Suchergebnisse

Purpose: The impact of social support on comprehensive measures of results (clinical and functional) of the course of schizophrenia was studied, understood and evaluated as a multidimensional construct differentiating sources of support (family vs. nonfamily). Methods: One hundred fifty-two patients diagnosed with schizophrenia were assessed with the Mannheim Interview on Social Support (MISS) and the Social Functioning Scale (SFS). The hypotheses were explored in a prospective longitudinal design, using a causal correlational analysis for their evaluation by applying structural equation models. Results: The only explanatory factor of social functioning was Nonfamily social support, while the only explanatory factor of clinical result measurements was Family social support, observing a clearly differentiated impact of the different sources of support on the schizophrenia result measurements. It was also found that while Family social support explained 6.8% of the variance in the clinical result measurements, Nonfamily social support explained 13.7% of the variance in social functioning. Conclusion: The results confirmed the differential importance of social support variables (family vs. nonfamily) in the clinical and functional result measurements of people with schizophrenia.

Purpose: The impact of Social Support (SS) on the clinical and functional evolution of patients diagnosed with schizophrenia was studied from a multidimensional concept of SS in the framework of the vulnerability-stress model. Methods: In total, 152 patients diagnosed with schizophrenia according to the International Classification of Diseases, Tenth Edition (ICD-10) treated in a Community Mental Health Unit were assessed using the Mannheim Interview on Social Support (MISS) and the Brief Psychiatric Rating Scale (BPRS). Then they were followed up for 3 years with a final assessment for the period using the Social Functioning Scale. The impact of SS was explored in clinical and functional measurements with a multiple regression analysis in a 3-year longitudinal prospective design. Results: The quality of Global Social Support (GSS) and satisfaction with GSS appeared to be protective factors from frequency and duration of hospital admissions, with explanatory intensity varying from 9% in survival time to relapse to 13% in number of relapses. Concerning functional measurements, GSS quantity, quality and satisfaction showed an explanatory power for several different dimensions of social functioning, varying from 12% in isolation to 20% in communication. Conclusion: The results confirm SS as a protective factor in the evolution of schizophrenia patients and enable the SS variables with the most explanatory power in their clinical and functional evolution to be identified.

Background: Studies examining the effects of incorporating patients' preferences into treatment outcomes highlight their impact on crucial aspects such as reduced dropout rates and enhanced effectiveness. Recognizing individuals' rights to participate in decisions about their treatments underscores the importance of studying treatment preferences and the factors influencing these choices. Aim: This study aims to identify treatment preferences (psychological, pharmacological, or combined) among a sample of patients and to discern the psychosocial and clinical factors influencing these preferences. Methods: A total of 2,133 individuals receiving care at a community mental health unit completed assessments on anxious-depressive symptoms, social and occupational adjustment, and their treatment preference. Data analysis was conducted using SPSS, with descriptive statistics, Chi-square tests, and one-way ANOVA applied. Results: Preferences for treatments were distributed as follows: Combined (49.8%), psychological (33%), and pharmacological (10.6%). Factors such as diagnosis, severity of depressive and anxious symptoms, and functional impact were related to treatment preference with a moderate effect size. Meanwhile, various sociodemographic factors correlated with the selected treatment, though with a weak effect size. Conclusions: There is a pronounced preference for combined treatments. The significance of psychological treatments is evident, as four out of five participants favored them in their choices. Addressing these preferences calls for an exploration within the broader context of prescription freedom in mental health.

Background: Patients with severe mental disorders have a high risk of premature death due to the interaction of various factors. Social functioning is a strategic functional factor in understanding the course of psychotic disorders. Aim: Analyze the relationship between social functioning and its various dimensions and survival during a 10-year follow-up. Method: The Social Functioning Scale (SFS) was administered to 163 close relatives of patients under treatment at a Community Mental Health Unit. Survival was described by Kaplan–Meier analysis and any differences in survival by level of social functioning were found by long-rank analysis. Finally, Cox regression was used to predict premature mortality. Results: Significant differences in mortality were identified in the interpersonal behavior dimension of social functioning, while there were no significant gender or diagnostic differences in the rest of the dimensions. The interpersonal behavior dimension and age were found to be factors predicting premature death. Conclusion: These findings show the protective effect of social functioning retained by patients with psychotic disorders on their survival, and the need to apply evidence-based psychotherapy focused on recovery of social functioning in the early stages of the disorder.

Background: In recent years, several variables in the course of schizophrenia and related psychotic disorders have been studied. However, an instrumental analysis of the evolution of social functioning and behaviour problems has scarcely been explored. Aim: To analyse the evolution of social functioning and behaviour problems and find any diagnosis or gender differences. Method: The Social Functioning Scale (SFS) and the Behaviour Problems Inventory (BPI) were administered in Stages I (2003–2007) and II (2014–2017) to 100 close relatives of patients under treatment at a Community Mental Health Unit. A related samples t-test, analysis of variance and multivariate analysis of variance were performed to study the evolution and differences in social functioning and behaviour problems. Then a stepwise multiple linear regression analysis was done to predict the evolution of social functioning. Results: No deterioration in the evolution of social functioning or behaviour problems was observed, and schizophrenia patient scores were lower. Women scored higher in withdrawal/social engagement, interpersonal behaviour, independence-performance, independence-competence and total social functioning, with no significant differences in behaviour problems. Previous social functioning, underactivity/social withdrawal and education are predictive factors in the evolution of social functioning. Conclusion: The results show the need for implementing psychosocial intervention programs that promote functional recovery and keep problems from becoming chronic.

Background: In recent years, more variables are being included in the use of mental health resource prediction models. Some studies have shown that how well the patient can function is important for this prediction. However, the relevance of a variable as important as behaviour problems has scarcely been explored. Aim: This study attempted to evaluate the effect of behaviour problems in patients with severe mental illness on the use of mental health resources. Method: A total of 185 patients at a Community Mental Health Unit were evaluated using the Behaviour Problem Inventory. Later, a bivariate logistic regression was done to identify what behaviour problems could be specific predictors of use of mental health resources. Results: The results showed that the general index of behaviour problems predicts both use of hospitalization resources and outpatient attention. Underactivity/social withdrawal is the best predictor of all the different areas. Conclusion: These results confirm the role of behaviour problems as predictors of the use of mental health resources in individuals with a severe mental illness.