Longitudinal evidence for a relation between depressive symptoms and quality of life in schizophrenia using structural equation modeling

Shaping tomorrow's support: baseline clinical characteristics predict later social functioning and quality of life in schizophrenia spectrum disorder

PURPOSE

We aimed to explore the multidimensional nature of social inclusion (mSI) among patients diagnosed with schizophrenia spectrum disorder (SSD), and to identify the predictors of 3-year mSI and the mSI prediction using traditional and data-driven approaches.

METHODS

We used the baseline and 3-year follow-up data of 1119 patients from the Genetic Risk and Outcome in Psychosis (GROUP) cohort in the Netherlands. The outcome mSI was defined as clusters derived from combined analyses of thirteen subscales from the Social Functioning Scale and the brief version of World Health Organization Quality of Life questionnaires through K-means clustering. Prediction models were built through multinomial logistic regression (ModelMLR) and random forest (ModelRF), internally validated via bootstrapping and compared by accuracy and the discriminability of mSI subgroups.

RESULTS

We identified five mSI subgroups: "very low (social functioning)/very low (quality of life)" (8.58%), "low/low" (12.87%), "high/low" (49.24%), "medium/high" (18.05%), and "high/high" (11.26%). The mSI was robustly predicted by a genetic predisposition for SSD, premorbid adjustment, positive, negative, and depressive symptoms, number of met needs, and baseline satisfaction with the environment and social life. The ModelRF (61.61% [54.90%, 68.01%]; P =0.013) was cautiously considered outperform the ModelMLR (59.16% [55.75%, 62.58%]; P =0.994).

CONCLUSION

We introduced and distinguished meaningful subgroups of mSI, which were modestly predictable from baseline clinical characteristics. A possibility for early prediction of mSI at the clinical stage may unlock the potential for faster and more impactful social support that is specifically tailored to the unique characteristics of the mSI subgroup to which a given patient belongs.

Depression severity mediates stigma and quality of life in clinically stable people with schizophrenia in rural China

BACKGROUND

Depressive symptoms associated with schizophrenia are closely related to stigma and quality of life(QOL). There is, however, no thorough research on the connection between the three. This study sought to investigate the possible factors influencing depressive symptoms in people with schizophrenia (PWS) in rural Chaohu, China, and to further explore the role of depression severity in stigma and lifestyle quality.

METHODS

Eight hundred twenty-one schizophrenia patients accomplished the entire scale, including the 9-item Patient Health Questionnaire (PHQ-9), the Social Impact Scale (SIS), and the World Health Organization on Quality of Life Brief Scale(WHOQOL-BREF). A straightforward mediation model was employed to determine if the intensity of the depression could act as a mediator between stigma and QOL.

RESULTS

Two hundred seventy-nine schizophrenia patients (34%) had depressive symptoms (PHQ ≥ 10), and 542 patients (66%) did not (PHQ < 10). Logistic regression showed that marital status, job status, physical exercise, standard of living, and stigma contributed to the depressed symptoms of schizophrenia. Depression severity partially mediated the effect between stigma and QOL, with a mediating effect of 48.3%.

CONCLUSIONS

This study discovered a significant incidence of depressed symptoms associated with schizophrenia, with depression severity serving as a mediator variable connecting stigma and QOL and partially moderating the association.

Revealing the impact of psychiatric comorbidities on treatment outcome in early psychosis using counterfactual model explanation

Introduction

Psychiatric comorbidities have a significant impact on the course of illness in patients with schizophrenia spectrum disorders. To accurately predict outcomes for individual patients using computerized prognostic models, it is essential to consider these comorbidities and their influence.

Methods

In our study, we utilized a multi-modal deep learning architecture to forecast symptomatic remission, focusing on a multicenter sample of patients with first-episode psychosis from the OPTiMiSE study. Additionally, we introduced a counterfactual model explanation technique to examine how scores on the Mini International Neuropsychiatric Interview (MINI) affected the likelihood of remission, both at the group level and for individual patients.

Results

Our findings at the group level revealed that most comorbidities had a negative association with remission. Among them, current and recurrent depressive disorders consistently exerted the greatest negative impact on the probability of remission across patients. However, we made an interesting observation: current suicidality within the past month and substance abuse within the past 12 months were associated with an increased chance of remission in patients. We found a high degree of variability among patients at the individual level. Through hierarchical clustering analysis, we identified two subgroups: one in which comorbidities had a relatively limited effect on remission (approximately 45% of patients), and another in which comorbidities more strongly influenced remission. By incorporating comorbidities into individualized prognostic prediction models, we determined which specific comorbidities had the greatest impact on remission at both the group level and for individual patients.

Discussion

These results highlight the importance of identifying and including relevant comorbidities in prediction models, providing valuable insights for improving the treatment and prognosis of patients with psychotic disorders. Furthermore, they open avenues for further research into the efficacy of treating these comorbidities to enhance overall patient outcomes.

Clozapine-related obsessive-compulsive symptoms and their impact on wellbeing: a naturalistic longitudinal study

BACKGROUND

Obsessive-compulsive symptoms (OCS) are commonly associated with clozapine treatment but are frequently overlooked by clinicians despite their potential impact on patients' quality of life. In this study, we explored whether OCS severity impacted subjective wellbeing and general functioning, independently of depressive and psychotic symptoms.

METHODS

We used anonymised electronic healthcare records from a large cohort of patients who were treated with clozapine and assessed annually for OCS, wellbeing, general functioning, and psychopathology using standardised scales as part of routine clinical practice. We used statistical mixed linear model techniques to evaluate the longitudinal influence of OCS severity on wellbeing and general functioning.

RESULTS

A total of 184 patients were included, with 527 face-to-face assessments and 64.7% evaluated three or more times. Different linear mixed models demonstrated that OCS in patients treated with clozapine were associated with significantly worse wellbeing scores, independently of depression and psychotic symptoms, but OCS did not impair general functioning. Obsessional thinking and hoarding behaviour, but not compulsions, were significantly associated with the impact on wellbeing, which may be attributable to the ego-syntonic nature of the compulsions.

CONCLUSIONS

Given the frequent occurrence of OCS and their negative impact on wellbeing, we encourage clinicians to routinely assess and treat OCS in patients who are taking clozapine.

Quality of life in patients with schizophrenia: A 2-year cohort study in primary mental health care in rural China

Objective

Quality of life (QoL) has been always an important way to evaluate the outcomes of schizophrenia, but there have been few previous longitudinal studies and few in middle-income countries. This study aimed to explore the QoL in Chinese patients with schizophrenia treated in primary mental health care and the risk factors of QoL over time.

Methods

Patients with schizophrenia treated in primary mental health care in rural/regional areas in Luoding, Guangdong, PR China, were evaluated with an extended questionnaire including the Chinese version of the World Health Organization Quality of Life (WHOQOL-BREF) at baseline and 2-year follow-up. Bivariate and multivariate analyses were conducted including Generalized Estimated Equation analyses (GEE).

Results

Four hundred and ninety-one patients with schizophrenia in primary care completed the 2-year follow up evaluation. The QoL physical, environmental, and social relationships domains showed improvement after the 2-year period, but the psychological domain did not. GEE results showed that earlier age of onset, older age, being employed, being unmarried, the thicker waist circumference, less use of clozapine or other SGAs, fewer hospitalizations, more frequent insomnia, more severe depressive and negative symptoms as well as worse treatment insight were independently associated with poor QoL in patients with schizophrenia.

Conclusion

According to our results, to improve the quality of life of patients with schizophrenia in primary care, we should pay more attention to the treatment of depression, negative and insomnia symptoms of schizophrenia, the choice and dosage of antipsychotic medication and improvement in the treatment compliance. The combined use of educational and behavioral strategies may improve treatment adherence.

Affective lability and social functioning in severe mental disorders

Social functioning is impaired in severe mental disorders despite clinical remission, illustrating the need to identify other mechanisms that hinder psychosocial recovery. Affective lability is elevated and associated with an increased clinical burden in psychosis spectrum disorders. We aimed to investigate putative associations between affective lability and social functioning in 293 participants with severe mental disorders (schizophrenia- and bipolar spectrum), and if such an association was independent of well-established predictors of social impairments. The Affective Lability Scale (ALS-SF) was used to measure affective lability covering the dimensions of anxiety-depression, depression-elation and anger. The interpersonal domain of the Social Functioning Scale (SFS) was used to measure social functioning. Correlation analyses were conducted to investigate associations between affective lability and social functioning, followed by a hierarchical multiple regression and follow-up analyses in diagnostic subgroups. Features related to premorbid and clinical characteristics were entered as independent variables together with the ALS-SF scores. We found that higher scores on all ALS-SF subdimensions were significantly associated with lower social functioning (p < 0.005) in the total sample. For the anxiety-depression dimension of the ALS-SF, this association persisted after controlling for potential confounders such as premorbid social functioning, duration of untreated illness and current symptoms (p = 0.019). Our results indicate that elevated affective lability may have a negative impact on social functioning in severe mental disorders, which warrants further investigation. Clinically, it might be fruitful to target affective lability in severe mental disorders to improve psychosocial outcomes.

Relationship of subjective quality of life with symptomatology, neurocognition and psychosocial functioning in first-episode psychosis: a structural equation modelling approach

Subjective quality of life (SQoL) represents an important outcome of psychotic disorders. However, determinants of SQoL and their complex inter-relationships in the early course of illness remain to be clarified. Association between neurocognitive impairment and SQoL in first-episode psychosis (FEP) is understudied. This study employed structural equation modeling (SEM) to examine relationships among SQoL, depressive, positive and negative symptoms, neurocognition, and psychosocial functioning in FEP patients. Three hundred and forty-seven patients aged 25-55 years presenting with FEP to early intervention program in Hong Kong were recruited. Assessment encompassing symptom profiles, psychosocial functioning and a battery of neurocognitive tests were conducted. SF-12 mental component summary scores were computed as the primary measure of SQoL. Our correlation analyses revealed differential relationships between negative symptom subdomains and SQoL, with amotivation, but not diminished expression, being related to SQoL. Final SEM model yielded a good model fit (comparative fix index = 0.94; root mean square error of approximation = 0.05; standardized root mean square residuals = 0.07) and demonstrated that depression, positive symptoms and psychosocial functioning were directly associated with SQoL, with depression showing the strongest effect. Amotivation, neurocognition and positive symptoms had an indirect effect on SQoL via the mediation of psychosocial functioning. This study affirms depression as a critical determinant of subjective mental wellbeing, and underscores an intermediary role of psychosocial functioning in linking amotivation, neurocognitive impairment and positive symptoms to SQoL in FEP patients. Depression and functional impairment thus constitute as crucial therapeutic targets for improvement of SQoL in the early illness stage.

[Rhythmic transcranial magnetic stimulation in the treatment of resistant depression in schizophrenia]

Rhythmic transcranial magnetic stimulation (rTMS) has long been actively used in the treatment of depressive disorders in various mental illnesses. At the same time, the question of the predictability of the results of this method for an individual patient remains open. Based on the existing ideas about the relationship of rTMS mechanisms with changes in the state of neural networks, one of the most perspective line is the search for prognostically significant neurophysiological markers. The study analyzed a wide range of EEG characteristics and evoked potentials recorded before treatment in the groups of responders and nonresponders in patients with depressive symptoms in schizophrenia, who have completed a course of rhythmic transcranial magnetic stimulation. The study revealed associations between an unfavorable treatment outcome and greater coherence in the alpha range (mainly in the caudal regions bilaterally) and less coherence in the beta1 range (involving temporal leads and left-hemisphere asymmetry). At the same time, such indicators as the amplitude of the N100 wave and the negativity of the mismatch were uninformative in terms of predicting the effectiveness of therapy.

The course and concomitants of depression in first-episode schizophrenia spectrum disorders: A 24-month longitudinal study

Depressive symptoms are common in schizophrenia and have been associated with both favourable and unfavourable outcomes. We studied the longitudinal course of depressive symptoms and explored their temporal relationships with other manifestations of the illness and its treatment. This longitudinal cohort study included 126 antipsychotic naïve or only briefly treated patients with first-episode schizophrenia spectrum disorders treated with a long-acting antipsychotic over 24 months. Depressive symptoms were assessed at three monthly intervals using the Calgary Depression Scale for Schizophrenia and changes over time were assessed using linear mixed-effect models for continuous repeated measures. Depressive symptoms were most prominent at baseline with highly significant reductions during the first three months of treatment and maintenance of improvement thereafter. Most improvement occurred with antipsychotic treatment alone, with few patients requiring additional antidepressants. We also found that depressive symptoms were associated with positive symptoms, better insight and poorer quality of life, but not with negative symptoms, extrapyramidal symptoms, substance use or cumulative antipsychotic dose.There were few differences between patients who met criteria for depression during the acute phase of treatment and those in the post-acute phase.

Deriving symptom networks from digital phenotyping data in serious mental illness

BACKGROUND

Symptoms of serious mental illness are multidimensional and often interact in complex ways. Generative models offer value in elucidating the underlying relationships that characterise these networks of symptoms.

AIMS

In this paper we use generative models to find unique interactions of schizophrenia symptoms as experienced on a moment-by-moment basis.

METHOD

Self-reported mood, anxiety and psychosis symptoms, self-reported measurements of sleep quality and social function, cognitive assessment, and smartphone touch screen data from two assessments modelled after the Trail Making A and B tests were collected with a digital phenotyping app for 47 patients in active treatment for schizophrenia over a 90-day period. Patients were retrospectively divided up into various non-exclusive subgroups based on measurements of depression, anxiety, sleep duration, cognition and psychosis symptoms taken in the clinic. Associated transition probabilities for the patient cohort and for the clinical subgroups were calculated using state transitions between adjacent 3-day timesteps of pairwise survey domains.

RESULTS

The three highest probabilities for associated transitions across all patients were anxiety-inducing mood (0.357, P < 0.001), psychosis-inducing mood (0.276, P < 0.001), and anxiety-inducing poor sleep (0.268, P < 0.001). These transition probabilities were compared against a validation set of 17 patients from a pilot study, and no significant differences were found. Unique symptom networks were found for clinical subgroups.

CONCLUSIONS

Using a generative model using digital phenotyping data, we show that certain symptoms of schizophrenia may play a role in elevating other schizophrenia symptoms in future timesteps. Symptom networks show that it is feasible to create clinically interpretable models that reflect the unique symptom interactions of psychosis-spectrum illness. These results offer a framework for researchers capturing temporal dynamics, for clinicians seeking to move towards preventative care, and for patients to better understand their lived experience.

Comorbidity Profiles of Psychotic Patients in Emergency Psychiatry

Objectives: Individuals with psychotic symptoms presenting to emergency psychiatry often have comorbid symptoms, such as substance misuse, depression, and anxiety. Many will also have symptoms linked to previous traumatic experiences such as impulsivity, often found in comorbid personality disorders. Although various studies have looked at specific comorbid symptoms, little is known regarding how these symptoms co-exist in individuals with psychotic symptoms and their link with social functioning. The primary objective of the present study was to identify comorbidity profiles among individuals seeking emergency room services for psychotic symptoms. The secondary objective was to investigate the relationship between comorbid symptoms and social functioning deficits in this same population. Methods: Data from 546 individuals seeking psychiatric help for psychotic symptoms was collected within the Signature Project (large data bank) in a psychiatric emergency. Participants answered brief measures of symptoms of alcohol/substance misuse (AUDIT, DAST), depression (PHQ-9), anxiety (STAI-6), childhood trauma (CEVQ), impulsivity (UPPS) and social functioning deficits (WHODAS). For this study, symptom measures and social functioning at baseline were used. Results: Cluster analyses conducted using three different methods revealed a consensus of five classes of comorbid presentations. Class 1 (n = 90) grouped people who had a high score for childhood trauma, with fairly high scores for anxiety and depression. Class 2 (n = 176) included people with mostly psychotic symptoms with little comorbid presentation across other measures. Class 3 (n = 81) grouped people with the highest anxiety and depression scores as well as high drug use and impulsivity. Individuals in Class 4 (n = 87) had the highest scores on alcohol and substance abuse, as well as high impulsivity. Class 5 (n = 112) grouped people with very low anxiety and depression scores but average trauma, alcohol, and substance misuse scores. Linear regressions revealed an association between social functioning, and depression, anxiety, and childhood trauma. Conclusions: Comorbid presentations of individuals with psychosis are frequent and diverse. Depression and anxiety, in particular, worsen social functioning deficits in people with psychotic symptoms. Given their impact on functioning, psychiatric treatments should address these comorbidities during hospitalization, as well as when followed in the community.

Rethinking Schizophrenia and Depression Comorbidity as One Psychiatric Disorder Entity: Evidence From Mouse Model

Schizophrenia is frequently accompanied by depressive symptoms, but the pathological mechanisms remain to be elucidated. In this study, we used chronic unpredicted mild stress plus MK801 injection to generate a mouse model of schizophrenia with depression, in which in vivo 2-photon calcium imaging and electrophysiological recordings were performed in conjunction with behavioral phenotyping. Compared to mice models with classical depression or to schizophrenia models, the animal models with schizophrenia and depression comorbidity presented worse psychotic and depressive symptoms. These behavioral deficits are associated with impaired neuronal calcium activities in the frontal cortex and thalamic nuclei. Moreover, in sharp contrast to classical models that have a satisfactory response to antipsychotic or antidepressant drugs, this novel schizophrenia with depression model is resilient to combined drug treatment in terms of behavioral and functional recovery. Taken together, these data indicate that schizophrenia with depression likely involves a unique pathophysiology that is different from schizophrenia or depression alone.

Modeling the Longitudinal Effects of Insight on Depression, Quality of Life and Suicidality in Schizophrenia Spectrum Disorders: Results from the FACE-SZ Cohort

Background: Up to half of the patients with schizophrenia attempt suicide during their lifetime. Better insight is associated with better functioning but also with increased suicidality. The direction of the relationship between insight and suicidality is not clear, hence we aimed to provide new elements using structural equation modeling. Methods: Insight, quality of life (QoL), depression, and suicidality were measured at baseline and at 12 months in individuals with schizophrenia spectrum disorders. The relationships between these variables were investigated by latent difference score models, controlling for chlorpromazine doses, positive and negative symptoms, and general psychopathology. Results: 738 patients were included, and 370 completed the study. Baseline levels of insight predicted changes in suicidality, whereas baseline levels of suicidality did not predict changes in insight, suggesting that better insight underlies suicidality and predicts its worsening. Our results suggest this temporal sequence: better insight → worse QoL → increased depression → increased suicidality, while insight also affects the three variables in parallel. Conclusion: Better insight predicts a worsening of QoL, depression and suicidality. These findings contribute to our global understanding of the longitudinal influence of insight on suicidality. We advocate that insight-targeted interventions should not be proposed without the monitoring of depression and suicide prevention.