Our life experiences shape how we perceive ourselves and the world, creating schemas that can negatively affect our mental health and prove resistant to change. However, a novel schema change model is now providing new avenues for innovative therapies in mental health treatment.
Developed by Dr. David Moscovitch, a Clinical Psychology professor at the University of Waterloo, the model integrates evidence-based findings from clinical psychology and cognitive neuroscience to explain how schemas are updated in the brain. Working directly with individuals struggling with mental health issues, Moscovitch designs psychological treatments to enhance their quality of life. He collaborated with his father, Dr. Morris Moscovitch, an eminent neuropsychology expert in memory and a professor emeritus at the University of Toronto, and Dr. Signy Sheldon, a Canada Research Chair in cognitive neuroscience at McGill University, to develop the novel neurocognitive model that promises to revolutionize the conceptualization and treatment of psychological disorders.
Moscovitch stated that their collaboration revealed how much cognitive neuroscience and clinical psychology have to learn from each other. Their new model was based on comprehensive scientific literature reviews, Moscovitch’s clinical disorders, cognitive-behavioral therapy, and social anxiety expertise, and his collaborators’ knowledge of memory and the brain, which they combined into their model.
Advancing therapeutic approaches
Individuals grappling with mental health concerns like anxiety and depression often hold negative self-schemas that negatively affect how they perceive themselves and their relationships with others. These negative schemas create patterns that reinforce harmful beliefs such as “I am unworthy of love” or “social interactions are threatening.”
Moscovitch and his team suggest that psychological therapies can optimally treat mental health issues by simultaneously strengthening positive schemas while weakening negative ones. While previous models have emphasized weakening negative schemas, Moscovitch’s innovative model sees both these processes as equally fundamental and complementary. Together, they form the Schema-Congruent and Schema-Incongruent Learning (SCIL) model.
Biological basis
The SCIL model involves two processes: schema-congruent learning, which involves encoding new information consistent with an adaptive schema, and schema-incongruent learning, which focuses on encoding new information inconsistent with a maladaptive schema. Combining these processes can enhance clinicians’ ability to support patients.
The biological basis of the model centers on the hippocampus’s role in encoding autobiographical memories, specific personal experiences at a particular time and place in the past. By activating the hippocampus using psychological interventions that simulate personal experiences, critical information can be provided to other brain regions where schemas are stored, promoting schema change.
Moscovitch emphasizes that the SCIL model outlines clear steps for clinicians when designing and implementing clinical interventions. This intentional approach can help guide patients toward the most effective mental health outcomes.
Developing evidence-based approaches
Moscovitch highlights the importance of both laboratory and clinical research in future studies. Clinicians can collaborate with patients to develop and implement evidence-based treatments, while cognitive neuroscientists can explore how to combine these treatments with newer interventions such as neurofeedback to activate the hippocampus more effectively.
Applied studies are needed to compare the effects of implementing the SCIL model versus traditional treatments, and to identify the active therapeutic components that contribute to schema change, both behaviorally and neurally. Additionally, researchers can investigate the value of incorporating novel neural tools into future treatment protocols.
The study detailing the SCIL model is published in the journal Perspectives on Psychological Science.
Source: University of Waterloo