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Benefit StepCoach: A study to understand the working alliance of a virtual/human coach with the user.

The study focuses on eHealth, or more specifically, the comparison between guided (human-supported) and unguided (self-help) digital eHealth interventions. Previous research has shown that when comparing the effectiveness of guided versus unguided eHealth interventions the results are inconsistent (Joiner, Nam & Whittemore, 2017; Kelders, Bohlmeijer, Pots & van Gemert-Pijnen, 2015). A possible underlying mechanism for the observed differences between studies could be the experienced working alliance by the patient, which is the relationship between a healthcare professional and client (Bordin, 1979). It consists of agreement on tasks and goals, and the bond between the two. Patient reported working alliance has previously been shown to predict effectiveness and adherence in both face-to-face settings (Goldberg, Davis & Hoyt, 2013; Martin, Garske & Davis, 2000) and digital settings.(Sucala et al., 2012). However, it remains unclear how the experienced working alliance develops within unguided digital eHealth interventions.

We expect that eHealth users experience a different working alliance with a human coach (guided eHealth) compared to a virtual coach (unguided eHealth). This is due to two different mechanisms: Firstly, pre-existing perceptions about the coach could affect the expected working alliance. Many patients indicate to prefer human contact over automated feedback (e.g. Smith et al., 2017), which we predict is due to lower expectancies of the “bond” with a virtual coach compared to a human coach. Studies show that the perception of interacting with a human being or computer (the label) only can affect social responses towards the interaction partner, even when the content of the interaction is equal (Aharoni & Fridlund, 2007, Appel et al., 2012). However, despite their expectations, people act socially towards technology and can form relationships with them (Reeves & Nass, 1996). Users are able to develop a working alliance with a virtual coach (Clarke et al., 2016), and do this more easily when the virtual coach shows human behaviour (Bickmore, Gruber & Picard, 2005). Therefore our second prediction is that using human cues during the intervention (such as humor, empathy and self-disclosure) will lead to a higher working alliance with the coach.

Previous studies have tested the main effects of the label and the use of human cues on working alliance, but the interaction of the two has not been tested before. Furthermore, previous studies have only used a short interaction to test such effects, while it is important to engage in a more long-term interaction. Lastly, there are no results on how working alliance affects adherence to and effectiveness of digital eHealth interventions.

The research goals are:

1. How does the label of the type of coach (human vs. virtual) influence the working alliance between the user and the human/virtual coach?
2. Does the use of human cues increase the working alliance between the user and the human/virtual coach?
3. Does a better working alliance between user and human/virtual coach lead to a higher level of adherence?
4. Does a better working alliance between user and human/virtual coach lead to a higher level of effectiveness?

The study is implemented with the help of the open source intervention platform, MobileCoach.

Related work

Aharoni, E., & Fridlund, A. J. (2007). Social reactions toward people vs. computers: How mere lables shape interactions. Computers in human behavior, 23(5), 2175-2189.
Appel, J., von der Pütten, A., Krämer, N. C., & Gratch, J. (2012). Does humanity matter? Analyzing the importance of social cues and perceived agency of a computer system for the emergence of social reactions during human-computer interaction. Advances in Human-Computer Interaction, 2012, 13.
Bickmore, T., Gruber, A., & Picard, R. (2005). Establishing the computer–patient working alliance in automated health behavior change interventions. Patient education and counseling, 59(1), 21-30.
Bordin, E. S. (1979). The generalizability of the psychoanalytic concept of the working alliance. Psychotherapy: Theory, research & practice, 16(3), 252.
Brandt, C. J., Clemensen, J., Nielsen, J. B., & Søndergaard, J. (2018). Drivers for successful long-term lifestyle change, the role of e-health: a qualitative interview study. BMJ open, 8(3), e017466.
Clarke, J., Proudfoot, J., Whitton, A., Birch, M. R., Boyd, M., Parker, G., Manicavasagar, V., Hadzi-Pavlovic, D., & Fogarty, A. (2016). Therapeutic alliance with a fully automated mobile phone and web-based intervention: secondary analysis of a randomized controlled trial. JMIR mental health, 3(1), e10.
Goldberg, S. B., Davis, J. M., & Hoyt, W. T. (2013). The role of therapeutic alliance in mindfulness interventions: Therapeutic alliance in mindfulness training for smokers. Journal of clinical psychology, 69(9), 936-950.
Joiner, K. L., Nam, S., & Whittemore, R. (2017). Lifestyle interventions based on the diabetes prevention program delivered via eHealth: A systematic review and meta-analysis. Preventive medicine, 100, 194-207.
Kelders, S. M., Bohlmeijer, E. T., Pots, W. T., & van Gemert-Pijnen, J. E. (2015). Comparing human and automated support for depression: Fractional factorial randomized controlled trial. Behaviour research and therapy, 72, 72-80.
Martin, D. J., Garske, J. P., & Davis, M. K. (2000). Relation of the therapeutic alliance with outcome and other variables: a meta-analytic review. Journal of consulting and clinical psychology, 68(3), 438.
Reeves, B., & Nass, C. I. (1996). The media equation: How people treat computers, television, and new media like real people and places. Cambridge university press.
Smith, E., Bradbury, K., Scott, L., Steele, M., Little, P., & Yardley, L. (2017). Providing online weight management in Primary Care: a mixed methods process evaluation of healthcare practitioners’ experiences of using and supporting patients using POWeR+. Implementation Science, 12(1), 69.
Sucala, M., Schnur, J. B., Constantino, M. J., Miller, S. J., Brackman, E. H., gomery, G. H. (2012). The therapeutic relationship in e-therapy for mental health: a systematic review. Journal of medical Internet research, 14(4), e110.

CDHI Research Team

Prabhakaran Santhanam, Sascha Gfeller, Prof. Dr. Elgar Fleisch & Prof. Dr. Tobias Kowatsch


Talia Cohen RodriguesDavid de Buisonjé, Phd Candidates, Universiteit Leiden