Burnout symptoms in forensic mental health nurses: Results from a longitudinal study

Peter De Looff, Robert Didden, Petri Embregts, Henk Nijman

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Burnout in nursing staff is a major cause for turnover and absenteeism. Identifying risk and protective factors may be helpful in decreasing burnout symptoms. Moreover, research indicates that ambulatory assessments of the autonomic nervous system might be helpful in detecting long‐term stress and burnout symptoms. One hundred and ten forensic nursing staff members completed questionnaires measuring experiences with aggressive behaviour, emotional intelligence, personality, and job stress during four waves of data collection across a 2‐year period. Multilevel analyses were used to test the predicted associations and moderation effects with (the development of) burnout symptoms. Burnout was predicted by a combination of emotional intelligence, job stress, aggression, personality factors, and skin conductance, but no moderation effects over time were found. Over a period of 2 years, the model approximately predicts a change in one burnout category on the Maslach Burnout Inventory. The amount of burnout symptoms in nurses might be used as an indicator to predict turnover and absenteeism considering the increase in symptoms over time. Nursing staff who experience severe aggression and who have relatively low levels of emotional intelligence and altruism and high levels of neuroticism and job stress should be monitored and supported to decrease the risk of burnout. Staff members can be trained to increase their emotional intelligence and relieve stress to decrease their burnout symptoms and turnover and absenteeism on the long term. Ambulatory assessment might be helpful as a nonintrusive way to detect increasing levels of burnout.
LanguageEnglish
JournalInternational Journal of Mental Health Nursing
DOIs
Publication statusE-pub ahead of print - 2019

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Absenteeism
Nursing Staff
Mental Health
Nurses
Altruism
Equipment and Supplies

Cite this

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title = "Burnout symptoms in forensic mental health nurses: Results from a longitudinal study",
abstract = "Burnout in nursing staff is a major cause for turnover and absenteeism. Identifying risk and protective factors may be helpful in decreasing burnout symptoms. Moreover, research indicates that ambulatory assessments of the autonomic nervous system might be helpful in detecting long‐term stress and burnout symptoms. One hundred and ten forensic nursing staff members completed questionnaires measuring experiences with aggressive behaviour, emotional intelligence, personality, and job stress during four waves of data collection across a 2‐year period. Multilevel analyses were used to test the predicted associations and moderation effects with (the development of) burnout symptoms. Burnout was predicted by a combination of emotional intelligence, job stress, aggression, personality factors, and skin conductance, but no moderation effects over time were found. Over a period of 2 years, the model approximately predicts a change in one burnout category on the Maslach Burnout Inventory. The amount of burnout symptoms in nurses might be used as an indicator to predict turnover and absenteeism considering the increase in symptoms over time. Nursing staff who experience severe aggression and who have relatively low levels of emotional intelligence and altruism and high levels of neuroticism and job stress should be monitored and supported to decrease the risk of burnout. Staff members can be trained to increase their emotional intelligence and relieve stress to decrease their burnout symptoms and turnover and absenteeism on the long term. Ambulatory assessment might be helpful as a nonintrusive way to detect increasing levels of burnout.",
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Burnout symptoms in forensic mental health nurses : Results from a longitudinal study. / De Looff, Peter; Didden, Robert; Embregts, Petri; Nijman, Henk.

In: International Journal of Mental Health Nursing, 2019.

Research output: Contribution to journalArticleScientificpeer-review

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