Multimodal fusion of brain signals for robust prediction of psychosis transition.

The prospective study of youths at clinical high risk (CHR) for psychosis, including neuroimaging, can identify neural signatures predictive of psychosis outcomes using algorithms that integrate complex information. Here, to identify risk and psychosis conversion, we implemented multiple kernel learning (MKL), a multimodal machine learning approach allowing patterns from each modality to inform each other. Baseline multimodal scans (n = 74, 11 converters) included structural, resting-state functional imaging, and diffusion-weighted data. Multimodal MKL outperformed unimodal models (AUC = 0.73 vs. 0.66 in predicting conversion). Moreover, patterns learned by MKL were robust to training set variations, suggesting it can identify cross-modality redundancies and synergies to stabilize the predictive pattern. We identified many predictors consistent with the literature, including frontal cortices, cingulate, thalamus, and striatum. This highlights the advantage of methods that leverage the complex pathophysiology of psychosis.

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.

A feasibility and pilot trial of the Brief Educational Guide for Individuals in Need (BEGIN): Psychoeducation for individuals at risk for psychosis.

Individuals at clinical high risk for psychosis (CHR) report a strong desire for psychoeducation, and clinical guidelines recommend psychoeducation in early psychosis care. Although several CHR psychoeducation models have been developed, additional research is needed to establish the effectiveness of these models. The goal of this study was to conduct a pilot trial of the Brief Educational Guide for Individuals in Need (BEGIN). BEGIN is a brief structured psychoeducation intervention designed to educate CHR individuals on symptoms and treatment options. We conducted a feasibility and pilot study of 25 CHR individuals (60% female, Mage = 20.6, 64% non-White, 52% Hispanic/Latino) identified via the Structured Interview for Psychosis Risk Syndromes. Qualitative interviews were administered to learn about their experience and analyzed using iterative thematic analysis. Participants (n = 12) completed pre- and post-BEGIN self-report measures to assess factors that influence treatment engagement, including CHR knowledge and motivation for therapy. Data were analyzed using Hedges' g effect sizes and paired samples t tests. The intervention completion rate (83%) and therapeutic alliance were high. Qualitative themes and quantitative measures converged on similar results showing how CHR individuals were impacted by receiving psychoeducation via BEGIN, including increased CHR knowledge (g = 1.37), competence to monitor symptoms (g = 0.53), hope (g = 0.87), and motivation for therapy (g = 0.46). This study demonstrated the feasibility, acceptability, and potential benefits of the BEGIN CHR psychoeducation model, including enhancing motivation for treatment. The flexible but standardized format can facilitate BEGIN's implementation and dissemination.This pilot study found that the Brief Educational Guide for Individuals in Need (BEGIN), a standardized five-session psychoeducation intervention for individuals at clinical high risk for psychosis (CHR), was feasible, acceptable, and enhanced mental health literacy and motivation for subsequent treatment. Clinicians can utilize the BEGIN intervention to ensure the empathic provision of psychoeducation when disclosing patients' CHR status. Future research with a larger sample will establish efficacy and the development of a clinician training to facilitate implementation (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk.

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 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 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-including those 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.

Association between doxycycline use and long-term functioning in patients with schizophrenia.

IMPORTANCE AND OBJECTIVE: The brain-penetrant tetracycline antibiotics, minocycline and doxycycline, have been proposed as potential candidate drugs for treatment of schizophrenia, based on preclinical studies and clinical trials. A potential long-term beneficial effect of these antibiotics for schizophrenia patients has not been investigated. This study was designed to determine if redemption of doxycycline prescription in schizophrenia is associated with decreased incidence of disability pension, a proxy for long-term functioning. DESIGN: We performed a population-based cohort study with data from schizophrenia patients available through the Danish registers. Survival analysis models with time-varying covariates were constructed to assess incidence rate ratios (IRR) of disability pension after exposure to doxycycline or a non-brain penetrant tetracycline, defined as at least one filled prescription. The analysis was adjusted for age, sex, calendar year, parental psychiatric status and educational level. RESULTS: We used data from 11,157 individuals with schizophrenia (4,945 female and 6,212 male; average age 22.4 years old, standard deviation (std) 4.50). 718 of these were exposed to brain-penetrant doxycycline, and 1,498 individuals redeemed a prescription of one or more of the non-brain-penetrant tetracyclines. The average years at risk per person in this cohort was 4.9, and 2,901 individuals received disability pension in the follow-up period. There was a significantly lower incidence rate of disability pension in schizophrenia patients who had redeemed doxycycline compared to patients who did not redeem a prescription of any tetracycline antibiotics (Incidence rate ratio (IRR) 0.68; 95 % CI 0.56, 0.83). There was also a significant lower rate of disability pension in schizophrenia patients who redeemed doxycycline compared to individuals who redeemed a prescription of one of the non-brain penetrant tetracycline antibiotics (IRR 0.69 95 % CI 0.55, 0.87). CONCLUSIONS: In this observational study, doxycycline exposure is associated with a reduced incidence of disability pension. These data support further studies on the potential long term neuroprotective effects of doxycycline and level of functioning in schizophrenia patients.

Securing direct stakeholder feedback to inform clinical research in serious mental illness: Results of a patient and family perspectives survey.

Mental illness research routinely includes unfamiliar or potentially frightening procedures like lumbar puncture (LP), contributing to low enrollment and retention. Previous studies related to LP acceptance have focused on older individuals, and little information on participant preferences for educational materials is available. We developed an online survey assessing existing knowledge, comfort and concerns, and preferences for educational materials in the context of our clinical study on schizophrenia spectrum conditions (SSCs). We found that participants were generally knowledgeable and interested in engaging with clinical SSC research. Frequency of engagement with research publications differed significantly by participant groups and age. Comfort levels were consistently highest for study procedures other than LP, though surprisingly the average number of informational needs per procedure was not significantly different for LP compared to other procedures. Preferences for format and source of educational materials varied across participant groups and age. Our results suggest that younger individuals with an SSC diagnosis are likely to have limited exposure to information, and proactively providing accessible and accurate educational materials may improve positive perceptions of LP. Providing content in a range of formats and sources will ensure that participants and their support networks have access to their preferred resources.

Differential Expression of Anomalous Self-Experiences in Spontaneous Speech in Clinical High-Risk and Early-Course Psychosis Quantified by Natural Language Processing.

BACKGROUND: Basic self-disturbance, or anomalous self-experiences (ASEs), is a core feature of the schizophrenia spectrum. We propose a novel method of natural language processing to quantify ASEs in spoken language by direct comparison to an inventory of self-disturbance, the Inventory of Psychotic-Like Anomalous Self-Experiences (IPASE). We hypothesized that there would be increased similarity in open-ended speech to the IPASE items in individuals with early-course psychosis (PSY) compared with healthy individuals, with clinical high-risk (CHR) individuals intermediate in similarity. METHODS: Open-ended interviews were obtained from 170 healthy control participants, 167 CHR participants, and 89 PSY participants. We calculated the semantic similarity between IPASE items and "I" sentences from transcribed speech samples using S-BERT (Sentence Bidirectional Encoder Representation from Text). Kolmogorov-Smirnov tests were used to compare distributions across groups. A nonnegative matrix factorization of cosine similarity was performed to rank IPASE items. RESULTS: Spoken language of CHR individuals had the greatest semantic similarity to IPASE items when compared to both healthy control (s = 0.44, p < 10-14) and PSY (s = 0.36, p < 10-6) individuals, while IPASE scores were higher among PSY than CHR group participants. In addition, the nonnegative matrix factorization approach produced a data-driven domain that differentiated the CHR group from the others. CONCLUSIONS: We found that open-ended interviews elicited language with increased semantic similarity to the IPASE by participants in the CHR group compared with patients with psychosis. This demonstrates the utility of these methods for differentiating patients from healthy control participants. This complementary approach has the capacity to scale to large studies investigating phenomenological features of schizophrenia and potentially other clinical populations.

ChatGPT and Bard exhibit spontaneous citation fabrication during psychiatry literature search.

ChatGPT (Generative Pre-Trained Transformer) is a large language model (LLM), which comprises a neural network that has learned information and patterns of language use from large amounts of text on the internet. ChatGPT, introduced by OpenAI, responds to human queries in a conversational manner. Here, we aimed to assess whether ChatGPT could reliably produce accurate references to supplement the literature search process. We describe our March 2023 exchange with ChatGPT, which generated thirty-five citations, two of which were real. 12 citations were similar to actual manuscripts (e.g., titles with incorrect author lists, journals, or publication years) and the remaining 21, while plausible, were in fact a pastiche of multiple existent manuscripts. In June 2023, we re-tested ChatGPT's performance and compared it to that of Google's GPT counterpart, Bard 2.0. We investigated performance in English, as well as in Spanish and Italian. Fabrications made by LLMs, including erroneous citations, have been called "hallucinations"; we discuss reasons for which this is a misnomer. Furthermore, we describe potential explanations for citation fabrication by GPTs, as well as measures being taken to remedy this issue, including reinforcement learning. Our results underscore that output from conversational LLMs should be verified.

Detecting at-risk mental states for psychosis (ARMS) using machine learning ensembles and facial features.

AIMS: Our study aimed to develop a machine learning ensemble to distinguish "at-risk mental states for psychosis" (ARMS) subjects from control individuals from the general population based on facial data extracted from video-recordings. METHODS: 58 non-help-seeking medication-naïve ARMS and 70 healthy subjects were screened from a general population sample. At-risk status was assessed with the Structured Interview for Prodromal Syndromes (SIPS), and "Subject's Overview" section was filmed (5-10 min). Several features were extracted, e.g., eye and mouth aspect ratio, Euler angles, coordinates from 51 facial landmarks. This elicited 649 facial features, which were further selected using Gradient Boosting Machines (AdaBoost combined with Random Forests). Data was split in 70/30 for training, and Monte Carlo cross validation was used. RESULTS: Final model reached 83 % of mean F1-score, and balanced accuracy of 85 %. Mean area under the curve for the receiver operator curve classifier was 93 %. Convergent validity testing showed that two features included in the model were significantly correlated with Avolition (SIPS N2 item) and expression of emotion (SIPS N3 item). CONCLUSION: Our model capitalized on short video-recordings from individuals recruited from the general population, effectively distinguishing between ARMS and controls. Results are encouraging for large-screening purposes in low-resource settings.

Gesticulation in individuals with at risk mental states for psychosis.

Nonverbal communication (NVC) is a complex behavior that involves different modalities that are impaired in the schizophrenia spectrum, including gesticulation. However, there are few studies that evaluate it in individuals with at-risk mental states (ARMS) for psychosis, mostly in developed countries. Given our prior findings of reduced movement during speech seen in Brazilian individuals with ARMS, we now aim to determine if this can be accounted for by reduced gesticulation behavior. Fifty-six medication-naïve ARMS and 64 healthy controls were filmed during speech tasks. The frequency of specifically coded gestures across four categories (and self-stimulatory behaviors) were compared between groups and tested for correlations with prodromal symptoms of the Structured Interview for Prodromal Syndromes (SIPS) and with the variables previously published. ARMS individuals showed a reduction in one gesture category, but it did not survive Bonferroni's correction. Gesture frequency was negatively correlated with prodromal symptoms and positively correlated with the variables of the amount of movement previously analyzed. The lack of significant differences between ARMS and control contradicts literature findings in other cultural context, in which a reduction is usually seen in at-risk individuals. However, gesture frequency might be a visual proxy of prodromal symptoms, and of other movement abnormalities. Results show the importance of analyzing NVC in ARMS and of considering different cultural and sociodemographic contexts in the search for markers of these states.

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 partial harmonization for CHR-P criteria. The semi-structured interview, named P ositive SY mptoms and Diagnostic Criteria for the C AARMS H armonized with the S IPS (PSYCHS), generates CHR-P criteria and severity scores for both CAARMS and SIPS. Conclusion: 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.

A Sex-Dependent Association Between Doxycycline Use and Development of Schizophrenia.

BACKGROUND: Doxycycline and minocycline are brain-penetrant tetracycline antibiotics, which recently gained interest because of their immunomodulatory and neuroprotective properties. Observational studies have suggested that exposure to these drugs may decrease the risk to develop schizophrenia, but results are inconsistent. The aim of this study was to investigate the potential association between doxycycline use and later onset of schizophrenia. DESIGN: We used data from 1 647 298 individuals born between 1980 and 2006 available through Danish population registers. 79 078 of those individuals were exposed to doxycycline, defined as redemption of at least 1 prescription. Survival analysis models stratified for sex with time-varying covariates were constructed to assess incidence rate ratios (IRRs) for schizophrenia (ICD-10 code F20.xx), with adjustment for age, calendar year, parental psychiatric status, and educational level. RESULTS: In the non-stratified analysis, there was no association between doxycycline exposure and schizophrenia risk. However, men who redeemed doxycycline had a significantly lower incidence rate for schizophrenia onset compared to men that did not (IRR 0.70; 95% CI 0.57-0.86). By contrast, women had a significantly higher incidence rate for schizophrenia onset, compared to women that did not redeem doxycycline prescriptions (IRR 1.23; 95% CI 1.08, 1.40). The effects were not found for other tetracycline antibiotics (IRR 1.00; 95% CI 0.91, 1.09). CONCLUSIONS: Doxycycline exposure is associated with a sex-dependent effect on schizophrenia risk. The next steps are replication of the results in independent well-characterized population cohorts, as well as preclinical studies to investigate sex-specific effects of doxycycline on biological mechanisms implicated in schizophrenia.

The association between mental health stigma and face emotion recognition in individuals at risk for psychosis.

Self-stigma has been associated with reduced accuracy of face emotion recognition in individuals at clinical high risk for psychosis (CHR). Stigma may also relate to slowing of performance during cognitive tasks for which a negative stereotype is relevant. This study aimed to investigate the association of mental illness stigma with face emotion recognition among CHR individuals. Participants were 143 CHR individuals identified using the Structured Interview for Psychosis-Risk Syndromes (SIPS). Face emotion recognition was assessed using the Penn Emotion Recognition Task (ER-40). Stigma was assessed using discrimination, stereotype awareness, and stereotype agreement subscales of the Mental Health Attitudes Interview for CHR. We tested associations of ER-40 accuracy and response times with these stigma variables, including the role of clinical and demographic factors. Racial/ethnic minoritized participants had higher attenuated positive symptoms than non-minoritized participants. Longer ER-40 response times were correlated with greater stereotype agreement (r=.17, p=.045) and discrimination (r=.22, p=.012). A regression model predicting ER-40 response times revealed an interaction of stereotype agreement with minoritized status (p=.008), with slower response times for minoritized participants as stereotype agreement increased. Greater disorganized symptoms and male gender also predicted longer response times. ER-40 accuracy was not associated with stigma. Overall, minoritized CHR individuals with greater internalized stigma took longer to identify face emotions. Future research is needed to assess whether slower response times are specific to social cues, and if internalized stigma interferes with performance in real-world social situations. Reducing stigma may be an important target for interventions that aim to improve social skills.

Linguistic correlates of suicidal ideation in youth at clinical high-risk for psychosis.

Suicidal ideation (SI) is prevalent among individuals at clinical high-risk for psychosis (CHR). Natural language processing (NLP) provides an efficient method to identify linguistic markers of suicidality. Prior work has demonstrated that an increased use of "I", as well as words with semantic similarity to "anger", "sadness", "stress" and "lonely", are correlated with SI in other cohorts. The current project analyzes data collected in an SI supplement to an NIH R01 study of thought disorder and social cognition in CHR. This study is the first to use NLP analyses of spoken language to identify linguistic correlates of recent suicidal ideation among CHR individuals. The sample included 43 CHR individuals, 10 with recent suicidal ideation and 33 without, as measured by the Columbia-Suicide Severity Rating Scale, as well as 14 healthy volunteers without SI. NLP methods include part-of-speech (POS) tagging, a GoEmotions-trained BERT Model, and Zero-Shot Learning. As hypothesized, individuals at CHR for psychosis who endorsed recent SI utilized more words with semantic similarity to "anger" compared to those who did not. Words with semantic similarity to "stress", "loneliness", and "sadness" were not significantly different between the two CHR groups. Contrary to our hypotheses, CHR individuals with recent SI did not use the word "I" more than those without recent SI. As anger is not characteristic of CHR, findings have implications for the consideration of subthreshold anger-related sentiment in suicidal risk assessment. As NLP is scalable, findings suggest that language markers may improve suicide screening and prediction in this population.

Natural Language Processing Markers for Psychosis and Other Psychiatric Disorders: Emerging Themes and Research Agenda From a Cross-Linguistic Workshop.

This workshop summary on natural language processing (NLP) markers for psychosis and other psychiatric disorders presents some of the clinical and research issues that NLP markers might address and some of the activities needed to move in that direction. We propose that the optimal development of NLP markers would occur in the context of research efforts to map out the underlying mechanisms of psychosis and other disorders. In this workshop, we identified some of the challenges to be addressed in developing and implementing NLP markers-based Clinical Decision Support Systems (CDSSs) in psychiatric practice, especially with respect to psychosis. Of note, a CDSS is meant to enhance decision-making by clinicians by providing additional relevant information primarily through software (although CDSSs are not without risks). In psychiatry, a field that relies on subjective clinical ratings that condense rich temporal behavioral information, the inclusion of computational quantitative NLP markers can plausibly lead to operationalized decision models in place of idiosyncratic ones, although ethical issues must always be paramount.

Psychoeducation for individuals at clinical high risk for psychosis: A scoping review.

Psychoeducation is recommended in the treatment of patients with schizophrenia and has been shown to improve satisfaction with mental health service and treatment adherence, reduce relapse and hospital readmission rates, and enhance functioning and quality of life. Youth at clinical high risk for psychosis (CHR) may also benefit from receiving psychoeducation as part of their treatment. The goal of this study was to conduct a scoping review to map out the existing literature on psychoeducation for CHR individuals, including content, utilization, and benefits, in order to identify areas for future research and clinical care. Following PRISMA guidelines, we conducted a systematic search of electronic databases (MEDLINE, Embase, PsycINFO, Scopus, and Web of Science Core Collection) to identify literature through 02/25/2022 that provided data or significant commentary about the provision of psychoeducation to CHR individuals. After screening titles and abstracts, four co-authors assessed full-text articles for eligibility. Thirty-three studies were included in the review. Psychoeducation is recommended in the treatment of CHR individuals, is a preferred treatment option among CHR individuals, and many CHR programs report offering psychoeducation. However, details about the psychoeducational content and method of delivery are notably absent from recommendations and reports on the provision of CHR psychoeducation in real-world settings. We identified two brief and structured CHR psychoeducation interventions and one longer-term psychoeducational multifamily group model for CHR that show feasibility and promise, though they have not yet undergone randomized trials to evaluate effectiveness of the psychoeducation. We also identified several comprehensive CHR interventions that included an explicit psychoeducation module, though the unique role of the psychoeducational component is unknown. Despite being recommended as a critical component of treatment for CHR individuals and preferred by CHR individuals, the ways in which psychoeducation are being delivered to CHR individuals in real-world practice is still largely ambiguous. Rigorous evaluations of psychoeducation treatment models are needed, as well as investment from clinical programs to facilitate the implementation and dissemination of standardized psychoeducation for CHR individuals.

Emergence of Language Related to Self-experience and Agency in Autobiographical Narratives of Individuals With Schizophrenia.

BACKGROUND AND HYPOTHESIS: Disturbances in self-experience are a central feature of schizophrenia and its study can enhance phenomenological understanding and inform mechanisms underlying clinical symptoms. Self-experience involves the sense of self-presence, of being the subject of one's own experiences and agent of one's own actions, and of being distinct from others. Self-experience is traditionally assessed by manual rating of interviews; however, natural language processing (NLP) offers automated approach that can augment manual ratings by rapid and reliable analysis of text. STUDY DESIGN: We elicited autobiographical narratives from 167 patients with schizophrenia or schizoaffective disorder (SZ) and 90 healthy controls (HC), amounting to 490 000 words and 26 000 sentences. We used NLP techniques to examine transcripts for language related to self-experience, machine learning to validate group differences in language, and canonical correlation analysis to examine the relationship between language and symptoms. STUDY RESULTS: Topics related to self-experience and agency emerged as significantly more expressed in SZ than HC (P < 10-13) and were decoupled from similarly emerging features such as emotional tone, semantic coherence, and concepts related to burden. Further validation on hold-out data showed that a classifier trained on these features achieved patient-control discrimination with AUC = 0.80 (P < 10-5). Canonical correlation analysis revealed significant relationships between self-experience and agency language features and clinical symptoms. CONCLUSIONS: Notably, the self-experience and agency topics emerged without any explicit probing by the interviewer and can be algorithmically detected even though they involve higher-order metacognitive processes. These findings illustrate the utility of NLP methods to examine phenomenological aspects of schizophrenia.