How has COVID‐19 affected mental health nurses and the delivery of mental health nursing care in the UK? Results of a mixed‐methods study

  1. Una Foye
  2. Christian Dalton‐Locke
  3. Jasmine Harju‐Seppänen
  4. Rebecca Lane
  5. Lewys Beames
  6. Norha Vera San Juan
  7. Sonia Johnson
  8. Alan Simpson

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Abstract

What is known on the subject?

  • During the COVID‐19 pandemic, there has been research considering the impact on medical healthcare professionals and the mental health needs of the general population. However, limited focus has been placed on mental health services or mental health staff providing care in the community and in hospitals. While nurses make up the largest section of the mental health workforce in the UK, the impact that this pandemic has had on their work has been largely ignored.

What the paper adds to existing knowledge?

  • This paper provides a unique insight into the experiences and impact that the COVID‐19 pandemic has had on mental health nurses across a range of community and inpatient settings to understand what has changed in their work and the care they can and do provide during this crisis. This includes exploring how services have changed, the move to remote working, the impact of the protective equipment crisis on nurses and the difficult working conditions facing those in inpatient settings where there is minimal guidance provided.

What are the implications for practice?

  • By understanding the impact the pandemic has had on mental health nursing care, we can understand the gaps in guidance that exist, the challenges being faced and the impact the crisis has had on care for mental health service users. By doing so, we can plan for the ongoing nature of this pandemic and the aftermath that the crisis may leave for our service users and workforce alike.

Abstract

Introduction

While evidence has emerged concerning the impact of COVID‐19 on the general population and the challenges facing health services, much less is known regarding how the pandemic has directly affected the delivery of mental health nursing care.

Aim

This paper aimed to explore how COVID‐19 has affected the ability of mental health nurses to deliver care in community and inpatient mental health services in the UK.

Method

We investigated staff reports regarding the impact of the COVID‐19 pandemic on mental healthcare and mental health service users in the UK, using a mixed‐methods online survey. A total of 897 nurses across a range of inpatient and community settings participated.

Discussion

Key themes within the data explore the following: new ways of working; remote working; risks of infection/infection control challenges; and the impact on service users. Targeted guidelines are required to support mental health nurses providing care and support during a pandemic to people in severe mental distress, often in unsuitable environments.

Implications for Practice

Service developments need to occur alongside tailored guidance and support for staff welfare supported by clear leadership. These findings identify areas requiring attention and investment to prepare for future crises and the consequences of the pandemic.

Article activity feed

  1. Version published to 10.1111/jpm.12745
  2. ScreenIT

    SciScore for 10.1101/2020.11.05.20226472: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: The university research ethics committee approved this study [ethics information to be added here].
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Quantitative data were then imported to SPSS 26 for analysis (IMB, 2019).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    The qualitative data was analysed within Excel, using a thematic analytic approach, as outlined by Braun and Clarke (2006).
    Excel
    suggested: None
    Microsoft Excel was used to record the extracted chunks of data and associated codes.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.11.05.20226472v1 on medRxiv