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Predictors of nurses′ job burnout and depressive symptoms: A dominance analysis of diverse emotion regulation strategies / 中国实用护理杂志
Article in Chinese | WPRIM (Western Pacific) | ID: wpr-864373
Responsible library: WPRO
ABSTRACT

Objective:

To examine the relative importance of four emotion regulation strategies (i.e. cognitive reappraisal, expressive suppression, rumination and mindfulness) in explaining job burnout and depression of nurses.

Methods:

We conducted a cross-sectional study with questionnaires for 1 037 nurses from two general hospitals. Maslach Burnout Inventory-Human Service Survey (MBI-HSS), the Patient Health Questionnaire-9 (PHQ-9), Emotion Regulation Questionnaire (ERQ), Ruminative Responses Scale (RRS) and Short Inventory of Mindfulness Capability (SIM-C) were assessed.

Results:

Dominance analysis revealed that in terms of job burnout, rumination, cognitive reappraisal and mindfulness could explain 41.38% (0.132/0.319), 30.09% (0.096/0.319) and 28.53% (0.091/0.319). In terms of depression, rumination and mindfulness could explain 68.6% (0.362/0.528)and 24.43% (0.129/0.528).

Conclusions:

Rumination and mindfulness were important predictors of job burnout and depression of nurses. This study indicates that reducing ruminative responses and enhancement of mindfulness are the important approach to reduce nurses′ job burnout and depression.
Full text: Available Health context: Sustainable Health Agenda for the Americas Health problem: Goal 3 Human resources for health Database: WPRIM (Western Pacific) Type of study: Diagnostic study / Observational study / Prognostic study / Risk factors Language: Chinese Journal: Chinese Journal of Practical Nursing Year: 2020 Document type: Article
Full text: Available Health context: Sustainable Health Agenda for the Americas Health problem: Goal 3 Human resources for health Database: WPRIM (Western Pacific) Type of study: Diagnostic study / Observational study / Prognostic study / Risk factors Language: Chinese Journal: Chinese Journal of Practical Nursing Year: 2020 Document type: Article
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