AIMS:Negative symptoms are a core component of schizophrenia, affecting up to 60% of individuals with the disorder. They are categorised into primary negative symptoms (PNS), which are intrinsic to the illness, and secondary negative symptoms, which arise from external factors such as depression or medication side effects. They can also be divided into diminished expression and amotivation/anhedonia subtypes. While inflammation has been implicated in schizophrenia and linked to negative symptoms, little is known about whether inflammatory profiles differ between negative symptom subtypes in individuals at Ultra-High Risk (UHR) for psychosis. METHODS:We conducted a secondary analysis of 147 UHR participants from the Staged Treatment in Early Psychosis (STEP) study to examine whether inflammatory markers (Alpha-2-Macroglobulin, IL-6, CRP, sICAM-1, sVCAM-1, and suPAR) differed across negative symptom subgroups, using multinomial and binomial logistic regression models adjusted for age, sex, smoking, and BMI. RESULTS:Overall, most inflammatory markers were not significantly associated with negative symptom subgroups. However, higher sICAM-1 levels were asscoiated with lower odds of primary negative symptoms compared with no negative symptoms. Additionally, younger age was associated with increased odds of PNS and amotivation, while smoking was associated with higher odds of secondary negative symptoms compared with no negative symptoms. DISCUSSION:These findings suggest that inflammation may not broadly distinguish negative symptom subtypes at the UHR stage, although sICAM-1 may play a role in early illness processes. Limitations include sample ascertainment, potential misclassification of negative symptoms, and the relatively small number of participants with PNS. Future studies with larger samples and longitudinal designs are needed to clarify whether inflammatory changes contribute to the emergence of specific negative symptom subtypes.

The Clinical High Risk (CHR) state for psychosis is consistently associated with widespread cortical thinning. However, the underlying mechanisms driving this neuroanatomical phenotype remain poorly understood. Here, we integrated the ENIGMA CHR Working Group's large pooled dataset (N = 1782 CHR, N = 1333 healthy controls) with an open-source PET molecular atlas to identify, for the first time, potential neurochemical drivers of cortical thinning associated with psychosis risk, transition, and its core symptoms. Using multilinear model analysis, we show that local chemoarchitecture significantly explains CT differences associated with CHR case-control status, the severity of negative symptoms, and future psychosis transition after excluding medication confounds. PET-based maps of dopamine, GABA, glutamate, serotonin, and norepinephrine consistently emerged as the strongest predictors of lower CT in CHR and psychosis transition (total dominance range: 62-69% and 58-87%, respectively), with contributions of monoamine systems being especially sensitive to medication exposure (8-23% change in dominance range). Negative symptom-associated cortical thinning was best explained by PET-based maps of dopamine, histamine, serotonin and opioid systems (total dominance range: 60-81%), with contributions of histamine being sensitive to medication exposure (9-19% change in dominance range). Combined, these results uniquely identify specific neurochemical systems - particularly monoaminergic, glutamatergic, and GABAergic pathways - as key molecular mechanisms associated with cortical thinning in people at high risk of developing psychosis.

AIM:This study assessed the feasibility of a stepped-care model for those at clinical high-risk for psychosis (CHRp) within a coordinated specialty care clinic in the United States. METHODS:Youth aged 12-30 completed a 12-month, three-step intervention where persistent or worsening symptoms received increasingly intensive treatment including Supportive Problem Solving, Cognitive Behavioural Case Management, and a Selective Serotonin Reuptake Inhibitor. RESULTS:Of 32 CHR youth admitted to the clinic over 18 months, 12 were eligible for the study, 10 consented (83.3% consent rate at 0.56 recruitment rate), eight participated, and five completed (62.5% completion rate). Reasons for ineligibility were mostly unrelated to the treatment, including disengagement before recruitment, pressing comorbid concerns that required other specialty care, and medication preferences. Those who completed treatment showed clinically significant improvements in social functioning, depression, and attenuated psychosis symptoms by 12-month follow-up, but sample size precluded statistical analysis. Three discontinued due to medication needs (more intensive care, perceived side effects). CONCLUSIONS:This small preliminary study supports larger scale trials of stepped-care interventions for CHRp in the US, but also illuminates key features of the US healthcare system that must shape implementation. The stepped-care intervention appeared tolerable and feasible in those who were eligible and engaged; clinical outcomes were promising. Comorbid treatment needs in this heterogenous population, including medication needs/preferences, and disengagement during referral to psychosis specialty care precluded participation for many. Future studies should evaluate larger samples, account for needs and preferences for medication, and place screening and early steps in general outpatient mental health services to evaluate real-world effectiveness.

Using the Cascade of Care framework, we explored the demographic and clinical characteristics of students at six stages in an early psychosis detection program at a college counseling center, with a focus on the transition between stages with the highest disengagement. We detailed and compared the demographic and clinical characteristics of those who (1) completed the Prodromal Questionnaire-Brief (PQ-B, N = 1588); (2) met the PQ-B cutoff score (n = 486); (3) were referred for secondary phone screening (n = 404); (4) completed secondary phone screening (n = 198); (5) completed a Coordinated Specialty Care (CSC) eligibility assessment (n = 51); and (6) were enrolled in CSC (n = 21). Education level and gender identity were associated with engagement at multiple stages of the early detection cascade. Graduate education level, transgender or gender diverse gender identity, alcohol use, and depressive symptoms predicted student follow-through with referral to secondary phone screenings.

OBJECTIVE:Time between the onset of psychosis and the start of treatment significantly influences outcomes. Rapid access to care is essential, yet barriers such as stigma, difficulties with navigating the mental health system, and financial constraints prolong this process. This mixed-methods study aimed to assess how these barriers affect participation in early psychosis services. METHODS:A directed content analysis of telephone log data was conducted from intake assessments at an early psychosis clinic. Stepwise logistic regression and analyses of variance were used to evaluate the impact of barriers on assessment completion and time from referral to assessment. RESULTS:Of 1,048 individuals screened for early psychosis services, 201 completed a telephone assessment. Individuals who dropped out had a higher proportion of barriers overall than did those who completed the assessment (p<0.01). Greater than 50% of interactions included at least one barrier, with logistical issues being the most common. Increased barriers were correlated with longer assessments and lower completion rates. Adults and Hispanic participants reported more barriers, compared with adolescents and non-Hispanic individuals, respectively. Significant contributors to nonengagement included unknown gender, public insurance, and various barriers. CONCLUSIONS:Identifiable barriers to intake assessment were frequently reported by clients and were associated with higher intake noncompletion and a longer assessment process. Efforts to address logistical barriers may represent an essential step in improving the linkage process and reducing the duration of untreated psychosis.

Recent neuroimaging studies and publicly disseminated analytic tools suggest that regional morphometric analyses covary for global thickness. We empirically demonstrated that this statistical approach severely underestimates regional thickness dysmorphology in psychiatric disorders. Study 1 included 90 healthy control participants, 51 participants at clinical high risk for psychosis, and 78 participants with early-illness schizophrenia. Study 2 included 56 healthy control participants, 83 participants with nonaffective psychosis, and 30 participants with affective psychosis. We examined global and regional thickness correlations, global thickness group differences, and regional thickness group differences with and without global thickness covariation. Global and regional thickness were strongly correlated across groups. Global thickness was lower in the schizophrenia spectrum groups than the other groups. Regional thickness deficits in schizophrenia spectrum groups were attenuated or eliminated with global thickness covariation. Eliminating the variation that regional thickness shares with global thickness eliminated disease-related effects. This statistical approach results in erroneous conclusions that regional thickness is normal in disorders like schizophrenia or clinical high risk syndrome.

Using data collected in routine care delivery to inform treatment is a key feature of a learning health system (LHS). In this study, we explored the experiences of service users and providers adopting measurement-based care (MBC) in early psychosis (EP) specialty care settings. Qualitative interviews were conducted with 32 providers and 12 service users across 18 programs in the Early Psychosis Intervention Network of California (EPI-CAL). These findings were compared with quantitative data from Beehive, EPI-CAL's data collection and review application. Regarding the clinical benefits of MBC in EP, three broad themes were identified - supporting safety monitoring and response, the assessment process, and delivery of psychotherapy. Outside of direct clinical care, Beehive was considered to support clinical supervision and external reporting, while service users reported data collection facilitated self-reflection. In the quantitative Beehive application data collected from 23 EP programs, high utilization of the safety alert system was evident (349 alerts in total, of which 338 [96.85 %] were resolved at a median of 2.03 days). However, service users' key survey data was only reviewed by assigned providers in 32.22 % (142 of 441) of cases. While providers and service users saw many benefits to Beehive, utilization was highly inconsistent outside of the alert system. Going forward, further consideration of how best to support EP providers to consistently use data in care is necessary to maximize the utility of the LHS approach and positively impact outcomes.

BACKGROUND:Since the late 1990s, there has been a worldwide surge of scientific interest in the pre-psychotic phase, resulting in the introduction of several clinical tools for early detection. The predictive accuracy of these tools has been limited, motivating the need for methodological and perspectival improvements. The EASE manual supports systematic assessment of anomalous self-experience, and proposes an overall model of understanding how most psychotic experiences may be initially generated on the basis of a unifying, fundamental, pre-reflective distortion of subjectivity. STUDY DESIGN:The EASE is time-consuming, so in order to spread the use of this essential perspective of psychosis risk we selected prototypical and frequent phenomena from the EASE, combining them into SQuEASE-11. To investigate this instrument for clinical relevance, basic psychometric properties, factor structure, and relationships with gold standard instruments and the full EASE, it was administered as an interview in the STEP intervention trial (Melbourne, Australia), with 328 clinical high-risk for psychosis (CHR-P) patients. STUDY RESULTS:The SQuEASE-11 had moderate internal consistency and revealed two correlated factors. Significant relationships were observed between the SQuEASE-11 and the widely used and validated instruments CAARMS, BPRS, SANS, MADRS, DACOBS, and SOFAS. The correlation with the full EASE was very strong. CONCLUSIONS:These 11 items do not necessarily relate specifically to ipseity disturbance, but the SQuEASE-11 seems to be a clinically relevant and brief supplementary first-line interview in CHR-P subjects. It may give a qualified indication of the need for a complete EASE interview, and it may also, importantly, inform treatment planning.

Approximately 25 % of individuals at Ultra High Risk (UHR) transition to a full psychotic disorder. Cognitive biases are thought to play a role in this risk, and improvements in cognitive biases have been associated with better clinical outcomes. Early intervention is crucial, yet no therapeutic approach has proven superior, and treatment adherence remains a challenge. Therapeutic alliance, shown to enhance adherence and clinical outcomes, might also influence depression and cognitive biases, but its role in these domains among UHR patients remains unclear. A total of 202 UHR participants (59.4 % females, mean age 17.4), taking part in the sequential multiple-assignment randomized trial (SMART), completed questionnaires assessing cognitive biases, attenuated psychotic symptoms, quality of life, general and social functioning, depression, and overall psychopathology at baseline, and at 6- and 12-month follow-ups. Additionally, both patients and their corresponding therapists rated working alliance following the 6- and 12-month treatment periods. The results revealed that patient-rated therapeutic alliance significantly predicted improvements in attenuated psychotic symptoms, cognitive biases, general psychopathology, social functioning, and quality of life, with the strongest effects observed when measured 6 months into treatment. The relationship between working alliance and decreases in attenuated psychotic symptoms, as well as between working alliance and reduction in general psychopathology, turned out to be mediated by improvements in cognitive biases. Therapist-rated working alliance did not significantly predict clinical improvements, showing only a minor association with quality of life. Strengthening the therapeutic alliance and prioritizing cognitive bias modification early in interventions for UHR patients may improve treatment outcomes. Further research is needed to validate these findings.

Screening for psychosis spectrum disorders in primary care could improve early identification and reduce the duration of untreated psychosis. However, the accuracy of psychosis screening in this setting is unknown. To address this, we conducted a diagnostic accuracy study of screening for psychosis spectrum disorders in eight behavioral health services integrated into primary care clinics. Patients attending an integrated behavioral health appointment at their primary care clinic completed the Prodromal Questionnaire - Brief (PQ-B) immediately prior to their intake assessment. This was compared to a diagnostic phone interview based on the Structured Interview for Psychosis Risk Syndromes (SIPS). In total, 145 participants completed all study procedures, of which 100 screened positive and 45 negative at a provisional PQ-B threshold of ≥20. The PQ-B was moderately accurate at differentiating psychosis spectrum from no psychosis spectrum disorders; a PQ-B distress score of ≥27 had a sensitivity and specificity of 71.2 % and 57.0 % respectively. In total, 66 individuals (45.5 %) met criteria for a psychosis spectrum disorder and 24 (16.7 %) were diagnosed with full psychosis, indicating a high prevalence of psychosis in the sample. Overall, screening for psychosis spectrum disorders in an IBH primary care setting identified a relatively high number of individuals and may identify people that would otherwise be missed. The PQ-B performed slightly less well than in population-based screening in community mental health settings. However, the findings suggest this may represent an effective way to streamline the pathway between specialty early psychosis programs and primary care clinics for those in need.

BACKGROUND:A longer duration of untreated psychosis (DUP) is associated with poorer treatment outcomes. Screening for psychosis spectrum disorders in the primary care setting could help support the earlier detection and treatment of individuals in need. However, the acceptability of screening for psychosis in this setting as part of routine care is currently unknown. METHODS:We conducted a qualitative interview study with providers and service users who participated in an early psychosis screening program conducted in an integrated behavioral health primary care (IBH-PC) setting. Interviews were recruited from one of eight WellSpace Federally Qualified Health Center IBH-PC clinics in the Sacramento, CA area. Transcripts of the recorded interviews were analyzed using thematic analysis. RESULTS:In total, 12 providers and eight service users participated in the interviews. Most service user and provider participants were supportive of psychosis screening in an IBH-PC setting, but not as part of the general practitioner consultation due to the brief, non-behavioral health nature of many of the appointments, and the expected low prevalence of psychosis in this population. The support of leadership, adequate training and support, staff turnover, and organizational changes were all seen to impact the successful implementation of the program. Different barriers and facilitators were considered important at each stage of the process from introducing the screening procedures to service users; to determining when, where, and how to screen; and how to effectively manage the referral and post-referral stages. CONCLUSIONS:Despite the additional challenges of screening in an IBH-PC setting relative to secondary mental health services, the process was considered acceptable and feasible to providers and service users. Services that plan to conduct psychosis screening in their clinics need to consider the challenges and their potential solutions to implementation at each stage of the screening process.

Objective: Learning health care networks can significantly improve the effectiveness, consistency, and cost-effectiveness of care delivery. As part of a data harmonization process, incorporation of the perspectives of community partners to maximize the relevance and utility of the data is critical. Methods: A mixed-methods focus group study was conducted with early psychosis program providers, leadership, service users, and family members to explore their priorities regarding data collection in early psychosis care. Focus group transcripts were analyzed through thematic analysis. Results: Twenty-two focus groups comprising 178 participants were conducted across 10 early psychosis programs. Participants considered functioning, quality of life, recovery, and symptoms of psychosis as key outcomes to assess, although variation by participants' roles was also evident. Participants emphasized the clinical utility of assessing a broad range of predictors of care outcomes, favored a broad conceptualization of the constructs assessed, and indicated a preference for client-reported measures. Participants also emphasized the importance of surveys adopting a recovery-oriented, strengths-based approach. Conclusions: Large-scale aggregation of health care data collected as part of routine care offers opportunities for research and may have a positive impact on care delivery and quality improvement activities. However, these benefits are contingent on the data being both relevant and accessible to those who deliver and receive such care. This study highlights an approach that may inform the development of core assessment batteries used, optimizing the utility of such data for all community partners.

BackgroundA prolonged first episode of psychosis (FEP) without adequate treatment is a predictor of poor clinical, functional, and health outcomes and significant economic burden. Team-based "coordinated specialty care" (CSC) for early psychosis (EP) has established effectiveness in promoting clinical and functional recovery. However, California's CSC program implementation has been unsystematic and could benefit from standardizing its processes and data collection infrastructure. To address this, we established a consortium of EP clinics across the state via a Learning Health Care Network (LHCN) framework to develop the Early Psychosis Intervention Network of California (EPI-CAL). EPI-CAL's LHCN developed a core battery of evidence-based measures for service users and family members and linked them together using a unique data collection and visualization application, Beehive.Methods and objectivesEPI-CAL's LHCN collects, visualizes, and aggregates data at the individual and clinic level for EP programs across California via Beehive. Beehive was designed to: (1) collect outcomes data from service users receiving care at EP programs and their support persons, (2) provide the data to providers on a secure web-based dashboard to support measurement-based care, and (3) allow data to be used for program or research analysis. We will (1) determine the feasibility of implementing an LHCN across a diverse, decentralized network of early psychosis programs, (2) determine if the implementation of an LHCN increases the delivery of measurement-based care, and (3) determine if the implementation of measurement-based care is associated with significant improvements in key service user outcomes. EPI-CAL's network will contribute data to the Early Psychosis Intervention Network (EPINET) program.DiscussionThe current study aims to establish an LHCN of EP clinics in California that implements harmonized data collection using Beehive and assesses the feasibility of establishing such a network. Our goal is for this harmonized data collection approach to be used to inform decisions and develop learning opportunities for service users, staff, and administrators, and to improve outcomes for service users and their supporters in CSC care. Further, the data will enable programs and research teams to examine what elements of care lead to program success and improved treatment outcomes for service users.Clinical trials registrationwww.ClinicalTrials.gov, identifier NCT04007510; registered 07/05/2019.

Background While over 90 clinical trials demonstrate the efficacy of the collaborative care model (CCM) to treat depression in primary care, there is significant variability in real-world CCM implementation and scalability. Our objective was to determine the feasibility and effectiveness of an adapted CCM in a safety-net primary care setting. Methods Bring It Up! (BIU) is a pilot trial comparing an adapted CCM (intervention group) to usual care (historical controls) for patients with depression in a primary care safety-net clinic. Inclusion criteria: 1) age ≥ 18; 2) PHQ-9 score ≥ 10; and 3) major depressive disorder diagnosis. We included patients who completed ≥ 6 months of treatment upon rolling enrollment (4/1/18 − 10/31/19). Historical controls completed ≥ 6 months of usual care in 2017. BIU included all aspects of CCM except accountable care and leveraged existing staff rather than a dedicated care manager. Referring PCPs received evidence-based depression care training, and the team enrolled patients and delivered depression care. Usual care consisted of appointments with PCP and behavioral health staff if referred by PCP. The primary outcome was depression remission (PHQ-9 < 5) within six months. Other depression care secondary outcomes included depression response and adherence to treatment guidelines. We also collected care coordination process outcomes. Data were extracted from the electronic health record. Results Thirty-six patients received the BIU intervention; 41 controls received usual care. Depression remission was achieved in 35.3% of intervention patients and 0% of controls (p = 0.001); and 47.1% of intervention patients achieved ≥ 50% reduction in PHQ-9 compared to 9.1% of controls (p = 0.003). Further, 72.7% of intervention patients had guideline-recommended antidepressant medication titration compared to 35.5% of controls (p = 0.003); 94.4% of intervention patients had PHQ-9 repeated compared to 53.7% of controls (p < 0.001). Conclusions An adapted CCM was feasible and improved depression care in a safety-net clinic. Trial registration Retrospectively registered with UCSF IRB on 12/22/2020. UCSF IRB number: 20-31424

Background and Hypothesis: Brain development/aging is not uniform across individuals,spawning efforts to characterize brain age from a biological perspective to model the effects of disease and maladaptive life processes on the brain. The brain age gap represents the discrepancy between estimated brain biological age and chronological age (in this case, based on structural magnetic resonance imaging, MRI). Structural MRI studies report an increased brain age gap (biological age > chronological age) in schizophrenia, with a greater brain age gap related to greater negative symptom severity. Less is known regarding the nature of this gap early in schizophrenia (ESZ), if this gap represents a psychosis conversion biomarker in clinical high-risk (CHR-P) individuals, and how altered brain development and/or agingmap onto specific symptom facets. Study Design: Using structural MRI, we compared the brain age gap among CHR-P (n = 51), ESZ (n = 78), and unaffected comparison participants (UCP; n = 90), and examined associations with CHR-P psychosis conversion (CHR-P converters n = 10; CHR-P non-converters; n = 23) and positive and negative symptoms. Study Results: ESZ showed a greater brain age gap relative to UCP and CHR-P (Ps < .010). CHR-P individuals who converted to psychosis showed a greater brain age gap (P = .043) relative to CHR-P non-converters. A larger brain age gap in ESZ was associated with increased experiential (P = .008), but not expressive negative symptom severity. Conclusions: Consistent with schizophrenia pathophysiological models positing abnormal brain maturation, results suggest abnormal brain development is present early in psychosis. An increased brain age gap may be especially relevant to motivational and functional deficits in schizophrenia.

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS + individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1,165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1,029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-includingthose from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS + from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS + in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.