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Digital Health and Technology

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Suicide Care Technologies 

These are technologies that are being tested by CAPES faculty to improve the research to practice pipeline for suicide risk screening, assessment, and/or intervention:

  • Computerized Adaptive Tests are validated, comprehensive, digital screening and assessment tests based on multidimensional item response theory that can accurately identify persons with particular mental health problems in under 2 minutes. Go to the Adaptive Testing Technologies website for more videos and information.
    • Adult Computerized Adaptive Tests include those for depression, anxiety, mania/hypomania, substance use disorder, psychosis, PTSD, social determinants of health, adult ADHD, and suicidality.
    • Kiddie Computerized Adaptive Tests are for children 7-17 and include self-rated and parent/caregiver-rated modules for: depression, anxiety, mania, ADHD, conduct disorder, oppositional defiant disorder, substance use disorder (self-rated), and suicidality (self-rated).
  • Jaspr Health is a digital suicide-care platform with automated, evidence-based protocols that has been shown to improve patient experiences, optimize provider care, and reduce healthcare system costs.
  • Early Mental Health Uncovering framework supports mental illness screening with non-intrusive active and passive modalities using a smartphone app.

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Publicly Available Apps

These are publicly available smartphone and tablet applications that are designed to improve uptake of evidence-based suicide prevention practices among clinicians or are digital forms of evidence-based suicide prevention practices directly provided to persons with suicidality:

  • Virtual Hope Box: Created by the National Center for PTSD and available to veterans and non-veterans. Includes a mix of personalized and pre-loaded content, with photos of friends and family, sound bites and videos of loved ones and special moments, music, relaxation exercises, games, helpline numbers, and reminders of reasons for living.
  • Safety Plan app: Created by the National Center for PTSD and available to veterans and non-veterans. For anyone who has experienced thoughts about suicide or self-harm. The app helps you make a safety plan, share your safety plan with loved ones, and use tools to manage distress.
  • Suicide Safe: Created by the Substance Abuse and Mental Health Services Administration, for clinicians. Provides clinicians with information and tools to identify and assess risk of suicide. Offers communication tips and referral resources for treatment and other support.

If you're interested in more about suicide prevention apps, see this published content analysis - where CAPES faculty Dr. Lourah Kelly and colleagues downloaded and rated all 74 suicide prevention apps in the Apple and Android app stores. 

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Peer-reviewed, Published Scientific Literature on Suicide Care Technologies 

  • Bailey, E., Bellairs-Walsh, I., Reavley, N. et al. Best practice for integrating digital interventions into clinical care for young people at risk of suicide: a Delphi study. BMC Psychiatry, 24, 71 (2024). https://doi.org/10.1186/s12888-023-05448-7
  • Boudreaux, E. D., Rundensteiner, E., Liu, F., Wang, B., Larkin, C., Agu, E., Ghosh, S., Semeter, J., Simon, G., & Davis-Martin, R. E. (2021). Applying machine learning approaches to suicide prediction using healthcare data: overview and future directions. Frontiers in Psychiatry, 12, 707916. https://doi.org/10.3389/fpsyt.2021.707916
  • Burke, T. A., Ammerman, B. A., & Jacobucci, R. (2019). The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behaviors: A systematic review. Journal of Affective Disorders, 245, 869–884. https://doi.org/10.1016/j.jad.2018.11.073 
  • Gibbons, R. D., Kupfer, D., Frank, E., Moore, T., Beiser, D. G., & Boudreaux, E. D. (2017). Development of a Computerized Adaptive Test Suicide Scale — The CAT-SS. The Journal of Clinical Psychiatry, 78(9), 1376–1382. https://doi.org/10.4088/JCP.16m10922 
  • Dimeff, L. A., Jobes, D. A., Koerner, K., Kako, N., Jerome, T., Kelley-Brimer, A., Boudreaux, E. D., Beadnell, B., Goering, P., Witterholt, S., Melin, G., Samike, V., & Schak, K. M. (2021). Using a tablet-based app to deliver evidence-based practices for suicidal patients in the emergency department: pilot randomized controlled trial. JMIR Mental Health, 8(3), e23022. https://doi.org/10.2196/23022
  • Haroz, E. E., Walsh, C. G., Goklish, N., Cwik, M. F., O'Keefe, V., & Barlow, A. (2020). Reaching those at highest risk for suicide: development of a model using machine learning methods for use with Native American communities. Suicide & Life-Threatening Behavior, 50(2), 422–436. https://doi.org/10.1111/sltb.12598  
  • Melia, R., Francis, K., Hickey, E., Bogue, J., Duggan, J., O'Sullivan, M., & Young, K. (2020). Mobile health technology interventions for suicide prevention: systematic review. JMIR mHealth and uHealth, 8(1), e12516. https://doi.org/10.2196/12516
  • Onie, S., Armstrong, S. O., Josifovski, N., Berlinquette, P., Livingstone, N., Holland, S., Finemore, C., Gale, N., Elder, E., Laggis, G., Heffernan, C., Theobald, A., Torok, M., Shand, F., & Larsen, M. (2024). The effect of explicit suicide language in engagement with a suicide prevention search page help-seeking prompt: nonrandomized trial. JMIR mental health, 11, e50283. https://doi.org/10.2196/50283
  • Somé, N. H., Noormohammadpour, P., & Lange, S. (2024). The use of machine learning on administrative and survey data to predict suicidal thoughts and behaviors: a systematic review. Frontiers in Psychiatry, 15, 1291362. https://doi.org/10.3389/fpsyt.2024.1291362 
  • Sutori, S., Hadlaczky, G., Eliasson, E. et al. (2023). Systematic review and meta-analysis: effectiveness of stand-alone digital suicide preventive interventions for the self-management of suicidality. Journal of Technology and Behavioral Science. https://doi.org/10.1007/s41347-023-00374-7
  • Torok, M., Han, J., Baker, S., Werner-Seidler, A., Wong, I., Larsen, M. E., & Christensen, H. (2020). Suicide prevention using self-guided digital interventions: a systematic review and meta-analysis of randomised controlled trials. The Lancet. Digital Health, 2(1), e25–e36. https://doi.org/10.1016/S2589-7500(19)30199-2