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Title: Predictors of response to systems training for emotional predictability and problem solving (STEPPS) for the treatment of borderline personality disorder
Author: Shepherd, Kirsty E.
ISNI:       0000 0004 6494 7834
Awarding Body: University of Surrey
Current Institution: University of Surrey
Date of Award: 2017
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Borderline Personality Disorder (BPD) is a heterogeneous diagnosis which encapsulates a wide range of symptom presentations. There are now a number of effective treatments for BPD but individuals vary in their response to these different treatments. Understanding people’s suitability to treatment would be beneficial in targeting and individualising BPD treatment efforts. This thesis aimed to explore the BPD related predictors of treatment response. Part one of this portfolio presents a narrative review of predictors of BPD treatment outcomes. BPD severity, symptoms and subgroups predictors were included in this review. Findings support previous reports that people with more severe BPD show larger improvements following treatment, although there was a tendency for this to occur in more skills-based treatments compared with reflective treatments. The findings on symptom level predictors were varied and would benefit from replication. Subgroup research is still in its early stages but findings suggest an important role of internal and external coping styles. Part two presents an empirical paper investigating predictors of response to Systems Training for Emotional Predictability and Problem Solving (STEPPS). Severity of BPD was examined as a predictor of outcomes alongside each of the 9 DSM symptom criteria for BPD. Findings are discussed in relation to the different methods of managing missing data. Severity was found to be predictive of response. When severity was broken down into its symptom level sub-parts, identity disturbance and dissociation were the most reliable predictors of response to STEPPS.
Supervisor: Draycott, Simon Sponsor: University of Surrey
Qualification Name: Thesis (D.Clin.Prac.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available