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. 2025 Jul 23:19:1552895.
doi: 10.3389/fnhum.2025.1552895. eCollection 2025.

Pattern formation, ruptures, and repairs in treatments of personality disorders: an idiographic case series study

Affiliations

Pattern formation, ruptures, and repairs in treatments of personality disorders: an idiographic case series study

Stine S Høgenhaug et al. Front Hum Neurosci. .

Abstract

Background: Any human communication is based on verbal, emotional, and movement patterns that weave within and between conversation partners. Personality disorders (PD), characterized by emotional dysregulation, attachment instability, and impulsivity, present disruptions in the integration of these coordination dynamics influencing alliance formation and outcome. Therapists, regardless of their clinical expertise, often find themselves grappling with the complexities of tailoring PD treatment. The alliance is often challenged by significant tension or breakdowns increasing risk of impaired progress. Thus, this multi-method comparative case series study investigated how four therapists tailored their treatment with four PD patients in a mentalization-based treatment program to identify patterns of interaction that might facilitate or hinder the therapeutic process during sessions characterized by severe disruption.

Methods: The Symptom Checklist (SCL-92) was applied to identify two successful and two unsuccessful PD treatments. The Rupture Resolution Rating System-Revised was used to detect sessions with rupture frequency peaks in each treatment case. Therapist adherence and competence were assessed with the Mentalization-Based Therapy Adherence and Competence Scale. Heart rate patterns were calculated with cross-recurrence quantification analysis to examine synchronization. An interpretative phenomenological analysis examined the therapeutic process, in addition to quantitative measures.

Results: In sessions with increased rupture frequency, therapists had difficulties managing ruptures and struggled to tailor their treatments no matter the treatment outcome and therapist experience level. Therapists showed high contribution to confrontation ruptures, low adherence and competence ratings, decreased ability to stimulate a mentalizing environment, and inattentiveness to the patients' mental and emotional states during rupture management. Interestingly, more positive heart rate recurrence correlations were identified in sessions from successful treatments showing different regulatory patterns in rupture peak sessions from good vs. poor outcome treatments.

Discussion: Our results make a significant contribution to psychotherapy research by offering a multifaceted perspective on how dynamical alliance processes might foster or hinder the therapeutic process. The clinical implications of low adherence, therapist strategic competence, and increased HR synchronization between therapist and patient in rupture intense sessions are discussed.

Keywords: adherence; alliance; interpersonal physiology; personality disorder; process research; recurrence quantification analysis; repair; rupture.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Figures

Line graph showing the Global Severity Index SCL over the treatment timeline from start to end for four patients. Patient 1's line trends downward slightly, Patient 2 shows a significant downward trend, Patient 3's line trends upward, and Patient 4 decreases sharply.
Figure 1
SCL-92 Progress From Pre-Post Treatment. Note: Line graph showing the Global Severity Index SCL over the treatment timeline from start to end for four patients.
Flowchart depicting session selection for patients with the maximum number of rupture segments. Four patients (1 to 4) with respective SUMS_max values (10, 21, 11, 23) are shown. Session IDs for each are listed: Patient 1 with 12, 17, 26; Patient 2 with 23, 33; Patient 3 with 3, 16, 34; Patient 4 with 2, 4. Selection criteria include research randomizer and HR data availability, resulting in chosen sessions: 26, 33, 3, and 2.
Figure 2
Flow Chart of Session Selection. Note: Flowchart depicting session selection for patients with the maximum number of rupture segments. SUMSmax = maximum sum score of rupture segments for patients and therapists within sessions.

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