Global prevalence of burnout symptoms among nurses: A systematic review and meta-analysis

Journal of Psychiatric Research 123 (2020) 9–20

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Journal of Psychiatric Research journal homepage: www.elsevier.com/locate/jpsychires

Global prevalence of burnout symptoms among nurses: A systematic review and meta-analysis

T

Tiffany Wooa, Roger Hob,c,d, Arthur Tange,∗, Wilson Tama,f a

Alice Lee Centre for Nursing Studies, National University of Singapore, Singapore Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore c Biomedical Global Institute of Healthcare Research & Technology (BIGHEART), National University of Singapore, Singapore d Center of Excellence in Behavioral Medicine, Nguyen Tat Thanh University, Viet Nam e Department of Software, Sungkyunkwan University, Suwon, Republic of Korea f Center of Excellence in Evidence-based Medicine, Nguyen Tat Thanh University, Viet Nam b

A R T I C LE I N FO

A B S T R A C T

Keywords: Burnout Depersonalisation Global Emotional exhaustion Nurse Prevalence

WHO recently declared burnout as a “occupational phenomenon” in the International Classification of Diseases 11th revision (ICD-11), recognizing burnout as a serious health issue. Amongst healthcare workers, nurses are known to struggle with burnout symptoms the most, carrying serious consequences for patients, other healthcare professionals and healthcare organisations. Evidence has suggested that burnout symptoms in nurses is high across specialties and countries, but no meta-analysis have been performed to investigate burnout symptoms prevalence in nurses globally. We conducted a systematic review and meta-analysis to examine burnout symptoms prevalence in nurses worldwide using 8 academic research databases. Risk of bias, heterogeneity and subgroup analyses were further conducted in the meta-analysis. 113 studies were included for systematic review and 61 studies for the meta-analysis, consisting 45,539 nurses worldwide in 49 countries across multiple specialties. An overall pooled-prevalence of burnout symptoms among global nurses was 11.23%. Significant differences were noted between geographical regions, specialties and type of burnout measurement used. SubSaharan African region had the highest burnout symptoms prevalence rate while Europe and Central Asia region had the lowest. Paediatric nurses had the highest burnout symptoms prevalence rates among all specialties while Geriatric care nurses had the lowest. This study is the first study to synthesize published studies and to estimate pooled-prevalence of burnout symptoms among nurses globally. The findings suggest that nurses have high burnout symptoms prevalence warranting attention and implementation. This study serves as an impetus for intervention studies and policy change to improve nurses’ work conditions and overall healthcare quality.

1. Introduction Burnout, first described by Freudenberger (1974), is a psychological condition involving a prolonged response to enduring interpersonal stressors (Leiter and Maslach, 2009). Fredenberger (1975) summarized the signs of burnout including the hopeless, fatigued, bored, resentful, disenchanted, discouraged, confused quickness to anger, instantaneous irritation, frustration responses, totally negative attitude, etc. Burnout was further developed independently by Maslach (Maslach and Jackson, 1981) to be characterised by three domains: emotional exhaustion (EE), depersonalisation (DP), and a diminished sense of personal accomplishment (PA). The interplay of these three domains distinguishes burnout from stress and other psychological conditions with similar symptoms, such as depression and fatigue (Awa et al., 2009). On

∗

28 May 2019, The World Health Organisation (WHO) declared burnout as a “occupational phenomenon” in International Classification of Diseases 11th revision (ICD-11), stating that burnout is a syndrome resulting from “chronic workspace stress that has not been successfully managed” (WHO, 2019). This recent declaration recognized burnout as a serious health issue, and WHO is planning to develop “evidencebased” guidelines for mental well-being in workplace. Healthcare workers (HCW) are consistently subjected to emotionally draining stressors in the provision of complex care and treatment to patients, thereby posing the risk of occupational burnout (GómezUrquixa et al., 2016). Among HCWs, nurses have been reported to have higher burnout prevalence (Lasebikan and Oyetunde, 2012). The frontline caring role that nurses play to patients at their most vulnerable leave nurses particularly susceptible to burnout through

Corresponding author. Natural Science Campus, 2066 Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do, 16419, Republic of Korea. E-mail address: [email protected] (A. Tang).

https://doi.org/10.1016/j.jpsychires.2019.12.015 Received 10 August 2019; Received in revised form 6 December 2019; Accepted 27 December 2019 0022-3956/ © 2020 Elsevier Ltd. All rights reserved.

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Studies were excluded if they:

unrelenting physical and psychological stress deriving from holistic patient care (Boyle, 2011). Burnout in nurses occur when excessive workloads are compounded by entrenched systemic issues such as working irregular hours, “voluntary” overtime, rotating shifts and understaffing. The resultant distressing mismatch between expectations and reality of nursing as a profession, increases propensity for burnout (Rezaei et al., 2018a,b). Burnout has consequences on physical and mental health of nurses, workplace, quality of nursing care, and patients’ conditions and recovery. It affects individual nurses by generating physical symptoms of fatigue, anxiety, sleep disorders, headache, insomnia, frequent colds alongside reduced concentration and memory (Merces et al., 2017; Pradas-Hernández et al., 2018); thereby, resulting in various forms of job withdrawal such as absenteeism, intention to leave and actual turnover (Leiter and Maslach, 2009). Alarmingly, the WHO (2016) estimated a global deficit of approximately 7.6 million nurses by 2030. The National Sample Survey of Registered Nurses in 2008 reported that 35% of employed, non-practicing nurses quoted burnout as the chief reason for quitting (McHugh et al., 2011). High nurse shortage and turnover rates correspond to high expenses due to recruitment efforts and orienting new nurses (Hart et al., 2014). Some recent reviews measure burnout prevalence among nurses working in specific specialties of care – emergency (Gómez-Urquiza et al., 2017); oncology (Gómez-Urquiza et al., 2016; Toh et al., 2012); paediatric (Pradas-Hernández et al., 2018); primary (Monsalve-Reyes et al., 2018). Several studies examined prevalence of professional burnout in nurses in specific countries or regions (Elbarazi et al., 2017; Rezaei et al., 2018a,b), however, no studies have estimated the overall prevalence of nurses’ burnout globally and only a few included metaanalysis (Gómez-Urquiza et al., 2017; Monsalve-Reyes et al., 2018; Pradas-Hernández et al., 2018; Rezaei et al., 2018a,b; Zhang et al., 2018). The aim of this study is to include all available evidence from literature for a focused examination of the prevalence of burnout symptoms in nurses worldwide, evaluated by means of a validated scale, e.g. Maslach Burnout Inventory (MBI) (Maslach and Jackson, 1981, 1986; Maslach et al., 1996). The primary objectives of this study are:

1 had mixed samples of HCWs without clearly defining independent data for nurses; 2 investigated dental nurses, nursing aides, nursing technicians, auxiliary nurses, nursing assistants or other equivalents, 3 used non-validated single questions, instruments or surveys; 4 were interventional studies without baseline prevalence data, case reports, case series, cohort studies, case-controls, conference abstracts, review articles, magazine articles, newspaper articles, commentaries, letters to the editor, or failed to provide sufficient data to calculate aggregate burnout prevalence; or 5 had inaccessible full texts; 2.2. Search strategy A three-step search strategy was utilised. An initial scoping-search was conducted with Google Scholar and Cumulative Index to Nursing and Allied Health Literature (CINAHL) to identify suitable keywords and index terms, while ensuring no similar systematic review had been conducted in the past five years. Search strategy was developed by the first reviewer (TW) for each database based on three key concepts – ‘burnout’, ‘nurses’ and ‘prevalence’. The final search strategy was crosschecked with the second reviewer (WT) for adequacy and coverage of topic. A medical librarian was also consulted during the search strategy development. Eight electronic databases were used in the searches: PubMed, Excerpta Medica Databse (EMBASE), Cochrane Central Register of Controlled Trials (CENTRAL), Scopus, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Proquest Theses and Dissertations, and Web of Science. Time frame of the searches is from inception up to 31 December 2018. Search alerts were set up to notify the authors of any relevant studies published between 1 January 2019 and February 2019. Lastly, the reference lists of relevant studies were manually screened to identify additional undetected, relevant studies. 2.3. Study selection

• What is the prevalence of burnout symptoms in nurses globally? • Do factors such as geographic location and specialty affect pre-

This study was conducted and reported in accordance with the Cochrane Handbook of Systematic Reviews (Higgins and Green, 2011) and Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines (Liberati et al., 2009) respectively.

Search results were imported and managed using EndNote X9 (Thomson Reuters, New York, USA). Duplicates were removed electronically and then manually. Subsequently, the two reviewers (TW and WT) independently screened the studies by title and abstract. Full-text of potential studies were retrieved and reviewed by the two reviewers. Study authors were contacted to obtain the full paper via ResearchGate or e-mail if it was not available in the library. Throughout the selection process, any disagreements between the two reviewers were resolved via discussion, failing which, consulting a third review (RH) would have been considered.

2.1. Eligibility criteria

2.4. Data extraction

valence of burnout symptoms in nurses?

2. Material and methods

Data extraction was performed using a standard data extraction form. The form was developed based on the Joanna Briggs Institute's Reviewers' Manual for The Systematic Review of Prevalence and Incidence Data (Munn et al., 2014). To maintain data extraction rigour, the two reviewers piloted the data extraction form on the first 15 studies to assess its appropriateness, accuracy and relevance. No issue was identified during the pilot trial.

Studies were included if they were quantitative studies which: 1 investigated burnout symptoms in nurses (Licensed Practical Nurses (LPNs) and above); 2 included mixed samples of HCWs with provision of independent information on nurses; 3 used validated instruments for measuring burnout symptoms (e.g. MBI, Professional quality of life scale (ProQOL) (Stamm, 2005, 2009), etc.); 4 presented aggregate prevalence or provided sufficient raw data for computation; 5 were intervention studies presenting appropriate baseline burnout prevalence data; and 6 were written in English.

2.5. Risk of bias assessment The final included studies were appraised for their risk of bias using an adaptation of the tool developed by Hoy et al. (2012) for prevalence studies, comprising ten items. The tool assesses both external and internal validity. For the first nine items, one point is given if it is rated as high risk. The last item is the total score of the first nine items. The 10

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T. Woo, et al.

overall risk is classified as low, moderate and high if the total score is 0–3, 4–6 and 7–9. The risk of bias assessment was conducted by R1 and counter-checked by R2 for discrepancies which were resolved by discussion.

2.6. Data synthesis Prevalence rates (p) were calculated as follows:

Prevalence =

number of nurses meeting high burnout criteria total number of nurses sampled

The standard error (SE) of burnout prevalence was computed using the below equation (Collett, 2003), number of nurses (n) and prevalence of high burnout symptoms in nurses (p).

SE =

p x (1 − p) n

In case there was no high burnout event (i.e. number of nurses meeting high burnout symptoms criteria = 0), 0.5 was substituted for approximating prevalence and standard error (Collett, 2003).

2.7. Meta-analysis Meta-analysis was conducted to synthesize results of included studies. Studies with a definition of high burnout symptoms based on the standard or commonly used cut-off for the respective measurement tool were included in the meta-analysis. Studies which did not use standard or commonly used burnout symptoms classifications were not included in the meta-analysis. The recommended cut-off scores of high burnout symptoms for the three subscales in MBI scale, namely Emotional Exhaustion, Depersonalisation, and Personal Accomplishment, were used (Maslach et al., 1996) and the classification of overall high burnout symptoms by Ramirez et al., (1996), i.e. high burnout in the Emotional Exhaustion and Depersonalisation subscale and low burnout in the Personal Accomplishment subscale, was adopted. The high burnout symptoms for the Professional Quality of Life (ProQOL) scale (Stamm, 2005, 2009, 2010) was classified by the total score ≥42 or the t-score > 57. For Copenhagen Burnout Inventory (CBI), the work-related burnout component was used and the cut-off for high burnout symptoms was taken as 75 or above (Kristensen et al., 2005). Similar approach was adopted for other scales. A pooled effect estimate was derived based on the computed prevalence of high burnout using random-effects model with the inverse-variance weighting (Higgins and Green, 2011). Results were presented with 95% confidence intervals (95% CI). (Higgins and Green, 2011). Heterogeneity between studies were assessed by Cochran's Q statistic and I2 index. (Denison et al., 2013; Fiest et al., 2014). I2 values of 25% is considered low, 50% moderate, and 75% high (Ho et al., 2014). As the analytical results revealed high heterogeneity, the random-effects model was employed. All statistical analyses were conducted using the Review Manager (RevMan Version 5.3) (The Nordic Cochrane Centre, Copenhagen). Predefined subgroup analyses were conducted to explore the sources of heterogeneity across studies – by geographical region, specialty, and burnout measurement tool – and assess their effect on nurses' prevalence of burnout symptoms (Munn et al., 2015). The geographical regions were grouped based on the World Bank Group (WBG) system's classification (The World Bank Group [WBG], 2019). Studies of nurses from multiple or unspecified specialties were grouped under “Multidepartment”. Lastly, as varying criteria may make the pooling of results in a meta-analysis difficult (Fiest et al., 2014), the type of burnout measurement tool used was analysed by grouping the studies according to the instruments used.

Fig. 1. PRISMA flow diagram.

3. Results 3.1. Search results summary 113 studies were included in this meta-analysis (The full list is provided in Appendix I). 28,022 studies were identified from the eight databases. After duplicates removal, 11,084 remaining studies were screened by title and abstract using the previously described eligibility criteria. Studies not meeting the inclusion criteria were removed. Over caution was applied for any uncertainties, including the respective study for full-text review. 1,073 remaining studies were eligible for fulltext review. 95 unavailable or inaccessible studies were excluded. These studies were mainly from local journals, or theses from respective university libraries inaccessible by the public. On stringently evaluating the full texts of the remaining 978 studies, 880 were excluded with reasons documented in Appendix II. Lastly, chain searching of the reference lists of relevant studies identified 15 additional studies for inclusion. Fig. 1 illustrates a summary of the literature identified at each stage of the process.

3.2. Characteristics of the included studies 113 studies involving of 45,539 nurses is covered in this review. All studies were cross-sectional or mixed-method studies, except for two 11

Country

Egypt United States Columbia India Brazil Egypt Sweden

United States Australia

United States Brazil United States United States United States Ireland

Taiwan United States

United States United States Brazil United Kingdom Brazil United Kingdom United States South Africa Turkey Swit-zerland Brazil Brazil United States United States Brazil

Brazil

Iran United States Germany Belgium

Colombia China Australia, China

Palestine Switzerland Australia

Author, Year

Abdo et al. (2015) Alsop (2012) Álvarez Verdugo (2013) Amin et al. (2015) Andolhe et al. (2015) Anwar et al. (2017) Astrom et al. (1990)

Barcley (2007) Bennett et al. (1994)

Berger et al. (2015) Bezerra et al. (2009) Brennan (1989) Campbell (2017) Cash (1994) Chernoff et al. (2019)

Chin et al. (2015) Copeland et al. (2018)

Couch (2017) Curran (2005) das Merces et al. (2016) Dawson (2015) de Vasconcelos et al. (2017) Dixon (2008) Dominguez-Gomez (2014) Elkonin et al. (2011) Erdogan et al. (2018) Favrod et al. (2018) França et al. (2012) Franco et al. (2011) Franklin (2014) French (2006) Fumis et al. (2017)

Galiana et al. (2017)

Gholami et al. (2016) Giles (2011) Goetz et al. (2012) Gosseries et al. (2012)

Grisales Romero et al. (2016) Guo et al. (2017) Guo et al. (2018)

Hamdan et al. (2017) Heeb et al. (2014) Hegney et al. (2015)

Table 1 Study characteristics.

12 Cross-sectional Cross-sectional Cross-sectional

Cross-sectional Cross-sectional Cross-sectional

Cross-sectional Cross-sectional Cross-sectional Cross-sectional

Cross-sectional

Cross-sectional Cross-sectional Cross-sectional Mixed method Cross-sectional Mixed method Mixed method Cross-sectional Cross-sectional Mixed method Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional

Cross-sectional Cross-sectional

Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional

Cross-sectional Cross-sectional

Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional

Study design

Article Article Article Article Article

Article

Article

Article Article Article Article Article

Article

Article

Journal Article Journal Article Journal Article

Journal Article Journal Article Journal Article

Journal Article Thesis Journal Article Journal Article

Journal Article

Thesis Thesis Journal Thesis Journal Thesis Thesis Journal Journal Journal Journal Journal Thesis Thesis Journal

Journal Article Journal Article

Journal Article Journal Article Thesis Thesis Thesis Journal Article

Thesis Journal Article

Journal Thesis Journal Journal Journal Journal Journal

Type of publica-tion

Nurses, physicians, admin staff Nursing & medical managers Nurses

Nurses, nursing assistants Nurses Nurses

Nurses Nurses, physicians, social workers, other allied HCW Nurses Nurses Nursesb Nurses, LPNs Nurses Nurses, administrators, care assistants, physicians, porters, radiographers Nurses Nurses, ancillary staff, clerical staff, physicians, psychiatric staff Nurses Nurses NPs Nurses Nurses Nurses Nurses Nurses Nurses Nurses, midwives Nurses Nursing residents Nurses Sexual assault nurse examiners Nurses, nurse technicians, physicians, respiratory therapists Nurses, nursing assistants, physicians, psycho-logists, social workers, others Nurses Nurses Nurses Nurses, physicians, others

Nurses, physicians Nursesa Nurses Nurses Nurses, nursing aides and technicians Nurses Nurses, nursing aides, LPNs

Population type

Emergency care Multi-specialty Multi-specialty

Multi-specialty Home care Multi-specialty Neurorehab-ilitation & nursing homes Multi-specialty Multi-specialty Multi-specialty

Palliative care

ICU Multi-specialty Primary care Multi-specialty ICU Palliative care Emergency care ICU Paediatric care Multi-specialty Emergency care Multi-specialty Multi-specialty Multi-specialty Multi-specialty

Multi-specialty Emergency care

Paediatric care Emergency care Multi-specialty Geriatric Multi-specialty Emergency care

Palliative care HIV/AIDs

Multi-specialty Multi-specialty Multi-specialty ICU ICU Multi-specialty Geriatric care

Specialty

161/444 257/449 1608

41/174 94 297

415 35 86 246/523

154/546

24 38 189 100 91 27 42 30 104 213 38 16 7 30 63/283

1384 57/147

239 17 13 18 58 50/97

195 54/84

284/523 26 22 129 100/287 227 234/358

Sample, n (nurse/nonnurse)

MBI-HSS MBI-HSS ProQOL

– 184 (71.60) 1487 (92.48)

(continued on next page)

MBI-HSS MBI-GSc MBI-GSc

– 94 (100) 276 (92.93)

MBI-HSS ProQOL AVEM MBI-HSS

ProQOL

– – AU - 46.05; CN - 29.50 – 46.70 –

–

–

ProQOL MBI-HSS MBI-HSS MBI-HSS MBI-HSS CBI ProQOL ProQOL MBI-HSS MBI-HSS MBI-HSS MBI-HSS Pro-QOL ProQOL MBI-HSS

343 (82.65) 34 (97.14) 66 (76.74) –

– 38 (100.00) 183 (96.83) – 81 (89.01) – 29 (69.05) 28 (93.33) 78 (75.00) 200 (93.90) – 13 (81.25) 7 (100) – –

– – – – 30.82 – 42.20 38.70 – – – 25.80 – – –

CBI ProQOL

ProQOL MBI-HSS MBI-HSS ProQOL MBI-HSS OLBI

MBI-HSSe ProQOL MBI-HSS ProQOL MBI-HSS MBI-HSSe Tool by Pines and Maslach (1978) MBI-HSS MBI-HSSe

BO tool

31.93 – – –

1384 (100.00) –

231 (96.65) 13 (76.47) 13 (100) 17 (94.44) 57 (98.28) –

– 37.00 – – – – 31.90 –

16 (8.21) 36 (66.67)

– 22 (84.62) 19 (86.36) – – – –

– 31.70 39.22 28.37 37.54 28.90 – 42.00 –

n (%) of female nurses

Age of nurses, mean years

T. Woo, et al.

Journal of Psychiatric Research 123 (2020) 9–20

Mixed method Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Mixed method Cross-sectional Cross-sectional

Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional

Portugal

United States United States United States Brazil United States China United States Australia Indonesia

Norway United States Sweden Spain

Iran

United Kingdom South Korea United States Kenya Austria United States South Africa United States United States United States Swit-zerland Iran

United States Spain Poland Uganda United States Brazil Turkey Sweden

Romania

France

Cyprus Caribbean Iran Brazil

Hernández-Marrero et al. (2016) Hilliker (2007) Hinderer et al. (2014) Holliday (2015) Holmes et al. (2014) Hooper et al. (2010) Hu et al. (2015) Hurley (2017) Huynh et al. (2018) Iftadi et al. (2016)

Isaksson Rø et al. (2010) Johnson (1996) Juthberg et al. (2010) Kareaga et al. (2009)

Khodadadi-zadeh et al. (2012) Kilfedder (2003) Kim et al. (2015) Knauer (2018) Kokonya et al. (2014) Lederer et al. (2008) Markwell et al. (2016) Mashego et al. (2016) Mason et al. (2014) Mealer et al. (2009) Mealer et al. (2012) Merlani et al. (2011) Mohammadpoorasl et al. (2012) Moore (2017) Moreno-Casbas et al. (2018) Mroczek et al. (2018) Muliira et al. (2016) Oganowski (1983) Oliveira et al. (2018) Önder et al. (2008) Peterson et al. (2008)

Popa et al. (2010)

13

Quenot et al. (2012)

Raftopoulos et al. (2012) Regis-Andrew (2012) Rezaei et al. (2018) Ribeiro et al. (2014)

Cross-sectional Cross-sectional Cross-sectional Cross-sectional

Interven-tional

Cross-sectional

Interventional Cross-sectional Cross-sectional Cross-sectional

Cross-sectional

United States

Helfrich et al. (2017)

Study design

Country

Author, Year

Table 1 (continued)

Article Article Article

Article Article Article

Article Article Article Article Article Article Article Article Article

Article

Journal Article Thesis Journal Article Journal Article

Journal Article

Journal Article

Thesis Journal Journal Journal Thesis Journal Journal Journal

Thesis Journal Thesis Journal Journal Journal Journal Journal Journal Journal Journal Journal

Journal Article

Thesis Journal Article Thesis Journal Article Journal Article Journal Article Thesis Journal Article Confe-rence Proceed-ings Journal Article Thesis Journal Article Journal Article

Journal Article

Journal Article

Type of publica-tion

physicians, nursing technicians

physicians physicians

medics, others

Nurses Nurses Nurses, physicians, paramedics Nurse-midwives Nurses Nurses Nurses Nurses, assistant nurses, physicians, paramedics, others Nurses, physicians, ambulance drives, paramedics Nurses, nursing aids, physicians, psychologist Nurses Nurses Nurses Nurses

Nurses, Nurses Nurses Nurses, Nurses, Nurses Nurses Nurses Nurses Nurses Nurses, Nurses

Nurses

Nurses Nurses Nurses, nursing assistants Nurses, physicians, auxiliary nurses, others

Nurses Nurses Nurses, nursing assistants Nurses Nurses Nurses Nurses Nurses, physicians, residents Nurses

Nurses, NPs, nurse care managers, physicians, physician assistants, clinical associates, admin staff Nurses, physicians

Population type

Multi-specialty Multi-specialty Psychiatric care Surgical clinic

ICU

Emergency care

ICU Multi-specialty Multi-specialty Maternal health Multi-specialty Oncology Multi-specialty Multi-specialty

Multi-specialty Multi-specialty Paediatric care Multi-specialty ICU Multi-specialty Maternal health ICU Multi-specialty ICU ICU Multi-specialty

Multi-specialty

Multi-specialty Multi-specialty Geriatric care Multi-specialty

Home care Emergency care Geriatric care Primary care Multi-specialty Primary care Emergency care Multi-specialty Operating Theatre

1482 58 200 188

29/53

2482/4693

62 635 165/432 224 104 29 248 1252/3719

510 335 17 283/345 150/183 158 83 26 332 744 2450/3052 712

135

172 29 50/146 430/1275

17 128 33/60 45 109 420 28 54/119 13

70/88

1276/4610

Multi-specialty

Palliative care

Sample, n (nurse/nonnurse)

Specialty

– 16 (94.12) 80 (62.50); – 45 (100) 96 (88.07) – 20 (71.43) 52 (96.30) 4 (30.77)

– – 37.00 – – – – 40.70 38.50 –

60 (96.77) 551 (86.77) 159 (96.36) 178 (79.46) 99 (95.19) 26 (89.66) – – – – 1189 (80.23) 53 (91.38) – 137 (72.87)

– – – – 37.20 –

443 (86.86) – – 236 (83.39) – 147 (93.04) 81 (97.59) – – 674 (90.59) – 613 (86.10)

85 (62.96)

41.65 41.00 36.90 34.00 – 32.60 31.18 47.00

– – – – – 43.60 – 34.37

40.10 – –

33.84

155 (90.12) 26 (100) 47 (94.00) –

–

–

47.00 40.40 46.60 –

n (%) of female nurses

Age of nurses, mean years

(continued on next page)

MBI-HSS MBI-HSS MBI-HSS MBI-HSS

MBI-HSS

MBI-HSS

ProQOL MBI-HSS AVEM ProQOL MBI-HSSe MBI-HSS MBI-HSS OLBI

MBI-HSS ProQOL ProQOL CSFT MBI-HSS ProQOL ProQOL ProQOL MBI-HSS MBI-HSS MBI-HSSe MBI-HSS

MBI-HSS MBI-HSS MBI-HSS Profess-ional Burnout for Nursing Professionals MBI-HSS

MBI-HSS ProQOL MBI-HSS MBI-HSS ProQOL MBI-HSS ProQOL MBI-HSS MBI-HSS

MBI-HSS

validated single- item measured

BO tool

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Journal of Psychiatric Research 123 (2020) 9–20

14

China China

L.F. Zhang et al. (2014a) X.C Zhang et al. (2014b)

Cross-sectional Cross-sectional

Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional

Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional

Article Article Article Article

Article

Article Article Article Article Article Article Article

Article Article Article Article Article

Journal Article Journal Article

Journal Journal Journal Journal Journal

Journal Article Confer-ence Proceed-ings Journal Article Journal Article Thesis Journal Article Journal Article

Journal Thesis Thesis Journal Journal Journal Journal

Journal Journal Journal Journal Journal Journal Journal

Type of publica-tion

Nurses Nurses, physicians Nurses, physicians Nurses, patients Nurses, nursing technicians, medical professionals Nurse Nurses

Nurses Nurses Nursesa Nurses Nurses

Nurses, physicians Nurses, physicians, medical students

Nurses, patients Nurses Nurses Nurses Nurses, physicians Nurses Nurses, physician's assistant medical officers, hospital attendants Nurses Nurses Nurses Nurses Nurse managers Nursing residents Nurses

Population type

Cardiology Emergency care Primary care Multi-specialty Paediatric oncohaemat-ology Multi-specialty ICU

Multi-specialty Multi-specialty Multi-specialty Multi-specialty Oncology

Multi-specialty Multi-specialty

Emergency care Psychiatric care Emergency care Multi-specialty Multi-specialty Multi-specialty Haemo-dialysis

Emergency care Palliative care Multi-specialty Multi-specialty ICU Multi-specialty Multi-specialty

Specialty

9698 426

70 57/100 131/267 228/456 57/188

153 144 138 179 549

4596/5788 34/87

58 115 39 602 172 48 198

148/538 185 270 180 3100/4092 245 151/361

Sample, n (nurse/nonnurse)

MBI-HSS MBI-HSS

– – 29.07 –

ProQOL MBI-HSS MBI-HSS MBI-HSS MBI-HSS

– – – 175 (76.75) –

– – – 28.33 –

MBI-HSS MBI-GS CBI ProQOL ProQOL

147 (96.08) – – – 522 (95.08)

MBI-HSS MBI-HSS

MBI-HSSe MBI-HSS ProQOL MBI-HSS MBI-HSSf MBI-GS MBI-HSS

MBI-GS MBI-HSS COPSOQ MBI-HSS MBI-HSS MBI-HSS MBI-HSS

BO tool

37.60 – – –

– –

– –

(62.45)

(72.30) (87.03) (65.56) (62.23)

40 (68.97) 71 (61.74) 34 (87.18) 584 (97.01) – 44 (91.67) 181 (91.41)

107 161 177 112 – 153 –

n (%) of female nurses

27.90 40.90 – 28.54 44.00 26.00 38.00

39.90 – 37.07 34.80 – – –

Age of nurses, mean years

AVEM: Work-Related Behaviours and Work Experience Patterns Questionnaire; MBI-GS: Maslach Burnout Inventory – General Survey; MBI-HSS: Maslach Burnout Inventory – Human Services Survey; CBI: Copenhagen Burnout Inventory; COPSOQ: Copenhagen Psychosocial Questionnaire; CSFT: Compassion Fatigue Self-Test; OLBI: Oldenburg Burnout Inventory; ProQOL: Professional Quality of Life Scale; BO – Burnout; ICU – Intensive/ Critical Care Units. a Specifically investigating 1st year nurses. b Specifically investigating full-time working nurses who are masters students. c Based on findings of Kalimo et al. (2003) - Computed total score=(0.40xEE)+(0.3xCY)+(0.3xRPE). d Used in the Physician Worklife Study that asks respondents to rate their level of burnout using a five-point ordinal scale. e Scores summed and converted into a percent score, by dividing the total attained by the maximal attainable score. f Total MBI score = mean score of physical exhaustion +mean score of depersonalisation/EE - mean score of personal accomplishment +10. g China, Hong Kong, Japan, South Korea, Taiwan; Saudi Arabia, UAE; Bangladesh, India, Nepal; Brunei, Indonesia, Laos, Philippines, Singapore, Thailand, Vietnam.

Young et al. (2011) Yuguero et al. (2017a) Yuguero et al. (2017b) Zaki et al. (2016) Zanatta et al. (2015)

Chile Czech Republic United States United States Canada, United States United States Spain Spain Saudi Arabia Brazil

Cross-sectional Cross-sectional

Belgium Romania

Vega et al. (2017) Vévodová et al. (2016) Wahl (2008) Wijdenes et al. (2019) Wu et al. (2016)

Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional

Egypt Canada United States China Japan Brazil Serbia

Sorour et al. (2012) Stanley (2006) Strommer (2011) Sun et al. (2018) Suzuki et al. (2009) Tavares et al. (2014) Trbojević-Stanković et al. (2015) Van Gerven et al. (2016) Vasile et al. (2010)

Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional

Spain Mexico Iran Iran Multi-countriesg Iran Malaysia

Ríos-Risquez et al. (2016) Rizo-Baeza et al. (2018) Roshangar et al. (2018) Sahraian et al. (2008) See et al. (2018) Shafaghat et al. (2016) Siau et al. (2018)

Study design

Country

Author, Year

Table 1 (continued)

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highest rate (13.68%) followed by Latin America and the Caribbean (10.51%) There was insignificant subgroup difference (χ2 = 6.86, p = 0.23; I2 = 27.1) (Fig. 2c). One study (See et al, 2018) was not used in the meta-analysis as it covered different regions in Asia.

interventional studies (Isaksson Ro, Gude, Tyssen and Aasland, 2010; Quenot et al., 2012). 86 of included studies (76.1%) were journal articles and 25 (22.1%) were theses. 60 (53.09%) were published from 2015 to 2019. Various burnout measuring tools were utilised in individual studies, including Maslach Burnout Inventory (MBI) (Maslach and Jackson, 1981, 1986; Maslach et al., 1996), Professional Quality of Life (ProQOL) (Stamm, 2005, 2009, 2010), the Compassion Fatigue Self-Test (CFST) (Figley and Stamm, 1996), Copenhagen Burnout Inventory (CBI) (Kristensen et al., 2005), Copenhagen Psychosocial Questionnaire (COPSOQ) (Kristensen et al., 2005) Oldenburg Burnout Inventory (OLBI) (Demerouti and Bakker, 2008), the Work-Related Behaviour and Experience Patterns (AVEM) (Schaarschmidt & Fischer, 1996, 2008), the Professional Burnout for Nursing Professionals (Moreno et al., 2000), a burnout tool developed by Pines and Maslach (Pines and Maslach, 1978) and a validated single-item burnout measure used in the Physician Worklife Study (McMurray et al., 2000). Burnout cut-off scores adopted by each article are reflected in Appendix III. Basic descriptive characteristics of the included studies are summarized in Table 1.

3.6.3. Burnout measurement instrument Subgroup analysis was conducted to examine for differences in the prevalence reported by the different burnout instruments utilised. Instruments used by two or fewer studies were not included in the analysis. Prevalence rate of high burnout was reported as the highest in the three studies using CBI (30.6%) while the pooled prevalence of the other three groups were 9.32%, 10.39–10.66% for ProQOL, MBI-HSS, and MBI-GS respectively. Subgroup differences were not statistically significant (χ2 = 2.40, p = 0.49; I2 = 0%). 3.7. Publication bias Publication bias was examined using funnel plot (Appendix V) which appeared asymmetrical, indicating possible publication bias.

3.3. Participants’ demographic data 4. Discussion The mean age of the nurses ranged from 25.80 to 47.00 years. Seven studies sampled female nurses only while one study had majority male nurses (Iftadi et al., 2017). 47 studies (41.59%) did not report the mean age and gender of respondents respectively. The studies were classified into 6 geographical regions according to the WBG classification (2019) for subgroup analysis. South Asia was combined with East Asia and Pacific to allow the single South Asian study to be included in the subgroup analysis. One study assessed multiple regions. The sample included LPNs, staff nurses, midwives, nurse practitioners and nurse managers who worked in the main specialties. One study (Zanatta and Lucca, 2015) investigated nurses in paediatric-oncology was categorised under “oncology” in our analyses.

This study included 113 published studies, yielding a total of 45,539 nurses across 49 countries. The pooled-prevalence rates from the included studies was 11.23% for high burnout symptoms (95% CI:8.83–13.63%) suggesting one-tenth of the nurses worldwide suffered high burnout symptoms. This finding is unsurprising given the job nature of nursing – physically, cognitively, and emotionally demanding (West, 2015). Analysis has revealed that nurses' burnout can be explained by the essence of nursing – caring. Despite tremendous evolution, caring remains the crux of nursing (Peery, 2010), and is categorised into five carative factors, modified by Wolf et al. (1994) from Watson's Theory of Human Caring (Watson, 1988). Peery's (2010) study uncovered these carative factors to be protective against nurse burnout, implying that failing to fulfil the core domains of nursing care leads to burnout. In a population that seeks to provide care, burnout is related to the lack of caring. In today's dynamic and increasingly high-tech healthcare delivery system, nurses are expected to adopt several new roles (Rashwan and Arisha, 2015). Often, this increases the time spent on non-nursing care tasks, compromising time and quality for nursing care. The consequent conflict of nurses' unfulfilled values is further aggravated by the confluence of aforementioned stressors.

3.4. Risk of bias assessment Results of the risk of bias assessment for each included study is presented in Appendix IV. There were 106 (93.8%) studies with score from 0 to 3 (i.e. low risk) and 7 studies (6.2%) with score 4 (i.e. moderate risk). 3.5. Prevalence of burnout symptoms 61 of the 113 studies had a definition of high burnout symptoms based on the standard or commonly used cut-off for the respective tool, and were included in the meta-analysis. Global prevalence of burnout symptoms among nurses was 11.23% (95% CI: 8.83–13.63) with high heterogeneity across 61 studies (χ2 = 4897.66, p < 0.01, I2 = 99) (Fig. 2a).

4.1. Specialty Significantly different prevalence rates of high burnout across specialties (p < 0.01) was observed and the prevalence rate was highest among Intensive and Critical Care nurses. The prevalence rate of high burnout was highest among Intensive and Critical Care nurses. Critical care nursing poses intense challenges due to its unique work characteristics, environment and patient population. The critical care setting is known to be highly stressful, demanding and volatile (van Mol et al., 2015). ICU nurses are often deal with end-of-life matters, continuous suffering of patients and medical futility (De Villers and DeVon, 2013), face ethical issues, as well as deal with demanding and distressed relatives (Curtive, Sprung & Azoulay, 2014). These challenges are further compounded by the lack of decision-making and communicative abilities of the ICU patients (Epp, 2012). Furthermore, ICU nurses are faced with steep learning curves as the ICU work environment has become increasingly technical. They are required to deal with multiple complicated machinery in addition to a challenging patient population (De Villers and DeVon, 2013). The result is increased moral distress and avoidance behaviours in such a high-stakes and emotionally charged environment.

3.6. Subgroup analyses Subgroup analyses were conducted for prevalence rates of high burnout symptoms and results are tabulated in Table 2. 3.6.1. Specialty There were five groups in total as those specialities with 2 or fewer studies were grouped as “Others”. The highest prevalence rate was in the Intensive and Critical Care group (14.36%, 95% CI: 1.59–27.14) while the lowest rate was in the Others group (4.41, 95% CI: 2.37–6.45). The difference between subgroups was statistically significant (χ2 = 19.69, p < 0.001; I2 = 79.7%) (Fig. 2b). 3.6.2. Geographical regions For prevalence of high burnout, Southeast Asia and Pacific had the 15

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Fig. 2(a). Forest plot assessing global prevalence of burnout symptoms among nurses, using data from 61 studies.

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Table 2 Subgroup analyses for prevalence rate of overall high burnout. Subgroups comparison

No. of studies

Pooled prevalence (%)

95% CI

I2 (%)

Test for subgroup difference

Specialty Intensive & critical care Multi-specialty Paediatric Emergency Others Geographic location Southeast Asia & Pacific Latin America & the Caribbean North America Europe & Central Asia Sub-Saharan Africa Middle East and North Africa Measurement tool MBI-HSS MBI-GS ProQOL CBI

61 9 29 3 6 14 61 8 7 27 13

11.21 14.36 13.11 11.74 10.18 4.41 10.34 13.68 10.51 10.27 10.06

8.85–13.85 1.59–27.14 9.52–16.70 −5.96–29.44 3.25–17.12 2.37–6.45 8.32–12.37 9.61–17.75 5.49–15.53 7.14–13.40 5.07–15.05

99 99 99 97 90 87 8 95 80 95 98

χ2 = 19.69, df = 4 (p < 0.01), Ι

3 3 59 27 4 25 3

8.94 4.68 10.96 10.39 10.66 9.32 30.60

−0.54 – 18.41 −0.76 – 10.12 8.61–13.32 6.05–14.73 2.54–18.79 6.55–12.09 2.95–58.25

93 97 99 99 95 95 97

2

= 79.7%

χ2 = 6.86, df = 5 (p = 0.23), Ι

2

= 27.1

χ2 = 2.40, df = 3 (p = 0.49), Ι

2

= 0%

4.3.1. Strengths and limitations This review has provided an estimation of the global burnout prevalence among nurses. The strengths of this study is the inclusion a large number of studies (n = 113), significantly enhancing this study's statistical power. Furthermore, 93.8% (n = 96) of the studies reviewed were of low risk of bias, and none of the studies had high risk of bias. Additionally, this study used a comprehensive search strategy through 8 major databases, ensuring its rigour by consulting an experienced librarian. It also included grey literature and screening reference lists of relevant papers. The use of two independent reviewers, demonstrating transparency of each stage of the synthesis process, and employing stringent methodology are also strengths of this study. This study has its limitations. Firstly, 92 of the included studies (81.41%) did not employ random sampling. The non-probabilistic nature of the sample majority possibly contributed to biases affecting the results. It is also possible that nurses with high burnout were not identified by the included studies. Nurses with high burnout are likely to be less represented in prevalence study if they have left the industry or are non-responders (Costello et al., 2018). Secondly, few included studies were conducted in developing countries; there is a particular paucity of research in Sub-Saharan Africa. This lack of available studies in certain subgroups resulted in the analysis of a small study size, potentially affecting the accuracy of the overall results. Thirdly, the burnout measurement instruments were different across studies. The most frequently used scale was MBI-HSS. The measures used also relied on self-report methods, making the results vulnerable to recall biases. Fourthly, a recent published study (Schonfeld et al., 2019) suggested that burnout and depression scales tap the same phenomenon, namely, distress/dysphoria and hence the interpretation of burnout should be cautious. Lastly, the inclusion of English articles only might result in relevant studies in other languages being overlooked.

4.2. Geographical region There was no significant subgroup difference for burnout prevalence across regions. Southeast Asia and Pacific had the highest prevalence rate (13.68%) among the six geographical regions. Southeast Asian countries face diverse health workforce challenges including shortages and maldistribution. Given the rapid economic growth, urbanisation and ageing of Southeast Asia and Pacific, the demand for quality and quantity of healthcare is increasing dramatically, both directly and indirectly impacting nurses' stress (Ramesh and Wu, 2008; Sheikh et al., 2017). This demand is compounded by the problem of nursing shortage. The average ratio of nurses to the general population in Europe is 10 times higher than that of Southeast Asia (Buchan and Calman, 2006; Drennan and Ross, 2019), while the World health report on the health workforce identified 57 countries with critical workforce shortages, of which six were in Southeast Asia (Kanchanachitra et al., 2011; World Health Organization, 2018). Furthermore, Southeast Asia presents daunting health challenges – it's volatile geography and climate has seen the onset of natural disasters, while the region has borne the brunt of several emerging and re-emerging infections, compounding healthcare challenges (Acuin et al., 2011; Angkurawaranon et al., 2014). The diverse problems faced by the diverse region sees the nurses of the region facing immense pressure. 4.3. Burnout measurement instruments No subgroup difference was observed between studies using different instruments (p = 0.49). The two most frequently used instruments were the MBI-HSS (n = 27, 10.39%) and ProQOL (n = 25,9.32%). The MBI-HSS tool assesses the three dimensions of burnout syndrome. The scores for each subscale are considered separately and not combined into a total score. A high level of burnout is indicated by a combination of high EE and DP, together with low PA. Among the included studies, a cut-off scores range defining H-BO were used, potentially contributing further to heterogeneity. Burnout as measured by ProQOL scale comprise one of two sub-parts measuring compassion fatigue (Stamm, 2010). It assesses burnout using 10 questions, for which raw scores are summed and converted into t-scores. The cut-off scores for H-BO are: raw-sum score ≥42, or t-score ≥57. Additionally, other burnout conceptualisations (such as CBI) consider exhaustion as the sole defining criterion of burnout, conflicting the multidimensional model in the MBI. The varying definitions of HBO explains the significant heterogeneity.

5. Conclusion This review and meta-analysis of 113 included studies from a systematic search across eight databases revealed a considerably higher burnout prevalence rate, affecting around one-tenth of the global nurse population (11.23%). Meta-analysis shows that geographic location and nursing specialty significantly contributes to prevalence rates of burnout. Furthermore, due to varying burnout instruments, cut-off score recommendations and definitions, there is significant heterogeneity in investigated rates of burnout prevalence. Due to the consequences of burnout on nurses, patients and healthcare organisations, this study encourages policymakers', hospital 17

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Fig. 2(b). Forest plot assessing global prevalence of burnout symptoms among nurses, by nursing expertise.

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Methodology, Validation, Writing - original draft, Writing - review & editing, Project administration. Wilson Tam: Conceptualization, Methodology, Software, Validation, Formal analysis, Data curation, Writing - original draft, Writing - review & editing, Supervision, Project administration. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.jpsychires.2019.12.015. References Acuin, J., Firestone, R., Htay, T.T., Khor, G.L., Thabrany, H., Saphonn, V., Wibulpolprasert, S., 2011. Southeast Asia: an emerging focus for global health. The Lancet 377 (9765), 534–535. https://doi.org/10.1016/s0140-6736(10)61426-2. Angkurawaranon, C., Jiraporncharoen, W., Chenthanakij, B., Doyle, P., Nitsch, D., 2014. Urbanization and non-communicable disease in Southeast Asia: a review of current evidence. Public Health 128 (10), 886–895. https://doi.org/10.1016/j.puhe.2014. 08.003. Epub 2014 Oct 13. Awa, W.L., Plaumann, M., Walter, U., 2009. Burnout prevention: a review of intervention programs. Patient Educ. Couns. 78 (2), 184–190. https://doi.org/10.1016/j.pec. 2009.04.008. Boyle, D.A., 2011. Countering compassion fatigue: a requisite nursing agenda. Online J. Issues Nurs. 16 (1). https://doi.org/10.3912/OJIN.Vol16No01Man02. 1B. Buchan, J., Calman, L., 2006. The Global Shortage of Registered Nurses: an Overview of Issues and Actions. International Council of Nurses, Geneva. http://www.icn.ch/ global/shortage.pdf, Accessed date: 22 February 2008. Collett, D., 2003. Modelling Binary Data/David Collett, second ed. Chapmann & Hall/ CRC, Boca Raton, FL. Costello, H., Walsh, S., Cooper, C., Livingston, G., 2018. A systematic review and metaanalysis of the prevalence and associations of stress and burnout among staff in longterm care facilities for people with dementia. Int. Psychogeriatr. 1–14. https://doi. org/10.1017/S1041610218001606. Curtis, J.R., Sprung, C.L., Azoulay, E., 2014. The importance of word choice in the care of critically ill patients and their families. Intensive Care Med. 40, 606–608. De Villers, M.J., DeVon, H.A., 2013. Moral distress and avoidance behavior in nurses working in critical care and noncritical care units. Nurs. Ethics 20, 589–603. https:// doi.org/10.1177/0969733012452882. PMID: 23186938. Demerouti, E., Bakker, A.B., 2008. The Oldenburg Burnout Inventory: A Good Alternative to Measure Burnout and Engagement. Denison, H.J., Dodds, R.M., Ntani, G., Cooper, R., Cooper, C., Sayer, A.A., Baird, J., 2013. How to get started with a systematic review in epidemiology: an introductory guide for early career researchers. Arch. Public Health 71 (1). https://doi.org/10.1186/ 0778-7367-71-21. 21-21. Drennan, V.M., Ross, F., 2019. Global nurse shortages-the facts, the impact and action for change. Br. Med. Bull. 130 (1), 25–37. https://doi.org/10.1093/bmb/ldz014. Elbarazi, I., Loney, T., Yousef, S., Elias, A., 2017. Prevalence of and factors associated with burnout among health care professionals in Arab countries: a systematic review. BMC Health Serv. Res. 17 (1). https://doi.org/10.1186/s12913-017-2319-8. 491410. Epp, K., 2012. Burnout in critical care nurses: a literature review. Dynics 23, 25–31 PMID: 23342935. Fiest, K.M., Pringsheim, T., Patten, S.B., Svenson, L.W., Jette, N., 2014. The role of systematic reviews and meta-analyses of incidence and prevalence studies in neuroepidemiology. Neuroepidemiology 42 (1), 16–24. https://doi.org/10.1159/ 000355533. Figley, C.R., Stamm, B.H., 1996. Psychometric review of compassion fatigue self test. In: Stamm, B.H. (Ed.), Measurement of Stress, Trauma and Adaptation. Sidran Press, Lutherville, MD. Freudenberger, H.J., 1974. Staff burn-out. J Soc. Iss. 30 (1), 159–165. https://doi.org/10. 1111/j.1540-4560.1974.tb00706.x. Fredenberger, H.J., 1975. The staff burn-out syndrome in alternative institutions. Psychother. Theory Res. Pract. 12, 73–82. Gómez-Urquiza, J.L., Aneas-López, A.B., Fuente-Solana, E.I., Albendín-García, L., DíazRodríguez, L., Fuente, G.A., 2016. Prevalence, risk factors, and levels of burnout among oncology nurses: a systematic review. Oncol. Nurs. Forum 43 (3), E104–E120. https://doi.org/10.1188/16.ONF.E104-E120. Gómez-Urquiza, J.L., De la Fuente-Solana, E.I., Albendín-García, L., Vargas-Pecino, C., Ortega-Campos, E.M., Cañadas-De la Fuente, G.A., 2017. Prevalence of burnout syndrome in emergency nurses: a meta-analysis. Crit. Care Nurse 37 (5), e1–e9. https://doi.org/10.4037/ccn2017508. Hart, P.L., Brannan, J.D., De Chesnay, M., 2014. Resilience in nurses: an integrative review. J. Nurs. Manag. 22 (6), 720–734. https://doi.org/10.1111/j.1365-2834.2012. 01485.x. Higgins, J.P.T., Green, S., 2011. Cochrane Handbook for Systematic Reviews of Interventions. John Wiley & Sons. Ho, R.C., Zhang, M.W., Tsang, T.Y., Toh, A.H., Pan, F., Lu, Y., ... Mak, K.K., 2014. The association between internet addiction and psychiatric co-morbidity: a meta-analysis. BMC Psychiatry 14 (1), 183. https://doi.org/10.1186/1471-244x-14-183. Hoy, D., Brooks, P., Woolf, A., Blyth, F., March, L., Bain, C., ... Buchbinder, R., 2012. Assessing risk of bias in prevalence studies: modification of an existing tool and

Fig. 2(c). Forest plot assessing global prevalence of burnout symptoms among nurses, by geographic location.

administrators' and nursing leaders’ intervention to prevent and minimise burnout among nurses. This study also recommends future research into effective evidence-based burnout interventions and policies to address the phenomenon.

CRediT authorship contribution statement Tiffany Woo: Conceptualization, Methodology, Software, Validation, Formal analysis, Data curation, Writing - original draft, Writing - review & editing. Roger Ho: Methodology, Validation, Writing - original draft, Writing - review & editing. Arthur Tang: 19

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Quenot, J.P., Rigaud, J.P., Prin, S., Barbar, S., Pavon, A., Hamet, M., ... Moutel, G., 2012. Suffering among carers working in critical care can be reduced by an intensive communication strategy on end-of-life practices. Intensive Care Med. 38 (1), 55–61. https://doi.org/10.1007/s00134-011-2413-z. Ramesh, M., Wu, X., 2008. Realigning public and private health care in southeast Asia. Pac. Rev. 21 (2), 171–187. https://doi.org/10.1080/09512740801990238. Ramirez, A.J., Graham, J., Richards, M.A., Cull, A., Gregory, W.M., 1996. Mental health of hospital consultants: the effects of stress and satisfaction at work. Lancet 347, 724–728. Rashwan, W., Arisha, A., 2015. Modeling behavior of nurses in clinical medical unit in university hospital: burnout implications. In: Proceedings of the 2015 Winter Simulation Conference. IEEE Press, Piscataway, NJ, pp. 3880–3891. Rezaei, O., Habibi, K., Arab Ghahestany, D., Sayadnasiri, M., Armoon, B., Khan, V., Fattah Moghadam, L., 2018a. Factors related to job burnout among nurses in the Razi Psychiatric Hospital, Iran. Int. J. Adolesc. Med. Health. https://doi.org/10.1515/ ijamh-2017-0146. Rezaei, S., Karami Matin, B., Hajizadeh, M., Soroush, A., Nouri, B., 2018b. Prevalence of burnout among nurses in Iran: a systematic review and meta-analysis. Int. Nurs. Rev. 65 (3), 361–369. https://doi.org/10.1111/inr.12426. Schaarschmidt, U., Fischer, A., 1996. Arbeitsbezogenes Verhaltens- und Erlebensmuster : (AVEM) ; Manual. Swets Test Services, Frankfurt, M. Schaarschmidt, U., Fischer, A.W., 2008. Arbeitsbezogenes Verhaltens- und Erlebensmuster : AVEM (Standardform ; AVEM-44 (Kurzform) ; Manual. Pearson, London. See, K.C., Zhao, M.Y., Nakataki, E., Chittawatanarat, K., Fang, W.F., Faruq, M.O., ... SABA Study Investigators and the Asian Critical Care Clinical Trials Group, 2018. Professional burnout among physicians and nurses in Asian intensive care units: a multinational survey. Intensive Care Med. 44 (12), 2079–2090. https://doi.org/10. 1007/s00134-018-5432-1. Schonfeld, I.S., Verkuilen, J., Bianchi, R., 2019. Inquiry into the correlation between burnout and depression. J. Occup. Health Psychol. 24 (6), 603–616. https://doi.org/ 10.1037/ocp0000151. Sheikh, K., Josyula, L.K., Zhang, X., Bigdeli, M., Ahmed, S.M., 2017. Governing the mixed health workforce: learning from Asian experiences. BMJ Glob Health 2 (2), e000267. Stamm, B.H., 2005. Professional Quality of Life Scale: Compassion Satisfaction and Fatigue Subscales, R-IV (ProQOL). Stamm, B.H., 2009. The concise ProQOL manual. In: Retrieved from ProQOL.Org. Stamm, B.H., 2010. The Concise ProQOL Manual, second ed. Retrieved from. https:// proqol.org/uploads/ProQOL_Concise_2ndEd_12-2010.pdf. The World Bank Group, 2019. Country Classification: World Bank Country and Lending Groups. Retrieved from. https://datahelpdesk.worldbank.org/knowledgebase/ articles/906519. Toh, S.G., Ang, E., Devi, M.K., 2012. Systematic review on the relationship between the nursing shortage and job satisfaction, stress and burnout levels among nurses in oncology/haematology settings. Int. J. Evid. Based Healthc. 10 (2), 126–141. https:// doi.org/10.1111/j.1744-1609.2012.00271.x. Watson, M.J., 1988. New dimensions of human caring theory. Nurs. Sci. Q. 1 (4), 175–181. https://doi.org/10.1177/089431848800100411. West, A.L., 2015. Associations among attachment style, burnout, and compassion fatigue in health and human service workers: a systematic review. J. Hum. Behav. Soc. Environ. 25 (6), 571–590. https://doi.org/10.1080/10911359.2014.988321. Wolf, Z.R., Giardino, E.R., Osborne, P.A., Ambrose, M.S., 1994. Dimensions of nurse caring. Image: J. Nurs. Scholarsh. 26 (2), 107–112. https://doi.org/10.1111/j.15475069.1994.tb00927.x. World Health Organisation, 2016. Health Workforce Requirements for Universal Health Coverage and the Sustainable Development Goals. (Human Resources for Health Observer, vol. 17 Retrieved from. http://www.who.int/iris/handle/10665/250330. World Health Organization, 2018. Decade for Health Workforce Strengthening in the South-East Asia Region 2015–2024; Second Review of Progress, 2018. World Health Organization, Regional Office for South-East Asia, New Delhi 2018. Licence: CC BYNC-SA 3.0 IGO. World Health Organisation, 2019. Burn-out an "occupational phenomenon": international classification of Diseases. Retrieved from. https://www.who.int/mental_health/ evidence/burn-out/en/. Zanatta, A.B., Lucca, S.R.d., 2015. Prevalence of burnout syndrome in health professionals of an onco-hematological pediatric hospital. Rev. Esc. Enferm. USP 49 (2), 253–258. https://doi.org/10.1590/S0080-623420150000200010. Zhang, Y.Y., Zhang, C., Han, X.R., Li, W., Wang, Y.L., 2018. Determinants of compassion satisfaction, compassion fatigue and burn out in nursing: a correlative meta-analysis. Medicine 97 (26), e11086. https://doi.org/10.1097/MD.0000000000011086.

evidence of interrater agreement. J. Clin. Epidemiol. 65 (9), 934–939. https://doi. org/10.1016/j.jclinepi.2011.11.014. Iftadi, I., Astuti, R.D., Rosita, M., 2017. Using NASA task load index and Maslach burnout inventory for evaluating the subjective mental and physical workload of nurse central surgical installation hospitals Karanganyar. In: 2016 2nd International Conference of Industrial, Mechanical, Electrical, and Chemical Engineering (ICIMECE). Institute of Electrical and Electronics Engineers Inc, Piscataway, NJ, pp. 127–131. Isaksson Ro, K.E., Gude, T., Tyssen, R., Aasland, O.G., 2010. A self-referral preventive intervention for burnout among Norwegian nurses: one-year follow-up study. Patient Educ. Couns. 78 (2), 191–197. https://doi.org/10.1016/j.pec.2009.07.008. Kanchanachitra, C., Lindelow, M., Johnston, T., Hanvoravongchai, P., Lorenzo, F.M., Huong, N.L., et al., 2011. Human resources for health in southeast Asia: shortages, distributional challenges, and international trade in health services. The Lancet 377 (9767), 769–781. https://doi.org/10.1016/s0140-6736(10)62035-1. Kristensen, T.S., Borritz, M., Villadsen, E., Christensen, K.B., 2005a. The copenhagen burnout inventory: a new tool for the assessment of burnout. Work Stress 19 (3), 192–207. https://doi.org/10.1080/02678370500297720. Kristensen, T.S., Hannerz, H., Hogh, A., Borg, V., 2005b. The Copenhagen Psychosocial Questionnaire—a tool for the assessment and improvement of the psychosocial work environment. Scand. J. Work Environ. Health 31 (6), 438–449. https://doi.org/10. 5271/sjweh.948. Lasebikan, V.O., Oyetunde, M.O., 2012. Burnout among nurses in a Nigerian general hospital: prevalence and associated factors. ISRN Nurs 2012https://doi.org/10.5402/ 2012/402157. 402157-402156. Leiter, M.P., Maslach, C., 2009. Nurse turnover: the mediating role of burnout. J. Nurs. Manag. 17 (3), 331–339. https://doi.org/10.1111/j.1365-2834.2009.01004.x. Liberati, A., Altman, D.G., Tetzlaff, J., Mulrow, C., Gøtzsche, P.C., Ioannidis, J.P., Clarke, M., Devereaux, P.J., Kleijnen, J., Moher, D., 2009. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ 339, b2700. https://doi.org/10. 1136/bmj.b2700. Maslach, C., Jackson, S.E., 1981. The measurement of experienced burnout. J. Organ. Behav. 2 (2), 99–113. https://doi.org/10.1002/job.4030020205. Maslach, C., Jackson, S.E., 1986. Maslach Burnout Inventory, second ed. Consulting Psychologists Press, Palo Alto, CA. Maslach, C., Jackson, S.E., Leiter, M.P., 1996. Maslach Burnout Inventory, third ed. Consulting Psychologists Press, Palo Alto, CA. McHugh, M.D., Kutney-Lee, A., Cimiotti, J.P., Sloane, D.M., Aiken, L.H., 2011. Nurses' widespread job dissatisfaction, burnout, and frustration with health benefits signal problems for patient care. Health Aff. 30 (2), 202–210. https://doi.org/10.1377/ hlthaff.2010.0100. McMurray, J.E., Linzer, M., Konrad, T.R., Douglas, J., Shugerman, R., Nelson, K., 2000. The work lives of women physicians. J. Gen. Intern. Med. 15 (6), 372–380. https:// doi.org/10.1111/j.1525-1497.2000.im9908009.x. Merces, M.C.d., Lopes, R.A., Silva, D.d.S.e., Oliveira, D.S., Lua, I., Mattos, A.I.S., Júnior, A.D., 2017. Prevalência da Síndrome de Burnout em profissionais de enfermagem da atenção básica à saúde Prevalence of Burnout Syndrome in nursing professionals of basic health care. J. Res.: Fundam. Care. Online 9 (1), 208. https://doi.org/10.9789/ 2175-5361.2017.v9i1.208-214. Monsalve-Reyes, C.S., San Luis-Costas, C., Gómez-Urquiza, J.L., Albendín-García, L., Aguayo, R., Cañadas-De la Fuente, G.A., 2018. Burnout syndrome and its prevalence in primary care nursing: a systematic review and meta-analysis. BMC Fam. Pract. 19 (1). https://doi.org/10.1186/s12875-018-0748-z. 59-57. Moreno, B., Garrosa, E., González, J.L., 2000. El desgaste profesional de enfermería: desarrollo y validación factorial del CDPE. Arch. Prevenvion Riesgos Laborales 3, 18–28. Munn, Z., Moola, S., Lisy, K., Riitano, D., 2014. The Joanna Briggs Institute Reviewers'. Manual 2014 edition/supplement. Munn, Z., Moola, S., Lisy, K., Riitano, D., Tufanaru, C., 2015. Methodological guidance for systematic reviews of observational epidemiological studies reporting prevalence and cumulative incidence data. Int. J. Evid. Based Healthc. 13 (3), 147–153. https://doi. org/10.1097/xeb.0000000000000054. Peery, A.I., 2010. Caring and burnout in registered nurses: what's the connection? Int. J. Hum. Caring 14 (2), 53–60. https://doi.org/10.20467/1091-5710.14.2.52. Pines, A., Maslach, C., 1978. Characteristics of staff burnout in mental health settings. Hosp. Community Psychiatry 29 (4), 233–237. https://doi.org/10.1176/ps.29.4.233. Pradas-Hernández, L., Ariza, T., Gómez-Urquiza, J.L., Albendín-García, L., Emilia, I.D.l.F., Cañadas-De la Fuente, G.A., 2018. Prevalence of burnout in paediatric nurses: a systematic review and meta-analysis. PLoS One 13 (4), e0195039. https://doi.org/ 10.1371/journal.pone.0195039.

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