Background

Mental health nursing is a fundamental aspect in the delivery of mental healthcare. Working within a multidisciplinary context, mental health nurses are tasked with supporting people experiencing mental ill health and emotional distress. They often work side by side with individuals and their loved ones in therapeutic practice and care coordinating recovery orientated practices in collaboration with other providers.1 Mental health nurses also work in potentially unpredictable, stressful and complex environments that require constant review and consideration of actions to assess, comfort, support and empower people experiencing mental ill health, including individuals at risk of suicide. Being in a client-facing role can be challenging, and research shows that recruiting and retaining specialised mental health nurses has proved difficult for the sector.2 Workforce pressures in mental healthcare have been exacerbated by the COVID-19 pandemic through increased workload and greater difficulty in providing care.3 4 New and historical pressures on mental health nurses can lead to negative workforce outcomes for both individual workers (staff burn-out, poor job satisfaction) and healthcare organisations (workplace culture, staff retention), possibly leading to worse outcomes for clients. Issues within the workforce have been previously described as having a lack of role clarity and having poor experiences working, including a lack of professional support and supervision.5 One potential approach to improving the workforce outcomes of mental health nurses has been the concept of clinical supervision (CS).

CS is a supportive, strengths-based process that allows healthcare workers to reflect on clinical experiences with a trusted and nurturing supervisor.6 In this context, CS is an agreed professional arrangement between a supervisor and one or more supervisees. Differing from performance management, CS typically involves regular structured discussion around topics of professional relevance and concern. With support from a trained supervisor, CS is a formalised, psychologically safe practice for reflective thinking and discussion regarding professional development issues, professional boundaries, caseload, decision-making regarding clinical issues and staff interpersonal issues.7 CS in various forms is often used in medicine, nursing, psychology and allied health.

The history of the terminology surrounding CS has been problematic. Lacking a universal definition, ‘CS’ can and has been interpreted in different ways for different settings.8 CS has been used to describe clinical-based observation of skills as a form of performance management. As such, there can be confusion and hesitancy from healthcare workers when considering CS, as to some it is seen as a punitive process that aims to reprimand or scrutinise workers for their performance. Additionally, while the aims of CS are to be a safe and supportive environment to nurture individuals in their professional development, there has been literature outlining the negative effects of people receiving inadequate supervision. Given the sensitive nature of issues discussed in CS, circumstances where there are breaks in trust or ethics in the supervision process can result in feelings of shame, self-doubt and mistrust.9

For the purposes of this review, we will be using the definition described in the position statement on CS for nurses and midwives published by the Australian College of Mental Health Nurses, Australian College of Midwifery and the Australian College of Nursing.8 This statement notes that while alternatives to the term ‘CS’ have been offered, they do not provide an adequate solution to the issue of misunderstanding the concept.

CS has been reported to have benefits for the workforce and for clients. Benefits of CS for workforce outcomes have been reported as supporting staff who work in isolation, assisting them to better deal with and attempt to overcome workplace issues, developing deeper nursing competence and knowledge, and reducing exhaustion and burn-out.10–13 Benefits for clients, while more difficult to effectively evaluate, have included stronger relationships with their healthcare providers and greater satisfaction with their quality of care.14 15 Given the potential benefits, CS has been suggested as a way to support the mental health nursing workforce.

CS is a complex idea that exists within a complex system. As such, there has been noted criticism of the evidence body aiming to evaluate the implementation and effectiveness of CS due to multiple confounding factors.16 17 Previous literature reviews exploring CS have focused on workforce outcomes in health workers generally,18 and the association between characteristics of supervision and personal formative and restorative outcomes.19 Currently, there has not been a review of the available published literature on the impacts of CS on the workforce focusing on mental health nursing. The justification for such a review is twofold; first, mental health nurses form the largest number of mental healthcare providers and face unique workforce challenges in terms of shortages and staff retention.20 Second, mental health nurses as a profession have struggled to fully implement CS within workplaces compared with other mental healthcare providers. This is due to their role in providing care around the clock, often in inpatient settings where nurses are the last staff to leave the ward. Therefore, the aims of this review are as follows:

Identify, map and analyse the available evidence reporting on the impact of CS on workforce outcomes for mental health nurses.

Identify any potential gaps in evidence for the effect of clinical supervision on workforce outcomes.

Methods and analysis

This article describes the protocol for a scoping review currently being conducted to answer the review aims. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Scoping Review Extension (PRISMA-ScR) guidelines are being used to guide the planning and reporting of this scoping review.21

Defining workforce

It is important to define the workforce outcomes that are relevant to this review. Given the reported potential benefits of CS, we define workforce outcomes as relating to the personal attributes of mental health nurses, and the structural attributes of the systems and context they work within (see figure 1). Definitions of how each attribute will be defined and conceptualised throughout the review process can be found in table 1.

Figure 1

Conceptualisation of measurable workforce outcomes explored in this scoping review.

Table 1

Definitions and conceptualisation of the individual concepts to be explored in this review

Development of the search strategy

The search strategy for this review followed an iterative process involving the research team with the assistance of a senior clinical and health sciences librarian (SD). Development of the search strategy initially followed a population concept context (PCC) framework. Based on the aims of the review, we determined the population to be mental health nurses, the concept to be CS, and the context to be workforce attributes (table 2). The target databases for this review were identified as Medline, CINAHL, Embase and PsycINFO. These databases were chosen as being the most relevant to the subject matter.22 A search strategy was initially developed for Medline and then adapted for the other databases.

Table 2

Population concept context framework with preliminary search strategies

Preliminary searches for this review were developed using each section of the PCC framework. However, initial searches combining the population and concept elements of the framework were returning relatively small numbers of articles (searched in Medline 1 August 2023, 249 articles). Therefore, it was decided to use the ‘Drop a Concept’ tactic.23 Instead of including workforce outcomes in the search—which makes the search more complicated and introduces the possibility that relevant articles may be missed—the research team decided to screen all articles relating to CS within mental health nursing and use the workforce outcomes aspect of the PCC framework as an inclusion criterion.

The search strategy used for this review consisted of subject headings, key words and related terms for mental health nursing and CS (table 3). Individual concepts were combined using Boolean operators and, where relevant, truncation and adjacent word features were used to identify potentially relevant articles. Articles were limited to those published in English. No publishing date limits were applied. The first 50 articles retrieved were screened by the authors to examine the validity of the search.

Table 3

Search strategy performed in Medline (Ovid)

Finding grey literature

In addition to searching academic journal databases, the authors will search for potentially relevant studies that have not been published in an academic journal, known as grey literature. Searching for grey literature will be conducted using Google and Grey Matters as databases. Additionally, included studies will be backwards and forwards citation searched to identify any relevant grey literature sources.

Eligibility criteria

Screening for this review will follow a two-step process. First, two researchers will independently screen identified articles by title and abstract against inclusion and exclusion criteria. To be considered for inclusion in our review, articles will need to meet all inclusion criteria and none of the exclusion criteria. Those criteria will be:

Inclusion criteria

Research involving mental health nurses.

Exploring the effect of CS in relation to workforce outcomes.

Exclusion criteria

Research protocols, commentaries, editorials, conference papers, posters, oral presentations, abstracts, social networks and blogs.

Non-English language publications.

Studies on preceptorship or other student-based mentorship structures.

Articles not excluded by title and abstract screening will then be screened by full text. Two authors (JHM and KR) using the same inclusion and exclusion criteria will determine the articles relevant to the review. In both stages of the screening, any disagreements between the authors will be discussed to resolve conflicts. If these conflicts cannot be resolved, a third researcher (NP) will settle the disputes. A PRISMA-ScR flow chart will be used to report on the process of identifying and excluding studies from the scoping review, with all reasons for exclusion documented. The reference lists of included articles will be handsearched to identify any relevant studies that may have been missed by the search.

Data analysis

Predefined data items will be used to summarise the included studies. These items will include:

Authors.

Year of publication.

Study location.

Study design.

Sample size.

Participant characteristics.

Type of supervision undertaken (one-on-one, group, mixed).

Mode of supervision (in-person, online).

Frequency of supervision.

Duration of supervision.

Model of CS undertaken (if described).

Workforce outcome(s) measured.

Research instruments used (if any).

Main findings.

Additionally, data analysis for this review will follow a narrative synthesis approach.24 This will be done in an inductive manner with no predetermined themes. Analysis will be performed by one author, with another checking the coding for accuracy and omissions.