A preliminary study examining terminology used by individuals with lived experience describing beliefs about being targeted or harmed by others.

While recent studies have prompted re-evaluation of the term "schizophrenia," few have examined the use of terms to describe persecutory ideation (PI) or paranoia. This study examines the preferences and terms used by a cross-diagnostic population of individuals (N = 184) with lived experience using an online survey. Participants most commonly described their PI in terms of the perceived source of threat, followed by clinical language, most commonly variants of "paranoia" and "anxiety." Of five selected terms assessed quantitatively - "anxiety," "paranoia," "persecutory thoughts," "suspiciousness," and "threat thoughts" - participants were more likely to report that "anxiety" aligned with their experience of PI, followed by "suspiciousness." Endorsement of terms more specific to PI was associated with self-report PI severity, while a preference for "anxiety" over other terms was both associated with less severe PI and lower scores on a measure of stigma. These results suggest that the heterogeneity of terms used by individuals with lived experience support a person-centered approach to language describing such experiences.

Automated Detection of Cognitive Distortions in Text Exchanges Between Clinicians and People With Serious Mental Illness.

OBJECTIVE: The authors tested whether natural language processing (NLP) methods can detect and classify cognitive distortions in text messages between clinicians and people with serious mental illness as effectively as clinically trained human raters. METHODS: Text messages (N=7,354) were collected from 39 clients in a randomized controlled trial of a 12-week texting intervention. Clinical annotators labeled messages for common cognitive distortions: mental filtering, jumping to conclusions, catastrophizing, "should" statements, and overgeneralizing. Multiple NLP classification methods were applied to the same messages, and performance was compared. RESULTS: A tuned model that used bidirectional encoder representations from transformers (F1=0.62) achieved performance comparable to that of clinical raters in classifying texts with any distortion (F1=0.63) and superior to that of other models. CONCLUSIONS: NLP methods can be used to effectively detect and classify cognitive distortions in text exchanges, and they have the potential to inform scalable automated tools for clinical support during message-based care for people with serious mental illness.

The relationship between appraisals of auditory verbal hallucinations and real-time affect and social functioning.

In addition to being a hallmark symptom of schizophrenia-spectrum disorders, auditory verbal hallucinations (AVH) are present in a range of psychiatric disorders as well as among individuals who are otherwise healthy. People who experience AVH are heterogeneous, and research has aimed to better understand what characteristics distinguish, among those who experience AVH, those who experience significant disruption and distress from those who do not. The cognitive model of AVH suggests that appraisals of voices determine the extent to which voices cause distress and social dysfunction. Previous work has relied largely on comparisons of "clinical" and "non-clinical" voice hearers, and few studies have been able to provide insight into the moment-to-moment relationships between appraisals and outcomes. The current study examines longitudinal data provided through ecological momentary assessment and passive sensors of 465 individuals who experience cross-diagnostic AVH. Results demonstrated associations of AVH appraisals to negative affect and social functioning. Above and beyond within-individual averages, when a participant reported increased appraisals of their voices as powerful and difficult to control, they were more likely to feel increased negative affect and reduced feelings of safety. AVH power appraisals were also associated with next-day number and duration of phone calls placed, and AVH controllability appraisals were associated with increased time near speech and reduced next-day time away from primary location. These results suggest that appraisals are state-like characteristics linked with day-to-day and moment-to-moment changes in impactful affective and behavioral outcomes; intervention approaches should aim to address these domains in real-time.

Fully automated detection of formal thought disorder with Time-series Augmented Representations for Detection of Incoherent Speech (TARDIS).

Formal thought disorder (ThD) is a clinical sign of schizophrenia amongst other serious mental health conditions. ThD can be recognized by observing incoherent speech - speech in which it is difficult to perceive connections between successive utterances and lacks a clear global theme. Automated assessment of the coherence of speech in patients with schizophrenia has been an active area of research for over a decade, in an effort to develop an objective and reliable instrument through which to quantify ThD. However, this work has largely been conducted in controlled settings using structured interviews and depended upon manual transcription services to render audio recordings amenable to computational analysis. In this paper, we present an evaluation of such automated methods in the context of a fully automated system using Automated Speech Recognition (ASR) in place of a manual transcription service, with "audio diaries" collected in naturalistic settings from participants experiencing Auditory Verbal Hallucinations (AVH). We show that performance lost due to ASR errors can often be restored through the application of Time-Series Augmented Representations for Detection of Incoherent Speech (TARDIS), a novel approach that involves treating the sequence of coherence scores from a transcript as a time-series, providing features for machine learning. With ASR, TARDIS improves average AUC across coherence metrics for detection of severe ThD by 0.09; average correlation with human-labeled derailment scores by 0.10; and average correlation between coherence estimates from manual and ASR-derived transcripts by 0.29. In addition, TARDIS improves the agreement between coherence estimates from manual transcripts and human judgment and correlation with self-reported estimates of AVH symptom severity. As such, TARDIS eliminates a fundamental barrier to the deployment of automated methods to detect linguistic indicators of ThD to monitor and improve clinical care in serious mental illness.

A Smartphone Intervention for People With Serious Mental Illness: Fully Remote Randomized Controlled Trial of CORE.

BACKGROUND: People with serious mental illness (SMI) have significant unmet mental health needs. Development and testing of digital interventions that can alleviate the suffering of people with SMI is a public health priority. OBJECTIVE: The aim of this study is to conduct a fully remote randomized waitlist-controlled trial of CORE, a smartphone intervention that comprises daily exercises designed to promote reassessment of dysfunctional beliefs in multiple domains. METHODS: Individuals were recruited via the web using Google and Facebook advertisements. Enrolled participants were randomized into either active intervention or waitlist control groups. Participants completed the Beck Depression Inventory-Second Edition (BDI-II), Generalized Anxiety Disorder-7 (GAD-7), Hamilton Program for Schizophrenia Voices, Green Paranoid Thought Scale, Recovery Assessment Scale (RAS), Rosenberg Self-Esteem Scale (RSES), Friendship Scale, and Sheehan Disability Scale (SDS) at baseline (T1), 30-day (T2), and 60-day (T3) assessment points. Participants in the active group used CORE from T1 to T2, and participants in the waitlist group used CORE from T2 to T3. Both groups completed usability and accessibility measures after they concluded their intervention periods. RESULTS: Overall, 315 individuals from 45 states participated in this study. The sample comprised individuals with self-reported bipolar disorder (111/315, 35.2%), major depressive disorder (136/315, 43.2%), and schizophrenia or schizoaffective disorder (68/315, 21.6%) who displayed moderate to severe symptoms and disability levels at baseline. Participants rated CORE as highly usable and acceptable. Intent-to-treat analyses showed significant treatment×time interactions for the BDI-II (F1,313=13.38; P<.001), GAD-7 (F1,313=5.87; P=.01), RAS (F1,313=23.42; P<.001), RSES (F1,313=19.28; P<.001), and SDS (F1,313=10.73; P=.001). Large effects were observed for the BDI-II (d=0.58), RAS (d=0.61), and RSES (d=0.64); a moderate effect size was observed for the SDS (d=0.44), and a small effect size was observed for the GAD-7 (d=0.20). Similar changes in outcome measures were later observed in the waitlist control group participants following crossover after they received CORE (T2 to T3). Approximately 41.5% (64/154) of participants in the active group and 60.2% (97/161) of participants in the waitlist group were retained at T2, and 33.1% (51/154) of participants in the active group and 40.3% (65/161) of participants in the waitlist group were retained at T3. CONCLUSIONS: We successfully recruited, screened, randomized, treated, and assessed a geographically dispersed sample of participants with SMI entirely via the web, demonstrating that fully remote clinical trials are feasible in this population; however, study retention remains challenging. CORE showed promise as a usable, acceptable, and effective tool for reducing the severity of psychiatric symptoms and disability while improving recovery and self-esteem. Rapid adoption and real-world dissemination of evidence-based mobile health interventions such as CORE are needed if we are to shorten the science-to-service gap and address the significant unmet mental health needs of people with SMI during the COVID-19 pandemic and beyond. TRIAL REGISTRATION: ClinicalTrials.gov NCT04068467; https://clinicaltrials.gov/ct2/show/NCT04068467.

mHealth for Young Adults with Early Psychosis: User Preferences and Their Relationship to Attitudes About Treatment-Seeking.

A long duration of untreated psychosis reduces benefits of early intervention for early psychosis. Digital technologies have potential to encourage help-seeking and reduce barriers to care. Because of high rates of smartphone ownership, mobile health (mHealth) interventions may be particularly well-suited to increase access. There is a lack of available information on the specific features that may be most appealing to young adults with early psychosis. The present study remotely recruited 77 young adults with psychosis and surveyed their interest in mHealth features, delivery modalities, and attitudes toward treatment. Overall, respondents reported high utilization of digital health and high interest in psychosis-specific mHealth. They expressed the highest interest (ordered by mean score by item) in information about medications and side effects (n = 69, 89.6% reporting being "interested" or "very interested"), managing stress and improving mood (n = 67, 89.3%) and symptoms of psychosis (n = 66, 88%), as well as in tracking changes in symptoms (n = 70, 90.9%), and goals (n = 66, 86.9%). They also reported high interest in content being delivered as text (n = 69, 89.6%) and also in communicating directly with providers. Respondents were less interested in social features, and those with most negative attitudes toward help-seeking had particularly low interest in features related to disclosing symptoms to others. These results suggest mHealth may have potential to engage individuals with early psychosis, and that the most effective strategies may be those that are most straightforward, including direct psychoeducational information.

Mobile Health for Caregivers of Young Adults With Early Psychosis: A Survey Study Examining User Preferences.

OBJECTIVE: Caregivers play a key role in supporting the recovery of young adults with early psychosis. This role often involves considerable responsibilities and burden. Despite the considerable needs of caregivers, troubling service gaps addressing these needs remain. Digital technologies may increase caregivers' access to supportive resources; however, technologies developed specifically for caregivers lag far behind those developed for their relatives affected by early psychosis. In particular, little is known about the mobile health (mHealth) features that may be most acceptable to caregivers. METHODS: The authors surveyed a sample of 43 caregivers on their interests regarding various features of a proposed mHealth intervention. RESULTS: Caregivers of young adults with early psychosis were highly interested in a caregiver-facing mHealth intervention, specifically one providing information about psychosis, treatments, and communication with their affected family member. CONCLUSIONS: Future caregiver-focused mHealth intervention interventions may be highly acceptable to this population and may address pressing service gaps.

Expanding the Reach of Research: Quantitative Evaluation of a Web-Based Approach for Remote Recruitment of People Who Hear Voices.

BACKGROUND: Similar to other populations with highly stigmatized medical or psychiatric conditions, people who hear voices (ie, experience auditory verbal hallucinations [AVH]) are often difficult to identify and reach for research. Technology-assisted remote research strategies reduce barriers to research recruitment; however, few studies have reported on the efficiency and effectiveness of these approaches. OBJECTIVE: This study introduces and evaluates the efficacy of technology-assisted remote research designed for people who experience AVH. METHODS: Our group developed an integrated, automated and human complementary web-based recruitment and enrollment apparatus that incorporated Google Ads, web-based screening, identification verification, hybrid automation, and interaction with live staff. We examined the efficacy of that apparatus by examining the number of web-based advertisement impressions (ie, number of times the web-based advertisement was viewed); clicks on that advertisement; engagement with web-based research materials; and the extent to which it succeeded in representing a broad sample of individuals with AVH, assessed through the self-reported AVH symptom severity and demographic representativeness (relative to the US population) of the sample recruited. RESULTS: Over an 18-month period, our Google Ads advertisement was viewed 872,496 times and clicked on 11,183 times. A total amount of US $4429.25 was spent on Google Ads, resulting in 772 individuals who experience AVH providing consent to participate in an entirely remote research study (US $0.40 per click on the advertisement and US $5.73 per consented participant) after verifying their phone number, passing a competency screening questionnaire, and providing consent. These participants reported high levels of AVH frequency (666/756, 88.1% daily or more), distress (689/755, 91.3%), and functional interference (697/755, 92.4%). They also represented a broad sample of diversity that mirrored the US population demographics. Approximately one-third (264/756, 34.9%) of the participants had never received treatment for their AVH and, therefore, were unlikely to be identified via traditional clinic-based research recruitment strategies. CONCLUSIONS: Web-based procedures allow for time saving, cost-efficient, and representative recruitment of individuals with AVH and can serve as a model for future studies focusing on hard-to-reach populations.

The Centroid Cannot Hold: Comparing Sequential and Global Estimates of Coherence as Indicators of Formal Thought Disorder.

Thought disorder (TD) as reflected in incoherent speech is a cardinal symptom of schizophrenia and related disorders. Quantification of the degree ofTD can inform diagnosis, monitoring, and timely intervention. Consequently, there has been an interest in applying methods ofdistributional semantics to quantify incoherence ofspoken language. Prior studies have generally involved few participants and utilized speech data collected in on-site structured interviews. In this paper we conduct a comprehensive evaluation ofapproaches to quantify incoherence using distributional semantics, including a novel variant that measures the global coherence oftext. This evaluation is conducted in the context of "audio diaries" collected from participants experiencing auditory verbal hallucinations using a smartphone application. Results reveal our novel global coherence metric using the centroid (weighted vector average) outperforms established approaches in their agreement with human annotators, supporting their preferential use in the context of short recordings ofunstructured and largely spontaneous speech.

Mobile RDoC: Using Smartphones to Understand the Relationship Between Auditory Verbal Hallucinations and Need for Care.

OBJECTIVE: Auditory verbal hallucinations (AVH) are common in multiple clinical populations but also occur in individuals who are otherwise considered healthy. Adopting the National Institute of Mental Health's Research Domain Criteria (RDoC) framework, the aim of the current study was to integrate a variety of measures to evaluate whether AVH experience varies across clinical and nonclinical individuals. METHODS: A total of 384 people with AVH from 41 US states participated in the study; 295 participants (77%) who received inpatient, outpatient, or combination treatments for AVH and 89 participants (23%) who never received care. Participants used a multi-modal smartphone data collection system to report on their AVH experiences and co-occurring psychological states multiple times daily, over 30 days. In parallel, smartphone sensors recorded their physical activity, geolocation, and calling and texting behavior continuously. RESULTS: The clinical sample experienced AVH more frequently than the nonclinical group and rated their AVH as significantly louder and more powerful. They experienced more co-occurring negative affect and were more socially withdrawn, spending significantly more time at home and significantly less time near other people. Participants with a history of inpatient care also rated their AVH as infused with significantly more negative content. The groups did not differ in their physical activity or use of their smartphones for digital communication. CONCLUSION: Smartphone-assisted remote data collection revealed real-time/real-place phenomenological, affective, and behavioral differences between clinical and nonclinical samples of people who experience AVH. The study provided strong support for the application of RDoC-informed approaches in psychosis research.