Evidence synthesis on coercion in mental health: An umbrella review.
Miriam Aragonés-CallejaVanessa Sánchez-MartínezPublished in: International journal of mental health nursing (2023)
Coercion in mental healthcare is ubiquitous and affects the physical health, recovery and psychological and emotional well-being of those who experience it. Numerous studies have explored different issues related to coercion, and the present umbrella review aims to gather, evaluate and synthesise the evidence found across systematic reviews. The protocol, registered in the International Prospective Register of Systematic Reviews (PROSPERO registration number: CRD42020196713), included 46 systematic reviews and meta-analyses of primary studies whose main theme was coercion and which were obtained from databases (Medline/PubMed, PsycINFO, EMBASE and CINAHL) and repositories of systematic reviews following the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. All the reviews were subjected to independent assessment of quality and risk of bias and were grouped in two categories: (1) evidence on specific coercive measures (including Community Treatment Orders, forced treatment, involuntary admissions, seclusion and restriction and informal coercion), taking into account their prevalence, related factors, effectiveness, harmful effects and alternatives to reduce their use; and (2) experiences, perceptions and attitudes concerning coercion of professionals, mental health service users and their caregivers or relatives. This umbrella review can be useful to professionals and users in addressing the wide variety of aspects encompassed by coercion and the implications for professionals' daily clinical practice in mental health units. This research received funding from two competitive calls.
Keyphrases
- meta analyses
- mental health
- systematic review
- randomized controlled trial
- healthcare
- clinical practice
- mental illness
- physical activity
- emergency department
- public health
- primary care
- risk factors
- risk assessment
- machine learning
- case control
- health information
- combination therapy
- replacement therapy
- deep learning
- health insurance
- social media
- climate change
- electronic health record