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Evidence Base for Using Technology Solutions
in Behavioral Health Care
December 17, 2014, 1-2:30pm (EST)
Nancy A. Skopp, Ph.D.
Research Psychologist and Program Manager
National Center for Telehealth & Technology (T2)
Defense Centers of Excellence for Psychological
Health and Traumatic Brain Injury (DCoE)
Joint Base Lewis-McChord, Wash.
Christina M. Armstrong, Ph.D.
Clinical Psychologist, Program Lead for T2 Education & Training Program
National Center for Telehealth & Technology (T2)
Defense Centers of Excellence for Psychological
Health and Traumatic Brain Injury (DCoE)
Joint Base Lewis-McChord, Wash.
Janyce “Jae” Osenbach, Ph.D.
Research Psychologist and Psychometrician
National Center for Telehealth & Technology (T2)
Defense Centers of Excellence for Psychological
Health and Traumatic Brain Injury (DCoE)
Joint Base Lewis-McChord, Wash.
Presenters:
Moderator:
Webinar Overview
2
Recent advances in the evidence base for technology-based behavioral health
applications have provided clinicians a better understanding and guidance on the
integration of these tools into clinical care. Participants will learn about research
findings on current technologies in use in clinical practice, such as audio
conferencing, video conferencing, and virtual reality, in addition to tools available
for use between patients, such as the use of websites and mobile applications
and wearable sensors. Clinicians will leave this training with a review of the
evidence base for using technology solutions in behavioral health care that will
inform their clinical practice.
At the conclusion of this webinar, learners will be able to:
 Describe a theoretical perspective useful in the conceptualization and
application of technology-based interventions for clinical practice
 Differentiate between the concepts of synchronous and asynchronous
technologies with respect to behavioral health interventions
 Examine the current status of literature on technologically-supported
behavioral health interventions
 Assess potential gaps and recognize future trends in behavioral health
technology tools into clinical care
2
Disclosures
 The views expressed in this presentation are those of the
presenters and do not reflect the official policy of the
Department of Defense or the U.S. Government.
 We have no relevant financial relationships to disclose.
 We will be discussing web and mobile applications that have
been developed by the Defense Department, including those
developed by the National Center for Telehealth and
Technology (T2). Some of these applications may fall under
FDA device regulations, and in those cases we will consult
with the USAMRMC Division of Regulated Activities and
Compliance for guidance.
3
Overview
1. Evidence Base and Theory
– Theory to inform modality selection
– Clinical practice technologies
– “White space” technologies
2. Key Concepts
– Media Synchronicity Theory
– Synchronous
– Asynchronous
4
5
 Synchronous - communication in real time
 Asynchronous - communication not in real time
Definitions
 Synchronous technologies support
convergence of understanding
 Asynchronous technologies maximize the
conveyance of information to support
individual level analysis
6
(Dennis, et.al., 2008)
Media Synchronicity Theory
(MST)
7
Synchronous
Convergence
(e.g., video telehealth)
Asynchronous
Conveyance
(e.g., website)
Treatment
Outcomes
(Castonguay, Constantino, & Holtforth, 2006; Hatcher, Barends, Hansell, & Gutfreund,
1995; Norcross, 2011; Jarvis-Selinger, Chan, Payne, Plohman,& Kendall, 2008
Model to Guide Selection of Modality
Delivery
Success
• Therapeutic Alliance
• Technology
• Training
(Figure 1. Dennis, Fuller, Valacich, 2008)
 Telephone Interventions
 Video Telehealth
 Virtual Worlds
8
Evidence Base
Synchronous Technologies
Telephone Interventions
Cons
 No non-verbal cues
 Potential interruptions
 Confidentiality
 Safety
9
Pros
 Convenient
 Widely available
 Inexpensive
 Remote outreach
 Ease of operation
Overview: Telephone
Interventions
10
 Wide range of behavioral health applications1
 Ability to overcome barriers to conventional
care2
 Literature characterized by heterogeneity3
– Uses
– Type of treatment
– Research methods
1(Bee et al., 2008; Brenes, Ingram & Danhauer, 2012; Eakin, Lawler, Vandelanotte & Owen, 2007; Villanti, McKay,
Abrams, Holtgrave & Bowie, 2010; van Velthoven, Car, Car, & Atun, 2012)
2(Bee et al., 2008; Brenes et al., 2012; Eakin et al., 2007; Mohr, Vella, Hart, Heckman, & Simon, 2008)
3(Bee et al., 2008)
Telephone Interventions:
Applications
11
 Depression1
 Anxiety disorders2
 Smoking cessation3
 Alcohol abuse4
 Health behaviors – HIV, weight management, chronic
disease prevention5
1(Bee et al., 2008; Choi et al., 2014; Mohr et al., 2008)
2(Bee et al. 2008; Brenes et al., 2012; Lovell et al., 2006)
3(Villanti et al., 2010)
4(Lenaerts, Mathei, Matthys, Zeeuws, Pas, Anderson & Aertgeerts, 2014)
5(Eakin et al., 2007; Simek, McPhate, & Haines, 2012; vanVelthoven et al., 2012)
Video Telehealth
Pros
 Remote outreach
 Increased access
 Transportation $0.00
 Remote treatment
for low-base-rate
problems
Cons
 Technical issues
 Confidentiality issues
 No federal laws
 Start-up costs and
remuneration
12
Video Telehealth at a Glance
1996-2012
Empirical
Studies
47 (of 65 studies); 45% were controlled
Most Common
Psychotherapy
45% CBT
Session
Format
71% individual; 17% group; 10% family; 2%
other
Populations 86% adult; 10% child/adolescent; 5% unclear
74% Civilian; 21% Veteran; 5% Civilian + Military
Feasibility 38% positive contributions
Therapeutic
Relationship
34% examined; 88% strong alliance
13
(Table 1. Backhaus et al., 2012)
Video Telehealth: Clinical
Applications
 Anxiety and mood disorders1
 Eating disorders2
 Addiction2
 Physical ailments2
 Smoking Cessation3
 Parenting and child problems4
1(Backhaus et al., 2012; Gros et al., 2013)
2(Backhaus et al., 2012)
3(Carlson et al., 2012)
4(Backhaus et al., 2012; Comer et al., 2013; Himle et al, 2012; Reese, Slone, Soares, & Sprang, 2012)
14
Video Telehealth (VT) Clinical
Outcome Data
VT
= In-persona
VT
≥ In-personb
Depression
Anxiety Disorders
Eating Disorders
Anger
Physical Health Problems
Smoking Cessation
Child Problems
Substance Abuse
Disorder
15
Table 2. aNo significant between group differences found; Backhaus et al., 2012; Gros et al., 2013; bNelson,
Barnard, & Cain, 2003; Bouchard et al., 2004; Choi et al., 2014;
Video Telehealth (VT):
General Empirical Findings
 VT works
 Literature to support efficacy of VT
- Heterogeneous groups
- Diverse range of problems
 Some literature does not support VT
- Individual differences
- Nature of the disorder?
(Backhaus et al., 2012; Gros et al., 2013)
16
Video Telehealth: VA and DoD
17
 Driving force of video telehealth
 Ongoing and completed RCTs
 Preliminary evidence supports VT
 VT comparable to in-person therapy
 Majority of VT is facility-to-facility
(Gros et al., 2013)
Video Telehealth: Recent VA RCT
 Telemedicine Outreach for PTSD (TOP)
 11 outpatient units serving rural veterans
 Cognitive processing therapy (CPT) >
Usual care
18

(Fortney et al., 2014)
Video Telehealth: Research
Gaps
19
 Influence of demographics
 More non-inferiority trials needed
 Majority of research on PTSD
 Need research on process variables
(Backhaus et al., 2012; Gros et al., 2013)
Video Telehealth:
Additional Considerations
 Technology
 Ongoing support
 Training
 Room set-up
 Protocol development
20
(Jarvis-Selinger et al., 2008)
Virtual Worlds (VW)
 Immersive, 3D environments1
 Individualized
representations - “avatars” 1
 Research nascent
 Preliminary pilot – social
anxiety disorder2
 Future directions3
21
1(Pridmore & Phillips-Wren, 2011)
2(Yuen, Herbert, Forman, Goetter, Comer, & Bradley, 2013)
3(Morie, Haynes, & Chance, 2011; Riva, Wiederhold, Mantovani & Gaggioli, 2011)
Emerging Technologies
 Holographic Projection1
 Telepresence systems seamlessly approximate
a “true-to-life” workspace2
– Eye gaze tracking
– Life-sized imaging
– Visual continuity
22
1(Stefan & David, 2013)
2(O’Hara, Kjeldskov, & Paay, 2011)
Synchronous Technology:
Additional Considerations
 Technical Requirements1
– Facility with delivery
– Resolution, bandwidth, disconnection
 Interpersonal and Individual Factors2
– Therapeutic relationship
– Client preferences
– What works for whom?
1(Gros et al., 2013; Jarvis-Selinger et al., 2008)
2(Cavanagh & Millings, 2013; DeLucia, Harold, & Tang, 2013; Sucala, Schnur, Constantino, Miller, Brackman,
& Mongomery, 2012)
23
Poll Question #1
Do you use synchronous telehealth
with your patients?
24
 Web
 Mobile apps
 Emerging technologies
25
Evidence Base
Asynchronous Technologies
General Research Findings
26
(Lawlor & Kirakowski, 2014; Mohr, Burns, Schueller, Clarke, & Klinkman, 2013; Richards &
Richardson, 2012)
Poll Question #2
Do you use websites with your patients?
27
General Research Findings
28
(Bush, Skopp, Smolenski, Crumpton, & Fairall, 2013; Donker, Petrie, Proudfoot, Clarke, Birch, & Christensen, 2013; Gaggioli, & Riva,
2013; Seko, Kidd, & Wiljer, 2013)
App Marketplace Research
29
(Aguirre, McCoy, & Roan, 2013; Juarascio, Manasse, Goldstein, Forman, & Butryn, 2014)
The Paid-App Fallacy
30
(Boudreaux, Waring, Hayes, Sadasivam, Mullen, & Pagoto, 2014; West, Hall, Hanson, Barnes,
Giraud-Carrier, & Barrett, 2012)
Poll Question #3
Do you use mobile apps with your patients?
31
More Research Needed
32
(Ben-Zeev, Schueller, Begale, Duffecy, Kane, & Mohr, 2014)
Future of Devices
33
T2 Research
34
(Bush, et al., 2013a; Bush, et al., 2014a; Bush, et al., 2013b; Luxton, et al., 2014)
Poll Question #4
Have you used T2 mobile apps or websites?
35
Conclusion
In conclusion, during this webinar we:
 Described a theoretical perspective useful in the
conceptualization and application of technology-based
interventions for clinical practice
 Differentiated between the concepts of synchronous and
asynchronous technologies with respect to behavioral health
interventions
 Examined the current status of literature on technologically
supported behavioral health interventions
 Assessed potential gaps and recognized future trends in
using behavioral health technology tools in clinical care
36
References
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Videoconferencing Psychotherapy: A systematic review. Psychological Services, 9, 111-131.
Bee, P.E., Bower, P. Lovell, K., Gilbody, S., Richards, D., Gask, L., & Roach, P. (2008). Psychotherapy
mediated by remote communication technologies: A meta-analytic review. BioMed Central
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Bush, N. E., Ouelette, G., & Kinn, J. (2014b). Utility of the T2 Mood Tracker mobile application among
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Castonguay, L.G., Constantino, M.J., & Holtforth, M.G. (2006). The working alliance: Where we are and where should
we go? Psychotherapy, 43, 271-279.
Carlson, L.E., Lounsberry, J.J., Maciejewski, O., Wright, K., Collacutt, V., & Taenzer, P. (2012). Telehealth-delivered
group smoking cessation for rual and urban participants: Feasibility and cessation rates. Addictive Behaviors, 27,
108-114.
Cavanagh, K., & Millings, A. (2013). (Inter) personal computing: The role of the therapeutic relationship in e-mental
health. Journal Contemporary Psychotherapy, 4, 197-206.
Choi, N.G., Marti, C.N., Bruce, M.L., Hegel, M.T., Wilson, M.A., & Kunik, M.E. (2014). Six-month postintervention for
depression and disability outcome of in-home telehealth problem-solving therapy for depressed, low-income
homebound older adults. Depression and Anxiety, 31, 653-661.
Comer, J.S., Furr, J.M., Cooper-Vince, C.E., Kerns, C.E., Chan, P.T., Edson, A.L., …et al., Freeman, J.B. (2013).
Internet-delivered, family-based treatment for early onset OCD: A preliminary case series. Journal of Clinical
Child & Adolescent Psychology, 43, 74-87.
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DeLucia, P., Harold, S.A., & Tang, Y. (2013). Innovation in Technology-aided psychotherapy through
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Psychotherapy, 43, 253-260.
Dennis, A.R., Fuller, R.M., & Valacich, J.S. (2008). Media, tasks, and communication processes: A
theory of media synchronicity. MIS Quarterly, 32, 575-600.
Donker, T., Petrie, K., Proudfoot, J., Clarke, J., Birch, M. R., & Christensen, H. (2013). Smartphones
for smarter delivery of mental health programs: A systematic review. Journal of Medical Internet
Research, 15(11), e247.
41
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Eakin, E.G., Lawler, S.P., Vandelanotte, C., & Owen, N. (2007). Telephone interventions for physical
activity and dietary behavior change: A systematic review. American Journal of Preventive
Medicine, 32, 419-434.
Fortney, J.C., Pyne, J.M., Kimbrell, T.A., Hudson, T.J., Robinson, D.E., Schneider, R., Moore, W.M,
…et al., Schnurr, P.P. (2014). Telemedicine-based collaborative care for posttraumatic stress
disorder: a randomized clinical trial. JAMA Psychiatry. Epub ahead of print.
Gaggioli, A., & Riva, G. (2013). From mobile mental health to mobile wellbeing: Opportunities and
challenges. Studies in Health Technology and Informatics, 184, 141-147.
Gros, D.F., Morland, L.A., Greene, C.J., Acierno, R., Strachan, M., Egede, L.E., …et al., Frueh, B.C.
(2013). Delivery of evidence-based psychotherapy via video telehealth. Journal of
Psychopathology and Behavioral Assessment, 35, 506-521.
42
References
Hatcher, R.L., Barends, A., Hansell, J., & Gutfreund, M.J. (1995). Patients’ and therapists’ shared and
unique views of the therapeutic alliance: An investigation using confirmatory factor analysis in a
nested design. Journal Consulting and Clinical Psychology, 63, 636-643.
Himle, M.B., Freitag, M., Walther, M., Franklin, S.A., Ely, L., & Woods, D.W. (2012). A randomized pilot
trial comparing video conference versus face-to-face delivery of behavior therapy for childhood
tic disorders, 50, 565-570.
Jarvis-Selinger, S., Chan, E., Payne, R., Polhman, L.L.M., & Kendall, H. (2008). Clinical telehealth
across the disciplines: Lessons learned. Telemedicine and e-Health, 14, 720-725.
Juarascio, A. S., Manasse, S. M., Goldstein, S. P., Forman, E. M., & Butryn, M. L. (2014). Review of
smartphone applications for the treatment of eating disorders. European Eating Disorders
Review, Advanced online publication.
Lawlor, A., & Kirakowski, J. (2014). Online support groups for mental health: A space for challenging43
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Lenaerts, E., Mathei, C., Matthys, F., Zeeuws, D., Pas, L., Anderson, P., & Aertgeerts, B. (2014).
Continuing care for patients with alcohol use disorders: A systematic review. Drug and Alcohol
Dependence, 135, 9-21.
Lovell, K., Cox, D., Haddock, G., Jones, C., Raines, D., Garvey, R., Roberts, C., & Hadley, S. (2006).
Telephone administered cognitive behaviour therapy for treatment of obessive compulsive
disorder: randomized controlled non-inferiority trial. British Medical Journal, 333, 883-886.
Luxton, D. D., Hansen, R. N., & Stanfill, K. (2014). Mobile app self-care versus in-office care for stress
reduction: A cost-minimization analysis. Journal of Telemedicine and Telecare, Advanced online
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44
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Mohr, D. C., Burns, M. N., Schueller, S. M., Clarke, G., & Klinkman, M. (2013). Behavioral intervention
technologies: Evidence review and recommendations for future research in mental health.
General Hospital Psychiatry, 35(4), 332-338.
Mohr, D.C., Vella, L., Hart, S., Heckman, T., & Simon, G. (2008). The effect of telephone-administered
psychotherapy on symptoms of depression and attrition: A meta-analysis. Clinical Psychology:
Science and Practice, 15, 243-253.
Morie, J.G., Haynes, E., & Chance, E. (2011). Warriors’ journey: A path to healing through narrative
exploration. International Journal of Disability and Human Development, 10, 17-23.
Nelson, E.L., Barnard, M., & Cain, S. (2003). Treating childhood depression over videoconferencing.
Telemedicine Journal ande-Health, 9, 49-55.
Norcross, J.C. (2011). Psychotherapy Relationships that Work: Evidence-Based Responsiveness. 2nd
45
References
Pridmore, J., & Phillips-Wren, G. (2011). Assessing decision making quality in face-to-face teams
versus virtual teams in a virtual world. Journal of Decision Systems, 3, 283-308.
Reese, R.J., Slone, N.C., Soares, N., & Sprang, R. (2012). Telehealth for underserved families: An
evidence-based parenting program. Psychological Services, 9, 320-322.
Richards, D., & Richardson, T. (2012). Computer-based psychological treatments for depression: A
systematic review and meta-analysis. Clinical Psychology Review, 32(4), 329-342.
Riva, G., Wiederhold, B.K., Mantovani, F., & Gaggioli, A. (2011). Interreality: The experiential use of
technology in the treatment of obesity. Clinical Practice and Epidemiology in Mental Health, 7,
51-61.
Seko, Y., Kidd, S., & Wiljer, D. (2013). Apps for those who help themselves: Mobile self-guided
interventions for adolescent mental health. Selected Papers Of Internet Research, 3. Retrieved
from http://spir.aoir.org/index.php/spir/article/view/833
46
References
Simek, E.M., McPhate, L., & Haines, T.P. (2012). Adherence to and efficacy of home exercise
programs to prevent falls: A systematic review and meta-analysis of the impact of exercise
program characteristics. Preventive Medicine: An International Journal Devoted to Practice and
Theory, 55, 262-275.
Stefan, S., & David, D. (2013). Face-to-face counseling versus high definition holographic projection
system. Efficacy and therapeutic alliance. A brief report. Journal of Cognitive and Behavioral
Psychotherapies, 13, 299-307.
Sucala, M., Schnur, J. B., Constantino, M. J., Miller, S. J., Brackman, E. H., Montgomery, G.H. (2012).
The therapeutic relationship in E-therapy for mental health: A systematic review. Journal of
Medical Internet Research, 14:e110
West, J. H., Hall, P. C., Hanson, C. L., Barnes, M. D., Giraud-Carrier, C., & Barrett, J. (2012). There’s
an app for that: Content analysis of paid health and fitness apps. Journal of Medical Internet
47
References
vanVelthoven, M.H.M.T., Car, L.R., Car, J., & Atun, R. (2012). Telephone consultation for improving
health of people living with or at risk of HIV: A systematic review. PLoSONE, 7, e36105-e36105
Villanti, A.C., McKay, H.S., Abrams, D.B., Holtgrave, D.R., Bowie, J.V. (2010). Smoking-cessation
interventions for U.S. young adults: A systematic review. American Journal of Preventive
Medicine, 39, 564-574.
Yuen, E.K., Herbert, J.D., Forman, E.M., Goetter, E.M., Comer, R., & Bradley, J. (2013). Treatment of
social anxiety disorder using online virtual environments in second life. Behavior Therapy, 44,
51-61.
48
Nancy A. Skopp, Ph.D.
49
 Dr. Nancy Skopp is a Research Psychologist and
Program Manager in the Research, Outcomes
and Investigations Division at the National Center
for Telehealth & Technology (T2), U.S.
Department of Defense.
 She is also an Affiliate Associate Professor at the
University of Washington’s Department of
Psychiatry & Behavioral Sciences.
 She is a Clinical Psychologist currently licensed
in the states of Texas and Washington.
 She holds doctoral and master’s degrees in
Clinical Psychology from the University of
Houston.
Nancy Skopp, Ph.D.
Janyce “Jae” Osenbach,
Ph.D.
50
Jae Osenbach, Ph.D.
 Dr. Jae Osenbach is a Research Psychologist
and Psychometrician in the Mobile Health
Program at the National Center for Telehealth &
Technology (T2), U.S. Department of Defense.
 She serves as a subject matter expert on mobile
apps and websites related to issues involving
military and veteran psychological health and
traumatic brain injury.
 She is also the lead for the Mobile Health
Program’s evaluations, surveys and
assessments, and serious games for behavioral
health.
 She holds a doctoral degree in Psychometrics
and Quantitative Psychology and a master’s
degree in Psychology from Fordham University.
Jae Osenbach, Ph.D.
janyce.e.osenbach.ctr@mail.mil
51
Nancy A. Skopp, Ph.D.
nancy.a.skopp.civ@mail.mil
http://t2health.dcoe.mil/
DCoE Contact Info
DCoE Outreach Center
1-866-966-1020 (toll-free)
http://www.dcoe.mil/
resources@dcoeoutreach.org
5252

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Evidence Base for Using Technology Solutions in Behavioral Health Care

  • 1. Evidence Base for Using Technology Solutions in Behavioral Health Care December 17, 2014, 1-2:30pm (EST) Nancy A. Skopp, Ph.D. Research Psychologist and Program Manager National Center for Telehealth & Technology (T2) Defense Centers of Excellence for Psychological Health and Traumatic Brain Injury (DCoE) Joint Base Lewis-McChord, Wash. Christina M. Armstrong, Ph.D. Clinical Psychologist, Program Lead for T2 Education & Training Program National Center for Telehealth & Technology (T2) Defense Centers of Excellence for Psychological Health and Traumatic Brain Injury (DCoE) Joint Base Lewis-McChord, Wash. Janyce “Jae” Osenbach, Ph.D. Research Psychologist and Psychometrician National Center for Telehealth & Technology (T2) Defense Centers of Excellence for Psychological Health and Traumatic Brain Injury (DCoE) Joint Base Lewis-McChord, Wash. Presenters: Moderator:
  • 2. Webinar Overview 2 Recent advances in the evidence base for technology-based behavioral health applications have provided clinicians a better understanding and guidance on the integration of these tools into clinical care. Participants will learn about research findings on current technologies in use in clinical practice, such as audio conferencing, video conferencing, and virtual reality, in addition to tools available for use between patients, such as the use of websites and mobile applications and wearable sensors. Clinicians will leave this training with a review of the evidence base for using technology solutions in behavioral health care that will inform their clinical practice. At the conclusion of this webinar, learners will be able to:  Describe a theoretical perspective useful in the conceptualization and application of technology-based interventions for clinical practice  Differentiate between the concepts of synchronous and asynchronous technologies with respect to behavioral health interventions  Examine the current status of literature on technologically-supported behavioral health interventions  Assess potential gaps and recognize future trends in behavioral health technology tools into clinical care 2
  • 3. Disclosures  The views expressed in this presentation are those of the presenters and do not reflect the official policy of the Department of Defense or the U.S. Government.  We have no relevant financial relationships to disclose.  We will be discussing web and mobile applications that have been developed by the Defense Department, including those developed by the National Center for Telehealth and Technology (T2). Some of these applications may fall under FDA device regulations, and in those cases we will consult with the USAMRMC Division of Regulated Activities and Compliance for guidance. 3
  • 4. Overview 1. Evidence Base and Theory – Theory to inform modality selection – Clinical practice technologies – “White space” technologies 2. Key Concepts – Media Synchronicity Theory – Synchronous – Asynchronous 4
  • 5. 5  Synchronous - communication in real time  Asynchronous - communication not in real time Definitions
  • 6.  Synchronous technologies support convergence of understanding  Asynchronous technologies maximize the conveyance of information to support individual level analysis 6 (Dennis, et.al., 2008) Media Synchronicity Theory (MST)
  • 7. 7 Synchronous Convergence (e.g., video telehealth) Asynchronous Conveyance (e.g., website) Treatment Outcomes (Castonguay, Constantino, & Holtforth, 2006; Hatcher, Barends, Hansell, & Gutfreund, 1995; Norcross, 2011; Jarvis-Selinger, Chan, Payne, Plohman,& Kendall, 2008 Model to Guide Selection of Modality Delivery Success • Therapeutic Alliance • Technology • Training (Figure 1. Dennis, Fuller, Valacich, 2008)
  • 8.  Telephone Interventions  Video Telehealth  Virtual Worlds 8 Evidence Base Synchronous Technologies
  • 9. Telephone Interventions Cons  No non-verbal cues  Potential interruptions  Confidentiality  Safety 9 Pros  Convenient  Widely available  Inexpensive  Remote outreach  Ease of operation
  • 10. Overview: Telephone Interventions 10  Wide range of behavioral health applications1  Ability to overcome barriers to conventional care2  Literature characterized by heterogeneity3 – Uses – Type of treatment – Research methods 1(Bee et al., 2008; Brenes, Ingram & Danhauer, 2012; Eakin, Lawler, Vandelanotte & Owen, 2007; Villanti, McKay, Abrams, Holtgrave & Bowie, 2010; van Velthoven, Car, Car, & Atun, 2012) 2(Bee et al., 2008; Brenes et al., 2012; Eakin et al., 2007; Mohr, Vella, Hart, Heckman, & Simon, 2008) 3(Bee et al., 2008)
  • 11. Telephone Interventions: Applications 11  Depression1  Anxiety disorders2  Smoking cessation3  Alcohol abuse4  Health behaviors – HIV, weight management, chronic disease prevention5 1(Bee et al., 2008; Choi et al., 2014; Mohr et al., 2008) 2(Bee et al. 2008; Brenes et al., 2012; Lovell et al., 2006) 3(Villanti et al., 2010) 4(Lenaerts, Mathei, Matthys, Zeeuws, Pas, Anderson & Aertgeerts, 2014) 5(Eakin et al., 2007; Simek, McPhate, & Haines, 2012; vanVelthoven et al., 2012)
  • 12. Video Telehealth Pros  Remote outreach  Increased access  Transportation $0.00  Remote treatment for low-base-rate problems Cons  Technical issues  Confidentiality issues  No federal laws  Start-up costs and remuneration 12
  • 13. Video Telehealth at a Glance 1996-2012 Empirical Studies 47 (of 65 studies); 45% were controlled Most Common Psychotherapy 45% CBT Session Format 71% individual; 17% group; 10% family; 2% other Populations 86% adult; 10% child/adolescent; 5% unclear 74% Civilian; 21% Veteran; 5% Civilian + Military Feasibility 38% positive contributions Therapeutic Relationship 34% examined; 88% strong alliance 13 (Table 1. Backhaus et al., 2012)
  • 14. Video Telehealth: Clinical Applications  Anxiety and mood disorders1  Eating disorders2  Addiction2  Physical ailments2  Smoking Cessation3  Parenting and child problems4 1(Backhaus et al., 2012; Gros et al., 2013) 2(Backhaus et al., 2012) 3(Carlson et al., 2012) 4(Backhaus et al., 2012; Comer et al., 2013; Himle et al, 2012; Reese, Slone, Soares, & Sprang, 2012) 14
  • 15. Video Telehealth (VT) Clinical Outcome Data VT = In-persona VT ≥ In-personb Depression Anxiety Disorders Eating Disorders Anger Physical Health Problems Smoking Cessation Child Problems Substance Abuse Disorder 15 Table 2. aNo significant between group differences found; Backhaus et al., 2012; Gros et al., 2013; bNelson, Barnard, & Cain, 2003; Bouchard et al., 2004; Choi et al., 2014;
  • 16. Video Telehealth (VT): General Empirical Findings  VT works  Literature to support efficacy of VT - Heterogeneous groups - Diverse range of problems  Some literature does not support VT - Individual differences - Nature of the disorder? (Backhaus et al., 2012; Gros et al., 2013) 16
  • 17. Video Telehealth: VA and DoD 17  Driving force of video telehealth  Ongoing and completed RCTs  Preliminary evidence supports VT  VT comparable to in-person therapy  Majority of VT is facility-to-facility (Gros et al., 2013)
  • 18. Video Telehealth: Recent VA RCT  Telemedicine Outreach for PTSD (TOP)  11 outpatient units serving rural veterans  Cognitive processing therapy (CPT) > Usual care 18 (Fortney et al., 2014)
  • 19. Video Telehealth: Research Gaps 19  Influence of demographics  More non-inferiority trials needed  Majority of research on PTSD  Need research on process variables (Backhaus et al., 2012; Gros et al., 2013)
  • 20. Video Telehealth: Additional Considerations  Technology  Ongoing support  Training  Room set-up  Protocol development 20 (Jarvis-Selinger et al., 2008)
  • 21. Virtual Worlds (VW)  Immersive, 3D environments1  Individualized representations - “avatars” 1  Research nascent  Preliminary pilot – social anxiety disorder2  Future directions3 21 1(Pridmore & Phillips-Wren, 2011) 2(Yuen, Herbert, Forman, Goetter, Comer, & Bradley, 2013) 3(Morie, Haynes, & Chance, 2011; Riva, Wiederhold, Mantovani & Gaggioli, 2011)
  • 22. Emerging Technologies  Holographic Projection1  Telepresence systems seamlessly approximate a “true-to-life” workspace2 – Eye gaze tracking – Life-sized imaging – Visual continuity 22 1(Stefan & David, 2013) 2(O’Hara, Kjeldskov, & Paay, 2011)
  • 23. Synchronous Technology: Additional Considerations  Technical Requirements1 – Facility with delivery – Resolution, bandwidth, disconnection  Interpersonal and Individual Factors2 – Therapeutic relationship – Client preferences – What works for whom? 1(Gros et al., 2013; Jarvis-Selinger et al., 2008) 2(Cavanagh & Millings, 2013; DeLucia, Harold, & Tang, 2013; Sucala, Schnur, Constantino, Miller, Brackman, & Mongomery, 2012) 23
  • 24. Poll Question #1 Do you use synchronous telehealth with your patients? 24
  • 25.  Web  Mobile apps  Emerging technologies 25 Evidence Base Asynchronous Technologies
  • 26. General Research Findings 26 (Lawlor & Kirakowski, 2014; Mohr, Burns, Schueller, Clarke, & Klinkman, 2013; Richards & Richardson, 2012)
  • 27. Poll Question #2 Do you use websites with your patients? 27
  • 28. General Research Findings 28 (Bush, Skopp, Smolenski, Crumpton, & Fairall, 2013; Donker, Petrie, Proudfoot, Clarke, Birch, & Christensen, 2013; Gaggioli, & Riva, 2013; Seko, Kidd, & Wiljer, 2013)
  • 29. App Marketplace Research 29 (Aguirre, McCoy, & Roan, 2013; Juarascio, Manasse, Goldstein, Forman, & Butryn, 2014)
  • 30. The Paid-App Fallacy 30 (Boudreaux, Waring, Hayes, Sadasivam, Mullen, & Pagoto, 2014; West, Hall, Hanson, Barnes, Giraud-Carrier, & Barrett, 2012)
  • 31. Poll Question #3 Do you use mobile apps with your patients? 31
  • 32. More Research Needed 32 (Ben-Zeev, Schueller, Begale, Duffecy, Kane, & Mohr, 2014)
  • 34. T2 Research 34 (Bush, et al., 2013a; Bush, et al., 2014a; Bush, et al., 2013b; Luxton, et al., 2014)
  • 35. Poll Question #4 Have you used T2 mobile apps or websites? 35
  • 36. Conclusion In conclusion, during this webinar we:  Described a theoretical perspective useful in the conceptualization and application of technology-based interventions for clinical practice  Differentiated between the concepts of synchronous and asynchronous technologies with respect to behavioral health interventions  Examined the current status of literature on technologically supported behavioral health interventions  Assessed potential gaps and recognized future trends in using behavioral health technology tools in clinical care 36
  • 37. References Aguirre, R. T. P., McCoy, M. K., & Roan, M. (2013). Development guidelines from a study of suicide prevention mobile applications (apps). Journal of Technology in Human Services, 31(3), 269- 293. Backhaus, A., Agha, Z., Maglione, M.L., Repp, A. Ross, B.,…et al., Thorp, S.R. (2012). Videoconferencing Psychotherapy: A systematic review. Psychological Services, 9, 111-131. Bee, P.E., Bower, P. Lovell, K., Gilbody, S., Richards, D., Gask, L., & Roach, P. (2008). Psychotherapy mediated by remote communication technologies: A meta-analytic review. BioMed Central Psychiatry, 8, 60. Ben-Zeev, D., Schueller, S. M., Begale, M., Duffecy, J., Kane, J. M., & Mohr, D. C. (2014). Strategies for mHealth research: Lessons from 3 mobile intervention studies. Administration and Policy in Mental Health and Mental Health Services Research, Advance online publication. 37
  • 38. References Brenes, G.A., Ingram, C.W., & Danhauer, S.C. (2011). Benefits and challenges of conducting psychotherapy by telephone. Professional Psychology: Research and Practice, 42, 543-549. Bouchard, S., Paquin, B., Payeur, R., Allard, M., Rivard,V., Fournier, T.,…Lapierre, J. (2004). Delivering cognitive-behavior therapy for panic disorder with agoraphobia in videoconference. Telemedicine Journal and e-health, 10, 13-25. Boudreaux, E. D., Waring, M. E., Hayes, R. B., Sadasivam, R. S., Mullen, S., & Pagoto, S. (2014). Evaluating and selecting mobile health apps: Strategies for healthcare providers and healthcare organizations. Translational Behavioral Medicine, Advanced online publication 38
  • 39. References Bush, N. E., Dobscha, S. K., Crumpton, R., Denneson, L. M., Hoffman, J. E., Crain, A., ... & Kinn, J. T. (2014a). A virtual hope box smartphone app as an accessory to therapy: Proof‐of‐concept in a clinical sample of veterans. Suicide and Life-Threatening Behavior, Advanced online publication. Bush, N. E., Ouelette, G., & Kinn, J. (2014b). Utility of the T2 Mood Tracker mobile application among Army Warrior Transition Unit service members. Military Medicine, In press. Bush, N. E., Prins, A., Laraway , S., O’Brien, K., Ruzek, J., & Ciulla, R. (2013a). A pilot evaluation of the afterdeployment.org online posttraumatic stress workshop for military service members and veterans. Psychological Trauma: Theory, Research, Practice, and Policy, Advance online publication. Bush, N. E., Skopp, N. A., Smolenski, D., Crumpton, R., & Fairall, J. (2013b). Behavioral screening measures delivered with a smartphone ‘app’: Psychometric properties and user preference. Journal of Nervous and Mental Disease, 201(11), 991-995. 39
  • 40. References Castonguay, L.G., Constantino, M.J., & Holtforth, M.G. (2006). The working alliance: Where we are and where should we go? Psychotherapy, 43, 271-279. Carlson, L.E., Lounsberry, J.J., Maciejewski, O., Wright, K., Collacutt, V., & Taenzer, P. (2012). Telehealth-delivered group smoking cessation for rual and urban participants: Feasibility and cessation rates. Addictive Behaviors, 27, 108-114. Cavanagh, K., & Millings, A. (2013). (Inter) personal computing: The role of the therapeutic relationship in e-mental health. Journal Contemporary Psychotherapy, 4, 197-206. Choi, N.G., Marti, C.N., Bruce, M.L., Hegel, M.T., Wilson, M.A., & Kunik, M.E. (2014). Six-month postintervention for depression and disability outcome of in-home telehealth problem-solving therapy for depressed, low-income homebound older adults. Depression and Anxiety, 31, 653-661. Comer, J.S., Furr, J.M., Cooper-Vince, C.E., Kerns, C.E., Chan, P.T., Edson, A.L., …et al., Freeman, J.B. (2013). Internet-delivered, family-based treatment for early onset OCD: A preliminary case series. Journal of Clinical Child & Adolescent Psychology, 43, 74-87. 40
  • 41. References DeLucia, P., Harold, S.A., & Tang, Y. (2013). Innovation in Technology-aided psychotherapy through human factors/ergonomics: Toward a collaborative approach. Journal of Contemporary Psychotherapy, 43, 253-260. Dennis, A.R., Fuller, R.M., & Valacich, J.S. (2008). Media, tasks, and communication processes: A theory of media synchronicity. MIS Quarterly, 32, 575-600. Donker, T., Petrie, K., Proudfoot, J., Clarke, J., Birch, M. R., & Christensen, H. (2013). Smartphones for smarter delivery of mental health programs: A systematic review. Journal of Medical Internet Research, 15(11), e247. 41
  • 42. References Eakin, E.G., Lawler, S.P., Vandelanotte, C., & Owen, N. (2007). Telephone interventions for physical activity and dietary behavior change: A systematic review. American Journal of Preventive Medicine, 32, 419-434. Fortney, J.C., Pyne, J.M., Kimbrell, T.A., Hudson, T.J., Robinson, D.E., Schneider, R., Moore, W.M, …et al., Schnurr, P.P. (2014). Telemedicine-based collaborative care for posttraumatic stress disorder: a randomized clinical trial. JAMA Psychiatry. Epub ahead of print. Gaggioli, A., & Riva, G. (2013). From mobile mental health to mobile wellbeing: Opportunities and challenges. Studies in Health Technology and Informatics, 184, 141-147. Gros, D.F., Morland, L.A., Greene, C.J., Acierno, R., Strachan, M., Egede, L.E., …et al., Frueh, B.C. (2013). Delivery of evidence-based psychotherapy via video telehealth. Journal of Psychopathology and Behavioral Assessment, 35, 506-521. 42
  • 43. References Hatcher, R.L., Barends, A., Hansell, J., & Gutfreund, M.J. (1995). Patients’ and therapists’ shared and unique views of the therapeutic alliance: An investigation using confirmatory factor analysis in a nested design. Journal Consulting and Clinical Psychology, 63, 636-643. Himle, M.B., Freitag, M., Walther, M., Franklin, S.A., Ely, L., & Woods, D.W. (2012). A randomized pilot trial comparing video conference versus face-to-face delivery of behavior therapy for childhood tic disorders, 50, 565-570. Jarvis-Selinger, S., Chan, E., Payne, R., Polhman, L.L.M., & Kendall, H. (2008). Clinical telehealth across the disciplines: Lessons learned. Telemedicine and e-Health, 14, 720-725. Juarascio, A. S., Manasse, S. M., Goldstein, S. P., Forman, E. M., & Butryn, M. L. (2014). Review of smartphone applications for the treatment of eating disorders. European Eating Disorders Review, Advanced online publication. Lawlor, A., & Kirakowski, J. (2014). Online support groups for mental health: A space for challenging43
  • 44. References Lenaerts, E., Mathei, C., Matthys, F., Zeeuws, D., Pas, L., Anderson, P., & Aertgeerts, B. (2014). Continuing care for patients with alcohol use disorders: A systematic review. Drug and Alcohol Dependence, 135, 9-21. Lovell, K., Cox, D., Haddock, G., Jones, C., Raines, D., Garvey, R., Roberts, C., & Hadley, S. (2006). Telephone administered cognitive behaviour therapy for treatment of obessive compulsive disorder: randomized controlled non-inferiority trial. British Medical Journal, 333, 883-886. Luxton, D. D., Hansen, R. N., & Stanfill, K. (2014). Mobile app self-care versus in-office care for stress reduction: A cost-minimization analysis. Journal of Telemedicine and Telecare, Advanced online publication. 44
  • 45. References Mohr, D. C., Burns, M. N., Schueller, S. M., Clarke, G., & Klinkman, M. (2013). Behavioral intervention technologies: Evidence review and recommendations for future research in mental health. General Hospital Psychiatry, 35(4), 332-338. Mohr, D.C., Vella, L., Hart, S., Heckman, T., & Simon, G. (2008). The effect of telephone-administered psychotherapy on symptoms of depression and attrition: A meta-analysis. Clinical Psychology: Science and Practice, 15, 243-253. Morie, J.G., Haynes, E., & Chance, E. (2011). Warriors’ journey: A path to healing through narrative exploration. International Journal of Disability and Human Development, 10, 17-23. Nelson, E.L., Barnard, M., & Cain, S. (2003). Treating childhood depression over videoconferencing. Telemedicine Journal ande-Health, 9, 49-55. Norcross, J.C. (2011). Psychotherapy Relationships that Work: Evidence-Based Responsiveness. 2nd 45
  • 46. References Pridmore, J., & Phillips-Wren, G. (2011). Assessing decision making quality in face-to-face teams versus virtual teams in a virtual world. Journal of Decision Systems, 3, 283-308. Reese, R.J., Slone, N.C., Soares, N., & Sprang, R. (2012). Telehealth for underserved families: An evidence-based parenting program. Psychological Services, 9, 320-322. Richards, D., & Richardson, T. (2012). Computer-based psychological treatments for depression: A systematic review and meta-analysis. Clinical Psychology Review, 32(4), 329-342. Riva, G., Wiederhold, B.K., Mantovani, F., & Gaggioli, A. (2011). Interreality: The experiential use of technology in the treatment of obesity. Clinical Practice and Epidemiology in Mental Health, 7, 51-61. Seko, Y., Kidd, S., & Wiljer, D. (2013). Apps for those who help themselves: Mobile self-guided interventions for adolescent mental health. Selected Papers Of Internet Research, 3. Retrieved from http://spir.aoir.org/index.php/spir/article/view/833 46
  • 47. References Simek, E.M., McPhate, L., & Haines, T.P. (2012). Adherence to and efficacy of home exercise programs to prevent falls: A systematic review and meta-analysis of the impact of exercise program characteristics. Preventive Medicine: An International Journal Devoted to Practice and Theory, 55, 262-275. Stefan, S., & David, D. (2013). Face-to-face counseling versus high definition holographic projection system. Efficacy and therapeutic alliance. A brief report. Journal of Cognitive and Behavioral Psychotherapies, 13, 299-307. Sucala, M., Schnur, J. B., Constantino, M. J., Miller, S. J., Brackman, E. H., Montgomery, G.H. (2012). The therapeutic relationship in E-therapy for mental health: A systematic review. Journal of Medical Internet Research, 14:e110 West, J. H., Hall, P. C., Hanson, C. L., Barnes, M. D., Giraud-Carrier, C., & Barrett, J. (2012). There’s an app for that: Content analysis of paid health and fitness apps. Journal of Medical Internet 47
  • 48. References vanVelthoven, M.H.M.T., Car, L.R., Car, J., & Atun, R. (2012). Telephone consultation for improving health of people living with or at risk of HIV: A systematic review. PLoSONE, 7, e36105-e36105 Villanti, A.C., McKay, H.S., Abrams, D.B., Holtgrave, D.R., Bowie, J.V. (2010). Smoking-cessation interventions for U.S. young adults: A systematic review. American Journal of Preventive Medicine, 39, 564-574. Yuen, E.K., Herbert, J.D., Forman, E.M., Goetter, E.M., Comer, R., & Bradley, J. (2013). Treatment of social anxiety disorder using online virtual environments in second life. Behavior Therapy, 44, 51-61. 48
  • 49. Nancy A. Skopp, Ph.D. 49  Dr. Nancy Skopp is a Research Psychologist and Program Manager in the Research, Outcomes and Investigations Division at the National Center for Telehealth & Technology (T2), U.S. Department of Defense.  She is also an Affiliate Associate Professor at the University of Washington’s Department of Psychiatry & Behavioral Sciences.  She is a Clinical Psychologist currently licensed in the states of Texas and Washington.  She holds doctoral and master’s degrees in Clinical Psychology from the University of Houston. Nancy Skopp, Ph.D.
  • 50. Janyce “Jae” Osenbach, Ph.D. 50 Jae Osenbach, Ph.D.  Dr. Jae Osenbach is a Research Psychologist and Psychometrician in the Mobile Health Program at the National Center for Telehealth & Technology (T2), U.S. Department of Defense.  She serves as a subject matter expert on mobile apps and websites related to issues involving military and veteran psychological health and traumatic brain injury.  She is also the lead for the Mobile Health Program’s evaluations, surveys and assessments, and serious games for behavioral health.  She holds a doctoral degree in Psychometrics and Quantitative Psychology and a master’s degree in Psychology from Fordham University.
  • 51. Jae Osenbach, Ph.D. janyce.e.osenbach.ctr@mail.mil 51 Nancy A. Skopp, Ph.D. nancy.a.skopp.civ@mail.mil http://t2health.dcoe.mil/
  • 52. DCoE Contact Info DCoE Outreach Center 1-866-966-1020 (toll-free) http://www.dcoe.mil/ resources@dcoeoutreach.org 5252

Editor's Notes

  1. Hello and welcome! Thanks so much for participating in this Webinar. I am very pleased to be here and to have this opportunity to share empirical findings technology-based behavioral health modalities. We’ll be discussing theory to inform the selection of technology-based behavioral health tools and treatment modalities as and empirical findings on clinical practice and “white space” technologies. I would like to introduce some key concepts we will be discussing today as you see displayed here MST synchronous and asynchronous technologies
  2. The various behavioral health technologies we will be discussing are grouped within synchronous and asynchronous communication categories. Many of you may already be familiar with these concepts, very simply… The former denotes communication between parties that occurs in real time (i.e.,video telehealth, telephone) The latter denotes communication between parties that does not occur at the same time (i.e., mobile app, websites).
  3. MST is currently a leading theoretical model to guide selection of technology-based communication modalities (Dennis et al. 2008) MST proposes that communication – which undergirds all bx health tech, can be broken into two basic processes: conveyance and convergence. The convergence process is the process of mutually agreeing on the meaning of the information (or failing) to agree). requires fewer cognitive resources because most of the information has already been conveyed and incorporated into the participants’ mental models Convergence is enhanced by media high in synchronicity such as video telehealth because it allows for more give and take between therapist and patient to arrive at mutual understanding The conveyance process is the transmission of new information and the processing of that information by the receiver to create or modify his/her mental representation Conveyance is maximized by media that are asynchronous Requires cognitive resources to read, understand, and integrate the information into a mental model Extending this model to technology facilitated behavioral health interventions, the white space between sessions corresponds to conveyance or the processing of novel information by the patient and the treatment sessions correspond to convergence in that the patient and therapist are processing the meaning of the information and putting it into context.
  4. Moreover, MST can be useful in guiding the selection of modality for technologically-based behavioral health interventions. The basic premise here is to match the media to the relevant communication process that you wish to support Conveyance denotes the transmission of information to an individual for individual level processing. Patients can benefit from mobile apps in the “white space” They can process information at their own pace reach an individual level of understanding that they can carry back into the session with their providers Convergence denotes more complex process of interpersonal information processing in the moment Synchronous media support the development of shared understanding between individuals During the therapy sessions, the convergence of shared meaning is achieved as patient and therapist process information together in real time. Moreover, asynchronous and synchronous technologies support two different communication functions that together support the success in the delivery of treatment and ultimately treatment outcomes. Conveyance and convergence processes will be performed at differing leveling and intensities depending on how familiar the participants are with the task, selected technology, and each other. Hence, additional factors influence successful treatment delivery and outcomes. Therapeutic alliance Technology that is functioning properly and well thought out Training for providers and patients to ensure proper execution
  5. In this next section, I will review the empirical base on the technologies displayed here.
  6. Many may not immediately think of telephone mediated interventions in a discussion of technology based behavior health, however there is actually a fairly substantial empirical base on such interventions. Telephone interventions are associated with a number of benefits and in certain instances may be offer significant advantages over other technologies For the purposes of this presentation, I will use the term “telephone intervention” This blanket term covers both therapy that is wholly mediated via telephone as well as interventions that may contain an “extended telephone support” component or those in which the telephone support is provided in a form that does not constitute therapy per se such as case management
  7. Telephone interventions have been applied to a broad range of behavior health problems including depression, anxiety, smoking cessation, and others Telephone therapy can help overcome barriers to treatment and deliver efficacious treatment A major obstacle in the delivery of MH services is the lack of availability of empirically supported treatments, particularly in rural areas (Mitchell et al. 2008) Provides assess to patients who might not otherwise be served They also noted that the LITERATURE IS HETEROGENEOUS ACROSS USES, TYPE OF TREATMENT, ETC. METHODOLOGICAL SHORTCOMINGS CALL FOR MORE RIGOROUS TRIALS
  8. Most of the work has been conducted on Depression (Mohr et al. 2008) Bee and colleagues (2008) conducted a systematic meta-analytic review of psychotherapy mediated by remote technologies The pooled effect size for depression intervention across 7 studies was .44 (medium) Majority constrasted against ususal care Mohr et al., 2008 did meta-analysis of telephone mediated psychotherapy (12 trials; 8= CBT) Pre-to post ES = .81, comparable to in-person depression treatment Mean attrition was 7.6% across all studies vs. 46.9% drop-out from Face-to-face psychotherapy (Wierzbicki & Pakarik, 1993) Choi et al. (2014) –3- arm study for depressed, home-bound older adults; Participants with telephone support experienced some symptom reductions between baseline and 12 weeks, owing to caring social interactions because these were socially isolated older adults. However, the continued decline in their depressive symptoms between 12 and 36 weeks is surprising Brenes et al. (2011) RCT of GAD for the elderly (over 60) telephone CBT vs. supportive therapy Declines several indices ES’s .61 - .85 Patients reported high satisfaction Attrition was only 8.3% Swinson (1995) ES = 0.98 for Telephone BT for agoraphobia –RURAL Primary Care patients – WLC Lovell et al. (2006) – Telephone vs. In-person – randomized controlled non-inferiority trial – Exposure/RP treatments found to be equivalent w/ high patient satisfaction of note, telephone calls were 50% shorter duration (30 minute sessions) N=72 Villanti et al., 2010 Systematic review found promising smoking cessation interventions were brief with extended telephone support and electronic media Lenaerts et al., 2014 Systematic review of continuing care for patients with alcohol use disorders by for alcohol -- more data needed – recommend telephone follow-up with a specialized nurse and calls initiated at pre-defined times by the patients themselves. van Velthoven et al., 2012 –Systematic Review of Telephone Consultation for Improving Health of People with or at risk for HIV Van Velthoven conducted systematic review of the effectiveness of telephone consultation for HIV/AIDS Giving telephone or in-person option of HIV test results vs in-person at the clinic; results given via telephone can increase the number of persons receiving their results and help support HIV-positive smoking Inconsistent findings for improving treatment adherence and MH outcomes Systematic Review of Telephone Interventions for Physical Activity and Dietary Behavior Change (Eakin et al., 2007) Solid evidence base support the efficacy of these behavior change interventions in which the telephone is the principal intervention method Average effect size was .60 (moderate) – 20/26 studies showed positive bx change Positive results were reported in: 69% of physical activity studies 83% of the dietary behavior studies 75% of interventions containing both components Length of intervention (6-12 Months) and number of calls (≥ 12) associated with positive outcomes Physical activity and dietary behavior changes key to prevention and management of chronic diseases
  9. Next let’s focus on video teleheath, VT studies, in general involve: video monitor with mounted video camera and telecommunication connection set up in MH clinic in local and remote sites Many of the pros of video telehealth overlap with telephone interventions with the added benefit of visual cues but increased possibility of technology dysfunction and increased training and technical support requirements, and costs
  10. Backhaus and colleagues recently conducted a systematic review of peer-reviewed articles to comprehensively examine many facets of psychotherapy delivered video telehealth CBT was the most common therapy type 45%; about 25% were categorized as “eclectic, various, or undefined” 3 (7%) studies examined family therapy -remaining were a psychoanalysis, biofeedback, Eye Movement Desensitization and Reprocessing (EMDR), Problem Solving, Coping Skills for PTSD and a few others. Populations largely civilian; 60% male At least one standardized measure with well-accepted psychometrics was reported by 29 (69%) of the empirical studies – SCID & BDI most commmon FEASIBILITY -Positive contributions include: reductions in travel burdens and costs, reduced intervention costs, increased accessto care for rural, underserved, or geographically isolated populations
  11. Backhaus et al. 2012 reviewed 47 empirical studies; Gros et al., 2013 reviewed the literature on Evidence-Based Psychotherapy Comer et al., 2013; Participants in the preliminary case series 5 children between the ages of 4 and 8 showed OCD symptom improvements and global severity improvements 60% no longer met diagnostic criteria for OCD at posttreatment. No participants got worse, all mothers characterized the quality of services received as ‘‘excellent.’’ Reese et al., 2012; small pilot Evidence-based parenting ADHD (decrease in parent stress; -.34 and child bx problems; -1.23)
  12. “DIFFERENCES REPORTED FOR VT AND IN-PERSON WERE GENERALLY SMALL AND NOT CONSISTENT ACROSS STUDIES, MEASURES, AND DISORDERS.” At least 3 of studies showed that VT was superior to in-person Choi et al., (2014) 3-arm RCT of depression among 158 older, low-income home-bound adults – Problem Solving Therapy (PST) VT and in-person were both efficacious Effects of VT-PST were sustained longer than in-person PST; Depression at 36 weeks ES-- VT = .68; in person=.20 Disability at 36 weeks ES – VT=.47; in-person=.25 Older adults adapted quickly to pc when saw convenience and in-person like quality; gave high ratings Could, in part, account for the differences Longer and more distractions during in-home sessions – perhaps VT appears more professional Bouchard et al. 2004 PD study 21 participants; VT was not randomly assigned – based on geographic location. Both groups - significant pre to post treatment improvement in panic, anxiety, depression, and impairment. VT should greater reduction in panic frequency than in person; no randomization & small sample size. Nelson et al., 2003 - RCT for childhood depression with 28 children aged 8-14 were randomized to 8 weekly sessions of CBT for MDD; VT vs in-person from the same facility; both groups had significant pre to post tx symptom reduction Remission rate = 82% across the total sample. VT group showed significantly faster decline in depressive symptoms compared to the in-person group. No differences in attrition or session attendance. VT group reported high satisfaction, in spite of occasional technology glitches Hypotheses about higher response for VT: 1. Novel, made patients feel “special” and this maximized tx; chance variation – this findings was not consistent across outcome measures. PTSD has received the most attention PTSD – more research needed – finding are mixed; 3 exposure studies showed larger effect sizes for in the in-person treatment conditions These findings contrast with non-exposure based tx that demonstrate similar outcomes across treatment conditions (Morland et al. 2010; 2011; Cognitive Processing Therapy -CPT). Specific treatment techniques unique to exposure therapy and potentially less effective via VT? Eating disorders – several studies of varying quality – overall support for Mitchell et al. 2008; RCT for bulimia (N = 128); pre to post reductions in binge eating, purging and depression; however in-person showed significantly less binge eating, purging than VT; Weekly weigh in was not done; could help explain, also technical and logistical problems at remote cite …MORE RESEARCH IS NEEDED. Anger Management – Moreland et al. 2010 RCT with 125 veterans Group CBT for anger in PTSD patients no differences were found for anger, PTSD or process variables therapeutic alliance significantly higher for in-person condition Physical Health Problems – Chronic pain, cancer, obesity (non-randomized control), epilepsy (only in-perosn RCT) – all positive results in terms of psychiatric sx reduction; no significant differences for epilepsy study- both group improved Child problems- Depression (Nelson et al., 2003) Childhood tic disorder (Himle et al. 2012) Addictive Behaviors – initial support for the use of technology to deliver limited individual and group treatments for addictive behaviors. Potential benefit of confidentiality for VT; interesting that there were positive findings; tx of addiction calls for drug screening, breathalyzers and management of intoxication; MORE RESEARCH IS NEEDED for SEVERE substance use and how to incorporate safety and assessment procedures.
  13. Overall, the future of video Telehealth in psychotherapy and clinical practice looks bright, particularly for the dissemination and implementation in EBPs in underserved areas and populations. Findings for anxiety disorders suggest that VT is a viable tx option, especially when in person-tx may be difficult (Gros et al., 2013) ADDITIONAL RESEARCH IS NEEDED ON SPECIFIC TREATMENT PRACTICES THAT MAY BE DIFFICULT TO COMPLET VIA VT, ESPCIALLY DX WHERE GROUP DIFFERENCES WERE FOUND (I.E., IMAGINAL EXPOSURE, IN-SESSION WEIGHING FOR EATING DISORDERS)
  14. Ongoing studies at the VA with non-inferiority designs and large sample sizes ~200 patients in the studies VT vs in-person RCT BA for depression in older veterans VA and exposure for active and retired SMs with PTSD PE for veterans with PTSD Group CPT for veterans with PTSD
  15. Fortney et al., 2014 - treatment resistant veterans Results TOP intervention increased engagement in CPT – TOP had 18x greater odds of initiating CPT 8x greater odds of completing at least 8 sessions Attending at least 8 sessions fully mediated effect of the TOP intervention Step beyond examining the difference between in-person vs. VT Goal was to examine the effectiveness of a collaborative care model to improve access and engagement in pharmacotherapy and psychotherapy among rural veterans Compared to usual care at VA community based distant VA and VA Community Based Outpatient clinics – Veterans had access to CPT and other tx TOP = menu of services to increase engagement – e.g., case mgr, pharmacist (telephone)- telepsychologist delivered CPT No symptom improvement among UC group!
  16. Age, gender, racial/ethnic differences Bulk of existing studies have relied on superiority designs Better understanding of potential differences or lack thereof can be obtained w/ non-inferiority designs Non-inferiority design is especially suited for VT research can determine if a novel intervention does not significantly differ from a standard intervention(Greene et al., 2008) pre-specified margin Gros et al. 2013 LIMITATIONS FOR VT Of 26 studies only 9 were RCTs Many studies small n More research is needed on nearly most dx As clinical outcomes have been shown to be roughly consistent across VT and in-person, more research is needed to understand which VT practices may be more beneficial than in-person practices Process variables: attrition, adherence, satisfaction and expectancy
  17. Provider of VT need to coordinate setup and maintenance with second treatment site or patients (home-based)(Gros et al., 2013); Training for therapist and patient AV settings should be inspected prior to each session and a backup procedures should be in place if technologies fail (e.g., phone), Patient orientation; providers need contact information for ER services in patient’s locality prior to first appt Orientation sessions that review operation of equipment, troubleshooting (e.g., checking connections to power supply, Internet) Room Set-up: lighting and monitor & chair placement in such a way the intervention does not appear to be dominated by one party or overly distant (Mitchell et al., 2008) Development of protocols –
  18. Users create an avatar navigate through an 3-D virtual environment where they do activities and interact with other avatars A number of studies on VW for distance education VW for behavioral health treatments in infancy Yuen et al., (2013) did pilot of Acceptance Based Behavior Therapy (ABBT) for social anxiety disorder - 12 weekly 1/hour sessions (n=14) VW Exposure -Practiced interacting with confederates at a bar; giving speeches Acceptability = 93% patients (very, mostly) Providers 100% Decreased avoidance – 86% agreed Therapists “Fairly feasible” – tech probs 14% dropout rate ES for social anxiety measures d=1.14 to 1.50 80% of people with social anxiety dx don’t get tx – Barriers – stigma, fear of negative eval Limitations Could not see each others faces – therapists could not read facial and body lang./patients expressed discomfort not seeing therapis Not clear if exposure in VW translates well outside session Riva et al., (2009) examined VW for obesity with a fast food worker Learning area (food mgt, stress mgt, food choice edu, etc.) Community area meet patients with same problem Practice area – controlled exposure in critical situations
  19. Stefan & David (2013): in-person Rational Emotive Therapy vs. VT with Holopodium (eonReality.com) – therapist is a hologram RCT with 56 students Outcome = distress and irrational beliefs, and therapeutic alliance – no significant differences found Telepresence provides the experience of being assembled in the same physical space. Telepresence systems approximate a “true-to-life” quality by minimizing spatial distortions (e.g., disparities in orientation) to create “shared geometries”
  20. Technical Underscore importance of training How to troubleshoot problems Interpersonal & Individual Factors Empirical evidence supports that strong therapeutic alliance is possible with VT (DeLucia et al., 2013) Design/implementation of video-conferencing technologies can affect communication, collaboration, trust – so potentially therapeutic rel. More research needed (Sucala et al., 2012) – systematic review 840 studies, only 11 examined; 6 as prinicipal objective Client preferences – consideration of stigma, comfort with tech, communication style Different dx may differentially respond to VT - more research needed
  21. Web is prolific, large number of randomized controlled trials (or RCTs) Huge body of evidence for clinical and white spaces High effect sizes (how effective the study was) Many at 0.5 or greater, fairly large effect Efficacy across a broad range of mental health outcomes Depression to schizophrenia, no rock unturned One concerning finding: unmoderated support groups – exacerbated symptoms Those with exacerbated symptoms use forums, or forums increasing symptoms
  22. Not a lot of research out there Dozen good RCTs No research on the use of apps in the white space All use in clinical space Quite a few listed in process on clinicaltrials.gov Effective for symptom management Effect sizes between .3 to .5, so moderate to large Privacy is a big issue for users Most apps used device’s GPS, or location recording, system Majority of apps do not encrypt data Most important finding so far – symptom assessments are psychometrically valid Found in both paper-and-pencil and computer-delivered comparisons
  23. Not a lot of RCTs, quite a few studies of app marketplaces Most mental health apps are on the iOS, which is Apple, or Android, which is Google, platforms Concerning disconnect of mental health app development Highest quality on iOS Most users have Android Majority of apps focused on depression, anxiety, or stress Not much out there on smoking cessation or sleep Many apps are not high-quality Less than one-fifth have evidence-based principles Most lack citations or references – leaves user on their own Most concerning 20 eating disorder apps, only 3 are evidence based (less than 15%) 27 suicide prevention, less than half include crisis hotline
  24. Paid-App fallacy Users assume expensive apps are better quality Want a good game? 99 cents! Not a “big name?” = no user confidence Best evidence-based apps are free Challenge for app developers, like T2
  25. Need more research on apps! Majority focused on feasibility and usability Need more RCTs Minimize the risk of bias Determine efficacy Problem = speed of technology RCT designs and grant applications take too long 3 year study now = obsolete app Component testing with small samples Not very popular Not all-inclusive Solution = speed up RCT process! Cover more areas of mental health
  26. Future of devices Movement towards mobile-Web, or device-responsive design Integration between apps and biometric trackers, like fitbit Apple Watch – “chunks” User doesn’t differentiate between apps and Web Huge gap for research Super exciting!
  27. Here at T2 = over 50 studies on our products Everything developed from evidence-based practices Frequently consult subject matter experts during design A few of the studies we have going on: RCT on telephone counseling for mild traumatic brain injury RCT on in-home depression treatment using video conferencing Reduced PTSD symptoms using AfterDeployment PTSD workbook Military Kids Connect website best for tweens, ages 9 to 13 Dr. Nigel Bush’s research on Virtual Hope Box app Users preferred the app to a physical hope box T2 Mood Tracker was used with the Warrior Transition Battalion 3 week period – used every other day Breathe2Relax – cost-offset at 700 users