Predicting inpatient aggression in forensic services using remote monitoring technology: Qualitative study of staff perspectives

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Abstract

Background: Monitoring risk of imminent aggression in inpatient forensic mental health services could be supported by passive remote monitoring technology, but staff attitudes towards the relevance and likelihood of engagement with this technology are unknown.
Objective: This study aimed to explore staff views, specifically potential benefits and implementation barriers, towards using this technology for monitoring risk of inpatient aggression.
Methods: Five semi-structured focus groups were conducted with 25 nurses in an inpatient forensic mental health service. Thematic analysis with two independent raters was used to identify themes and subthemes related to staff attitudes towards passive remote monitoring. Subsequent member-checking was conducted to ensure the validity of the themes identified by the raters.
Results: Five main themes were identified, one of which concerned the potential benefits that passive remote monitoring could provide for monitoring risk of aggression. Staff suggested it could provide an early warning of impending aggression and enable support to be provided earlier. The remaining themes concerned implementation barriers, including risks to the users’ physical and mental wellbeing; data security concerns and potential access by third parties; the negative impact of a constant stream of real-time data on staff workload; and design characteristics and user awareness of the benefits of passive remote monitoring.
Conclusions: Passive remote monitoring technology could support existing methods of monitoring inpatient aggression risk, but multiple barriers to implementation exist. Empirical research is required to investigate whether these potential benefits can be realised, and to identify ways of addressing these barriers to ensure acceptability and user-engagement.
Original languageEnglish
Article numbere15620
Pages (from-to)e15620
JournalJournal of Medical Internet Research
Volume21
Issue number9
DOIs
Publication statusPublished - 19 Sept 2019

Keywords

  • Aggression
  • Remote sensing technology
  • Risk assessment
  • Telemedicine
  • Wearable sensors

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