Family psychoeducation in schizophrenia and schizophrenia related disorder, treatment compliance, and suicidal risk reduction: questions about their relationship from a naturalistic observation.

Introduction: The Profamille V3.2 multi-family psycho-educational program directed at caregivers of relatives with schizophrenia or schizophrenia related disorder has been shown to decrease the annual prevalence of suicide attempts. It has been reported that psychoeducation of families can sometimes improve compliance with treatment. This study investigates whether the Profamille program improves compliance and thus reduces the risk of suicide among patients. Method: This is a retrospective study of 179 groups of family caregivers, encompassing 1946 participants enrolled in Module 1 of the Profamille program and followed up one year after completion of the module. Evaluations were conducted using questionnaires filled out by family caregivers at three distinct times: prior to beginning the program, upon its completion, and again one year following its conclusion. The annual prevalence of suicide attempts was measured both before the program began and one year after its conclusion, while compliance to treatment was evaluated at the start and end of the program. Result: After the Profamille program, the annual prevalence of suicide attempts fell by a factor of 2 (p-value = 0.00002) and patient compliance improved (p-value <0.000001). This reduction in suicide attempts was observed independently of improved compliance. Compliance seems to have an additional effect, but only after participation in the program. Conclusion: The Profamille program reduces patients' risk of suicide even when patients are not taking the treatment. When family psychoeducation is not proposed in schizophrenia or schizophrenia related disorder, this can represent a loss of chance for patients.

Differential associations between insight and quality-of-life dimensions among individuals with schizophrenia.

PURPOSE/OBJECTIVE: In schizophrenia, insight, the recognition that one has a medical illness that requires treatment, has long been related to deteriorated quality of life. Yet, insight and quality of life are broad constructs that encompass several dimensions. Here, we investigated differential associations between insight and quality-of-life dimensions using a psychological network approach. RESEARCH METHOD/DESIGN: We extracted data from the French network of rehabilitation centers REHABase (January 2016 to December 2022, N = 1,056). Our psychological network analysis modeled insight and quality of life as a network of interacting dimensions: three insight dimensions (awareness of illness, reattribution of symptoms to the disease, and recognition of treatment need) and eight quality-of-life dimensions (autonomy, physical and psychosocial well-being, relationships with family, friends and romantic partners, resilience, and self-esteem). RESULTS: Insight was negatively associated with quality of life. Our psychological network analysis revealed a strong negative association between awareness of disease and self-esteem. Both dimensions were the strongest nodes in the overall network. Our network analysis also revealed a significant but positive connection between recognition of treatment needs and resilience. CONCLUSION/IMPLICATIONS: While insight and quality of life are overall negatively associated, we found both negative and positive connections between insight and quality-of-life dimensions. The negative relationship between insight and quality of life may reflect the deleterious effects of diagnostic labeling on a patient's self-esteem. Yet, acknowledgment of treatment needs may have positive effects on quality of life and may promote recovery, perhaps because it emphasizes the need for support rather than labels and abnormalities. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Contribution of socio-demographic and clinical characteristics to predict initial referrals to psychosocial interventions in patients with serious mental illness.

AIMS: Psychosocial rehabilitation (PSR) is at the core of psychiatric recovery. There is a paucity of evidence regarding how the needs and characteristics of patients guide clinical decisions to refer to PSR interventions. Here, we used explainable machine learning methods to determine how socio-demographic and clinical characteristics contribute to initial referrals to PSR interventions in patients with serious mental illness. METHODS: Data were extracted from the French network of rehabilitation centres, REHABase, collected between years 2016 and 2022 and analysed between February and September 2022. Participants presented with serious mental illnesses, including schizophrenia spectrum disorders, bipolar disorders, autism spectrum disorders, depressive disorders, anxiety disorders and personality disorders. Information from 37 socio-demographic and clinical variables was extracted at baseline and used as potential predictors. Several machine learning models were tested to predict initial referrals to four PSR interventions: cognitive behavioural therapy (CBT), cognitive remediation (CR), psychoeducation (PE) and vocational training (VT). Explanatory power of predictors was determined using the artificial intelligence-based SHAP (SHapley Additive exPlanations) method from the best performing algorithm. RESULTS: Data from a total of 1146 patients were included (mean age, 33.2 years [range, 16-72 years]; 366 [39.2%] women). A random forest algorithm demonstrated the best predictive performance, with a moderate or average predictive accuracy [micro-averaged area under the receiver operating curve from 'external' cross-validation: 0.672]. SHAP dependence plots demonstrated insightful associations between socio-demographic and clinical predictors and referrals to PSR programmes. For instance, patients with psychotic disorders were more likely to be referred to PE and CR, while those with non-psychotic disorders were more likely to be referred to CBT and VT. Likewise, patients with social dysfunctions and lack of educational attainment were more likely to be referred to CR and VT, while those with better functioning and education were more likely to be referred to CBT and PE. CONCLUSIONS: A combination of socio-demographic and clinical features was not sufficient to accurately predict initial referrals to four PSR programmes among a French network of rehabilitation centres. Referrals to PSR interventions may also involve service- and clinician-level factors. Considering socio-demographic and clinical predictors revealed disparities in referrals with respect to diagnoses, current clinical and psychological issues, functioning and education.

Functioning, clinical severity, education and sex moderate the inverse relationship between insight and quality of life in patients with schizophrenia.

BACKGROUND: In schizophrenia, insight, the recognition that one has a medical illness that requires treatment, has long been related to deteriorated quality of life, a phenomenon that has been described as the "insight paradox". Here, we aimed to determine whether certain socio-demographic and clinical characteristics strengthen or weaken this negative relationship. METHODS: We used data from the French network of rehabilitation centers REHABase (N = 769). We explored mean differences in quality-of-life scores between patients with good insight vs. poor insight. We also explored modifying effects of socio-demographic and clinical characteristics (sex, education, age, functioning, clinical severity, duration of illness). RESULTS: Patients with good insight had a decreased quality-of-life total score. Similar effects were found for the following sub-dimensions of quality of life: autonomy, physical and psychological well-being, and self-esteem. The negative effect of insight on quality of life was attenuated for people who had >12 years of education and for people with a higher level of functioning. By contrast, the negative effect of insight on quality of life was accentuated in people with greater clinical severity. Functioning and clinical severity showed similar modifying effects for other quality-of-life dimensions: autonomy, physical and psychological well-being, and self-esteem. Finally, males demonstrated an increased negative association between insight and self-esteem. CONCLUSIONS: The relationship between insight and quality of life is moderated by socio-demographic and clinical circumstances. Future inquiries may utilize our findings by integrating socio-demographic and clinical factors in treatment programs designs to conjointly improve insight and quality of life.