Enhancing Mental Health and Wellbeing Outcomes for Psychotherapy and Counselling through Idiographic Analysis: A Four-Quadrant Approach
Jenna Jacob, Research Lead, Child Outcomes Research Consortium (CORC) at Anna Freud
I completed a Ph.D. by published works at the University of Roehampton in 2020. This is an alternative route to a Ph.D. qualification, where the research is already published and then the candidate pulls together a supporting piece of work, to evidence the impact of the cohesive body of publications. My specific area of interest and focus has for some time been the exploration of mental health and wellbeing outcomes through personal goal measurement in children’s and young people’s support settings.
Through considering the impact of my published work on goal setting and tracking, I wanted to think about how we can take things forward to support those who work to support children and young people’s mental health and wellbeing. This included suggestions of where we go next with ‘goals taxonomies’ that have been developed (watch this space) and how to best use the data collected using goal-based outcome tools, such as the Goal-Based Outcome Tool (GBO Tool). Setting and monitoring goals can be central to pluralistic practice because it means the therapy is oriented around what the client wants from it, rather than what the therapist or organisation sees as desired outcomes.
For most outcome measures, like CORE-OM or RCADS, scores are aggregated on different items into one total score, or a small number of subscale scores. However, the consideration of only one dimension of the data collected using outcome measures means that we cannot necessarily capture the outcomes of complex and individualised therapy, or support processes to the fullest. What I mean by this is that there are nuances in change and areas of importance to individuals that it is not possible to tap into through the aggregation of data (though the latter may still be useful as an indicator of change at a team or service level). The meaningful use of all outcome measures is key and it was thinking about the use of the measures live in the room to inform clinical conversations–and balancing this with the need to evidence outcomes at an overarching level–that led to the development of what I called ‘three layers of analysis’ initially, and then this turned into ‘four quadrants’ after (many) discussions about it with my supervisors and research group colleagues.
When writing the final published paper (see here), we expanded on the original ideas, suggesting that our proposed approach to data analysis could be applied to other idiographic patient reported outcome measures (I-PROMs), due to the similarities across the measures. ‘Idiographic measures’, in contrast to standardised ‘nomothetic ones’ (like the CORE-10 or PHQ), have items that the client, themselves, decides upon. This includes the Goal Form that Mick Cooper developed, or problem-based measures like PSYCHLOPS. As a worked example, we collaborated with Charlie Duncan, Senior Research Fellow at BACP, who applied the data analyses to GBO Tool data she has collected as part of her own Ph.D.
The four quadrants are:
- Individual goal progress on single goals. This may provide points for ongoing discussion with the client.
- Individual progress on aggregated goal scores. Progress summarised as an individual’s overall sense of direction of travel may be a useful reflection tool for practitioners and for clients to get a sense of direction of travel.
- Team/service level progress by goal theme. Analysis of data at the theme level (e.g., ‘developing self-esteem’, ‘overcoming anxiety’) can be helpful to identify clients’ needs and how these are being addressed by the service. From this organisation of the information, the service may focus on areas of need/training or client outreach.
- Team/service level progress by aggregate goal scores. This is useful as an overall indicator of change and can be used to evidence outcomes for local and national targets
I-PROMs are multi-layered, due to the personalised/individualised nature of them, which requires some balancing of approaches. We hope that providing examples based on real data, and highlighting the different purposes in our paper, will go some way to help with the exploration of the data derived in a range of ways.
There might be other layers that we haven’t detailed here, for example, you might want to consider analyses with the practitioner’s perspective in mind. With that, you might delineate slightly different approaches to analysis in addition to the first and second quadrants we identified in our work. It is important to acknowledge that different types of outcome measurement serve different purposes. It has long been recommended that I-PROMs are used alongside standardised measures (i.e., those with fixed items) to ensure a breadth of information is captured. Alongside this, in both pluralistic and other therapies, the dynamic use of measures to inform important conversations about progress and outcome is the most important thing. In doing so, it is only fitting that the meaningful consideration of the data in a range of ways sits alongside this.