Use of Digital Tools in Clinical Practice

Learning objectives:

1. Identify and describe at least three behavioral intervention technologies (BITs) matching each to specific clinical scenarios or needs.
2. Demonstrate understanding of supportive accountability and describe at least two ways digital tools can be used to enhance assessment or treatment as adjunct to traditional care.
3. Evaluate digital tools for their evidence-base, cultural responsiveness, and clinical appropriateness, and develop a list of resources to recommend or integrate into practice.

Webinar description: 

As digital mental health tools rapidly evolve, clinicians face both exciting opportunities and challenges. This webinar provides a practical, evidence-informed overview of how digital technologies can enhance clinical care. Participants will learn about Behavioral Intervention Technologies (BITs), with applied examples including virtual reality for exposure therapy, mobile apps, AI-based companions, and therapist enablement tools such as measurement-based care platforms. Grounded in the supportive accountability model, this training will equip clinicians to critically evaluate digital tools for scientific basis, cultural responsiveness, and clinical utility. Emphasis will be placed on balancing innovation with ethical integration into treatment. By the end of the session, attendees will be able to make informed, ethical, and competent decisions about incorporating digital tools into their practice.

Relevant references:

• One Mind PsyberGuide: https://onemindpsyberguide.org/guide/about-psyberguide/
• Meyerhoff, J., Kornfield, R., Lattie, E. G., Knapp, A. A., Kruzan, K. P., Jacobs, M., ... & Graham, A. K. (2023). From formative design to service-ready therapeutic: A pragmatic approach to designing digital mental health interventions across domains. Internet Interventions, 34, 100677. https://doi.org/10.1016/j.invent.2023.100677
  • URL: https://www.sciencedirect.com/science/article/pii/S2214782923000775

• Mohr, D., Cuijpers, P., & Lehman, K. (2011). Supportive accountability: a model for providing human support to enhance adherence to eHealth interventions. Journal of medical Internet research, 13(1), e1602. doi: 10.2196/jmir.1602
  • URL: https://www.jmir.org/2011/1/E30

• Nelson, B. W., Peiper, N. C., & Forman-Hoffman, V. L. (2024). Digital mental health interventions as stand-alone vs. augmented treatment as usual. BMC public health, 24(1), 969. https://doi.org/10.1186/s12889-024-18412-1
  • URL: https://link.springer.com/article/10.1186/s12889-024-18412-1

• Olawade, D. B., Wada, O. Z., Odetayo, A., David-Olawade, A. C., Asaolu, F., & Eberhardt, J. (2024). Enhancing mental health with Artificial Intelligence: Current trends and future prospects. Journal of medicine, surgery, and public health, 100099. https://doi.org/10.1016/j.glmedi.2024.100099
  • URL: https://www.sciencedirect.com/science/article/pii/S2949916X24000525