Machine learning to help improve engagement in gambling addiction treatment

Professor Matt Field will lead a major research project to look at the factors underlying dropout in gambling addiction services.

A man gambling on his smartphone

Professor Matt Field will lead a major research project to look at the factors underlying dropout in gambling addiction services, including among people who are referred (or self-refer) to a service but do not attend an initial appointment.

The project is one of three to be awarded an exploratory grant from The Academic Forum for the 海角视频 of Gambling (AFSG).

Using data from the NHS Northern Gambling Service, the team will use machine learning methods to study predictors of treatment retention/dropout and to better understand why a significant 40% of those referred to the service do not attend an initial appointment.

High dropout rates are a recognised challenge in addiction treatment services worldwide, and understanding the specific drivers within the UK's problem gambling support system remains limited. There can be many drivers behind dropout, although current understanding of the precise reasons and predictors of dropout among people in the UK seeking help for problem gambling is relatively weak.

鈥淢y colleagues and I are excited to begin this programme of work, which will use advanced statistical techniques that have been used in other areas of mental health and clinical psychology in recent years. We are delighted to partner with the NHS Northern Gambling Clinics, and our findings will shed light on the factors that determine dropout from treatment, in many cases even before the initial clinical assessment. Our approach has the potential to identify client characteristics and other contextual factors that can be the target of focussed interventions to improve engagement and retention in treatment, and thereby improve the outcomes of treatment鈥. Professor Matt Field

Findings from all three projects aim to ultimately improve the identification and treatment of gambling harms in the UK.

Read the to find out more about the three projects awarded.

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