Exploring therapeutic alliance for digital mental health

It is well established that successful psychological therapies require the development of a therapeutic alliance (TA) between therapist and client based on the negotiation of shared treatment goals. The world-wide expansion of digital therapies for mental health problems have led researchers to consider the of concept of TA in relation to digital mental health technology. Understanding digital TA is key to designing effective digital mental health systems. The supervisors and their collaborators (Dr Lederman and Dr D’Alfonso) based at the School of Computing and Information Systems, University of Melbourne are leaders in this field of digital TA. The supervisors (Professors Berry and Bucci) have developed the first tool to measure digital therapeutic alliance (Mobile Agnew therapeutic Relationship Measure; MARM) and the measure has been subject to a preliminary validation (Berry et al., 2018). This measure is an important development as it allows us to both determine the strength of association between alliance and outcome in the context of digital technologies and to develop digital mental health platforms so that they more closely mirror key components of alliance in face-to-face therapy. Our previous work has found that although users of digital interventions do identify relationship concepts, current apps were not capable of portraying uniquely human-like qualities such as friendliness, collaboration, and agreement essential for TA, meaning that they might be less effective than face-to-face interventions. This PhD has two principle aims: 1) fully validate and if necessary further fine the MARM measure of digital TA; 2) explore how we can maximise current software capabilities to more closely emulate characteristics conducive to the development for TA, for example, improved responsiveness and tailored and personalised intervention strategies.

Training/techniques to be provided:
The PhD researcher will undertake training in the following:
1) systematic literature reviews and meta-analysis
2) Exploratory factor analysis and advanced statistical methods in SPSS
3) Confirmatory factor analysis and Stata
4) Qualitative methods: data collection and analysis including the use of NVivo

Entry Requirements:
Candidates are expected to hold (or be about to obtain) a minimum upper second class honours degree (or equivalent) in a related area / subject. Candidates with experience in mental health research are particularly encouraged to apply.

For international students we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences. For more information please visit www.internationalphd.manchester.ac.uk