Published on in Vol 21, No 9 (2019): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15620, first published .
Predicting Inpatient Aggression in Forensic Services Using Remote Monitoring Technology: Qualitative Study of Staff Perspectives

Predicting Inpatient Aggression in Forensic Services Using Remote Monitoring Technology: Qualitative Study of Staff Perspectives

Predicting Inpatient Aggression in Forensic Services Using Remote Monitoring Technology: Qualitative Study of Staff Perspectives

Journals

  1. Hammarström L, Devik S, Hellzén O, Häggström M. The path of compassion in forensic psychiatry. Archives of Psychiatric Nursing 2020;34(6):435 View
  2. McLoughlin L, Carey C, Dooley S, Kennedy H, McLoughlin I. An observational study of a cross platform risk assessment mobile application in a forensic inpatient setting. Journal of Psychiatric Research 2021;138:388 View
  3. Simons R, Koordeman R, de Looff P, Otten R. Physiological Measurements of Stress Preceding Incidents of Challenging Behavior in People With Severe to Profound Intellectual Disabilities: Longitudinal Study Protocol of Single-Case Studies. JMIR Research Protocols 2021;10(7):e24911 View
  4. Jameel L, Valmaggia L, Barnes G, Cella M. mHealth technology to assess, monitor and treat daily functioning difficulties in people with severe mental illness: A systematic review. Journal of Psychiatric Research 2022;145:35 View
  5. Jilka S, Hudson G, Jansli S, Negbenose E, Wilson E, Odoi C, Mutepua M, Wykes T. How to make study documents clear and relevant: the impact of patient involvement. BJPsych Open 2021;7(6) View
  6. de Looff P, Cornet L, de Kogel C, Fernández-Castilla B, Embregts P, Didden R, Nijman H. Heart rate and skin conductance associations with physical aggression, psychopathy, antisocial personality disorder and conduct disorder: An updated meta-analysis. Neuroscience & Biobehavioral Reviews 2022;132:553 View
  7. Anastasi G, Bambi S. Utilization and effects of security technologies in mental health: A scoping review. International Journal of Mental Health Nursing 2023;32(6):1561 View
  8. Dewa L, Broyd J, Hira R, Dudley A, Hafferty J, Bates R, Aylin P. A service evaluation of passive remote monitoring technology for patients in a high-secure forensic psychiatric hospital: a qualitative study. BMC Psychiatry 2023;23(1) View
  9. Rogan J, Bucci S, Firth J. Health Care Professionals’ Views on the Use of Passive Sensing, AI, and Machine Learning in Mental Health Care: Systematic Review With Meta-Synthesis. JMIR Mental Health 2024;11:e49577 View
  10. Rogan J, Firth J, Bucci S. Healthcare Professionals' Views on the Use of Passive Sensing and Machine Learning Approaches in Secondary Mental Healthcare: A Qualitative Study. Health Expectations 2024;27(6) View
  11. Griffiths J, Saunders K, Foye U, Greenburgh A, Regan C, Cooper R, Powell R, Thomas E, Brennan G, Rojas-García A, Lloyd-Evans B, Johnson S, Simpson A. The use and impact of surveillance-based technology initiatives in inpatient and acute mental health settings: a systematic review. BMC Medicine 2024;22(1) View