The development of the Leeds alliance in supervision scale (LASS): A brief sessional measure of the supervisory alliance

Background: Clinical supervision is a central practice in the development of clinicians. The supervisory alliance is a key process within clinical supervision, amd may have a real impact of supervisee development. This may provide a rationale for the use of sessional measures to provide ongoing feedback on the supervisory alliance. Various measures of supervisory alliance exist. However these instruments are too long to be used on a sessional basis. Objectives: To develop a short-form measure (LASS) of the supervisory alliance from the perspective of the supervisee that has the clinical utility to be used on a sessional basis, and the psychometric properties to be a credible instrument for research. Study 1: Items from existing measures of the supervisory alliance were qualitatively analysed to produce a 25-item experimental measure. This was administered to 98 UK trainee Clinical Psychologists. Principal Components Analysis (PCA) of the data resulted in a 2-factor solution. Hierarchical Cluster Analysis led to the identification of 3 clusters measuring the supervisory alliance. Representative items were chosen, resulting in the 3-item LASS. Study 2: The LASS, and other related measures, were administered to 140 UK trainee Clinical Psychologists. Analysis of this data found that the LASS had acceptable internal consistency and test re-test reliability, but provided evidence that the LASS was sensitive to change. The results of the analysis investigating concurrent and convergent validity indicated that the LASS is a valid measure of the supervisory alliance. Conclusions: The LASS is a

Name dc:type.qualificationname

D.Clin.Psyc

Level dc:type.qualificationlevel

doctoral

Grantor dc:publisher.institution

University of Leeds

Year dc:date.issued

2010

Author dc:creator

• Wainwright, Nigel Antony

Advisors dc:contributor.advisor

• Green, D.
• Latchford, G.

Identifier

uk.bl.ethos.531512

OAI identifier oai:identifier

oai:etheses.whiterose.ac.uk:1118