How are compassion fatigue, burnout, and compassion satisfaction affected by quality of working life? Findings from a survey of mental health staff in Italy

BACKGROUND: Quality of working life includes elements such as autonomy, trust, ergonomics, participation, job complexity, and work-life balance. The overarching aim of this study was to investigate if and how quality of working life affects Compassion Fatigue, Burnout, and Compassion Satisfaction among mental health practitioners. METHODS: Staff working in three Italian Mental Health Departments completed the Professional Quality of Life Scale, measuring Compassion Fatigue, Burnout, and Compassion Satisfaction, and the Quality of Working Life Questionnaire. The latter was used to collect socio-demographics, occupational characteristics and 13 indicators of quality of working life. Multiple regressions controlling for other variables were undertaken to predict Compassion Fatigue, Burnout, and Compassion Satisfaction. RESULTS: Four hundred questionnaires were completed. In bivariate analyses, experiencing more ergonomic problems, perceiving risks for the future, a higher impact of work on life, and lower levels of trust and of perceived quality of meetings were associated with poorer outcomes. Multivariate analysis showed that (a) ergonomic problems and impact of work on life predicted higher levels of both Compassion Fatigue and Burnout; (b) impact of life on work was associated with Compassion Fatigue and lower levels of trust and perceiving more risks for the future with Burnout only; (c) perceived quality of meetings, need of training, and perceiving no risks for the future predicted higher levels of Compassion Satisfaction. CONCLUSIONS: In order to provide adequate mental health services, service providers need to give their employees adequate ergonomic conditions, giving special attention to time pressures. Building trustful relationships with management and within the teams is also crucial. Training and meetings are other important targets for potential improvement. Additionally, insecurity about the future should be addressed as it can affect both Burnout and Compassion Satisfaction. Finally, strategies to reduce possible work-life conflicts need to be considered

A multi-element psychosocial intervention for early psychosis (GET UP PIANO TRIAL) conducted in a catchment area of 10 million inhabitants: study protocol for a pragmatic cluster randomized controlled trial

Multi-element interventions for first-episode psychosis (FEP) are promising, but have mostly been conducted in non-epidemiologically representative samples, thereby raising the risk of underestimating the complexities involved in treating FEP in 'real-world' services

Superwellness Program: a cognitive-behavioral therapy-based group intervention to reduce weight gain in patients treated with antipsychotic drugs

Objective: To assess the effectiveness of a cognitive-behavioral therapy-based intervention (Superwellness Program) on weight gain compared with a treatment-as-usual (TAU) approach in patients treated with antipsychotics, and to evaluate the relationship between body mass index (BMI) variation and clinical variables. Method: Eighty-five patients treated with antipsychotics were allocated across two groups, experimental (n=59) and control (n=26). The Superwellness Program (experimental group) consisted of 32 twice-weekly 1-hour sessions, conducted by a psychologist and a nutritionist/nurse, concurrently with moderate food intake and moderate physical activity plans. Sociodemographic, clinical, and biological variables were collected at baseline, at the end of intervention (16 weeks), and after 6 months. Results: BMI change from baseline differed significantly between the experimental and control groups, with a larger decrease in the experimental group (F = 5.5, p = 0.021). Duration of illness moderated the effect of treatment on BMI (p = 0.026). No significant (p = 0.499) effect of intervention during the follow-up period was found. Interestingly, the intervention indirectly induced a significant (p = 0.024) reduction in metabolic risk by reducing BMI. Conclusion: A cognitive-behavioral therapy-based intervention could be useful in reducing weight in a clinical population taking antipsychotics, with consequent benefit to physical and mental health

Prosody abilities in a large sample of affective and non-affective first episode psychosis patients

Objective: Prosody comprehension deficits have been reported in major psychoses. It is still not clear whether these deficits occur at early psychosis stages. The aims of our study were to investigate a) linguistic and emotional prosody comprehension abilities in First Episode Psychosis (FEP) patients compared to healthy controls (HC); b) performance differences between non-affective (FEP-NA) and affective (FEP-A) patients, and c) association between symptoms severity and prosodic features. Methods: A total of 208 FEP (156 FEP-NA and 52 FEP-A) patients and 77 HC were enrolled and assessed with the Italian version of the "Protocole Montreal d'Evaluation de la Communication" to evaluate linguistic and emotional prosody comprehension. Clinical variables were assessed with a comprehensive set of standardized measures. Results: FEP patients displayed significant linguistic and emotional prosody deficits compared to HC, with FEP-NA showing greater impairment than FEP-A. Also, significant correlations between symptom severity and prosodic features in FEP patients were found. Conclusions: Our results suggest that prosodic impairments occur at the onset of psychosis being more prominent in FEP-NA and in those with severe psychopathology. These findings further support the hypothesis that aprosodia is a core feature of psychosis

Classification of first-episode psychosis in a large cohort of patients using support vector machine and multiple kernel learning techniques

First episode psychosis (FEP) patients are of particular interest for neuroimaging investigations because of the absence of confounding effects due to medications and chronicity. Nonetheless, imaging data are prone to heterogeneity because for example of age, gender or parameter setting differences. With this work, we wanted to take into account possible nuisance effects of age and gender differences across dataset, not correcting the data as a pre-processing step, but including the effect of nuisance covariates in the classification phase. To this aim, we developed a method which, based on multiple kernel learning (MKL), exploits the effect of these confounding variables with a subject-depending kernel weighting procedure. We applied this method to a dataset of cortical thickness obtained from structural magnetic resonance images (MRI) of 127 FEP patients and 127 healthy controls, who underwent either a 3Tesla (T) or a 1.5T MRI acquisition. We obtained good accuracies, notably better than those obtained with standard SVM or MKL methods, up to more than 80% for frontal and temporal areas. To our best knowledge, this is the largest classification study in FEP population, showing that fronto-temporal cortical thickness can be used as a potential marker to classify patients with psychosis

Classification of first-episode psychosis in a large cohort of patients using support vector machine and multiple kernel learning techniques

First episode psychosis (FEP) patients are of particular interest for neuroimaging investigations because of the absence of confounding effects due to medications and chronicity. Nonetheless, imaging data are prone to heterogeneity because for example of age, gender or parameter setting differences. With this work, we wanted to take into account possible nuisance effects of age and gender differences across dataset, not correcting the data as a pre-processing step, but including the effect of nuisance covariates in the classification phase. To this aim, we developed a method which, based on multiple kernel learning (MKL), exploits the effect of these confounding variables with a subject-depending kernel weighting procedure. We applied this method to a dataset of cortical thickness obtained from structural magnetic resonance images (MRI) of 127 FEP patients and 127 healthy controls, who underwent either a 3Tesla (T) or a 1.5T MRI acquisition. We obtained good accuracies, notably better than those obtained with standard SVM or MKL methods, up to more than 80% for frontal and temporal areas. To our best knowledge, this is the largest classification study in FEP population, showing that fronto-temporal cortical thickness can be used as a potential marker to classify patients with psychosis

Hippocampal Subfield Volumes in Patients With First-Episode Psychosis

Background: Hippocampal abnormalities have been largely reported in patients with schizophrenia and bipolar disorder, and are considered to be involved in the pathophysiology of the psychosis. The hippocampus consists of several subfields but it remains unclear their involvement in the early stages of psychosis. Aim: The aim of this study was to investigate volumetric alterations in hippocampal subfields in patients at the first-episode psychosis (FEP). Methods: Magnetic resonance imaging (MRI) data were collected in 134 subjects (58 FEP patients; 76 healthy controls [HC]). A novel automated hippocampal segmentation algorithm was used to segment the hippocampal subfields, based on an atlas constructed from ultra-high resolution imaging on ex vivo hippocampal tissue. The general linear model was used to investigate volume differences between FEP patients and HC, with age, gender and total intracranial volume as covariates. Results: We found significantly lower volumes of bilateral CA1, CA4, and granule cell layer (GCL), and of left CA3, and left molecular layer (ML) in FEP patients compared to HC. Only the volumes of the left hippocampus and its subfields were significantly lower in FEP than HC at the False Discovery Rate (FDR) of 0.1. No correlation was found between hippocampal subfield volume and duration of illness, age of onset, duration of medication, and Positive and Negative Syndrome Scale (PANSS). Conclusion: We report abnormally low volumes of left hippocampal subfields in patients with FEP, sustaining its role as a putative neural marker of psychosis onset

Transesophageal endoscopic ultrasound in the diagnosis of the lung masses: a multicenter experience with fine-needle aspiration and fine-needle biopsy needles

Background and aim: Intraparenchymal lung masses inaccessible through bronchoscopy or endobronchial ultrasound guidance pose a diagnostic challenge. Furthermore, some fragile or hypoxic patients may be poor candidates for transbronchial approaches. Endoscopic ultrasound-guided fine-needle aspiration/biopsy (EUS-FNA/FNB) offers a potential diagnostic approach to lung cancers adjacent to the esophagus. We aimed to evaluate the feasibility, accuracy, and safety of trans-esophageal EUS-FNA/FNB for tissue sampling of pulmonary nodules. Methods: We retrospectively analyzed data from patients with pulmonary lesions who underwent EUS-FNA/FNB between March 2015 and August 2021 at eight Italian endoscopic referral centers. Results: A total of 47 patients (36 male; mean age 64.47 ± 9.05 years) were included (22 EUS-FNAs and 25 EUS-FNBs). Overall diagnostic accuracy rate was 88.9% (76.3-96.2%). The sensitivity and diagnostic accuracy were superior for EUS FNB sampling versus EUS-FNA (100% vs. 78.73%); P = 0.05, and (100% vs. 78.57%); P = 0.05, respectively. Additionally, sample adequacy was superior for EUS-FNB sampling versus EUS-FNA (100% vs. 78.5%); P = 0.05. Multivariate logistic regression analysis for diagnostic accuracy showed nodule size at the cutoff of 15 mm (OR 2.29, 1.04-5.5, P = 0.05) and use of FNB needle (OR 4.33, 1.05-6.31, P = 0.05) as significant predictors of higher diagnostic accuracy. There were no procedure-related adverse events. Conclusion: This study highlights the efficacy and safety of EUS-FNA/FNB as a minimally invasive procedure for diagnosing and staging peri-esophageal parenchymal lung lesions. The diagnostic yield of EUS-FNB was superior to EUS-FNA