Agents of change: Understanding the therapeutic processes associated with the helpfulness of therapy for mental health problems with relational agent MYLO

Hannah Gaffney, Warren Mansell, Sara Tai, Hannah Gaffney, Warren Mansell, Sara Tai

Abstract

Objective: To understand the therapeutic processes associated with the helpfulness of an online relational agent intervention, Manage Your Life Online (MYLO).

Methods: Fifteen participants experiencing a mental health related problem used Manage Your Life Online for 2 weeks. At follow-up, the participants each identified two helpful and two unhelpful questions posed by Manage Your Life Online within a single intervention session. Qualitative interviews were conducted and analyzed using thematic and content analysis to gain insight into the process of therapy with Manage Your Life Online.

Results: MYLO appeared acceptable to participants with a range of presenting problems. Questions enabling free expression, increased awareness, and new insights were key to a helpful intervention. The findings were consistent with the core processes of therapeutic change, according to Perceptual Control Theory, a unifying theory of psychological distress. Questions that elicited intense emotions, were repetitive, confusing, or inappropriate were identified as unhelpful and were associated with disengagement or loss of faith in Manage Your Life Online.

Conclusions: The findings provide insight into the likely core therapy processes experienced as helpful or hindering and outlines further ways to optimize acceptability of Manage Your Life Online.

Keywords: Mental health; artificial intelligence; computer-assisted; conversational agent; psychotherapeutic processes; psychotherapy; relational agent; therapy.

© The Author(s) 2020.

Figures

Figure 1.
Figure 1.
MYLO conversation screen example.
Figure 2.
Figure 2.
Illustration of the two-level hierarchical structure of data, split by questions identified as helpful and unhelpful.
Figure 3.
Figure 3.
Recruitment flow diagram.
Figure 4.
Figure 4.
Boxplot of scores on all variables by unhelpful and helpful questions.
Figure 5.
Figure 5.
Thematic map of participants’ reasons for choosing a question as being particularly helpful.
Figure 6.
Figure 6.
Thematic map of participants’ reasons for choosing a question as being particularly unhelpful.

References

    1. McManus S, Bebbington P, Jenkins R, Brugha T. (eds). Mental Health and Wellbeing in England: Adult Psychiatric Morbidity Survey 2014. Leeds: NHS Digital; 2016.
    1. Kessler RC, Aguilar-Gaxiola S, Alonso J, Chatterji S, Lee S, Ormel J, et al. The global burden of mental disorders: An update from the WHO World Mental Health (WMH) surveys. Epidemiol Psichiatr Soc 2009; 18: 23–33.
    1. Rethink Mental Illness. Right treatment, right time, (2018, accessed 18 December 2019).
    1. Bennion MR, Hardy G, Moore RK, Millings A. E-therapies in England for stress, anxiety or depression: what is being used in the NHS? A survey of mental health services. BMJ Open 2017; 7: e014844.
    1. NHS. The NHS long term plan, (2019, accessed 18 December 2019).
    1. NHS England. Five Year Forward View for Mental Health: One Year on. 2017: 31pp, (accessed 18 December 2019).
    1. Gilbody S, Brabyn S, Lovell K, Kessler D, Devlin T, Smith L, et al. Telephone-supported computerised cognitive-behavioural therapy: REEACT-2 large-scale pragmatic randomised controlled trial. Br J Psychiatry 2017; 210: 362–367.
    1. Duarte A, Walker S, Littlewood E, Brabyn S, Hewitt C, Gilbody S, et al. Cost-effectiveness of computerized cognitive-behavioural therapy for the treatment of depression in primary care: findings from the Randomised Evaluation of the Effectiveness and Acceptability of Computerised Therapy (REEACT) trial. Psychol Med 2017; 47: 1825–1835.
    1. Knowles SE, Toms G, Sanders C, Bee P, Lovell K, Rennick-Egglestone S, et al. Qualitative meta-synthesis of user experience of computerised therapy for depression and anxiety. PLoS One 2014; 9.
    1. Marzano L, Bardill A, Fields B, Herd K, Veale D, Grey N, et al. The application of mHealth to mental health: Opportunities and challenges. The Lancet Psychiatry 2015; 2: 942–948.
    1. Bohannon J. The synthetic therapist. Science (80-) 2015; 349: 250–251.
    1. Bickmore T, Gruber A. Relational agents in clinical psychiatry. Harv Rev Psychiatry 2010; 18: 119–130.
    1. Hoermann S, McCabe KL, Milne DN, Calvo RA. Application of synchronous text-based dialogue systems in mental health interventions: Systematic review. J Med Internet Res 2017; 19: 267.
    1. Scholten MR, Kelders SM, Van Gemert-Pijnen JE. Self-guided Web-based interventions: Scoping review on user needs and the potential of embodied conversational agents to address them. Journal of Medical Internet Research. 2017; 19: e383.
    1. Provoost S, Lau HM, Ruwaard J, Riper H. Embodied conversational agents in clinical psychology: A scoping review. J Med Internet Res 2017; 19: 1–23.
    1. Luxton DD. An Introduction to artificial intelligence in behavioral and mental health care. In: Luxton D (ed) Artifical intelligence in behavioural and mental health care San Diego, USA: Academic Press, 2016, pp. 1–26.
    1. National Institute for Health and Care Excellence. Evidence Standards Framework for Digital Health Technologies. 2018; 1–29. (2018, accessed 18 December 2019).
    1. Torous J, Roberts LW. Needed innovation in digital health and smartphone applications for mental health transparency and trust. JAMA Psychiatry 2017; 74: 437–438.
    1. Hofmann SG, Hayes SC. The future of intervention science: Process-based therapy. Clin Psychol Sci 2019; 7: 37–50.
    1. Torous J, Levin ME, Ahern DK, Oser ML. Cognitive behavioral mobile applications: Clinical studies, marketplace overview, and research agenda. Cogn Behav Pract 2017; 24: 215–225.
    1. Hollis C, Sampson S, Simons L, Davies EB, Churchill R, Betton V, et al. Identifying research priorities for digital technology in mental health care: Results of the James Lind Alliance Priority Setting Partnership. The Lancet Psychiatry 2018; 5: 845--854.
    1. Timulak L, McElvaney R. Qualitative meta-analysis of insight events in psychotherapy. Couns Psychol Q 2013; 26: 131–150.
    1. Timulak L. Significant events in psychotherapy: An update of research findings. Psychol Psychother Theory, Res Pract 2010; 83: 421–47.
    1. Swift JK, Tompkins KA, Parkin SR. Understanding the client’s perspective of helpful and hindering events in psychotherapy sessions: A micro-process approach. J Clin Psychol 2017; 73: 1543–1555.
    1. Kazdin AE. Mediators and mechanisms of change in psychotherapy research. Annu Rev Clin Psychol 2007; 3: 1--27.
    1. Barlow DH, Farchione TJ, Bullis JR, Gallagher MW, Murray-Latin H, Sauer-Zavala S, et al. The unified protocol for transdiagnostic treatment of Emotional Disorders compared with diagnosis-specific protocols for anxiety disorders: A randomized clinical trial. JAMA Psychiatry 2017; 74: 875–884.
    1. Newby JM, Mewton L, Andrews G. Transdiagnostic versus disorder-specific internet-delivered cognitive behaviour therapy for anxiety and depression in primary care. J Anxiety Disord 2017; 46: 25–34.
    1. Lamers F, Van Oppen P, Comijs HC, Smit JH, Spinhoven P, Van Balkom AJLM, et al. Comorbidity patterns of anxiety and depressive disorders in a large cohort study: The Netherlands Study of Depression and Anxiety (NESDA). J Clin Psychiatry 2011; 72: 342–348.
    1. Carey TA, Mullan RJ. Evaluating the method of levels. Couns Psychol Q 2008; 21: 247–256.
    1. Powers W. Behavior: The control of perception. Chicago: Aldine publishing co, 1973.
    1. Carey T. The method of levels: How to do psychotherapy without getting in the way. Hayward, USA: Living Control Systems Publishing, 2006, p. 380.
    1. Gaffney H, Mansell W, Edwards R, Wright J. Manage Your Life Online (MYLO): A pilot trial of a conversational computer-based intervention for problem solving in a student sample. Behav Cogn Psychother 2014; 42: 731–746.
    1. Bird T, Mansell W, Wright J, Gaffney H, Tai S. Manage Your Life Online: A web-based randomized controlled trial evaluating the effectiveness of a problem-solving intervention in a student sample. Behav Cogn Psychother 2018; 46: 1–13.
    1. Yardley L, Morrison L, Bradbury K, Muller I. The person-based approach to intervention development: Application to digital health-related behavior change interventions. J Med Internet Res. 2015; 17: e30.
    1. Horvath AO, Del Re AC, Flückiger C, Symonds D. Alliance in individual psychotherapy. Psychotherapy 2011; 48: 9–16.
    1. Barak A, Klein B, Proudfoot JG. Defining internet-supported therapeutic interventions. Annals of Behavioral Medicine 2009; 38: 4–17.
    1. Cocklin A, Tai S, Mansell W. Client perceptions of helpfulness in therapy: A novel video-rating methodology for examining process variables at brief intervals during a single session. Behav Cogn Psychother 2017; 45: 647–660.
    1. Duncan BL, Miller SD, Sparks JA, Claud DA, Beach P, Reynolds LR, et al. The session rating scale: Preliminary psychometric properties of a “working” alliance measure. J Br Ther 2003; 3: 3–12.
    1. Higginson S, Mansell W. What is the mechanism of psychological change? A qualitative analysis of six individuals who experienced personal change and recovery. Psychol Psychother Theory, Res Pract 2008; 81: 309–328.
    1. Higginson S. Reorganisation of conflict Master’s degree Dissertation. University of Manchester, UK, 2007.
    1. Morris L. Examination of the effectiveness and acceptability of a transdiagnostic group for clients with common mental health problems Doctoral Thesis. University of Manchester, UK, 2016.
    1. Kroenke K, Spitzer RL, Williams JBW. The PHQ-9: Validity of a brief depression severity measure. J Gen Intern Med 2001; 16: 606–613.
    1. Spitzer RL, Kroenke K, Williams JBW, Lo B. A brief measure for assessing generalized anxiety disorder. JAMA Intern Med 2006; 166: 1092–1097.
    1. Shepherd M, Matthews V, Ashworth M, Christey J, Wright K, Godfrey E, et al. A client-generated psychometric instrument: The development of ‘PSYCHLOPS.’ Couns Psychother Res 2006; 4: 27--31.
    1. Ashworth M, Robinson S, Godfrey E, Shepherd M, Evans C, Parmentier H, et al. Measuring mental health outcomes in primary care: The psychometric properties of a new patient-generated outcome measure, “PSYCHLOPS” (‘psychological outcome profiles’). Prim Care Ment Heal 2005; 3: 261--270.
    1. StataCorp. Stata Statistical Software: Release 15. College Station: StataCorp LLC, 2017.
    1. Faul F, Erdfelder E, Lang E-G, Buchner A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 2007; 2: 175–191.
    1. Seltman HJ. Chapter 15 mixed models. In: experimental design and analysis, 2015, pp. 357–378. (accessed 18 December 2019).
    1. Mooney CZ, Duval RD. Bootstrapping: A nonparametric approach to statistical inference California, USA: SAGE, 1993, p. 73.
    1. Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol 2006; 3: 77--101.
    1. Elo S, Kyngäs H. The qualitative content analysis process. J Adv Nurs 2008; 62: 107–115.
    1. Vaismoradi M, Turunen H, Bondas T. Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study. Nurs Heal Sci 2013; 15: 398–405.
    1. Swift JK, Callahan JL, Cooper M, Parkin SR. The impact of accommodating client preference in psychotherapy: A meta-analysis. J Clin Psychol 2018; 74: 1924–1937.
    1. Leys C, Ley C, Klein O, Bernard P, Licata L. Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median. J Exp Soc Psychol 2013; 49: 764–766.
    1. Altman D. Practical statistics for medical research. London: Chapman and Hall, 1991.
    1. Fitzpatrick KK, Darcy A, Vierhile M. Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): A randomized controlled trial. JMIR Ment Heal 2017; 4: e19.
    1. Fulmer R, Joerin A, Gentile B, Lakerink L, Rauws M. Using psychological artificial intelligence (Tess) to relieve symptoms of depression and anxiety: A randomized controlled trial. JMIR Ment Health 2018; 5: e64.
    1. Gaffney H, Mansell W, Tai S. Conversational agents in the treatment of mental health problems: Mixed-method systematic review. JMIR Ment Heal 2019; 6: e14166.
    1. Ring L, Shi L, Totzke K, Bickmore T. Social support agents for older adults: Longitudinal affective computing in the home. J multimodal user interfaces 2015; 9: 79–88.
    1. Ly KH, Ly AM, Andersson G. A fully automated conversational agent for promoting mental well-being: A pilot RCT using mixed methods. Internet Interv 2017; 10: 39–46.
    1. Inkster B, Sarda S, Subramanian V. An empathy-driven, conversational artificial intelligence agent (Wysa) for digital mental well-being: Real-world data evaluation mixed-methods study. JMIR mHealth uHealth 2018; 6: e12106.
    1. Carryer JR, Greenberg LS. Optimal levels of emotional arousal in experiential therapy of depression. J Consult Clin Psychol 2010; 78: 190–199.
    1. Scott MJ. Improving Access to Psychological Therapies (IAPT) - The need for radical reform. J Health Psychol 2018; 23: 1136–1147.
    1. Snijders TAB, Bosker RJ. Standard errors and sample sizes for two-level research. J Educ Stat 2008; 18: 237–259.
    1. Wisniewski H, Henson P, Keshavan M, Hollis C, Torous J. Digital mental health apps and the therapeutic alliance: Initial review. BJPsych Open 2019; 5: 1–5.
    1. Schnur JB, Montgomery GH, Miller SJ, Sucala M, Brackman EH, Constantino MJ. The therapeutic relationship in E-Therapy for mental health: A systematic review. J Med Internet Res. 2012; 14: e110.
    1. Shieh YY, Fouladi RT. The effect of multicollinearity on multilevel modeling parameter estimates and standard errors. Educ Psychol Meas 2003; 63: 951–985.
    1. Carey TA, Kelly RE, Mansell W, Tai SJ. What’s therapeutic about the therapeutic relationship? A hypothesis for practice informed by Perceptual Control Theory. Cogn Behav Ther 2012; 5: 47–59.
    1. Griffiths R, Mansell W, Carey TA, Edge D, Emsley R, Tai SJ. Method of levels therapy for first-episode psychosis: rationale, design and baseline data for the feasibility randomised controlled Next Level study. BJPsych Open 2018; 4: 339–45.
    1. Chorpita BF. Commentary: Metaknowledge is power: Envisioning models to address unmet mental health needs: reflections on Kazdin (2019). J Child Psychol Psychiatry 2019; 60: 473–6.
    1. Kazdin AE. Annual research review: Expanding mental health services through novel models of intervention delivery. J Child Psychol Psychiatry 2019; 4: 455–472.
    1. Campion J, Knapp M. The economic case for improved coverage of public mental health interventions. The Lancet Psychiatry 2018; 5: 103–105.

Source: PubMed

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