Characterizing and detecting delirium with clinical and computational measures of speech and language disturbance.

BACKGROUND: Delirium is a critically underdiagnosed syndrome of altered mental status affecting more than 50% of older adults admitted to hospital. Few studies have incorporated speech and language disturbance in delirium detection. We sought to describe speech and language disturbances in delirium, and provide a proof of concept for detecting delirium using computational speech and language features. METHODS: Participants underwent delirium assessment and completed language tasks. Speech and language disturbances were rated using standardized clinical scales. Recordings and transcripts were processed using an automated pipeline to extract acoustic and textual features. We used binomial, elastic net, machine learning models to predict delirium status. RESULTS: We included 33 older adults admitted to hospital, of whom 10 met criteria for delirium. The group with delirium scored higher on total language disturbances and incoherence, and lower on category fluency. Both groups scored lower on category fluency than the normative population. Cognitive dysfunction as a continuous measure was correlated with higher total language disturbance, incoherence, loss of goal and lower category fluency. Including computational language features in the model predicting delirium status increased accuracy to 78%. LIMITATIONS: This was a proof-of-concept study with limited sample size, without a set-aside cross-validation sample. Subsequent studies are needed before establishing a generalizable model for detecting delirium. CONCLUSION: Language impairments were elevated among patients with delirium and may also be used to identify subthreshold cognitive disturbances. Computational speech and language features are promising as accurate, noninvasive and efficient biomarkers of delirium.

Longitudinal perspectives on the psychosis spectrum in 22q11.2 deletion syndrome.

The prevalence of psychotic disorders in individuals with 22q11.2 Deletion Syndrome (22q11DS) reaches 25-35% in young adulthood and may provide a neurogenetic model for clinical risk of psychotic disorders in the general population. This review focuses on prospective longitudinal studies in 22q11DS, which capture fluctuations in psychosis symptoms over time and may provide insights into potential demographic, clinical, cognitive, and neuroimaging predictors of psychosis-spectrum outcomes in the general population. Findings are compared and contrasted with those from idiopathic psychosis-spectrum populations. Onset of psychotic disorders in 22q11DS can occur over a wide range of ages, peaking in late adolescence. Symptoms may be gradually progressive or episodic in nature, highlighting the importance and challenge of risk and resilience prediction models. Converging results suggest that psychosis-spectrum outcomes in 22q11DS are predicted by lower baseline functioning, higher baseline psychosis-spectrum symptoms, presence of mood disturbance or anxiety, and lower baseline and subsequent decline in global measures of cognition. Predictors of transition to threshold psychotic disorders and ages of onset are similar in idiopathic clinical risk. They also share similarly global cognitive deficits, but not to the same extent as in 22q11DS. While neuroimaging studies in idiopathic clinical risk suggest loss of prefrontal gray matter, there is no consistent evidence yet emerging in the limited literature in 22q11DS. Interventional efforts in 22q11DS aimed at halting progression to psychosis or mitigating outcomes in early psychosis may be best implemented during the adolescent age range. Collaborative longitudinal efforts may help to address existing gaps in our understanding.

Musical auditory processing, cognition, and psychopathology in 22q11.2 deletion syndrome.

Chromosome 22q11.2 deletion syndrome (22q11DS) is associated with impairment in multiple domains of cognition and risk for several psychiatric disorders. Musical auditory processing is highly heritable, and is impaired in individuals with schizophrenia and other neurodevelopmental disorders, but has never been studied in 22q11DS, notwithstanding anecdotal evidence of its sparing. We aimed to characterize musical auditory processing in 22q11DS and explore potential relationships with other cognitive domains, musical engagement, and psychiatric disorders. The Distorted Tunes Task and Global Musical Sophistication Index were used to assess pitch discrimination and general musical engagement in 58 individuals with 22q11DS aged 8-29 years. Psychopathology was assessed with sections from the modified Schedule for Affective Disorders and Schizophrenia for School-Age Children and the Structured Interview for Prodromal Syndromes. The Penn computerized neurocognitive battery (CNB) examined four domains of cognition (executive functioning, episodic memory, complex cognition, and social cognition). Significant musical auditory processing impairment and reduced musical engagement were found in individuals with 22q11DS. However, deficits in musical auditory processing were not associated with reduced musical engagement. After covarying for age and sex, episodic memory and overall CNB performance accuracy were significantly related to performance in musical auditory processing. There were no relationships between musical auditory processing and presence of any psychiatric diagnoses. Individuals with 22q11DS experience significant deficits in musical auditory processing and reduced musical engagement. Pitch discrimination is associated with overall cognitive ability, but appears to be largely independent of psychiatric illness.

Lacrimal intubation during dacryocystorhinostomy utilizing the STENTube.

The traditional use of the Crawford tube for lacrimal intubation during dacryocystorhinostomy (DCR) carries several drawbacks. We describe the use of the STENTube for DCR intubation and detail its advantages. Retrospective, noncomparative, interventional case series; 313 patients with nasolacrimal duct obstruction (NLDO) underwent 339 DCRs (216 external, 123 endonasal) with the STENTube from January 2007 - June 2013 by 5 surgeons (RS, QN, TS, SB, TN) across 3 institutions (SUNY Downstate Medical Center, Texas Oculoplastics Consultants, and Moorfields Eye Hospital). Study outcome measures included patient demographics, surgical complications, and epiphora improvement/resolution. 206 (66%) females and 107 (34%) males had a mean age of 63 years (range 2-94 years). Distribution of diagnoses included: 314 complete idiopathic acquired NLDO, 20 partial idiopathic acquired NLDO, and 5 congenital complete NLDO. 316 (93%) were primary DCRs and 23 (7%) were revisions. Epiphora improved in 312 (92%) cases with 294 (86%) experiencing resolution with patent lacrimal irrigation at a mean last follow-up of 9.4 months. Twenty-eight (8%) patients experienced surgical complications with 16 (5%) experiencing tube prolapse, and 20 (6%) requiring re-operation. The STENTube represents a simple method for lacrimal intubation during external or endonasal DCR at a comparable cost to the Crawford tube. It allows for low prolapse rates without the need for additional endonasal fixation procedures, resulting in a simple and comfortable post-operative extraction without risk of lacrimal trauma. The STENTube is our preferred intubation technique during DCR, and should be considered by oculofacial surgeons performing DCR with intubation.

Orbital floor fracture with entrapment: Imaging and clinical correlations in 45 cases.

Orbital floor fractures (OFF) with entrapment require prompt clinical and radiographic recognition for timely surgical correction. Correct CT radiographic interpretation of entrapped fractures can be subtle and thus missed. We reviewed the clinical, radiographic and intraoperative findings of 45 cases of entrapped OFF to correlate pre- and intraoperative findings with radiography. Retrospective review and statistical analysis of 45 patients with OFF using the chi squared and Kruskal-Wallis tests. Main outcome measures included patient demographics, clinical features, radiologic interpretation, intraoperative findings, and treatment outcomes. Twenty-one cases (47%) had radiologic evaluations of orbital CT scans that included commentary on possible entrapment. Intraoperatively, 16 (76%) of these patients had the inferior rectus muscle incarcerated in the fracture, while 5 (24%) patients had incarceration of the orbital fat. Possibility of entrapment was not commented on in the radiology reports of the remaining 24 (53%) cases. Intraoperatively, 13 (54%) of these patients had the inferior rectus muscle incarcerated in the fracture, while 11 (46%) patients had incarceration of the orbital fat. It is vital to assess the possibility of entrapment, especially in young patients, in the setting of OFF as a delay in diagnosis may lead to persistent diplopia, disfigurement, or bradycardia. Most radiology reports did not mention the possibility of entrapment in this cohort. A key concept is that entrapment occurs when any orbital tissue (muscle or fat) is trapped in the fracture site.

Pediatric Idiopathic Orbital Inflammation: Clinical Features of 30 Cases.

PURPOSE: Pediatric idiopathic orbital inflammation (IOI) is a rare entity with little known about the clinical presentation and natural history. The authors report the demographics, clinical presentations, radiographic and histopathologic characteristics, and treatment outcome of 30 children with IOI. METHODS: Retrospective chart review of 30 patients 18 years and younger diagnosed with IOI and statistical analysis using analysis of variance and Fisher's exact test. This study was reviewed and approved by the Institutional Review Board of SUNY Downstate Medical Center. RESULTS: There were 9 males (30%) and 21 females (70%) with pediatric IOI who presented at a median age of 11 years (range 2-18 years). Primary IOI was found in 19 patients (63%) and recurrent IOI in 11 patients (37%). Overall, 26 patients (87%) had unilateral IOI while 4 patients (13%) had bilateral disease at presentation. There were 12 patients (40%) with systemic constitutional signs. The most common ophthalmic findings included periorbital edema (n = 20, 67%) and blepharoptosis (n = 17, 57%). All patients had orbital radiography with common findings of dacryoadenitis (n = 12, 40%), orbital mass (n = 12, 40%), or myositis (n=10, 33%). The presence of a radiographic orbital mass was significantly related to the clinical presence of blepharoptosis (p = 0.03). The most common treatment was oral glucocorticoids in 24 patients (80%). Over mean follow up of 19 months (range 6-64 months), females were more likely to display recurrent disease (p = 0.01). CONCLUSIONS: Idiopathic orbital inflammation is an uncommon but important cause of acute orbital syndrome in children, manifesting as a bilateral condition in 13% and with constitutional symptoms in 40%. Posttreatment recurrence is found in 37% of cases.

Bilateral lacrimal gland disease: clinical features of 97 cases.

OBJECTIVE: Bilateral lacrimal gland (LG) disease is a unique presentation that can result from varied causes. We reviewed the diagnoses, clinical features, and outcomes of 97 patients with this entity. DESIGN: Case series. PARTICIPANTS: Ninety-seven patients with bilateral LG disease. METHODS: Retrospective review and statistical analysis using analysis of variance and the Fisher exact test. MAIN OUTCOME MEASURES: Patient demographics, clinical features, diagnostic testing, diagnosis, and treatment. RESULTS: Patient age ranging from 8 to 84 years (mean, 46 years). The predominant gender was female (77%), and race included black (49%), white (38%), and Hispanic (12%) patients. Diagnoses fell into 4 categories: inflammatory (n = 51; 53%), structural (n = 20; 21%), lymphoproliferative (n = 19; 20%), and uncommon (n = 7; 7%) entities. The most common diagnoses included idiopathic orbital inflammation (IOI; n = 29; 30%), sarcoidosis (n = 19; 20%), prolapsed LG (n = 15; 15%), lymphoma (n = 11; 11%), lymphoid hyperplasia (n = 8; 8%), and dacryops (n = 5; 5%). Inflammatory conditions were more likely in younger patients (P<0.05) and in those with pain (P<0.001) and mechanical blepharoptosis (P<0.01) at presentation, whereas lymphoma was more common in older patients (P<0.001) without active signs of inflammation at presentation. Black patients were more likely to have sarcoidosis (P<0.01). Laboratory results showed high angiotensin converting enzyme level being significantly more likely in patients with sarcoidosis (P<0.05). However, sensitivity was limited to 45%, with 25% of patients diagnosed with IOI also demonstrating positive results. Corticosteroid therapy was the treatment of choice in 38 cases, corresponding to resolution of symptoms in 29% and improvement in an additional 32%. Overall, chronic underlying disease was found in 71% of patients, among whom 26% achieved a disease-free state, whereas 3% succumbed to their underlying disease. CONCLUSIONS: The cause of bilateral lacrimal gland disease most commonly was inflammatory, followed by structural and lymphoproliferative. Patient characteristics and clinical presentations were key features distinguishing between competing possibilities. Despite local control with corticosteroids or radiotherapy, underlying disease continued in 71% of patients and led to death in 3%.

Contribution of congenital heart disease to neuropsychiatric outcome in school-age children with 22q11.2 deletion syndrome.

Children with 22q11.2 deletion syndrome (22q11DS) present with congenital heart disease (CHD) and high prevalence of psychiatric disorders and neurocognitive deficits. Although CHD has been implicated in neurodevelopment, its role in the neuropsychiatric outcome in 22q11DS is poorly understood. We investigated whether CHD contributes to the high prevalence of psychiatric disorders and neurocognitive impairments in 22q11DS. Fifty-four children ages 8-14 years with 22q11DS and 16 age-matched non-deleted children with CHD participated. They were assessed using semi-structured interviews and a Computerized Neurocognitive Battery. CHD status was assessed using available medical records. Prevalence of psychiatric disorders and cognitive profiles were compared among the groups. There were no significant differences between the prevalence of psychiatric disorders in the 22q11DS with and without CHD. In 22q11DS with CHD, the prevalence rates were 41% anxiety disorders, 37% ADHD and 71% psychosis spectrum. In 22q11DS without CHD, the rates were 33% anxiety disorders, 41% ADHD and 64% psychosis spectrum. In comparison, the non-deleted CHD group had lower rates of psychopathology (25% anxiety disorders, 6% ADHD, and 13% psychosis spectrum). Similarly, the 22q11DS groups, regardless of CHD status, had significantly greater neurocognitive deficits across multiple domains, compared to the CHD-only group. We conclude that CHD in this sample of children with 22q11.2DS does not have a major impact on the prevalence of psychiatric disorders and is not associated with increased neurocognitive deficits. These findings suggest that the 22q11.2 deletion status itself may confer significant neuropsychiatric vulnerability in this population.

Exploring online and offline social experiences and interaction patterns of young adults with psychosis with the social media and internet social engagement questionnaire: Analyses and future directions.

Objective: Social interactions and experiences are increasingly occurring online, including for young adults with psychosis. Healthy social interactions and experiences are widely recognized as a critical component of social recovery, yet research thus far has focused predominantly on offline interactions with limited understanding of these interactions online. We developed the Social Media and Internet sociaL Engagement (SMILE) questionnaire to assess the type, frequency, and nature of online social interactions and experiences among young adults with early psychosis to better assess online social activity and ultimately support personalized interventions. Methods: Participants (N = 49) completed the SMILE questionnaire which asked about online platforms used, frequency of use, and if positive and negative experiences were more likely to happen online or offline. Participants completed additional self-report measures of victimization, positive psychotic symptoms, social functioning, and demographics. Exploratory factor analysis and correlations between identified factors and clinical measures of interest were completed. Results: Exploratory factor analysis revealed three factors: positive engagement, victimization, and internalizing experiences. Most participants (6%-37%) experienced positive engagement offline. Victimization occurred equally online and offline (8%-27% and 4%-24%, respectively). Most participants (37%-51%) endorsed internalizing experiences as occurring equally offline and online, but approximately a third of participants reported internalizing experiences more frequently offline (20%-35%). Victimization was moderately (r = 0.34) correlated with overall online social experiences, suggesting more online time may increase the likelihood of victimization. Age was inversely related to the frequency of overall online social experiences. Conclusion: Young adults with early psychosis experience positive and negative social experiences online and offline. New scales and measures to comprehensively assess the nature and function of online social interactions and experiences are needed.

Detecting schizophrenia, bipolar disorder, psychosis vulnerability and major depressive disorder from 5 minutes of online-collected speech.

Background: Psychosis poses substantial social and healthcare burdens. The analysis of speech is a promising approach for the diagnosis and monitoring of psychosis, capturing symptoms like thought disorder and flattened affect. Recent advancements in Natural Language Processing (NLP) methodologies enable the automated extraction of informative speech features, which has been leveraged for early psychosis detection and assessment of symptomology. However, critical gaps persist, including the absence of standardized sample collection protocols, small sample sizes, and a lack of multi-illness classification, limiting clinical applicability. Our study aimed to (1) identify an optimal assessment approach for the online and remote collection of speech, in the context of assessing the psychosis spectrum and evaluate whether a fully automated, speech-based machine learning (ML) pipeline can discriminate among different conditions on the schizophrenia-bipolar spectrum (SSD-BD-SPE), help-seeking comparison subjects (MDD), and healthy controls (HC) at varying layers of analysis and diagnostic complexity. Methods: We adopted online data collection methods to collect 20 minutes of speech and demographic information from individuals. Participants were categorized as "healthy" help-seekers (HC), having a schizophrenia-spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), or being on the psychosis spectrum with sub-clinical psychotic experiences (SPE). SPE status was determined based on self-reported clinical diagnosis and responses to the PHQ-8 and PQ-16 screening questionnaires, while other diagnoses were determined based on self-report from participants. Linguistic and paralinguistic features were extracted and ensemble learning algorithms (e.g., XGBoost) were used to train models. A 70%-30% train-test split and 30-fold cross-validation was used to validate the model performance. Results: The final analysis sample included 1140 individuals and 22,650 minutes of speech. Using 5-minutes of speech, our model could discriminate between HC and those with a serious mental illness (SSD or BD) with 86% accuracy (AUC = 0.91, Recall = 0.7, Precision = 0.98). Furthermore, our model could discern among HC, SPE, BD and SSD groups with 86% accuracy (F1 macro = 0.855, Recall Macro = 0.86, Precision Macro = 0.86). Finally, in a 5-class discrimination task including individuals with MDD, our model had 76% accuracy (F1 macro = 0.757, Recall Macro = 0.758, Precision Macro = 0.766). Conclusion: Our ML pipeline demonstrated disorder-specific learning, achieving excellent or good accuracy across several classification tasks. We demonstrated that the screening of mental disorders is possible via a fully automated, remote speech assessment pipeline. We tested our model on relatively high number conditions (5 classes) in the literature and in a stratified sample of psychosis spectrum, including HC, SPE, SSD and BD (4 classes). We tested our model on a large sample (N = 1150) and demonstrated best-in-class accuracy with remotely collected speech data in the psychosis spectrum, however, further clinical validation is needed to test the reliability of model performance.

The Mental Health Toll of the COVID-19 Pandemic on Adolescents Receiving Inpatient Psychiatric Treatment.

Objective: During the COVID-19 pandemic, the prevalence of depression and anxiety among children and adolescents significantly increased, along with the number of visits to emergency departments due to suicidality and/or suicide attempts. Relatedly, health care workers experienced significant burnout and symptoms of anxiety, depression, and posttraumatic stress disorder during this time. However, the corresponding impact on psychiatric inpatient treatment has not yet been researched. We hypothesized that during the pandemic, adolescents hospitalized in an acute care psychiatric inpatient unit had increased incidents of suicide attempts and nonsuicidal self-injurious behaviors and of aggressive behaviors toward others, resulting in greater use of constant observation and restraints. Method: This study was a retrospective chart review based on electronic medical record data examining use of restraints and constant observation one year before the pandemic (March 2019 to February 2020) and 1 year following the onset of the pandemic (March 2020 to February 2021) in an acute-care adolescent (12 to 17 years old) psychiatric inpatient unit. Results: There were 571 admissions during the year before the pandemic and 500 admissions during the pandemic. The number of patients who were restrained (χ2 = 7.86, p = 0.005), number of patients who were placed on constant observation (χ2 = 13.41, p < 0.001), and number of constant observation orders per patient (χ2 = 91.90, p < 0.001) were all significantly greater during the pandemic. Conclusion: Psychiatrically hospitalized adolescents during the pandemic received more intensive interventions such as restraints and constant observation. Severe patient psychopathology and staff shortages, as well as limitations of and decreases to the dialectical behavior therapy program, may have been the contributing factor.

Race-Based Disparities in the Frequency and Duration of Restraint Use in a Psychiatric Inpatient Setting.

OBJECTIVE: Patients' race and age have each been identified as risk factors for experiencing restraint events during psychiatric hospitalization. Restraint duration is also an important variable in determining disparities in treatment. To the authors' knowledge, no studies to date have examined the effect of the interaction of race and age on restraint use and duration in inpatient psychiatric settings. This retrospective chart review of electronic medical records of patients admitted between 2012 and 2019 sought to examine whether race and age interacted in predicting differences in the use and duration of restraints in a psychiatric inpatient setting. METHODS: Logistic and hierarchical regression analyses were conducted on data from a sample of 29,739 adolescent (ages 12-17 years) and adult (ages ≥18 years) inpatients to determine whether the interaction of race and age group (adolescent or adult) significantly predicted a restraint event or differences in restraint duration. RESULTS: Black (adjusted OR [AOR]=1.85) and multiracial (AOR=1.36) patients were more likely to experience a restraint event than were their White peers. Black race was also significantly (p=0.001) associated with longer restraint duration. No significant interaction was detected between race and age in predicting restraint events or duration. CONCLUSIONS: Although the interaction between race and age did not predict restraint events or duration, the findings indicate racial disparities in the frequency and duration of restraint events among Black and multiracial individuals and may inform efforts to reduce these events.

Functional phenotypes in schizophrenia spectrum disorders: defining the constructs and identifying biopsychosocial correlates using data-driven methods.

Functional impairments contribute to poor quality of life in schizophrenia spectrum disorders (SSD). We sought to (Objective I) define the main functional phenotypes in SSD, then (Objective II) identify key biopsychosocial correlates, emphasizing interpretable data-driven methods. Objective I was tested on independent samples: Dataset I (N = 282) and Dataset II (N = 317), with SSD participants who underwent assessment of multiple functioning areas. Participants were clustered based on functioning. Objective II was evaluated in Dataset I by identifying key features for classifying functional phenotype clusters from among 65 sociodemographic, psychological, clinical, cognitive, and brain volume measures. Findings were replicated across latent discriminant analyses (LDA) and one-vs.-rest binomial regularized regressions to identify key predictors. We identified three clusters of participants in each dataset, demonstrating replicable functional phenotypes: Cluster 1-poor functioning across domains; Cluster 2-impaired Role Functioning, but partially preserved Independent and Social Functioning; Cluster 3-good functioning across domains. Key correlates were Avolition, anhedonia, left hippocampal volume, and measures of emotional intelligence and subjective social experience. Avolition appeared more closely tied to role functioning, and anhedonia to independent and social functioning. Thus, we found three replicable functional phenotypes with evidence that recovery may not be uniform across domains. Avolition and anhedonia were both critical but played different roles for different functional domains. It may be important to identify critical functional areas for individual patients and target interventions accordingly.

Multivariate Association between Functional Connectivity Gradients and Cognition in Schizophrenia Spectrum Disorders.

BACKGROUND: Schizophrenia Spectrum Disorders (SSDs), which are characterized by social cognitive deficits, have been associated with dysconnectivity in "unimodal" (e.g., visual, auditory) and "multimodal" (e.g., default-mode and frontoparietal) cortical networks. However, little is known regarding how such dysconnectivity relates to social and non-social cognition, and how such brain-behavioral relationships associate with clinical outcomes of SSDs. METHODS: We analyzed cognitive (non-social and social) measures and resting-state functional magnetic resonance imaging data from the 'Social Processes Initiative in Neurobiology of the Schizophrenia(s) (SPINS)' study (247 stable participants with SSDs and 172 healthy controls, ages 18-55). We extracted gradients from parcellated connectomes and examined the association between the first 3 gradients and the cognitive measures using partial least squares correlation (PLSC). We then correlated the PLSC dimensions with functioning and symptoms in the SSDs group. RESULTS: The SSDs group showed significantly lower differentiation on all three gradients. The first PLSC dimension explained 68.53% (p<.001) of the covariance and showed a significant difference between SSDs and Controls (bootstrap p<.05). PLSC showed that all cognitive measures were associated with gradient scores of unimodal and multimodal networks (Gradient 1), auditory, sensorimotor, and visual networks (Gradient 2), and perceptual networks and striatum (Gradient 3), which were less differentiated in SSDs. Furthermore, the first dimension was positively correlated with negative symptoms and functioning in the SSDs group. CONCLUSIONS: These results suggest a potential role of lower differentiation of brain networks in cognitive and functional impairments in SSDs.

Racial and ethnic inequities in psychiatric inpatient building and unit assignment.

Racism is a social determinant of mental health which has a disproportionally negative impact on the experiences of psychiatric inpatients of color. Distinct differences in the physical space and clinical settings of two inpatient buildings at a hospital system in the tristate (New York, New Jersey, Connecticut) area of the United States led to the present investigation of racial inequities in the assignment of patients to specific buildings and units. Archival electronic medical record data were analyzed from over 18,000 unique patients over a period of six years. Hierarchical logistic regression analyses were conducted with assigned building (old vs. new building) as the binary outcome variable. Non-Hispanic White patients were set as the reference group. Black, Hispanic/Latinx, and Asian patients were significantly less likely to be assigned to better resourced units in the new building. When limiting the analysis to only general adult units, Black and Hispanic/Latinx patients were significantly less likely to be assigned to units in the new building. These results suggest ethnoracial inequities in patient assignment to buildings which differed in clinical and physical conditions. The findings serve as a call to action for hospital systems to examine the ways in which structural racism impact clinical care.

Latent Factors of Language Disturbance and Relationships to Quantitative Speech Features.

BACKGROUND AND HYPOTHESIS: Quantitative acoustic and textual measures derived from speech ("speech features") may provide valuable biomarkers for psychiatric disorders, particularly schizophrenia spectrum disorders (SSD). We sought to identify cross-diagnostic latent factors for speech disturbance with relevance for SSD and computational modeling. STUDY DESIGN: Clinical ratings for speech disturbance were generated across 14 items for a cross-diagnostic sample (N = 334), including SSD (n = 90). Speech features were quantified using an automated pipeline for brief recorded samples of free speech. Factor models for the clinical ratings were generated using exploratory factor analysis, then tested with confirmatory factor analysis in the cross-diagnostic and SSD groups. The relationships between factor scores and computational speech features were examined for 202 of the participants. STUDY RESULTS: We found a 3-factor model with a good fit in the cross-diagnostic group and an acceptable fit for the SSD subsample. The model identifies an impaired expressivity factor and 2 interrelated disorganized factors for inefficient and incoherent speech. Incoherent speech was specific to psychosis groups, while inefficient speech and impaired expressivity showed intermediate effects in people with nonpsychotic disorders. Each of the 3 factors had significant and distinct relationships with speech features, which differed for the cross-diagnostic vs SSD groups. CONCLUSIONS: We report a cross-diagnostic 3-factor model for speech disturbance which is supported by good statistical measures, intuitive, applicable to SSD, and relatable to linguistic theories. It provides a valuable framework for understanding speech disturbance and appropriate targets for modeling with quantitative speech features.

Clinical and computational speech measures are associated with social cognition in schizophrenia spectrum disorders.

In this study, we compared three domains of social cognition (emotion processing, mentalizing, and attribution bias) to clinical and computational language measures in 63 participants with schizophrenia spectrum disorders. Based on the active inference model for discourse, we hypothesized that emotion processing and mentalizing, but not attribution bias, would be related to language disturbances. Clinical ratings for speech disturbance assessed disorganized and underproductive dimensions. Computational features included speech graph metrics, use of modal verbs, use of first-person pronouns, cosine similarity of adjacent utterances, and measures of sentiment; these were represented by four principal components. We found that higher clinical ratings for disorganized speech were predicted by greater impairments in both emotion processing and mentalizing, and that these relationships remained significant when accounting for demographic variables, overall psychosis symptoms, and verbal ability. Similarly, a computational speech component reflecting insular speech was consistently predicted by impairment in emotion processing. There were notable trends for computational speech components reflecting underproductive speech and decreased content-rich speech predicting mentalizing ability. Exploratory longitudinal analyses in a small subset of participants (n = 17) found that improvements in both emotion processing and mentalizing predicted improvements in disorganized speech. Attribution bias did not demonstrate strong relationships with language measures. Altogether, our findings are consistent with the active inference model of discourse and suggest greater emphasis on treatments that target social cognitive and language systems.

Feasibility of Mobile Health and Social Media-Based Interventions for Young Adults With Early Psychosis and Clinical Risk for Psychosis: Survey Study.

BACKGROUND: Digital technology, the internet, and social media are increasingly investigated as promising means for monitoring symptoms and delivering mental health treatment. These apps and interventions have demonstrated preliminary acceptability and feasibility, but previous reports suggest that access to technology may still be limited among individuals with psychotic disorders relative to the general population. OBJECTIVE: We evaluated and compared access to and use of technology and social media in young adults with psychotic disorders (PD), young adults with clinical risk for psychosis (CR), and psychosis-free youths (PF). METHODS: Participants were recruited through a coordinated specialty care clinic dedicated toward early psychosis as well as ongoing studies. We surveyed 21 PD, 23 CR, and 15 PF participants regarding access to technology and use of social media, specifically Facebook and Twitter. Statistical analyses were conducted in R. Categorical variables were compared among groups using Fisher exact test, continuous variables were compared using 1-way ANOVA, and multiple linear regressions were used to evaluate for covariates. RESULTS: Access to technology and social media were similar among PD, CR, and PF participants. Individuals with PD, but not CR, were less likely to post at a weekly or higher frequency compared to PF individuals. We found that decreased active social media posting was unique to psychotic disorders and did not occur with other psychiatric diagnoses or demographic variables. Additionally, variation in age, sex, and White versus non-White race did not affect posting frequency. CONCLUSIONS: For young people with psychosis spectrum disorders, there appears to be no "technology gap" limiting the implementation of digital and mobile health interventions. Active posting to social media was reduced for individuals with psychosis, which may be related to negative symptoms or impairment in social functioning.

Metabolic disturbances, hemoglobin A1c, and social cognition impairment in Schizophrenia spectrum disorders.

Social cognitive impairments are core features of schizophrenia spectrum disorders (SSD) and are associated with greater functional impairment and decreased quality of life. Metabolic disturbances have been related to greater impairment in general neurocognition, but their relationship to social cognition has not been previously reported. In this study, metabolic measures and social cognition were assessed in 245 participants with SSD and 165 healthy comparison subjects (HC), excluding those with hemoglobin A1c (HbA1c) > 6.5%. Tasks assessed emotion processing, theory of mind, and social perception. Functional connectivity within and between social cognitive networks was measured during a naturalistic social task. Among SSD, a significant inverse relationship was found between social cognition and cumulative metabolic burden (ß = -0.38, p < 0.001) and HbA1c (ß = -0.37, p < 0.001). The relationship between social cognition and HbA1c was robust across domains and measures of social cognition and after accounting for age, sex, race, non-social neurocognition, hospitalization, and treatment with different antipsychotic medications. Negative connectivity between affect sharing and motor resonance networks was a partial mediator of this relationship across SSD and HC groups (ß = -0.05, p = 0.008). There was a group x HbA1c effect indicating that SSD participants were more adversely affected by increasing HbA1c. Thus, we provide the first report of a robust relationship in SSD between social cognition and abnormal glucose metabolism. If replicated and found to be causal, insulin sensitivity and blood glucose may present as promising targets for improving social cognition, functional outcomes, and quality of life in SSD.