Working alliance in treating staff and patients with Schizophrenia Spectrum Disorder living in Residential Facilities

Author:

Fusar‐Poli Laura1,Panariello Fabio2ORCID,Berry Katherine34ORCID,Rocchetti Matteo15,Casiraghi Letizia1,Malvezzi Matteo6,Starace Fabrizio7,Zamparini Manuel8,Zarbo Cristina8,de Girolamo Giovanni8,

Affiliation:

1. Department of Brain and Behavioural Sciences University of Pavia Pavia Italy

2. Department of Biomedical and NeuroMotor Sciences (DIBINEM) University of Bologna Bologna Italy

3. Division of Psychology and Mental Health University of Manchester Manchester UK

4. Department of Research and Innovation Research and Innovation, Greater Manchester Mental Health NHS Foundation Trust Manchester UK

5. Department of Mental Health and Dependence ASST of Pavia Pavia Italy

6. Department of Biostatistics University of Parma Parma Italy

7. Department of Mental Health and Dependence AUSL of Modena Modena Italy

8. Unit of Epidemiological and Evaluation Psychiatry IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli Brescia Italy

Abstract

AbstractObjectivesWorking Alliance (WA) is important in the care of patients with Schizophrenia Spectrum Disorders (SSD). This study aims to determine which sociodemographic and clinical factors are associated with WA, as assessed by patients and staff members in Residential Facilities (RFs), and may predict WA dyads' discrepancies.MethodsThree hundred and three SSD patients and 165 healthcare workers were recruited from 98 RFs and characterized for sociodemographic features. WA was rated by the Working Alliance Inventory (WAI) for patients (WAI‐P) and staff members (WAI‐T). SSD patients were assessed for the severity of psychopathology and psychosocial functioning.ResultsPearson's correlation revealed a positive correlation (ρ = .314; p < .001) between WAI‐P and WAI‐T ratings. Linear regression showed that patients with higher education reported lower WAI‐P ratings (β = −.50, p = .044), while not being engaged in work or study was associated with lower WAI‐T scores (β = −4.17, p = .015). A shorter lifetime hospitalization was associated with higher WAI‐P ratings (β = 5.90, p = .008), while higher psychopathology severity negatively predicted WAI‐T (β = −.10, p = .002) and WAI‐P ratings (β = −.19, p < .001). Better functioning level positively foresaw WAI‐T (β = .14, p < .001) and WAI‐P ratings (β = .12, p < .001). Regarding discrepancies, staff members' age was associated with higher dyads discrepancy in Total scale and Agreement subscale scores, which were also associated with more severe negative symptoms, while patients' age was negatively correlated to Relationship subscale discrepancy.ConclusionsThis study provides insight into the factors that influence WA in SSD patients and health workers in RFs. The findings address interventions to improve WA and ultimately patient outcomes.

Publisher

Wiley

Subject

Clinical Psychology,General Medicine

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