Burnout, mood disorders and socioeconomic consequences among civil servants: a protocol for a systematic review

Ethics

Due to the characteristics of the design of this study, it was deemed unnecessary to obtain approval from the ethics committee.

Patient and public involvement

As this is a systematic review protocol, no patient or public will be involved.

Study registration

This systematic review has been registered on the International Prospective Register of Systematic Reviews (PROSPERO) under the registration code CRD42023410761¹⁸. The review’s development will be based on the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)¹⁹.

Plans for dissemination

The findings of this comprehensive analysis will be shared through peer-reviewed journals, discussed in seminars and presented at relevant conferences and symposia. Any modifications made to the methodology will be meticulously documented, including saved searches and analytical techniques, and stored in bibliographic databases utilized for data gathering and synthesis.

Research objectives

To synthesize what has been published in relation to burnout and mood disorders among civil servants or public workers and the socioeconomic consequences of these conditions for the society and for the workers.

Research questions

Primary research question: What intervention strategies have been applied for mood disorders and burnout syndrome in the case of civil servants or public workers.

Secondary research question: What are the socioeconomic consequences of mood disorders and burnout in this population?

Search strategy

To enhance the methodological transparency and reproducibility of the results, we will conduct a search strategy based on the PRISMA¹⁹ checklist. Furthermore, we formulated a guiding question for this review using the PICO acronym (Population / Intervention (Exposure) / Comparison (Control) / Outcomes)²⁰, to ensure a comprehensive and systematic search of the scientific literature.

Main databases regarding health and economics published papers will be queried. We will search on: MEDLINE, CINAHL, Scopus, PsycINFO, PsycArticles, EconLit, Web of Science and The Cochrane Library of Systematic Reviews. Only peer review articles, papers and reviews will be included. They must be written in English or in Spanish, otherwise they are excluded.

As an example of a search strategy, the following equation will be used:

( ( ( burnout OR (mood AND disorder*) OR anxiety OR depression OR stress) AND ( "Civil Servant" OR ( public AND worker AND administration ) OR "Government Worker" OR "Public Employee" OR state AND worker OR state AND employee) AND ( economic AND (consequences OR effects OR results) OR "sick leaves" OR absenteeism OR presenteeism OR "early retirement")))

Selection of studies

The selection of studies will be based on the inclusion and exclusion criteria detailed in Table 1. Search strategies will be developed based on keywords: Burnout, Mood Disorders, Anxiety, Depression, Stress, Civil Servant, Public Worker, Administration, Government Worker, Public Employee, State Worker, State Employee, Economic Consequences, Economic Effects, Economic Results, Sick Leaves, Absenteeism, Early Retirement. Boolean operators ’AND’ and ’OR’ will be combined with keywords.

Screening

The screening phase will utilize the online software Covidence, which is endorsed by Cochrane. Covidence offers a free trial period for its systematic review software. To ensure precision, two independent reviewers will conduct the screening process. In case of any inconsistencies, Covidence will highlight them. To resolve such issues, a third reviewer, who has no affiliation with the previous two, will act as a tiebreaker. It's important to note that the decision of the third reviewer will not be automatically accepted, and if necessary, further discussion may take place.

The evidence selection process will be done as shown in the flowchart formulated based on the PRISMA recommendations¹⁹. See Figure 1.

Figure 1. PRISMA flow diagram.

Identification of studies to be included in the systematic review.

Data extraction

To assess the quality of the included studies and synthesize the evidence, a Microsoft Excel spreadsheet, which has been pre-defined and tested through a pilot sample, will be utilized to extract data. The data extracted will comprise of the title, reference, publication year, study design, population under study, study location, participants' general and demographic characteristics, diagnostic criteria employed, treatments or intervention applied, study methodology, identified costs, main findings, funding sources, and methods for assessing the risk of bias.

Two researchers who will be blind to each other's work will perform the data extraction. A third researcher will review the extraction without the knowledge of the others. In case of discrepancies, the third researcher will act as a tiebreaker. Finally, the obtained data will be discussed among the entire participating team to establish a final consensus.

Methodological evaluation

In order to assess the risks of bias, aspects such as the use of randomisation in studies involving the formation of treatment groups, treatment allocation, blinding, and timing of outcome assessment (during evaluation or at the time of results) will be considered. Mixed Methods Appraisal Tool (MMAT) version 2018²¹ will be used to guide the quality assessment.

Data synthesis

The content of the included studies will be subject to a descriptive synthesis, which will cover population characteristics, study context, type of diagnostics investigated, cost identified, methods used, and significance of results. There is no minimum number of studies required to be included in this review. To ensure evidence synthesis and control the risk of bias due to selective publication, the methodological evaluation steps described earlier will be followed. In the event that a sufficient number of studies following a similar strategy were found, which consequently would allow for data synthesis, they would be grouped based on the similarity of design, type of intervention, and sample size. In the analysis of the extracted data, special focus will be placed on gender analysis, as well as the consequences for women at different levels of responsibility or leadership positions.