Theatre improvisation training to promote social cognition: A novel recovery-oriented intervention for youths at clinical risk for psychosis

Personal Recovery Among People at Risk for Developing Serious Mental Health Problems: A Qualitative Systematic Review

OBJECTIVE

Personal recovery refers to a person's pursuit of a full, meaningful life despite the potentially debilitating impact of a mental illness. An evidence base describing personal recovery among people at risk for developing a mental illness is lacking, limiting the potential for mental health services to support personal recovery. To address this gap, the authors synthesized the extant research describing personal recovery among people at risk for developing a mental illness.

METHODS

A systematic search of several literature databases (MEDLINE, Embase, APA PsycInfo, Web of Science Core Collection, and Cochrane Library) was conducted to retrieve qualitative and case studies and first-person accounts. The Joanna Briggs Institute guidelines for systematic reviews were followed. Included studies reported on participants at variable risk for developing a schizophrenia spectrum, bipolar, major depressive, or borderline personality disorder. Articles were retrieved through a librarian-assisted search and through use of additional strategies (e.g., expert consultation). Abstracts were screened by the research team, and themes were developed by using thematic synthesis.

RESULTS

The 36 included articles were synthesized, and six themes were generated: difficulties and challenges; establishing an understanding of, and finding ways to cope with, one's mental health challenges; reestablishing a sense of agency and personhood; receiving support from people and services, as well as restoring relationships; reestablishing hope, meaning, and purpose; and overcoming stigma and destigmatizing mental illness in others.

CONCLUSIONS

These findings provide a conceptual foundation that can guide future research on personal recovery and clinical interventions that foster it among people at risk for mental illness.

Functional phenotypes in schizophrenia spectrum disorders: defining the constructs and identifying biopsychosocial correlates using data-driven methods

Functional impairments contribute to poor quality of life in schizophrenia spectrum disorders (SSD). We sought to (Objective I) define the main functional phenotypes in SSD, then (Objective II) identify key biopsychosocial correlates, emphasizing interpretable data-driven methods. Objective I was tested on independent samples: Dataset I (N = 282) and Dataset II (N = 317), with SSD participants who underwent assessment of multiple functioning areas. Participants were clustered based on functioning. Objective II was evaluated in Dataset I by identifying key features for classifying functional phenotype clusters from among 65 sociodemographic, psychological, clinical, cognitive, and brain volume measures. Findings were replicated across latent discriminant analyses (LDA) and one-vs.-rest binomial regularized regressions to identify key predictors. We identified three clusters of participants in each dataset, demonstrating replicable functional phenotypes: Cluster 1-poor functioning across domains; Cluster 2-impaired Role Functioning, but partially preserved Independent and Social Functioning; Cluster 3-good functioning across domains. Key correlates were Avolition, anhedonia, left hippocampal volume, and measures of emotional intelligence and subjective social experience. Avolition appeared more closely tied to role functioning, and anhedonia to independent and social functioning. Thus, we found three replicable functional phenotypes with evidence that recovery may not be uniform across domains. Avolition and anhedonia were both critical but played different roles for different functional domains. It may be important to identify critical functional areas for individual patients and target interventions accordingly.

Clinical and computational speech measures are associated with social cognition in schizophrenia spectrum disorders

In this study, we compared three domains of social cognition (emotion processing, mentalizing, and attribution bias) to clinical and computational language measures in 63 participants with schizophrenia spectrum disorders. Based on the active inference model for discourse, we hypothesized that emotion processing and mentalizing, but not attribution bias, would be related to language disturbances. Clinical ratings for speech disturbance assessed disorganized and underproductive dimensions. Computational features included speech graph metrics, use of modal verbs, use of first-person pronouns, cosine similarity of adjacent utterances, and measures of sentiment; these were represented by four principal components. We found that higher clinical ratings for disorganized speech were predicted by greater impairments in both emotion processing and mentalizing, and that these relationships remained significant when accounting for demographic variables, overall psychosis symptoms, and verbal ability. Similarly, a computational speech component reflecting insular speech was consistently predicted by impairment in emotion processing. There were notable trends for computational speech components reflecting underproductive speech and decreased content-rich speech predicting mentalizing ability. Exploratory longitudinal analyses in a small subset of participants (n = 17) found that improvements in both emotion processing and mentalizing predicted improvements in disorganized speech. Attribution bias did not demonstrate strong relationships with language measures. Altogether, our findings are consistent with the active inference model of discourse and suggest greater emphasis on treatments that target social cognitive and language systems.

Psychosocial Exoskeletons: Normal Development, Psychopathological and Sociopathological Phenomena, and Therapeutic Applications

In medical therapeutics, exoskeleton refers to external protections, supports, and appliances. By analogy, psychosocial exoskeletons can be envisioned as assistive psychological and social structures that brace and extend individuals' coping abilities. This article considers the utility of defining "psychosocial exoskeletons" as a framework to encompass psychological and social devices that enhance coping, and "therapeutic psychosocial exoskeletons" as devices assisting psychiatric treatment. Clinical observations were augmented via selective narrative review using PubMed and PsychInfo.A range of psychological and social devices were identified that constitute psychosocial exoskeletons. In extremes, psychosocial exoskeletons may prescribe comprehensive lifestyles including dress, rites, taboos, and acceptable relationships. These devices may enhance normal or psychopathological development.Therapeutic psychosocial exoskeletons consist of intentionally prescribed psychotherapeutic and sociotherapeutic interventions assembled to address patient-centered problems. Elements may include counseling and psychotherapies, peer-based recovery programs, institutional programs, and social interventions involving financial assistance, supported employment, pets, and other practical resources.

Facial expression-based indicators of schizophrenia: Evidence from recent research

Impaired ability to recognize emotion in other's face (decoding) or to express emotion through the face (encoding) are considered critical in schizophrenia. The topic of research draws considerable attention since clinicians rely heavily on the patient's facial expressions for diagnosis and on the patient's ability to understand the clinician's communicative intent. While most researchers argue in favor of a generalized emotion deficit, others indicate an emotion-specific deficit in schizophrenia. An early review (Mandal et al., 1998) indicated a possible breakdown in perception-expression-experience link of emotion; later reviews (Kohler et al., 2010; Chan et al., 2010) pointed to a generalized emotion processing deficit due to perceptual deficits in schizophrenia. The present review (2010-2022) revisits this controversy with 47 published studies (37 decoding, 10 encoding) conducted on 2364 patients in 20 countries. Schizophrenia is characterized by reduced emotion processing ability, especially with negative symptoms and at an acute state of illness. It is however still unclear whether this dysfunction is independent of a generalized face perception deficit or of subjective experience of emotion in schizophrenia.

Interaction in acting training and its different manifestations in novice and professional actors

This study aimed to identify the characteristics of interactions during acting training and the underlying intrapersonal changes evoked by a training process that emphasizes paying attention to a partner (the Meisner technique). This was operationalized by conducting a post-hoc analysis and categorizing the utterances made by novice and professional actors during acting training based on video and audio recordings. In Study 1, novice participants tended to change their way of communication as the course progressed, decreasing the number of utterances that simply described the partner's behavior and increasing those that speculated about the partner's inner state. We then used a different focus placed on the interaction, as implied by the different kinds of utterances used, to describe the divergences between novice and professional actors regarding their interaction characteristics. In Study 2, results showed that while professional actors devoted themselves more to the connection with their partner and demonstrated more balanced communication, novice actors relied on general inference to speculate about others' affective states. By comparing the characteristics of the utterances between novice and professional actors as they played different roles or made switches (i.e., changing from passive to active utterance in communication), this study suggests that an important impact of acting training on social abilities relates to its potential to increase the levels of involvement in on-going interactions.

Metabolic disturbances, hemoglobin A1c, and social cognition impairment in Schizophrenia spectrum disorders

Social cognitive impairments are core features of schizophrenia spectrum disorders (SSD) and are associated with greater functional impairment and decreased quality of life. Metabolic disturbances have been related to greater impairment in general neurocognition, but their relationship to social cognition has not been previously reported. In this study, metabolic measures and social cognition were assessed in 245 participants with SSD and 165 healthy comparison subjects (HC), excluding those with hemoglobin A1c (HbA1c) > 6.5%. Tasks assessed emotion processing, theory of mind, and social perception. Functional connectivity within and between social cognitive networks was measured during a naturalistic social task. Among SSD, a significant inverse relationship was found between social cognition and cumulative metabolic burden (β = -0.38, p < 0.001) and HbA1c (β = -0.37, p < 0.001). The relationship between social cognition and HbA1c was robust across domains and measures of social cognition and after accounting for age, sex, race, non-social neurocognition, hospitalization, and treatment with different antipsychotic medications. Negative connectivity between affect sharing and motor resonance networks was a partial mediator of this relationship across SSD and HC groups (β = -0.05, p = 0.008). There was a group x HbA1c effect indicating that SSD participants were more adversely affected by increasing HbA1c. Thus, we provide the first report of a robust relationship in SSD between social cognition and abnormal glucose metabolism. If replicated and found to be causal, insulin sensitivity and blood glucose may present as promising targets for improving social cognition, functional outcomes, and quality of life in SSD.

Effects of Improv Training on Older Adults in a Long Term Care Facility

Adjusting to life in a long term care facility (LTCF) can be challenging for older adults. Improvisation (shortened to improv) is a unique activity that encourages creativity and adaptive cognitive stimulation, through performing short scenes with content suggestions. We sought to assess whether improv training, in the form of a course entitled Humor Doesn't Retire (HDR), could impact patient-centered outcomes in a LTCF. About 15 adults (mean age 83.6 years) living in a LTCF participated in the 8-week HDR course with pre and 1-month post mixed method surveys assessing validated Patient Reported Outcomes Measurement Information System (PROMIS) measures and qualitative open-ended responses. Participants experienced significant improvements in social isolation and perceived stress (p < .05), and trend improvements in positive affect, self-efficacy, and anxiety. Participants described themes of increased attentiveness, becoming more relaxed, increased cognitive stimulation, and improved communication skills. In conclusion, LTCFs may want to consider offering improv training to positively improve the lives of older adult residents.

Modeling brain, symptom, and behavior in the winds of change

Neuropsychopharmacology addresses pressing questions in the study of three intertwined complex systems: the brain, human behavior, and symptoms of illness. The field seeks to understand the perturbations that impinge upon those systems, either driving greater health or illness. In the pursuit of this aim, investigators often perform analyses that make certain assumptions about the nature of the systems that are being perturbed. Those assumptions can be encoded in powerful computational models that serve to bridge the wide gulf between a descriptive analysis and a formal theory of a system's response. Here we review a set of three such models along a continuum of complexity, moving from a local treatment to a network treatment: one commonly applied form of the general linear model, impulse response models, and network control models. For each, we describe the model's basic form, review its use in the field, and provide a frank assessment of its relative strengths and weaknesses. The discussion naturally motivates future efforts to interlink data analysis, computational modeling, and formal theory. Our goal is to inspire practitioners to consider the assumptions implicit in their analytical approach, align those assumptions to the complexity of the systems under study, and take advantage of exciting recent advances in modeling the relations between perturbations and system function.