Technological approaches to trauma treatment have exploded in the past decade and offer promise for providing low cost and clinically-effective support for trauma survivors. Web-based interventions as well as phone apps (see examples in Table 1) have received some empirical support.
Although these tools offer unique vehicles to overcome critical barriers to care such as cost, location, stigma, etc., they are not without their own challenges. The three primary factors that we must address as clinicians, educators and researchers are: engagement, clinical technology education infusion and cost sustainability.
Name | Target Problem | Reference |
Interapy | Trauma and a host of other mental health challenges | Lange et al., 2003; Rewaard et al., 2009 |
My Trauma Recovery | Posttraumatic distress and coping support | Benight, et al., 2008; Wang, Wang & Maercker, 2013 |
My Disaster Recovery | Post-disaster recovery | Steinmetz et al., 2012 |
PTSD Coach App | Posttraumatic stress management | Possemato et al, 2016 |
PTSD Family Coach App | Support for families related to PTSD in a family member | Unavailable |
Technological approaches to trauma treatment have exploded in the past decade and offer promise for providing low cost and clinically-effective support for trauma survivors. Web-based interventions as well as phone apps (see examples in Table 1, click on table to enlarge) have received some empirical support.
Although these tools offer unique vehicles to overcome critical barriers to care such as cost, location, stigma, etc., they are not without their own challenges. The three primary factors that we must address as clinicians, educators and researchers are: engagement, clinical technology education infusion and cost sustainability.
Number 1 - Engagement is one of the chief concerns that we must address. The first issue is how we actually measure engagement. Is engagement simply time logged on to the site? Number of key strokes hit? Pages visited? Self-report of time on the site? These are all complex questions with difficult answers and often with surprising findings. For example, in our own data we have seen a small correlation between objective and subjective engagement measures (Yeager, 2016). What exactly does this mean? Another key question is how much exposure to these interventions is enough in order to achieve a therapeutic benefit? The dose response information has yet to be clearly addressed. These are important challenges to our understanding, and optimism, concerning the viability of these tools. For instance, many people who start these programs quit very quickly and many actually do not even get started. Ruggiero et al. (2006), for example, found that between 37 percent and 64 percent completed modules for a web-intervention following 9/11. Price et al. (2012) found that almost half of their users (48 percent) did not engage at all with a web-intervention following a hurricane. Recently, Yeager (2016) evaluated the utility of the Health Action Process Approach to help elucidate the predictors of engagement with the My Trauma Recovery web-intervention for trauma. She found that many social cognitive predictors were important to consider including: outcome expectancies, pre-treatment self-efficacy, perceived need and PTSD symptoms.
Number 2 - Clinical technology education infusion is the standard of practice for educating our clinical students and practicing clinicians on how to effectively utilize technology. European colleagues have already begun to have specific courses at the University level. In the U.S. we have yet to embark in this area in a substantive way. Evaluation is needed to determine how clinicians need to be trained in order to maximize the benefit of these tools. For example, is maximum benefit for PTSD Coach achieved when a clinician sees the individual first (see Possemato et al., 2016)? Should the clinician evaluate the individual’s level e-health readiness, a concept defined as a user’s preparedness to engage in an e-health intervention (Bhalla, Durham, Al-Tabaa, & Yeager, 2016)? Recent work in our laboratory suggests that an individual’s trauma coping self-efficacy may play an important role in utilization of a trauma recovery website. Much more work is needed in this area relative to how these tools are best integrated into existing trauma techniques, as well as how do we best educate students and providers in this area.
Number 3 - Cost sustainability is a critical factor that has been underappreciated in the area of technology and trauma intervention. The interventions developed over the past decade, either web-based or apps) have required significant financial infusion. For example, the My Disaster Recovery website was developed through a Small Business Technology Transfer Grant from the U.S. National Institute of Mental Health taking several years and costing over $500,000. This does not include the costs for randomized clinical trial work, re-programming across time for improvements, etc. Current investment is around a million dollars. The Veteran’s Administration has put well over a million dollars into technology-based interventions including PTSD Coach, PTSD Family Coach, Afterdeployment.org, PTSD Coach Online to name a few.
The public versus private investment into these tools creates a unique environment for future investment. Recently, venture capital began to flow into this area. For example, a company called Lantern received 17 million dollars in venture capital for e-mental health interventions. Will “big business” offer solutions to this never ending problem of sustainability? Will corporatization result in less than optimal tools that make money for a company? Sustainability for these tools, critical evaluation, and future development requires extensive resources (similar to the pharmaceutical development cycle).
The source of these resources remains an interesting question. What is clear is that the cycle of development is currently too long given the speed at which technology accelerates. I have referred to this as the Development, Deployment & Determination (DDD) gap. Technological advancements (e.g., speed of processing) double every couple of years (Moore’s Law). Our DDD cycle at best takes 10 years for us to develop, deploy and critically evaluate. This keeps us forever behind and creates a risk for implementation of untested “best new gadget” and possible abandonment of good “old” systems. This does not even entertain the possible training and education requirements for new systems with our clinical providers (e.g., virtual reality systems of care).
In summary, the future is bright with opportunities with integration of technology into our systems and approaches of care with trauma survivors. Yet with opportunity comes risk and challenges that must be systematically addressed.
About the Author
Charles Benight, PhD, is a professor of psychology at the University of Colorado at Colorado Springs and is the founder and the current director of the CU-Trauma, Health and Hazards Center. Dr. Benight's primary area of research interest is in understanding human adaptation from trauma as well as the development of theoretically-based technology solutions for trauma recovery. He is currently a member of the ISTSS Board of Directors, serving as Treasurer.
References
Benight, C. C., Ruzek, J., & Waldrep, E. (2008). Internet interventions for traumatic stress: A review and theoretically-based example. Journal of Traumatic Stress, 26, 513-520.
Bhalla, A., Durham, R. Al-Tabaa, N. & Yeager, C. (2016). The development and initial psychometric validation of the eHealth readiness scale. Computers and Human Behavior, 65, 460-467.
Lange, A., Rietdijk, D., Hudcovicova, M., Van de Ven, J-P., Schrieken, B., & Emmelkamp, P. M. G. (2003). Interapy: A controlled randomized trial of the standardized treatment of posttraumatic stress through the internet. Journal of Consulting and Clinical Psychology, 71, 901-909.
Possemato, K. A., Kuhn, E., Johnson, E. M., Hoffman, J. E., Owen, J. E., Kanuri, N., Brooks, E. (2016). Using PTSD coach in primary care with and without clinician support: A pilot randomized controlled trial. General Hospital Psychiatry, 38, 94-98.
Price, M., Gros, D. F., McCauley, J. L., Gros, K. S., & Ruggiero, K. J. (2012). Nonuse and Dropout Attrition for a Web-Based Mental Health Intervention Delivered in a Post-Disaster Context. Psychiatry, 75(3), 267–284. http://doi.org/10.1521/psyc.2012.75.3.267
Ruggiero, K. J., Resnick, H. S., Acierno, R., Carpenter, M. J., Kilpatrick, D. G., Coffey, S. F., Galea, S. (2006). Internet-based intervention for mental health and substance use problems in disaster-affected populations: A pilot feasibility study. Behavior Therapy, 37, 190–205.
Ruwaard, J., Schrieken, B., Schrijver, M., Broeksteeg, J., Dekker, J., Vermeulen, H., & Lange, A. (2009). Standardized web-based cognitive behavioural therapy of mild to moderate depression: a randomized controlled trial with a long-term follow-up. Cognitive Behaviour Therapy, 38(4), 206–221.
Steinmetz, S., Benight, C. C., Bishop, S., & James, L. (2012). My Disaster Recovery: A pilot randomized controlled trial of an internet intervention. Anxiety, Stress & Coping, 25, 593-600.
Wang, Z., Wang, J., & Maercker, A. (2013). Chinese My Trauma Recovery, a web-based intervention for traumatized persons in two parallel samples: Randomized controlled trial. Journal of Medical Internet Research, 15(9), e213.
Yeager, C. (2016). Understanding engagement with a Trauma Recovery Web intervention using the Health Action Process Approach (HAPA) framework. Unpublished Master’s Thesis. University of Colorado at Colorado Springs.