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Prevalence and severity of verbal, physical, and sexual inpatient violence against nurses in Swiss psychiatric hospitals and associated nurse-related characteristics: Cross-sectional multicentre study.

Nanja SchlupBeatrice GehriMichael Simon
Published in: International journal of mental health nursing (2021)
This analysis (1) describes the prevalence and severity of psychiatric inpatient violence against nurses in Switzerland's German-speaking region and (2) investigates the associations between nurse-related characteristics (socio-demographics; previous exposure to severe forms of psychiatric inpatient violence; attitude towards psychiatric inpatient violence) and nurses' exposure to various types of psychiatric inpatient violence. We used cross-sectional survey data from the MatchRN Psychiatry study sample of 1128 nurses working on 115 units across 13 psychiatric hospitals. In addition to lifetime severe assaults, nurses' exposure to violence against property, verbal violence, verbal sexual violence, physical violence, and physical sexual violence was assessed for the 30 days prior to the survey. Descriptive statistics (frequency and percentage) were calculated for each class of violence as also for items under study. With generalized linear mixed models, odds ratios and 95% confidence intervals were calculated. Of nurse respondents, 73% reported facing verbal violence, 63% violence against property, 40% verbal sexual violence, 28% physical violence, and 14% physical sexual violence. Almost 30% had been subjected to a serious assault in their professional lifetimes. All nurse characteristics were associated with psychiatric inpatient violence against nurses, especially a history of sexual assault (OR 4.53, 95%-CI 2.19-9.34; P = 0.00) and ≤3 years' professional experience (OR 3.70, 95%-CI 1.95-7.02; P = 0.00). Prevalence data suggest that widely used strategies such as aggression management courses or alarm devices cannot fully reduce patient violence against nurses in psychiatry. This situation demands proactive strategies in safety and violence prevention.
Keyphrases
  • mental health
  • primary care
  • healthcare
  • working memory
  • physical activity
  • machine learning
  • electronic health record
  • case report
  • big data
  • drug induced
  • neural network
  • data analysis