Prevalence of Violence Perpetrated by Healthcare Workers in Long-Term Care: A Systematic Review and Meta-Analysis.
Alessio ContiAlessandro ScacchiMarco ClariMarco ScattagliaValerio DimonteMaria Michela GianinoPublished in: International journal of environmental research and public health (2022)
This systematic review and meta-analysis aimed to determine the prevalence of violence perpetrated by healthcare workers (HCWs) against patients in long-term care (LTC). For this purpose, five relevant databases were searched. Two reviewers extracted data from the included articles independently and assessed their quality. Overall and subgroup random-effects pooled prevalence meta-analyses were performed. A series of meta-analyses stratified by study quality were also performed due to high heterogeneity. Nineteen articles were included, physical restraint (22%; CI: 15-29), verbal abuse (22%; CI: 16-28), and neglect (20%; CI: 15-26) attained the highest overall prevalence, while sexual abuse was less reported (2%; CI: 1-3). The prevalence of witnessed violence is generally higher than those reported by HCWs, and patients and their relatives reported fewer cases of violence than HCWs. Differences in violence perpetrated among LTC settings were found. Neglect (64%; CI: 56-72) and financial abuse (7%; CI: 3-12) reported by HCWs were higher in home care, while verbal abuse (21%; CI: 7-39) reported by patients or their families was higher in nursing homes. Our findings highlight that violence perpetrated by HCWs toward patients represents a significant concern in LTC, suggesting the adoption of reliable monitoring approaches and provision of assistance to victims in reporting abuse.
Keyphrases
- end stage renal disease
- mental health
- newly diagnosed
- ejection fraction
- chronic kidney disease
- risk factors
- intimate partner violence
- peritoneal dialysis
- systematic review
- prognostic factors
- randomized controlled trial
- physical activity
- machine learning
- big data
- patient reported
- artificial intelligence
- drug induced
- health insurance
- data analysis