"It's hard to argue with a computer": Investigating Psychotherapists' Attitudes towards Automated Evaluation

ABSTRACT

We present CORE-MI, an automated evaluation and assessment system that provides feedback to mental health counselors on the quality of their care. CORE-MI is the first system of its kind for psychotherapy, and an early example of applied machine-learning in a human service context. In this paper, we describe the CORE-MI system and report on a qualitative evaluation with 21 counselors and trainees. We discuss the applicability of CORE-MI to clinical practice and explore user perceptions of surveillance, workplace misuse, and notions of objectivity, and system reliability that may apply to automated evaluation systems generally.

References

1. Atkins, D.C., Steyvers, M., Imel, Z.E. and Smyth, P. 2014. Scaling up the evaluation of psychotherapy: evaluating motivational interviewing fidelity via statistical text classification. Implementation Science. 9, 1 (Dec. 2014).
2. Baer, J.S., Wells, E.A., Rosengren, D.B., Hartzler, B., Beadnell, B. and Dunn, C. 2009. Agency context and tailored training in technology transfer: A pilot evaluation of motivational interviewing training for community counselors. Journal of Substance Abuse Treatment. 37, 2 (Sep. 2009), 191--202.
3. Bagroy, S., Kumaraguru, P. and De Choudhury, M. 2017. A Social Media Based Index of Mental WellBeing in College Campuses. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (2017), 1634--1646.
4. Bardram, J.E., Frost, M., Szántó, K., Faurholt-Jepsen, M., Vinberg, M. and Kessing, L.V. 2013. Designing mobile health technology for bipolar disorder: a field trial of the monarca system. CHI '13 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (2013), 2627.
5. Boyatzis, R.E. 1998. Transforming qualitative information: thematic analysis and code development. Sage Publications.
6. Caliskan, A., Bryson, J.J. and Narayanan, A. 2017. Semantics derived automatically from language corpora contain human-like biases. Science. 356, 6334 (Apr. 2017), 183--186.
7. Can, D., Atkins, D.C. and Narayanan, S.S. 2015. A dialog act tagging approach to behavioral coding: a case study of addiction counseling conversations. INTERSPEECH (2015).
8. Can, D., Georgiou, P.G., Atkins, D.C. and Narayanan, S.S. 2012. A case study. Detecting counselor reflections in psychotherapy for addictions using linguistic features. 2251--2254.
9. Can, D., Marín, R.A., Georgiou, P.G., Imel, Z.E., Atkins, D.C. and Narayanan, S.S. 2016. "It sounds like...": A natural language processing approach to detecting counselor reflections in motivational interviewing. Journal of Counseling Psychology. 63, 3 (2016), 343--350.
10. Chang, K., Chan, M.K. and Canny, J. 2011. AnalyzeThis: unobtrusive mental health monitoring by voice. CHI EA '11 CHI '11 Extended Abstracts on Human Factors in Computing Systems (2011), 1951.
11. Charmaz, K. 2006. Constructing grounded theory. Sage Publications.
12. Christensen, H., Griffiths, K., Groves, C. and Korten, A. 2006. Free range users and one hit wonders: community users of an Internet-based cognitive behaviour therapy program. Australian and New Zealand Journal of Psychiatry. 40, 1 (Jan. 2006), 59-- 62.
13. Coyle, D., Doherty, G. and Sharry, J. 2010. PlayWrite: end-user adaptable games to support adolescent mental health. CHI EA '10 CHI '10 Extended Abstracts on Human Factors in Computing Systems (2010), 3889.
14. D. Can, J. Gibson, C. Vaz, P. G. Georgiou and S. S. Narayanan 2014. Barista: A framework for concurrent speech processing by USC-SAIL. 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014): Florence, Italy, 4 9 May 2014 (Piscataway, NJ, May 2014), 3306--3310.
15. De Choudhury, M., Kiciman, E., Dredze, M., Coppersmith, G. and Kumar, M. 2016. Discovering Shifts to Suicidal Ideation from Mental Health Content in Social Media. CHI '16 Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (2016), 2098--2110.
16. Emerging Technology from the arXiv 2016. Neural Network Learns to Identify Criminals by Their Faces. MIT Technology Review.
17. Falender, C.A., Cornish, J.A.E., Goodyear, R., Hatcher, R., Kaslow, N.J., Leventhal, G., Shafranske, E., Sigmon, S.T., Stoltenberg, C. and Grus, C. 2004. Defining competencies in psychology supervision: A consensus statement. Journal of Clinical Psychology. 60, 7 (Jul. 2004), 771--785.
18. Hill, C.E. ed. 2012. Consensual qualitative research: a practical resource for investigating social science phenomena. American Psychological Association.
19. Hirsch, T., Merced, K., Narayanan, S., Imel, Z.E. and Atkins, D.C. 2017. Designing Contestability: Interaction Design, Machine Learning, and Mental Health. ACM Conference on Designing Interactive Systems (DIS'17) (2017), 95--99.
20. Höök, K. 2000. Steps to take before intelligent user interfaces become real. Interacting with Computers. 12, 4 (Feb. 2000), 409--426.
21. Höök, K., Karlgren, J., Wærn, A., Dahlbäck, N., Gustaf Jansson, C., Karlgren, K. and Lemaire, B. 1996. A glass box approach to adaptive hypermedia. User Modeling and User-Adapted Interaction. 6, 2--3 (Jul. 1996), 157--184.
22. Imel, Z.E., Baldwin, S.A., Baer, J.S., Hartzler, B., Dunn, C., Rosengren, D.B. and Atkins, D.C. 2014. Evaluating therapist adherence in motivational interviewing by comparing performance with standardized and real patients. Journal of Consulting and Clinical Psychology. 82, 3 (Jun. 2014), 472--481.
23. Imel, Z.E., Steyvers, M. and Atkins, D.C. 2015. Computational psychotherapy research: Scaling up the evaluation of patient--provider interactions. Psychotherapy. 52, 1 (2015), 19--30.
24. James Gibson, Geoff Gray, Tad Hirsch, Zac E. Imel, Shrikanth Narayanan and David C. Atkins 2016. Developing an Automated Report Card for Addiction Counseling: The Counselor Observer Ratings Expert for MI (CORE-MI). (San Jose, CA, 2016).
25. Jamison-Powell, S., Linehan, C., Daley, L., Garbett, A. and Lawson, S. 2012. "I can't get no sleep": discussing #insomnia on twitter. CHI '12 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (2012), 1501.
26. Johansson, R. and Andersson, G. 2012. Internet-based psychological treatments for depression. Expert Review of Neurotherapeutics. 12, 7 (Jul. 2012), 861-- 870.
27. Kenny, P., Parsons, T.D., Gratch, J. and Rizzo, A.A. 2008. Evaluation of Justina: A Virtual Patient with PTSD. Intelligent Virtual Agents. H. Prendinger, J. Lester, and M. Ishizuka, eds. Springer Berlin Heidelberg. 394--408.
28. Lambert, M.J. ed. 2013. Bergin and Garfield's handbook of psychotherapy and behavior change. John Wiley & Sons.
29. Lederman, R., Wadley, G., Gleeson, J., Bendall, S. and Álvarez-Jiménez, M. 2014. Moderated online social therapy: Designing and evaluating technology for mental health. ACM Transactions on ComputerHuman Interaction. 21, 1 (Feb. 2014), 1--26.
30. Li, J. 2014. Examining the impact of game interventions on depression among older adults. CHI PLAY '14 Proceedings of the first ACM SIGCHI annual symposium on Computer-human interaction in play (2014), 291--294.
31. Lord, S.P., Can, D., Yi, M., Marin, R., Dunn, C.W., Imel, Z.E., Georgiou, P., Narayanan, S., Steyvers, M. and Atkins, D.C. 2015. Advancing methods for reliably assessing motivational interviewing fidelity using the motivational interviewing skills code. Journal of Substance Abuse Treatment. 49, (Feb. 2015), 50--57.
32. Lundahl, B. and Burke, B.L. 2009. The effectiveness and applicability of motivational interviewing: a practice-friendly review of four meta-analyses. Journal of Clinical Psychology. 65, 11 (Nov. 2009), 1232--1245.
33. Manikonda, L. and De Choudhury, M. 2017. Modeling and Understanding Visual Attributes of Mental Health Disclosures in Social Media. CHI '17 Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (2017), 170--181.
34. Matthews, M. and Doherty, G. 2011. In the mood: engaging teenagers in psychotherapy using mobile phones. CHI '11 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (2011), 2947.
35. Miller, W. and Rollnick, S. 2012. Motivational Interviewing. Guilford.
36. Miller, W.R., Moyers, T.B., Ernst, D. and Amrhein, P. 2008. Manual for the Motivational Interviewing Skill Code (MISC), Version 2.1. University of New Mexico Center on Alcoholism, Substance Use, and Addictions.
37. Moyers, T.B., Martin, T., Manuel, J.K., Miller, W.R. and Ernst, D. 2010. Revised Global Scales: Motivational Interviewing Treatment Integrity 3.1.1 (MITI 3.1.1). University of New Mexico Center on Alcoholism, Substance Abuse and Addictions (CASAA).
38. Pace, B., Tanana, M., Xiao, B., Dembe, A., S Ba, C., Soma, C., Steyvers, M., Narayanan, S., Atkins, D. and Imel, Z. 2016. What About the Words? Natural Language Processing in Psychotherapy.
39. Rennick-Egglestone, S., Knowles, S., Toms, G., Bee, P., Lovell, K. and Bower, P. 2016. Health Technologies "In the Wild": Experiences of Engagement with Computerised CBT. CHI '16 Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (2016), 2124--2135.
40. Schwalbe, C.S., Oh, H.Y. and Zweben, A. 2014. Sustaining motivational interviewing: a meta-analysis of training studies. Addiction (Abingdon, England). 109, 8 (Aug. 2014), 1287--1294.
41. Simm, W., Ferrario, M.A., Gradinar, A., Tavares Smith, M., Forshaw, S., Smith, I. and Whittle, J. 2016. Anxiety and Autism: Towards Personalized Digital Health. CHI '16 Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (2016), 1270--1281.
42. Simms, D.C., O'Donnell, S. and Molyneaux, H. 2009. The Use of Virtual Reality in the Treatment of Posttraumatic Stress Disorder (PTSD). Virtual and Mixed Reality. R. Shumaker, ed. Springer Berlin Heidelberg. 615--624.
43. Stumpf, S., Rajaram, V., Li, L., Burnett, M., Dietterich, T., Sullivan, E., Drummond, R. and Herlocker, J. 2007. Toward harnessing user feedback for machine learning. (2007), 82.
44. Sweeney, L. 2013. Discrimination in Online Ad Delivery. Queue. 11, 3 (Mar. 2013), 10.
45. Tanana, M., Hallgren, K.A., Imel, Z.E., Atkins, D.C. and Srikumar, V. 2016. A Comparison of Natural Language Processing Methods for Automated Coding of Motivational Interviewing. Journal of Substance Abuse Treatment. 65, (2016), 43--50.
46. Tracey, T.J.G., Wampold, B.E., Lichtenberg, J.W. and Goodyear, R.K. 2014. Expertise in psychotherapy: an elusive goal? The American Psychologist. 69, 3 (Apr. 2014), 218--229.
47. Treatment Episode Data Set (TEDS): Substance Abuse Treatment Admissions by Primary Substance of Abuse, According to Sex, Age Group, Race, and Ethnicity among admissions aged 12 and older Year = 2015, UNITED STATES: 2015. https://wwwdasis.samhsa.gov/webt/quicklink/US15.ht m.
48. Wehbe, R.R., Watson, D.K., Tondello, G.F., Ganaba, M., Stocco, M., Lee, A. and Nacke, L.E. 2016. ABOVE WATER: An Educational Game for Anxiety. CHI PLAY Companion '16 Proceedings of the 2016 Annual Symposium on Computer-Human Interaction in Play Companion Extended Abstracts (2016), 79--84.
49. Whiteford, H.A., Degenhardt, L., Rehm, J., Baxter, A.J., Ferrari, A.J., Erskine, H.E., Charlson, F.J., Norman, R.E., Flaxman, A.D., Johns, N., Burstein, R., Murray, C.J. and Vos, T. 2013. Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010. The Lancet. 382, 9904 (Nov. 2013), 1575--1586.
50. Wrzesien, M., Burkhardt, J.-M., Alcañiz Raya, M. and Botella, C. 2011. Mixing psychology and HCI in evaluation of augmented reality mental health technology. CHI EA '11 CHI '11 Extended Abstracts on Human Factors in Computing Systems (2011), 2119.
51. Xiao, B., Imel, Z.E., Georgiou, P.G., Atkins, D.C. and Narayanan, S.S. 2015. "Rate My Therapist": Automated Detection of Empathy in Drug and Alcohol Counseling via Speech and Language Processing. PLOS ONE. 10, 12 (Dec. 2015), e0143055.
52. Yang, Q., Zimmerman, J., Steinfeld, A., Carey, L. and Antaki, J.F. 2016. Investigating the Heart Pump Implant Decision Process: Opportunities for Decision Support Tools to Help. (2016), 4477--4488.

Index Terms

• Human-centered computing