We spoke to Bibire Baykeens, a student at Imperial College London, who utilised the CRIS powered by Akrivia Health platform to conduct research on dysregulated behaviours in adolescents.
What was the motivation for completing a project on dysregulated behaviours?
Bibire had a set of research projects to choose from for a four-month research block. With her interest in psychiatry, she looked to the projects involving dysregulated behaviours, specifically disordered eating, substance misuse, and self-harm.
Before formulating the research questions, Bibire and her project partner did some background reading and found when first investigated, dysregulated behaviours seemed to stem from emotional dysregulation, typically from people with Emotionally Unstable Personality Disorder (EUPD) or borderline personality disorder (BDP). Based on these findings, Bibire decided it would be interesting to look at the prevalence of dysregulated behaviours amongst young people who have psychiatric disorders with elements of emotional dysregulation. Not just EUPD, but also autism, attention deficit hyperactivity disorder (ADHD), Bipolar, Schizophrenia, and schizoaffective disorder. These five behaviours were chosen as they were most often cited in the literature as types of disorders with a high prevalence of mood instability, an element of emotional dysregulation often presented at a young age.
For West London NHS Trust there was an interest to have an inventory audit or service evaluation to see if the needs of these young people were being addressed because it has been reported clinically that they are being underserved but there hadn’t yet been a project or research paper to reflect this.
What key question, or questions did Bibire hope the project would answer?
The project focused on the prevalence of behaviours. The focus was primarily on dysregulated behaviours such as emotionally unstable personality disorder, Autism, ADHD, Schizophrenia and Schizoaffective disorder, and Bipolar. Bibire also focused on substance misuse, disordered eating, and self-harm. Following this, the psychological therapies (dialectal behaviour therapy, mentalisation-based therapy, and schema therapy) useful for targeting emotional dysregulation were explored. These types of therapies are known to have elements of targeting emotional dysregulation and teaching emotional regulation to those receiving the therapy. Whilst these therapies are often used for those with emotionally unstable personality disorder, emotional dysregulation is a different psychiatric disorder. Based on this, Bibire wanted to firstly, see the prevalence of the behaviours, and then, support that the individual had received the treatment. Therefore, the question Bibire posed was:
Whilst building her two cohorts, Bibire also explored the number of referrals to DBT (dialectical behaviour therapy), MBT (mentalisation based therapies), and as an addition, looked at the referrals to the mental health teams within the trust as well to see where these young people are ending up in terms of referrals to services.
What impact does Bibire hope the paper will have?
Bibire hopes that if the paper is published, her work could be a part of a ‘big beginnings’ in looking at this issue at West London Trust. If the paper is published, Bibire hopes that her work could stem beyond West London Trust and provide an opportunity for other healthcare organisations to review their own services for young people, and to conduct their own research project with Akrivia Health.
As an audit or service evaluation, it serves as a starting point to prove enough that there are some gaps in the services that need to be addressed. She feels if the paper does end up having some semblance of a change to service, then that would be the icing on the cake.
Which features or functionality of the platform were most beneficial for the project?
Building the project in the Platform
Bibire found that being able to build and save the cohorts based on user specified inclusion and exclusion criteria, proved to be helpful. Particularly, within the cohort builder, the suggested criteria.
To work with the de-identified aggregated data Bibire needed, she built two cohorts in the platform. The two cohorts Bibire built were young people, all genders, between the ages of 16 and 25. ICD10 codes were used to identify the six disorders, as well as a search on the free text for different variations of terms such as ‘self-harm’. One cohort with, and one cohort without, the dysregulated behaviours and involved an exclusion criterion with text variations such as ‘no history of self-harm’ within the clinical notes. Bibire worked with the de-identified and anonymised data of 2200 patients, which outside of a data platform, is a large cohort size to identify in a short time-restricted period.
Within data export, Bibire exported the demographic data, age, gender, ethnicity, and occupation. Exporting diagnosis was done in more detail exploring reason, clinical note free text, assessments, and collecting team referrals, specialist referrals, and dates.
What were the findings of the study?
Based on the literature, Bibire had two hypothesises related to the behaviours of young people with Emotionally unstable personality disorder, and the therapies available. Based on her findings, Bibire found that although there was a high prevalence of the behaviours, the data did not support her first hypothesis.
Bibire discussed the possible reasons behind this, one is that we might have poorly judged the prevalence of EPD in those with Bipolar. Secondly, age ranges. Typically, with personality disorders, there is almost a hesitancy with diagnosing younger people with personality disorders. There were fewer numbers than she thought she would have originally.
Final words and comments
‘As a product in its early days, the platform has so much potential. I really applaud what you do and what you are trying to do as a team, and as an organisation. I didn’t really know much about it and the research was the first time that we had really used the platform. I had one expectation: that it would be slightly easier in the sense that I would not have to do the manual data collection. While I knew that some things took longer, having access to the de-identified patient data in the Akrivia Health platform allowed me to build a big cohort than I would have been able to outside of the platform. There are always pros and cons. I hadn’t thought that my project would be easier because I was using the Akrivia Health platform, I had only thought that I would be able to access a larger cohort of patients. In the end, I would not have wished to do a different project’