Benchmarking and Change Mechanisms in Personality Disorder Treatment

Personality disorders (PDs) are characterized by problems with identity and interpersonal relationships and the presence of pathological personality traits (American Psychiatric Association, 2013). Personality disorders are prevalent, affecting about 6 - 9.5% of people in the community (Winsper et al., 2020) and result in increased morbidity and mortality (Grant et al., 2008). Several effective psychotherapies for PDs have been developed in the past decades. Meta-analyses of randomized controlled trials (RCTs) demonstrate that psychotherapy for PDs is efficacious and that different treatment models for PDs produce comparable effects (Budge et al., 2013; Cristea et al., 2017; Storebø et al., 2020). However, two important questions remain: (1) how effective are PD treatments outside of the controlled settings of RCTs and (2) what are the core processes that produce change in PD treatment?

First, evidence on the efficacy of PD treatment in controlled circumstances (RCTs) does not necessarily translate directly to the effectiveness of treatment as it is actually being delivered in routine clinical practice. Several studies have demonstrated the effectiveness of PD treatment in naturalistic settings (Gregory \& Sachdeva, 2016; Lowyck et al., 2015), however, these studies have not systematically compared their effects with those from published RCTs (Malmivaara, 2015). Therefore, the primary aim of the present study is to compare the effects of intensive psychodynamic therapy (PDT) for PDs in a naturalistic setting to benchmarks found in RCTs. Specifically, the primary objective of this study is to investigate the non-inferiority with a margin of d = 0.2 of intensive PDT for PDs as it is delivered in routine clinical practice compared to benchmarks from published RCTs of PDT for PDs. The benchmarks are created by meta-analytically aggregating the effects found in well-conducted RCTs following the methods proposed by Minami et al. (2008). The primary outcome is change in general symptom severity as measured by the global severity index (GSI) on the Brief Symptom Inventory (BSI) from start to end of treatment (approximately 8 months after the start of treatment).

Second, the effectiveness of intensive PDT for PD in terms of pre-post effect sizes will be investigated as well as clinical significant change (CSC) and deterioration using reliable change indices (Jacobson \& Truax, 1991) from baseline to treatment termination as well as 6-month and 1- and 2-year follow up, on the following outcomes: psychological distress (Brief Symptom Inventory; BSI), borderline personality disorder symptoms (Personality Assessment Inventory for BPD; PAI-BOR); personality functioning (Level of Personality Functioning Scale; LPFS), interpersonal functioning (Inventory of Interpersonal Problems; IIP), post-traumatic stress (Post-traumatic stress disorder Checklist for DSM-5; PCL-5), resilience (Connor-Davidson Resilience Scale; CD-RISC) and quality of life (EQ-5D).

Third, in order to ensure that existing therapies for PDs focus on the actual core processes that produce change, more research is needed to address why and how treatment for PD works (Kramer, 2018). The present study's secondary aim is therefore to investigate whether outcomes in intensive PDT are associated with a number of theoretically expected mechanisms of change. It has been argued that successful treatment for PDs fosters epistemic trust, that is, trust in communicated knowledge, which in turn allows for the re-emergence of learning from benign social influences, increasing resilience and reducing PD symptoms (Fonagy et al., 2019). Epistemic trust is thus theoretically considered a core change mechanism in all effective treatments for PD, however, no study to date has empirically tested this. The secondary objective of the present study is to investigate whether trajectories of change in epistemic trust, mistrust and credulity across treatment (as measured using the Epistemic Trust, Mistrust and Credulity Questionnaire, ETMCQ) are associated with the trajectories of symptom change across treatment (as measured using the Brief Symptom Inventory, BSI, and the Personality Assessment Inventory for borderline PD, PAI-BOR) using parallel process growth curve modeling (MacCallum et al., 1997). Mentalizing and therapeutic alliance are investigated as secondary change mechanisms to assess the relative importance of epistemic trust as a change mechanism in the treatment of PD.

This observational clinical study aims to recruit N = 110 PD patients consecutively admitted to a treatment unit that specializes in intensive PDT for PDs (Klipp, UPC KU Leuven, Belgium). Patients follow one of three programs that differ in treatment intensity: (1) inpatient treatment program (5 days a week), (2) day treatment program (4 days a week), and (3) a part-time outpatient treatment program of two half days per week. Patients attend one of these programs and stay in the program for at least 6 months (with an average duration of 8 months). For pragmatic reasons, patients are not randomized across the treatment programs. Sensitivity analyses will be performed and if appropriate given our sample size, differences in baseline characteristics and treatment effects between the programs will be investigated.

Self-report questionnaires on personality functioning, symptoms, resilience, quality of life, epistemic trust, mentalizing and the therapeutic alliance are filled out via REDCAP, an online platform, at baseline, after 3 and 6 months of treatment, at discharge, and 6-months and at 1 and 2 year follow-up. Automated invitations and reminders are sent via e-mail. Automated scoring and codebooks are implemented via REDCAP. A designated study data manager follows up participant progress and provides support. The data manager additionally logs drop-out including the reason for treatment termination and the occurrence of the following serious adverse events (SAE's): suicide attempt, life-threatening self-harm, patient death, serious injury or medical disease that requires hospitalization.

References:

American Psychiatric Association. (2013). Diagnositic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing. https://doi.org/10.1176/appi.books.9780890425596.744053

Budge, S. L., Moore, J. T., Del Re, A. C., Wampold, B. E., Baardseth, T. P., \& Nienhuis, J. B. (2013). The effectiveness of evidence-based treatments for personality disorders when comparing treatment-as-usual and bona fide treatments. Clin Psychol Rev, 33(8), 1057-1066. https://doi.org/10.1016/j.cpr.2013.08.003

Cristea, I. A., Gentili, C., Cotet, C. D., Palomba, D., Barbui, C., \& Cuijpers, P. (2017). Efficacy of Psychotherapies for Borderline Personality Disorder: A Systematic Review and Meta-analysis. Jama Psychiatry, 74(4), 319-328. https://doi.org/10.1001/jamapsychiatry.2016.4287

Fonagy, P., Luyten, P., Allison, E., \& Campbell, C. (2019). Mentalizing, Epistemic Trust and the Phenomenology of Psychotherapy. Psychopathology. https://doi.org/10.1159/000501526

Grant, B. F., Chou, S. P., Goldstein, R. B., Huang, B., Stinson, F. S., Saha, T. D., Smith, S. M., Dawson, D. A., Pulay, A. J., Pickering, R. P., \& Ruan, W. J. (2008). Prevalence, correlates, disability, and comorbidity of DSM-IV borderline personality disorder: results from the Wave 2 National Epidemiologic Survey on Alcohol and Related Conditions. Journal of Clinical Psychiatry, 69(4), 533-545. https://doi.org/10.4088/jcp.v69n0404

Gregory, R. J., \& Sachdeva, S. (2016). Naturalistic Outcomes of Evidence-Based Therapies for Borderline Personality Disorder at a Medical University Clinic. Am J Psychother, 70(2), 167-184. https://doi.org/10.1176/appi.psychotherapy.2016.70.2.167

Jacobson, N. S., \& Truax, P. (1991). Clinical significance: a statistical approach to defining meaningful change in psychotherapy research. J Consult Clin Psychol, 59(1), 12-19. https://doi.org/10.1037//0022-006x.59.1.12

Kramer, U. (2018). Mechanisms of Change in Treatments of Personality Disorders: Introduction to the Special Section. Journal of Personality Disorders, 32(Suppl), 1-11. https://doi.org/10.1521/pedi.2018.32.supp.1

Lowyck, B., Vermote, R., Verhaest, Y., Vandeneede, B., Wampers, M., Luyten, P., \& Wampers, M. (2015). Hospitalization-based psychodynamic treatment for personality disorders: A five-year follow-up. Psychoanalytic Psychology, 32, 381-402. https://doi.org/10.1037/a0038959

MacCallum, R. C., Kim, C., Malarkey, W. B., \& Kiecolt-Glaser, J. K. (1997). Studying multivariate change using multilevel models and latent curve models. Multivariate Behavioral Research, 32, 215-253. https://doi.org/10.1207/s15327906mbr3203

Malmivaara, A. (2015). Benchmarking Controlled Trial--a novel concept covering all observational effectiveness studies. Ann Med, 47(4), 332-340. https://doi.org/10.3109/07853890.2015.1027255

Storebø, O. J., Stoffers-Winterling, J. M., Völlm, B. A., Kongerslev, M. T., Mattivi, J. T., Jørgensen, M. S., Faltinsen, E., Todorovac, A., Sales, C. P., Callesen, H. E., Lieb, K., \& Simonsen, E. (2020). Psychological therapies for people with borderline personality disorder. Cochrane Database Syst Rev, 5(5), Cd012955. https://doi.org/10.1002/14651858.CD012955.pub2

Winsper, C., Bilgin, A., Thompson, A., Marwaha, S., Chanen, A. M., Singh, S. P., Wang, A., \& Furtado, V. (2020). The prevalence of personality disorders in the community: a global systematic review and meta-analysis. The British Journal of Psychiatry, 216(2), 69-78. https://doi.org/10.1192/bjp.2019.166