Temporal organization of discursive voices and their association with outcomes in a case of psychotherapy
DOI:
https://doi.org/10.21615/cesp.7585Keywords:
discursive voices, change in psychotherapy, case study, vector auto-regression, entropy, borderline personality disorder, dialogical self theoryAbstract
Voices are the expression of subjective states of patients and therapists in their discourse during psychotherapy. Some voices can be monological, potentially becoming rigid and limiting the experience, and others dialogical, allowing for greater flexibility and reflexivity. The interaction of voices may be disorganized or organized throughout the psychotherapy. A secondary analysis is presented of a case study of a patient diagnosed with Borderline Personality Disorder (BPD). In this 44-session successful psychotherapy (OQ-45.2), different voices were identified using the Discourse Positioning Analysis Model in Psychotherapy (MAPP), and entropy levels (Hs) were assessed in the interaction of these voices using the State Space Grid (SSG) technique. The objective of this study was to describe the temporal association between the interaction of the patient and therapist's reflective voices, their level of organization (entropy), and the patient's outcomes in psychotherapy. To achieve this objective, an idiographic analysis based on vector auto regression (VAR) was conducted. The results suggest a good fit of the model for one-session delays (lag 1). There was temporal stability (autoregression) [p < .01] and a positive trend [p < .00] of the patient's outcomes, and a positive cross-regression between the degree of organization of voices (t-1) and patient outcomes (t) [p < .01]. A temporal dynamic is suggested in which greater organization of patient-therapist voice interactions influences the quality of the patient's outcomes. No significant association could be established between outcomes and reflective voices despite their positive synchronous correlation (lag 0). Studies at the nomothetic level are needed to test an extension of this model.
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