Automating the analysis of facial emotion expression dynamics: A computational framework and application in psychotic disorders.

Facial emotion expressions play a central role in interpersonal interactions; these displays are used to predict and influence the behavior of others. Despite their importance, quantifying and analyzing the dynamics of brief facial emotion expressions remains an understudied methodological challenge. Here, we present a method that leverages machine learning and network modeling to assess the dynamics of facial expressions. Using video recordings of clinical interviews, we demonstrate the utility of this approach in a sample of 96 people diagnosed with psychotic disorders and 116 never-psychotic adults. Participants diagnosed with schizophrenia tended to move from neutral expressions to uncommon expressions (e.g., fear, surprise), whereas participants diagnosed with other psychoses (e.g., mood disorders with psychosis) moved toward expressions of sadness. This method has broad applications to the study of normal and altered expressions of emotion and can be integrated with telemedicine to improve psychiatric assessment and treatment.

Long-Term Course of Remission and Recovery in Psychotic Disorders.

OBJECTIVE: Understanding prognosis is critical to anticipating public health needs and providing care to individuals with psychotic disorders. However, the long-term course of remission and recovery remains unclear. In this study, the most common trajectories of illness course are described for a cohort of individuals followed for 25 years since first admission for psychosis. METHODS: Participants are from the Suffolk County Mental Health Project, an epidemiological study of first-admission psychosis. Data for the present study was collected from six follow-ups, with 311 individuals assessed at the 25-year follow-up. Common patterns of remission and recovery were assessed in the baseline cohort of 591 individuals and the subsample from the 25-year follow up. RESULTS: In the baseline cohort and the 25-year subsample, the most common trajectory for individuals with schizophrenia spectrum disorders was no remission and no recovery. Among individuals with other psychotic disorders, in both the baseline and 25-year cohorts, the modal pattern was one of intermittent remission and recovery. Individuals with other psychotic disorders were more likely to experience stable remission (15.1%) and stable recovery (21.1%), outcomes that were rare among individuals with schizophrenia spectrum disorders (0% and 0.6%, respectively). CONCLUSIONS: The modal longitudinal pattern for individuals with other psychoses is one of multiple transitions into and out of symptomatic and functional recovery. Engagement in a long-term health care plan may help individuals detect and respond to these changes. Sustained remission and recovery are rare among people with schizophrenia spectrum disorders. Efforts should be directed toward developing more effective treatments for this population.

Behavioral meaures of psychotic disorders: Using automatic facial coding to detect nonverbal expressions in video.

Emotional deficits in psychosis are prevalent and difficult to treat. In particular, much remains unknown about facial expression abnormalities, and a key reason is that expressions are very labor-intensive to code. Automatic facial coding (AFC) can remove this barrier. The current study sought to both provide evidence for the utility of AFC in psychosis for research purposes and to provide evidence that AFC are valid measures of clinical constructs. Changes of facial expressions and head position of participants-39 with schizophrenia/schizoaffective disorder (SZ), 46 with other psychotic disorders (OP), and 108 never psychotic individuals (NP)-were assessed via FaceReader, a commercially available automated facial expression analysis software, using video recorded during a clinical interview. We first examined the behavioral measures of the psychotic disorder groups and tested if they can discriminate between the groups. Next, we evaluated links of behavioral measures with clinical symptoms, controlling for group membership. We found the SZ group was characterized by significantly less variation in neutral expressions, happy expressions, arousal, and head movements compared to NP. These measures discriminated SZ from NP well (AUC = 0.79, sensitivity = 0.79, specificity = 0.67) but discriminated SZ from OP less well (AUC = 0.66, sensitivity = 0.77, specificity = 0.46). We also found significant correlations between clinician-rated symptoms and most behavioral measures (particularly happy expressions, arousal, and head movements). Taken together, these results suggest that AFC can provide useful behavioral measures of psychosis, which could improve research on non-verbal expressions in psychosis and, ultimately, enhance treatment.

The Course of General Cognitive Ability in Individuals With Psychotic Disorders.

Importance: Schizophrenia is associated with major cognitive deficits and has been conceptualized as both a neurodevelopmental and a neurodegenerative disorder. However, when deficits develop and how they change over the course of illness is uncertain. Objective: To trace cognition from elementary school to old age to test neurodevelopmental and neurodegenerative theories of psychotic disorders. Design, Setting, and Participants: Data were taken from the Suffolk County Mental Health Project, a first-admission longitudinal cohort study of individuals with psychotic disorders. Participants were recruited from all 12 inpatient psychiatric facilities in Suffolk County, New York. This analysis concerns the 428 participants with at least 2 estimates of general cognitive ability. Data were collected between September 1989 and October 2019, and data were analyzed from January 2020 to October 2021. Exposures: Psychiatric hospitalization for psychosis. Main Outcomes and Measures: Preadmission cognitive scores were extracted from school and medical records. Postonset cognitive scores were based on neuropsychological testing at 6-month, 24-month, 20-year, and 25-year follow-ups. Results: Of the 428 included individuals (212 with schizophrenia and 216 with other psychotic disorders), 254 (59.6%) were male, and the mean (SD) age at psychosis onset was 27 (9) years. Three phases of cognitive change were observed: normative, declining, and deteriorating. In the first phase, cognition was stable. Fourteen years before psychosis onset, those with schizophrenia began to experience cognitive decline at a rate of 0.35 intelligence quotient (IQ) points per year (95% CI, 0.29-0.42; P < .001), a significantly faster decline than those with other psychotic disorders (0.15 IQ points per year; 95% CI, 0.08-0.22, P < .001). At 22 years after onset, both groups declined at a rate of 0.59 IQ points per year (95% CI, 0.25-0.94; P < .001). Conclusions and Relevance: In this cohort study, cognitive trajectories in schizophrenia were consistent with both a neurodevelopmental and neurodegenerative pattern, resulting in a loss of 16 IQ points over the period of observation. Cognitive decline began long prior to psychosis onset, suggesting the window for primary prevention is earlier than previously thought. A window for secondary prevention emerges in the third decade of illness, when cognitive declines accelerate in individuals with schizophrenia and other psychotic disorders.

Pleasant and unpleasant odor identification ability is associated with distinct dimensions of negative symptoms transdiagnostically in psychotic disorders.

Negative symptoms are among the greatest sources of functional impairment for individuals with schizophrenia, yet their mechanisms remain poorly understood. Olfactory impairment is associated with negative symptoms. The processing of pleasant olfactory stimuli is subserved by reward-related neural circuitry while unpleasant olfactory processing is subserved by emotion-related neural circuitry, suggesting that these two odor dimensions may offer a window into differential mechanisms of negative symptoms. We examined whether pleasant and unpleasant odor identification bears differential relationships with avolition and inexpressivity dimensions of negative symptoms, whether these relationships are transdiagnostic, and whether pleasant and unpleasant odor processing also relate differently to other domains of functioning in a sample of individuals diagnosed with schizophrenia (N = 54), other psychotic disorders (N = 65), and never-psychotic adults (N = 160). Hierarchical regressions showed that pleasant odor identification was uniquely associated with avolition, while unpleasant odor identification was uniquely associated with inexpressivity. These relationships were largely transdiagnostic across groups. Additionally, pleasant and unpleasant odor identification displayed signs of specificity with other functional and cognitive measures. These results align with past work suggesting dissociable pathomechanisms of negative symptoms and provide a potential avenue for future work using valence-specific olfactory dysfunction as a semi-objective and low-cost marker for understanding and predicting the severity of specific negative symptom profiles.

Predicting Long-Term Outcomes in First-Admission Psychosis: Does the Hierarchical Taxonomy of Psychopathology Aid DSM in Prognostication?

The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirical, dimensional model of psychological symptoms and functioning. Its goals are to augment the use and address the limitations of traditional diagnoses, such as arbitrary thresholds of severity, within-disorder heterogeneity, and low reliability. HiTOP has made inroads to addressing these problems, but its prognostic validity is uncertain. The present study sought to test the prediction of long-term outcomes in psychotic disorders was improved when the HiTOP dimensional approach was considered along with traditional (ie, DSM) diagnoses. We analyzed data from the Suffolk County Mental Health Project (N = 316), an epidemiologic study of a first-admission psychosis cohort followed for 20 years. We compared 5 diagnostic groups (schizophrenia/schizoaffective, bipolar disorder with psychosis, major depressive disorder with psychosis, substance-induced psychosis, and other psychoses) and 5 dimensions derived from the HiTOP thought disorder spectrum (reality distortion, disorganization, inexpressivity, avolition, and functional impairment). Both nosologies predicted a significant amount of variance in most outcomes. However, except for cognitive functioning, HiTOP showed consistently greater predictive power across outcomes-it explained 1.7-fold more variance than diagnoses in psychiatric and physical health outcomes, 2.1-fold more variance in community functioning, and 3.4-fold more variance in neural responses. Even when controlling for diagnosis, HiTOP dimensions incrementally predicted almost all outcomes. These findings support a shift away from the exclusive use of categorical diagnoses and toward the incorporation of HiTOP dimensions for better prognostication and linkage with neurobiology.