Measuring adherence in social recovery therapy with people with first episode psychosis

Measuring adherence in social recovery therapy with people with first episode psychosis

Full title

Christine Lowen, Jo Hodgekins, Katherine Pugh, Clio Berry, Mike Fitzsimmons, Paul French, Catarina Sacadura, Max Birchwood, Chris Jackson, Eleanor Baggott, Mark Bernard and David Fowler

 

ABSTRACT

Background:

The SUPEREDEN3 study, a phase II randomized controlled trial, suggests that social recovery therapy (SRT) is useful in improving functional outcomes in people with first episode psychosis. SRT incorporates cognitive behavioural therapy (CBT) techniques with case management and employment support, and therefore has a different emphasis to traditional CBT for psychosis, requiring a new adherence tool.

Aims:

This paper describes the SRT adherence checklist and content of the therapy delivered in the SUPEREDEN3 trial, outlining the frequency of SRT techniques and proportion of participants who received a full therapy dose. It was hypothesized that behavioural techniques would be used frequently, consistent with the behavioural emphasis of SRT.

Method:

Research therapists completed an adherence checklist after each therapy session, endorsing elements of SRT present. Data from 1236 therapy sessions were reviewed to determine whether participants received full, partial or no therapy dose.

Results:

Of the 75 participants randomized to receive SRT, 57.3% received a full dose, 24% a partial dose, and 18.7% received no dose. Behavioural techniques were endorsed in 50.5% of sessions, with cognitive techniques endorsed in 34.9% of sessions.

Conclusions:
This report describes an adherence checklist which should be used when delivering SRT in both research and clinical practice. As hypothesized, behavioural techniques were a prominent feature of the SRT delivered in SUPEREDEN3, consistent with the behavioural emphasis of the approach. The use of this adherence tool would be considered essential for anyone delivering SRT looking to ensure adherence to the model.
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