Observing therapist-patient interactions to predict dropout from psychotherapy

Over about the last 50 years, clinical research has proven without a doubt that psychotherapy significantly alleviates the symptoms of a wide range of mental illnesses, for example, depression, anxiety, post-traumatic stress disorder, eating disorders, and addictions (Lutz et al., 2021a). However, psychotherapy can only unfold its effects when the patient receives an adequate “dose” (Nordomo et al., 2021), meaning enough sessions to sufficiently facilitate change in thinking patterns, unhealthy behavior, emotion regulation etc. However, large reviews of clinical studies have shown that on average 20% of psychotherapy patients drop out of treatment prematurely (Swift et al., 2017). These patients typically show persistent symptoms and impairment in daily life and tend to keep making use of the health care system even though they are more dissatisfied with treatment (Björk et al., 2009; Cahill et al., 2003; Carpender et al., 1979).

Why do patients drop out?

This question has been quite difficult to answer, as patients who drop out of treatments are logically rarely available to be interviewed as to why they stopped coming. To date, the research points to a variety of different factors:

1) Patient characteristics: Patients who are younger, have less education, and eating or personality disorders seem more likely to dropout (Swift & Greenberg, 2012).

2) Treatment progress: Patients may drop out, because they don’t think therapy is working, or in contrast, because they feel that they have reached a “good enough level” of improvement (Roe et al., 2006; Zimmermann et al., 2017).

3) Organizational issues: Patients may want to continue treatment, but have trouble attending because of work or childcare obligations, for example (Bados et al., 2007; Eurelings-Bontekoe et al., 2009).

4) Therapist characteristics: Therapists vary greatly in their dropout rates (1-73%), suggesting that not all therapists are equally capable of creating a bond with patients and motivating them to complete treatment (Saxon et al., 2017; Sharf et al., 2010; Zimmermann et al., 2017).

What can we do about it?

In order to reduce dropout rates and increase treatment success, we have to recognize who is at a greater risk of quitting treatment prematurely before they do so to be able to react accordingly. However, therapists’ subjective perceptions of their own capabilities and their patients’ progress have been shown to be biased. Therapists tend to be overly optimistic and underestimate negative developments, which can be counteracted by using feedback systems (Lambert et al., 2018). Therefore, efforts have been made to empirically predict incoming patients’ dropout risk by comparing their intake characteristics (sociodemographic and clinical data) with large datasets of patients who have already been treated (and subsequently dropped out or not; Lutz et al., 2021b). While this approach brings us a step closer to recognizing at-risk patients, it ignores the role of the therapist and the individual interactions between therapist and patient that likely also contribute to dropout.

Capturing therapist-patient interactions

In the referenced article, the Inventory of Therapeutic Interventions and Skills (Boyle et al., 2020), a video rating inventory, was applied to assess therapists’ interactions with patients (e.g., how they implemented interventions with patients and how they communicated, showed empathy etc.) in an early session of psychotherapy. The Inventory also provides context to the therapist’s behavior by assessing treatment difficulty and patient motivation. We found that the inclusion of these observation-based variables improved the accuracy of dropout predictions in comparison to the consideration of patient characteristics at the beginning of treatment alone. Specifically, the more difficult an observer rated the treatment with a patient, the significantly higher the likelihood of dropout at a later point. Further, when therapists were observed using fewer cognitive techniques and spending more time providing summaries and asking for patients’ feedback, patients were more likely to quit treatment early.

Reference Article

Poster, K., Bennemann, B., Hofmann, S. G., & Lutz, W. (2021). Therapist interventions and skills as predictors of dropout in outpatient psychotherapy. Behavior Therapy. Advance online publication. https://doi.org/10.1016/j.beth.2021.05.001

Discussion Questions

  1. How would you use the information that a patient you just started treating is at a higher-than-average risk of dropping out of treatment?
  2. Do you think it might be helpful to share and discuss such a prediction with the patient? Why or why not?
  3. How could a supervisor support a therapist who shows a higher-than-average dropout rate in their caseload?

About the Authors

Kaitlyn Poster, PhD conducted research on the assessment of treatment integrity and its associations with psychotherapy outcome, mechanisms of change, and dropout during her doctorate at the Department of Clinical Psychology and Psychotherapy at the University of Trier, Germany. She now works as a licensed clinical psychologist at an interdisciplinary outpatient clinic and in psychotherapy training.

Björn Bennemann, MSc is a fourth year PhD Student at the Department of Clinical Psychology and Psychotherapy at the University of Trier, Germany. His research focuses on the comparison and application of machine learning techniques to predict dropout from psychotherapy early in treatment.

Wolfgang Lutz, PhD is a Professor of Clinical Psychology and Psychotherapy at the University of Trier, Germany. He is the head of the University of Trier’s Psychotherapy Research and Training Clinic and President Elect of the Society for Psychotherapy Research. His research focuses on psychotherapy outcome prediction, the empirically-based personalization of psychotherapy, and the implementation of digital feedback and clinical support systems.

Stefan Hofmann, PhD is a Professor of Clinical Psychology and the director of the Psychotherapy and Emotion Research Laboratory at Boston University. He also holds the Alexander von Humboldt professorship at the University of Marburg, Germany. His research focuses on the psychopathology of social phobia, mechanisms of change in the treatment of anxiety disorders, the translation of neuroscience into clinical techniques and the development of process-based psychotherapy.

References Cited

Bados, A., Balaguer, G., & Saldaña, C. (2007). The efficacy of cognitive–behavioral therapy and the problem of drop‐out. Journal of clinical psychology, 63(6), 585-592. https://doi.org/10.1002/jclp.20368

Björk, T., Björck, C., Clinton, D., Sohlberg, S., & Norring, C. (2009). What happened to the ones who dropped out? Outcome in eating disorder patients who complete or prematurely terminate treatment. European Eating Disorders Review: The Journal of the Eating Disorders Association, 17(2), 109–119. https://doi.org/10.1002/erv.911

Boyle, K., Deisenhofer, A.-K., Rubel, J. A., Bennemann, B., Weinmann-Lutz, B, & Lutz, W. (2020). Assessing treatment integrity in personalized CBT: the inventory of therapeutic interventions and skills. Cognitive Behaviour Therapy 49(3), 210-227. https://doi.org/10.1080/16506073.2019.1625945

Cahill, J., Barkham, M., Hardy, G., Rees, A., Shapiro, D. A., Stiles, W. B., & Macaskill, N. (2003). Outcomes of patients completing and not completing cognitive therapy for depression. British Journal of Clinical Psychology, 42(2), 133–143. https://doi.org/10.1348/014466503321903553

Carpenter, P. J., Del Gaudio, A. C., & Morrow, G. R. (1979). Dropouts and terminators from a community mental health center: Their use of other psychiatric services. Psychiatric Quarterly, 51(4), 271–279.

Eurelings-Bontekoe, E. H., van Dam, A., Luyten, P., Verhulst, W. A., Van Tilburg, C. A., de Heus, P., & Koelen, J. (2009). Structural personality organization as assessed with theory driven profile interpretation of the Dutch short form of the MMPI predicts dropout and treatment response in brief cognitive behavioral group therapy for axis I disorders. Journal of personality Assessment, 91(5), 439-452. https://doi.org/10.1080/00223890903087927

Lambert, M. J., Whipple, J. L., & Kleinstäuber, M. (2018). Collecting and delivering progress feedback: A meta-analysis of routine outcome monitoring. Psychotherapy, 55(4), 520. https://doi.org/10.1037/pst0000167

Lutz, W., de Jong, K., Rubel, J., & Delgadillo, J. (2021). Measuring, Predicting and Tracking Change in Psychotherapy. In M. Barkham, W. Lutz, & L. G. Castonguay (Eds.), Bergin and Garfield’s Handbook of Psychotherapy and Behavior Change (7th ed., pp. 89-133). Wiley.

Lutz, W., Deisenhofer, A.-K., Rubel, J., Bennemann, B., Giesemann, J., Poster, K., & Schwartz, B. (2021). Prospective evaluation of clinical decision support system in psychological therapy. Journal of Consulting and Clinical Psychology. https://doi.org/10.1037/ccp0000642

Nordmo, M., Monsen, J. T., Høglend, P. A., & Solbakken, O. A. (2021). Investigating the dose–response effect in open-ended psychotherapy. Psychotherapy Research, 31(7), 859-869. https://doi.org/10.1080/10503307.2020.1861359

Roe, D., Dekel, R., Harel, G., & Fennig, S. (2006). Clients’ reasons for terminating psychotherapy: A quantitative and qualitative inquiry. Psychology and Psychotherapy: Theory, Research and Practice, 79(4), 529-538. https://doi.org/10.1348/147608305X90412

Saxon, D., Barkham, M., Foster, A., & Parry, G. (2017). The Contribution of Therapist Effects to Patient Dropout and Deterioration in the Psychological Therapies. Clinical Psychology and Psychotherapy, 24(3), 575-588. https://doi.org/10.1002/cpp.2028

Sharf, J., Primavera, L. H., & Diener, M. J. (2010). Dropout and therapeutic alliance: A meta-analysis of adult individual psychotherapy. Psychotherapy: Theory, Research, Practice, Training, 47(4), 637-645. https://doi.org/10.1037/a0021175

Swift, J. K. & Greenberg, R. P. (2012). Premature discontinuation in adult psychotherapy: A meta-analysis. Journal of Consulting and Clinical Psychology, 80(4), 547-559. https://doi.org/10.1037/a0028226

Swift, J. K., Greenberg, R. P., Tompkins, K. A., & Parkin, S. R. (2017). Treatment refusal and premature termination in psychotherapy, pharmacotherapy, and their combination: A meta-analysis of head-to-head comparisons. Psychotherapy (Chicago, Ill-), 54(1), 47-57. https://doi.org/10.1037/pst0000104

Zimmermann, D., Rubel., J. Page, A. C., & Lutz, W. (2017). Therapist Effects on and Predictors of Non-Consensual Dropout in Psychotherapy. Clinial Psychology & Psychotherapy, 24(2), 312-321. https://doi.org/10.1002/cpp.2022

 

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