 0.56) and diagnosis (SZ = 0.64, SAD = 0.64, and BD = 0.59) models. However, the only model that showed evidence of specificity was B1, i.e., the model was able to discriminate B1 vs. CON and did not misclassify other psychosis cases (B2 or B3) as B1 at rates above nominal chance. The GMD-based classifier evidence for B1 showed a negative association with an estimate of premorbid general intellectual ability, regardless of group membership, i.e. psychosis or CON. Our findings indicate that, complimentary to clinical diagnoses, the B-SNIP Psychosis Biotypes may offer a promising approach to capture specific aspects of psychosis neurobiology.