Literature DB >> 33191828

Surviving and thriving - a mixed-methods study of staff experiences of occupational wellbeing in a psychiatric place of safety service.

Olivia Harris1, Pamela Jacobsen1, Rachael Searle-Barnes2, Megan Wilkinson-Tough2.   

Abstract

BACKGROUND: Under the S136 of the UK Mental Health Act, people experiencing a mental health crisis may be taken to a locally agreed location (Place of Safety) by police for urgent assessment. Research has shown that mental health professionals (MHPs) face high levels of burnout, but we know very little about the particular challenges staff who work in extreme clinical settings such as a Place of Safety service face. AIM: This study aimed to fill this gap by exploring the wellbeing experiences of staff in a Place of Safety service.
METHOD: A mixed-methods approach was used, with quantitative data on job satisfaction (Job Satisfaction Survey) and burnout (Maslach Burnout Inventory-Human Services Survey) and qualitative data from focus groups. Purposive sampling was used. Qualitative data was analysed using thematic analysis and descriptive statistics were calculated for the quantitative data.
RESULTS: Twenty staff scored within the moderate range for emotional exhaustion, depersonalisation and personal accomplishment, and in the satisfied range for job satisfaction. Three overarching themes were identified: (i) united as insiders, (ii) surviving and thriving, and (iii) narratives of coping.
CONCLUSIONS: Despite unique setting-related stressors, participants showed comparable levels of wellbeing to other MHPs. Implications are discussed.

Entities:  

Keywords:  Burnout; inpatient; mixed methods; place of safety; staff wellbeing

Year:  2020        PMID: 33191828     DOI: 10.1080/09638237.2020.1844870

Source DB:  PubMed          Journal:  J Ment Health        ISSN: 0963-8237


  1 in total

1.  Relationships among thriving at work, organisational commitment and job satisfaction among Chinese front-line primary public health workers during COVID-19 pandemic: a structural equation model analysis.

Authors:  Mo Yi; Di Jiang; Jingjing Wang; Zeyi Zhang; Yuanmin Jia; Baosheng Zhao; Lei Guo; Ou Chen
Journal:  BMJ Open       Date:  2022-06-07       Impact factor: 3.006

  1 in total

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