Tobacco smoking and nicotine vaping in persons with first episode psychosis.

Tobacco smoking is highly prevalent in persons with psychosis and is the leading cause of preventable mortality in this population. Less is known about tobacco smoking in persons with first episode psychosis (FEP) and there have been no estimates about the prevalence of nicotine vaping in FEP. This study reports rates of tobacco smoking and nicotine vaping in young people with FEP enrolled in Coordinated Specialty Care programs in Pennsylvania and Maryland. Using data collected from 2021 to 2023, we examined lifetime and recent smoking and vaping and compared smokers and vapers to nonusers on symptoms, functioning, and substance use. The sample included 445 participants aged 13-35 with recent psychosis onset. Assessments were collected by program staff. Overall, 28 % of participants engaged in either smoking or vaping within 30 days of the admission assessment. Smokers and vapers were disproportionately male, cannabis users, and had lower negative symptom severity than non-smokers. Vapers had higher role and social functioning. Both smoking and vaping were related to a longer time from psychosis onset to program enrollment. We compare these findings to previous studies and suggest steps for addressing smoking and vaping in this vulnerable population.

A reduction in cigarette smoking improves health-related quality of life and does not worsen psychiatric symptoms in individuals with serious mental illness.

INTRODUCTION: Individuals with serious mental illness (SMI) smoke cigarettes at a much higher rate than the general population, increasing their risk for medical illnesses and mortality. However, individuals with SMI do not get enough support to quit smoking, partially because of concerns from medical providers that reducing smoking may worsen their symptoms or quality of life. METHODS: Veterans with SMI and nicotine dependence (n = 178) completed a 12-week smoking cessation trial (parent trial dates: 2010-2014) including assessments of smoking status, psychiatric symptoms (Brief Psychiatric Rating Scale), and quality of life (Lehman Quality of Life Interview-Short Version) at up to four time points: baseline, post-treatment, three-month follow-up, and 9-month follow-up. Bayesian multilevel modeling estimated the impact of changes in the self-reported number of cigarettes per day in the past seven days on psychiatric symptoms and quality of life. RESULTS: Between subjects, each additional pack of cigarettes smoked per day was associated with a 0.83 point higher score (95%CI: 0.03 to 1.7) on a negative symptoms scale ranging from 0 to 35. Within subjects, each one-pack reduction in the number of cigarettes smoked per day was associated with an improvement of 0.32 (95%CI = 0.12 to 0.54) on the health-related quality of life scale, which ranges from 0 to 7 points. There were no other significant between- or within-subjects effects of smoking on psychiatric symptoms or quality of life. CONCLUSIONS: Individuals with SMI and their providers should pursue smoking cessation without fear of worsening psychiatric symptoms or quality of life.

Frequency and predictors of virtual hope box use in individuals experiencing suicidal ideation: An ecological momentary assessment investigation.

INTRODUCTION: The Virtual Hope Box (VHB) is a smartphone application designed to support emotion regulation when one is distressed, in a crisis, or experiencing suicidal ideation (SI). Initial proof of concept studies indicate that individuals are more likely to use the VHB than traditional hope boxes, and find it both easy to setup and helpful. To our knowledge, no studies have harnessed ambulatory assessment methodology to assess VHB use as it relates to incidence of suicidal thinking. METHODS: As such, we recruited N = 50 undergraduates who endorsed SI either the past year or past 2 weeks to complete a 10-day investigation. At baseline, participants were oriented to the VHB and instructed on how to use the application. Over the next 10 days, participants responded to prompts five times per day on their personal smartphones regarding their current experiences of SI and stress as well as VHB usage. RESULTS: Results found that most participants used the VHB at least once, rated its usefulness as high, and rated their perceived likelihood of future use as high. In addition, increases in state SI severity were related to subsequent VHB use. CONCLUSION: The VHB may be a useful tool for managing crises in undergraduates experiencing suicidal thoughts.

Computerized analysis of facial expression reveals objective indices of blunted facial affect.

Blunted affect is associated with severe mental illness, particularly schizophrenia. Mechanisms of blunted affect are poorly understood, potentially due to a lack of phenomenological clarity. Here, we examine clinician rated blunted affect and computerized facial metrics derived from ambulatory video assessment using machine learning. With high predictive accuracy (80-82%), we found that head orientation, eye movement, and facets of mouth movement were associated with clinical ratings of blunted affect. Features denoting larger muscle movements were associated with social cognition (R2 = 0.37) and cognition (R2 = 0.40). Findings provide potential insights on psychological and pathophysiological contributors to blunted affect.

The Temporal Dynamics of Wish to Live, Wish to Die, and Their Short-Term Prospective Relationships With Suicidal Desire.

The internal debate hypothesis (Kovacs & Beck, 1977) suggests that those at risk for suicidal thoughts and behaviors may experience fluctuations in both the wish to live (WTL) and wish to die (WTD). Previous research has investigated this hypothesis using various cross-sectional (Goods et al., 2019 [cf. Page & Stritzke, 2020]) and longitudinal methodologies (e.g., Bryan et al., 2016). No investigations have determined the within-day temporal dynamics of WTL and WTD using ecological moment assessment (EMA), however. N = 49 undergraduate university students recruited from a research participant pool from a large southeastern university in the United States with a lifetime history of suicide ideation completed the current 10-day EMA investigation. Results demonstrated that WTL, WTD, and resulting suicidal ambivalence (i.e., relatively equal WTL/WTD ratings) demonstrated similar within-person person variability; however, WTD scores appeared to demonstrate higher average variability compared to WTL and ambivalence scores. Although state WTL and WTD were concurrently related to state suicidal desire, only WTD prospectively predicted suicidal desire when controlling for the influence of the outcome variable at the previous timepoint. Ambivalence scores also prospectively predicted suicidal desire when controlling for suicidal desire at the previous timepoint. Results support the clinical and theoretical utility of separate WTL and WTD assessment. WTD was relatively stable within this sample but may be closely related to risk for future suicidal thinking. Changes in WTL may reduce state risk for suicidal desire but could be more trait-like in nature compared to WTD. Future research that investigates these hypotheses should consider the study limitations outlined.

Alogia and pressured speech do not fall on a continuum of speech production using objective speech technologies.

Speech production is affected in a variety of serious mental illnesses (SMI; e.g., schizophrenia, unipolar depression, bipolar disorders) and at its extremes can be observed in the gross reduction of speech (e.g., alogia) or increase of speech (e.g., pressured speech). The present study evaluated whether clinically-rated alogia and pressured speech represent antithetical constructs when analyzed using objective metrics of speech production. We examined natural speech using acoustic and natural language processing features from two archival studies using several different speaking tasks and a combined 107 patients meeting criteria for SMI. Contrary to expectations, we did not find that alogia and pressured speech presented as opposing ends of a speech production continuum. Objective speech markers were associated with clinically rated alogia but not pressured speech, and these results were consistent across speaking tasks and studies. Implications for our understanding of speech production symptoms in SMI are discussed, as well as implications for Natural Language Processing and digital phenotyping efforts more generally.

Examining the Interrelationships Among Suicide Cognitions, Suicidal Ideation, and Theoretically Derived Protective Factors.

INTRODUCTION: Several protective factors for mitigating suicidal ideation (SI) such as positive affect, reasons for living, purpose in life, meaning in life, gratitude, grit, optimism, social support, and hope have been identified and received empirical support. However, few studies have examined the interrelationships of these protective factors and the identification of protective factors most closely linked to lower levels of SI may be useful for both theory-building initiatives and improvement of suicide-specific interventions. Network analysis offers an approach for testing the relation among these constructs, SI, and suicide risk factors. METHODS: A sample N = 557 undergraduate students oversampled for lifetime SI completed a cross-sectional, online survey. The data was used to estimate an undirected, cross-sectional network of the aforementioned protective factors. RESULTS: The resulting inferred network implicates strong negative influence of suicide cognitions, but not recent SI, and the strong positive influence of presence of meaning in life, trait hope, and low negative affect. CONCLUSIONS: Implications for dimensionality of SI versus suicide cognitions, targeting presence of meaning in life, trait hope, and negative affect in treatment, and cross-cultural variations in reasons for living are discussed. The study is limited by the cross-sectional and convenience sampling methodology.HighlightsProtective factors may have less direct influence on suicidal ideationSuicide cognitions and the suicidal mode may be of phenomenological importancePresence of meaning and trait hope may be primary targets for suicide interventions.

Talking about Health: A Topic Analysis of Narratives from Individuals with Schizophrenia and Other Serious Mental Illnesses.

Individuals with schizophrenia have higher mortality and shorter lifespans. There are a multitude of factors which create these conditions, but one aspect is worse physical health, particularly cardiovascular and metabolic health. Many interventions to improve the health of individuals with schizophrenia have been created, but on the whole, there has been limited effectiveness in improving quality of life or lifespan. One potential new avenue for inquiry involves a more patient-centric perspective; understanding aspects of physical health most important, and potentially most amenable to change, for individuals based on their life narratives. This study used topic modeling, a type of Natural Language Processing (NLP) on unstructured speech samples from individuals (n = 366) with serious mental illness, primarily schizophrenia, in order to extract topics. Speech samples were drawn from three studies collected over a decade in two geographically distinct regions of the United States. Several health-related topics emerged, primarily centered around food, living situation, and lifestyle (e.g., routine, hobbies). The implications of these findings for how individuals with serious mental illness and schizophrenia think about their health, and what may be most effective for future health promotion policies and interventions, are discussed.

Natural Language Processing and Psychosis: On the Need for Comprehensive Psychometric Evaluation.

BACKGROUND AND HYPOTHESIS: Despite decades of "proof of concept" findings supporting the use of Natural Language Processing (NLP) in psychosis research, clinical implementation has been slow. One obstacle reflects the lack of comprehensive psychometric evaluation of these measures. There is overwhelming evidence that criterion and content validity can be achieved for many purposes, particularly using machine learning procedures. However, there has been very little evaluation of test-retest reliability, divergent validity (sufficient to address concerns of a "generalized deficit"), and potential biases from demographics and other individual differences. STUDY DESIGN: This article highlights these concerns in development of an NLP measure for tracking clinically rated paranoia from video "selfies" recorded from smartphone devices. Patients with schizophrenia or bipolar disorder were recruited and tracked over a week-long epoch. A small NLP-based feature set from 499 language samples were modeled on clinically rated paranoia using regularized regression. STUDY RESULTS: While test-retest reliability was high, criterion, and convergent/divergent validity were only achieved when considering moderating variables, notably whether a patient was away from home, around strangers, or alone at the time of the recording. Moreover, there were systematic racial and sex biases in the model, in part, reflecting whether patients submitted videos when they were away from home, around strangers, or alone. CONCLUSIONS: Advancing NLP measures for psychosis will require deliberate consideration of test-retest reliability, divergent validity, systematic biases and the potential role of moderators. In our example, a comprehensive psychometric evaluation revealed clear strengths and weaknesses that can be systematically addressed in future research.

How do social factors relate to blunted facial affect in schizophrenia? A digital phenotyping study using ambulatory video recordings.

Clinical interviews and laboratory-based emotional induction paradigms provide consistent evidence that facial affect is blunted in many individuals with schizophrenia. Although it is clear that blunted facial affect is not a by-product of diminished emotional experience in schizophrenia, factors contributing to blunted affect remain unclear. The current study used a combination of ambulatory video recordings that were evaluated via computerized facial affect analysis and concurrently completed ecological momentary assessment surveys to assess whether blunted affect reflects insufficient reactivity to affective or contextual factors. Specifically, whether individuals with schizophrenia require more intense affective experiences to produce expression, or whether they are less reactive to social factors (i.e. being in the presence of others, social motivation). Participants included outpatients with schizophrenia (n = 33) and healthy controls (n = 31) who completed six days of study procedures. Multilevel linear models were evaluated using both Null-Hypothesis Statistical Testing and Bayesian analyses. Individuals with schizophrenia displayed comparable expression of positive and negative emotion to controls during daily life, and no evidence was found for a different intensity of experience required for expression in either group. However, social factors differentially influenced facial expression in schizophrenia compared to controls, such that individuals with schizophrenia did not modulate their expressions based on social motivation to the same extent as controls. These findings suggest that social motivation may play an important role in determining when blunting occurs.

Ambulatory audio and video recording for digital phenotyping in schizophrenia: Adherence & data usability.

Ambulatory audio and video recording provides a wealth of information which can be used for a broad range of applications, including digital phenotyping, telepsychiatry, and telepsychology. However, these technologies are in their infancy, and guidelines for their use and analysis have yet to be established. The current project used ambulatory assessment data from individuals with schizophrenia (N = 52) and controls (N = 55) over a week to assess factors influencing sufficiency and useability of video and audio data. Logistic multilevel models examined the effect of relevant variables on video provision and video quality. There was no difference by group in video provision or quality. Videos were less likely to be provided later in the study and later in the day. Video quality was lower later in the day, particularly for controls. Participants were more likely to provide videos if alone or at home than in other settings. Black participants were less likely to have analyzable video frames than White participants. These results suggest potential racial disparities in camera technologies and/or facial analysis algorithms. Implications of these findings and recommendations for future study development, such as instructions to provide to participants to optimize video quality, are discussed.

Computerized analysis of facial expressions in serious mental illness.

Blunted facial affect is a transdiagnostic component of Serious Mental Illness (SMI) and is associated with a host of negative outcomes. However, blunted facial affect is a poorly understood phenomenon, with no known cures or treatments. A critical step in better understanding its phenotypic expression involves clarifying which facial expressions are altered in specific ways and under what contexts. The current literature suggests that individuals with SMI show decreased positive facial expressions, but typical, or even increased negative facial expressions during laboratory tasks. While this literature has coalesced around general trends, significantly more nuance is available regarding what components facial expressions are atypical and how those components are associated with increased severity of clinical ratings. The present project leveraged computerized facial analysis to test whether clinician-rated blunted affect is driven by decreases in duration, intensity, or frequency of positive versus other facial expressions during a structured clinical interview. Stable outpatients meeting criteria for SMI (N = 59) were examined. Facial expression did not generally vary as a function of clinical diagnosis. Overall, clinically-rated blunted affect was not associated with positive expressions, but was associated with decreased surprise and increased anger, sadness, and fear expressions. Blunted affect is not a monolithic lack of expressivity, and increased precision in operationally defining it is critical for uncovering its causes and maintaining factors. Our discussion focuses on this effort, and on advancing digital phenotyping of blunted facial affect more generally.

High Predictive Accuracy of Negative Schizotypy With Acoustic Measures.

Negative schizotypal traits potentially can be digitally phenotyped using objective vocal analysis. Prior attempts have shown mixed success in this regard, potentially because acoustic analysis has relied on small, constrained feature sets. We employed machine learning to (a) optimize and cross-validate predictive models of self-reported negative schizotypy using a large acoustic feature set, (b) evaluate model performance as a function of sex and speaking task, (c) understand potential mechanisms underlying negative schizotypal traits by evaluating the key acoustic features within these models, and (d) examine model performance in its convergence with clinical symptoms and cognitive functioning. Accuracy was good (> 80%) and was improved by considering speaking task and sex. However, the features identified as most predictive of negative schizotypal traits were generally not considered critical to their conceptual definitions. Implications for validating and implementing digital phenotyping to understand and quantify negative schizotypy are discussed.

Predicting self-injurious thoughts in daily life using ambulatory assessment of state cognition.

Self-injurious thoughts (SITs) fluctuate considerably from moment to moment. As such, "static" and temporally stable predictors (e.g., demographic variables, prior history) are suboptimal in predicting imminent SITs. This concern is particularly true for "online" cognitive abilities, which are important for understanding SITs, but are typically measured using tests selected for temporal stability. Advances in ambulatory assessments (i.e., real-time assessment in a naturalistic environment) allow for measuring cognition with improved temporal resolution. The present study measured relationships between "state" cognitive performance, measured using an ambulatory-based Trail Making Test, and SITs. Self-reported state hope and social connectedness was also measured. Data were collected using a specially designed mobile application (administered 4x/week up to 28 days) in substance use inpatients (N = 99). Consistent with prior literature, state hope and social connectedness was significantly associated with state SITs. Importantly, poorer state cognitive performance also significantly predicted state SITs, independent of hallmark static and state self-report risk variables. These findings highlight the potential importance of "online" cognition to predict SITs. Ambulatory recording reflects an efficient, sensitive, and ecological valid methodology for evaluating subjective and objectives predictors of imminent SITs.

Digital phenotyping of negative symptoms: the relationship to clinician ratings.

Negative symptoms are a critical, but poorly understood, aspect of schizophrenia. Measurement of negative symptoms primarily relies on clinician ratings, an endeavor with established reliability and validity. There have been increasing attempts to digitally phenotype negative symptoms using objective biobehavioral technologies, eg, using computerized analysis of vocal, speech, facial, hand and other behaviors. Surprisingly, biobehavioral technologies and clinician ratings are only modestly inter-related, and findings from individual studies often do not replicate or are counterintuitive. In this article, we document and evaluate this lack of convergence in 4 case studies, in an archival dataset of 877 audio/video samples, and in the extant literature. We then explain this divergence in terms of "resolution"-a critical psychometric property in biomedical, engineering, and computational sciences defined as precision in distinguishing various aspects of a signal. We demonstrate how convergence between clinical ratings and biobehavioral data can be achieved by scaling data across various resolutions. Clinical ratings reflect an indispensable tool that integrates considerable information into actionable, yet "low resolution" ordinal ratings. This allows viewing of the "forest" of negative symptoms. Unfortunately, their resolution cannot be scaled or decomposed with sufficient precision to isolate the time, setting, and nature of negative symptoms for many purposes (ie, to see the "trees"). Biobehavioral measures afford precision for understanding when, where, and why negative symptoms emerge, though much work is needed to validate them. Digital phenotyping of negative symptoms can provide unprecedented opportunities for tracking, understanding, and treating them, but requires consideration of resolution.

Using machine learning of computerized vocal expression to measure blunted vocal affect and alogia.

Negative symptoms are a transdiagnostic feature of serious mental illness (SMI) that can be potentially "digitally phenotyped" using objective vocal analysis. In prior studies, vocal measures show low convergence with clinical ratings, potentially because analysis has used small, constrained acoustic feature sets. We sought to evaluate (1) whether clinically rated blunted vocal affect (BvA)/alogia could be accurately modelled using machine learning (ML) with a large feature set from two separate tasks (i.e., a 20-s "picture" and a 60-s "free-recall" task), (2) whether "Predicted" BvA/alogia (computed from the ML model) are associated with demographics, diagnosis, psychiatric symptoms, and cognitive/social functioning, and (3) which key vocal features are central to BvA/Alogia ratings. Accuracy was high (>90%) and was improved when computed separately by speaking task. ML scores were associated with poor cognitive performance and social functioning and were higher in patients with schizophrenia versus depression or mania diagnoses. However, the features identified as most predictive of BvA/Alogia were generally not considered critical to their operational definitions. Implications for validating and implementing digital phenotyping to reduce SMI burden are discussed.

Engagement in specialized early intervention services for psychosis as an interplay between personal agency and critical structures: A qualitative study.

BACKGROUND: Specialized early intervention programs for individuals experiencing a first episode of psychosis prioritize service engagement, generally operationalized as attendance, treatment completion, therapeutic alliance, and treatment adherence. However, there are critical theoretical and methodological gaps in understanding how service users experience and define their engagement with the service. OBJECTIVES: This study aimed to explore how current and former service users define their engagement with a specialized early intervention program. DESIGN: A qualitative descriptive approach was used to explore service users' decisions to use, remain involved with, and/or leave early intervention services. SETTING: This study took place in an early intervention service for psychosis in Montreal, Canada. PARTICIPANTS: Twenty-four participants who had experienced a first episode of psychosis and had been engaged in the service to varying degrees (fully engaged, partially engaged, disengaged) took part in in-depth interviews. METHODS: In-depth interviews were employed to collect rich insights into participants' experiences and perceptions. The interviews were transcribed and analysed using thematic analysis, beginning with an inductive approach and completing the analysis using a theoretical approach. During the analysis, our original notions of engagement and disengagement were challenged by theorizing engagement in terms of agency and structure. Researchers engaged in reflexive practices to maintain and promote research rigor and trustworthiness. RESULTS: Participants' narratives were thematically analyzed and organized into three themes: fluidity and temporality of engagement and disengagement; engagement as an ongoing negotiation; and critical structures and agency. Participants described engagement in a variety of ways, some of which were broader than service use and focused on self-care and commitment to recovery. These conceptions were subject to change as the individuals' perceptions of their needs changed. As needs changed, individuals also negotiated and renegotiated their care needs with themselves and with their treatment team. These exercises of agency were constrained by key structures: the treatment team, family and friends, and societal conceptions of mental health. CONCLUSIONS: Our study findings argue for an expanded definition of engagement which prioritizes individuals' experience and acknowledges the steps towards recovery that they may make outside of the purview of the service. It also underlines the importance of a treatment structure which aligns with individuals' needs for both support and autonomy.

Strengthening spatial reasoning: elucidating the attentional and neural mechanisms associated with mental rotation skill development.

Spatial reasoning is a critical skill in many everyday tasks and in science, technology, engineering, and mathematics disciplines. The current study examined how training on mental rotation (a spatial reasoning task) impacts the completeness of an encoded representation and the ability to rotate the representation. We used a multisession, multimethod design with an active control group to determine how mental rotation ability impacts performance for a trained stimulus category and an untrained stimulus category. Participants in the experimental group (n = 18) showed greater improvement than the active control group (n = 18) on the mental rotation tasks. The number of saccades between objects decreased and saccade amplitude increased after training, suggesting that participants in the experimental group encoded more of the object and possibly had more complete mental representations after training. Functional magnetic resonance imaging data revealed distinct neural activation associated with mental rotation, notably in the right motor cortex and right lateral occipital cortex. These brain areas are often associated with rotation and encoding complete representations, respectively. Furthermore, logistic regression revealed that activation in these brain regions during the post-training scan significantly predicted training group assignment. Overall, the current study suggests that effective mental rotation training protocols should aim to improve the encoding and manipulation of mental representations.

Ambulatory digital phenotyping of blunted affect and alogia using objective facial and vocal analysis: Proof of concept.

Negative symptoms reflect one of the most debilitating aspects of one of the most debilitating diseases known to humankind. As yet, our treatments for negative symptoms are palliative at best and our understanding of their causes is relatively superficial. To address this, we are developing objective ambulatory tools for digitally phenotyping their severity which can be used outside the confines of the traditional clinical and research settings. The present study evaluated the feasibility, reliability and validity of ambulatory vocal acoustic and facial emotion expression analysis. Videos were provided by 25 patients with schizophrenia or schizoaffective disorder and 27 nonpsychiatric controls using inexpensive, non-invasive ambulatory recording methods. Controls provided 411 video recordings, and patients provided 377 video recordings; an average of 15.22 and 14.50 per participant per group respectively. The vast majority (over 80%) of these videos were usable for analysis. An empirically-supported, limited-feature vocal (7 features) and facial (3 features) set was examined. Within participants, these features varied considerably over time, but showed moderate to good test-retest reliability in many cases once contextual factors (e.g., activity involved in at the time of testing) were accounted for. Vocal and facial features showed statistically significant convergence with a "gold standard" negative symptom measure. Ambulatory vocal/facial features were more strongly associated with engagement in social or work activities in patients than negative symptom ratings. These data support the use of ambulatory vocal/facial analytic technologies for digital phenotyping of these negative symptoms.