RESUMO
AIM: There is concern that the provision of the clinical high risk for psychosis (CHR) label is stigmatizing. Prior research suggests people have nuanced reactions to feedback involving the CHR label, including a positive experience receiving feedback and improvement in negative emotions (e.g., shame), while also exhibiting concerns about self-perception and perceptions from others related to the label. The current pilot study aimed to evaluate whether individuals at CHR showed changes in emotional and stigma-related experiences following a CHR psychoeducation intervention, BEGIN: Brief Educational Guide for Individuals in Need. METHOD: Participants at CHR (N = 26) identified via the Structured Interview for Psychosis-Risk Syndromes completed the Mental Health Attitudes Interview measuring symptom-related and CHR label-related stigma at pre- and post-intervention. RESULTS: Stigma did not increase and participants had greater positive emotions (e.g., feeling hopeful and relieved), post-BEGIN. CONCLUSION: This study suggests that standardized CHR psychoeducation does not increase stigma in individuals at CHR.
RESUMO
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).
RESUMO
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.