ABSTRACT
Background:
Changes during psychotherapy often include sudden symptom improvements, called sudden gains (SGs), which have been identified as being superior to gradual symptom change with regard to treatment success. This study investigates the role of therapists in initiating and/or consolidating SGs.
Methods:
The analyses are based on a sample of patients (N = 1937) who were seen by 155 therapists and received individual psychotherapy at a university outpatient clinic. First, the therapist effect (TE) on SG was investigated using multilevel modeling (MLM). Second, MLM was used to explore the relative importance of patient and therapist variability in SGs as they relate to outcome.
Results:
The TE on SGs accounted for 1.8% of variance, meaning that therapists are accountable for inter-individual differences in their patients’ likelihood to experience SGs. Furthermore, results revealed a significant effect of SGs on outcome for both levels, while therapist differences regarding the consolidation of SGs were not significant.
Conclusions:
The analyses indicated that some therapists are better in facilitating and initiating SGs. The process of triggering SGs seems to be a therapist skill or competence, which opens up an additional pathway to positive outcomes that could be used to improve clinical training.
Keywords:
Acknowledgements
We thank Dr. Kaitlyn Poster for proofreading the manuscript.
Ethical Standard
The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.
Notes
1 Percentage of missing data for the OQ-30: pre-treatment scores = .7%, post-treatment scores = 27.5%
2 Percentage of missing data for the BSI: pre-treatment scores = .5%, post-treatment scores = 27.5%
3 BIC values can be requested from the first author.
4 As Bayesian approaches can provide estimates that are more reliable when variances are small we reran the analyses using the brms package (Bürkner, Citation2017). These analyses provided slightly smaller TEs for patient outcome: HSCL-11 TE = 3.1%, OQ-30 TE = 1.1% and BSI TE = 2.2%
5 The estimated TE on SGs based on Bayesian estimations was 1.5%.
6 OQ-30: fixed slope model BIC = 3256.46, random slope model BIC = 3265.48; BSI: fixed slope model BIC = 2901.34, random slope model BIC = 2914.29.