(PS1-A2) Treatment Plans for People with Gambling Disorders Should Target Underlying Psychological Profiles

While about two-thirds of the general adult population have gambled in the past year, only about 2% will develop a gambling disorder. These rates have increased in recent years, coinciding with the increased accessibility to online and sports gambling opportunities.

Research has shown that various mental health indicators are related to problem gambling (PG). Yet, not only are existing treatments mostly equivalent in terms of their effectiveness, showing only modest benefits, but an important portion of people with a gambling disorder recover naturally, without ever seeking any treatment. Efforts to predict who recovers have been largely unsuccessful. Even risk factors known to be associated with the disorder, such as depression, have little impact when predicting remission.

If people naturally remit from gambling disorders, and risk factors associated with the disorder barely predict remission, should efforts even be made to develop new treatment programs?

Maybe the answer lies in the way that researchers have been thinking about those who develop a gambling disorder. Past research on remission from PG has failed to recognize that people with a gambling disorder do not form a homogenous group. Yet, a prominent theoretical model– the Pathways Model – posits three distinct pathways that lead to PG: (i) ‘Behaviorally conditioned’, (ii) ‘Emotionally vulnerable’, and (iii) ‘Antisocial-impulsivist’ pathways.

The present study uses longitudinal data collected annually over five consecutive years in two Canadian provinces (n = 5,929). Data has already been collected and cleaned. Latent class analyses (LCA) were conducted on baseline data to cluster participants based on key variables suggested by the Pathways Model. The LCA was conducted only on participants without PG at baseline, but who developed gambling problems at either follow-up assessment (n = 408). This allows us to test the theoretical model’s central tenets, namely that some risk factors precede PG, depending on the pathway, while other key indicators follow the emergence of PG. Our analyses yielded three groups of participants that closely resemble those described by the Pathways Model.

To fully address the clinical implications of the model, we will also present results combining latent growth curve analyses of affective and cognitive key variables, such as depression or gambling fallacies (i.e., faulty gambling-related cognitions). Could it be that the link between PG remission and mental health depends on why a person has the disorder? We expect chronicity of PG over five years to not only vary as a function of the gambling pathways, but also as a function of affective and cognitive risk trajectories, within each pathway. For example, addressing faulty cognitions should mostly predict remission in the Behaviorally conditioned group. Conversely, a decrease in depression levels over time should only predict remission in the Emotionally vulnerable group, who gambles mostly as a coping mechanism for depression. If results show that people in a specific pathway require more years to recover, and recovery depends on resolving underlying mental health indicators, then this would have profound implications on how addiction and mental health services should be integrated.