Environment, workload, and nurse burnout in public hospitals in Chile

Multicenter, observational, cross-sectional study. According to established inclusion criteria, the universe of hospitals and nurses was the object of work. Data collection was carried out through a nurse survey. Work environment was measured with the instrument Practice Environment Scale of the Nursing Work Index, staffing through the nurses’ report on patient load, and burnout with the Maslach Burnout Inventory emotional exhaustion subscale.

Results:

Thirty-four hospitals (92%) and 1,395 nurses (75.3%) participated in the study. The prevalence of burnout was 34.7%, being higher in Santiago than in other regions of the country (p = 0.001). The logistic regression analyses showed a significant association between work environment and burnout (OR 0.57, 95% CI 0.41–0.79, p = 0.001). No association was established between staffing, skill mix and burnout.

Conclusion:

A high percentage of nurses in Chile has burnout, which is significantly associated with the quality of the environment. The implementation of organizational strategies to improve work environments could reduce burnout and improve the quality of care.

DESCRIPTORS
Burnout, Psychological; Stress; Working Environment; Workload; Nursing

General characteristics of hospitals	Total n= 34	Santiago n= 10	Regions n= 24	p value
Size according to number of beds, $\bar{x}$ (DS)	409 (162)	507 (144)	368 (154)	0.021^* * p< 0.05
Work environment score, $\bar{x}$ (SD)	2.69 (0.18)	2.62 (0.20)	2.72 (0.16)	0.147
Poor work environment, n (%)	9 (26.5)	4 (40.0)	5 (20.8)
Average work environment, n (%)	16 (47.0)	4 (40.0)	12 (50.0)	0.621
Good work environment, n (%)	9 (26.5)	2 (20.0)	7 (29.2)
Patients per nurse, $\bar{x}$ (SD)	19.0 (6.3)	15.4 (4.5)	20.5 (6.4)	0.028^* * p< 0.05
Skill mix, %	29.5	30.6	29.0	0.340
Nurses characteristics	n= 1.395	n= 523	n= 872
Age, $\bar{x}$ (SD)	31.9 (7.4)	31.4 (6.6)	32.2 (7.9)	0.065
Female, n (%)	1.204 (86.7)	448 (86.0)	756 (87.2)	0.520
Years of work as a nurse, $\bar{x}$ (SD)	6.2 (6.9)	5.7 (5.8)	6.5 (7.4)	0.040^* * p< 0.05
Graduate certificate or master’s degree, n (%)	371 (26.9)	163 (31.8)	208 (24.1)	0.002^* * p< 0.05

Burnout	Total n= 1,395	Santiago n= 523	Regions n= 872	p value
Burnout score, $\bar{x}$ (DS)	22.7 (11.8)	24.3 (12.0)	21.7 (11.6)	0.0001^* * p < 0.05 † Nurses with a score > 27 on the MBI emotional exhaustion scale Note: (n= 1,395).
Nurses with burnout^† * p < 0.05 † Nurses with a score > 27 on the MBI emotional exhaustion scale Note: (n= 1,395). , n (%)	476 (34.7)	206 (40.0)	270 (31.5)	0.001^* * p < 0.05 † Nurses with a score > 27 on the MBI emotional exhaustion scale Note: (n= 1,395).

Emotional Burnout Scale	Total n= 1,395	Santiago n= 523	Regions n= 872	p value
Emotional Burnout Scale	n (%)	n (%)	n (%)	p value
I feel emotionally exhausted because of work	651 (46.7)	269 (51.4)	382 (43.8)	0.382
I feel exhausted at the end of the day	1.00 (72.0)	387 (74.0)	618 (70.9)	0.208
I feel fatigued when I wake up and have to face a new day at work	668 (47.9)	265 (50.7)	403 (46.2)	0.107
Working with people all day is a real effort for me	258 (1 8.5)	115 (22.0)	143 (16.4)	0.009^* * p< 0.05 Note: (n= 1395).
I’m stressed because of work	329 (23.6)	144 (27.5)	185 (21.2)	0.007^* * p< 0.05 Note: (n= 1395).
I feel frustrated in my work	203 (14.6)	92 (17.6)	111 (12.7)	0.013^* * p< 0.05 Note: (n= 1395).
I think I work too hard	624 (44.7)	263 (50.3)	361 (41.4)	0.001^* * p< 0.05 Note: (n= 1395).
Working directly with people causes me a lot of stress	225 (16.1)	98 (18.7)	127 (14.6)	0.040^* * p< 0.05 Note: (n= 1395).
I feel like I can’t take it anymore	138 (9.9)	61 (11.7)	77 (8.8)	0.086

Burnout	OR^† * p < 0.05 † OR = Odds Ratio ‡ CI = Confidence Interval The table presents logistic regression calculations, considering clustering of nurses per hospital, adjusted for the hospitals (location and size) and nurses (sex and age) characteristics.	CI^* * p < 0.05 † OR = Odds Ratio ‡ CI = Confidence Interval The table presents logistic regression calculations, considering clustering of nurses per hospital, adjusted for the hospitals (location and size) and nurses (sex and age) characteristics.	p value
	Unadjusted model
Work environment (ref. Poor environment)
Average versus poor	0.66	0.43–1.01	0.057
Good versus poor	0.53	0.36–0.77	0.001^* * p < 0.05 † OR = Odds Ratio ‡ CI = Confidence Interval The table presents logistic regression calculations, considering clustering of nurses per hospital, adjusted for the hospitals (location and size) and nurses (sex and age) characteristics.
Staffing (patients per nurse)	1.00	0.96–1.04	0.970
Skill mix	1.00	0.56–1.80	0.995
	Adjusted model
Work environment (ref. Poor environment)
Average versus poor	0.70	0.50–0.98	0.037^* * p < 0.05 † OR = Odds Ratio ‡ CI = Confidence Interval The table presents logistic regression calculations, considering clustering of nurses per hospital, adjusted for the hospitals (location and size) and nurses (sex and age) characteristics.
Good versus poor	0.57	0.41–0.79	0.001^* * p < 0.05 † OR = Odds Ratio ‡ CI = Confidence Interval The table presents logistic regression calculations, considering clustering of nurses per hospital, adjusted for the hospitals (location and size) and nurses (sex and age) characteristics.
Staffing (patients per nurse)	1.01	0.97–1.06	0.624
Skill mix	0.96	0.54–1.72	0.896

Universidade de São Paulo, Escola de Enfermagem Av. Dr. Enéas de Carvalho Aguiar, 419 , 05403-000 São Paulo - SP/ Brasil, Tel./Fax: (55 11) 3061-7553, - São Paulo - SP - Brazil
E-mail: reeusp@usp.br

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[1] Corresponding author: Marta Simonetti, Monseñor Álvaro del Portillo, 13265, Las Condes, 7620001 – Santiago, Chile msimonetti@uandes.cl