Approach Bias Retraining to Augment Smoking Cessation

Brief summary

Reproduced verbatim from the official ClinicalTrials.gov record. Not medical advice.

Tobacco use is the most preventable cause of disease, disability, and death in the United States. Standard smoking cessation care (cognitive behavioral therapy and nicotine replacement therapy), is effective in approximately 20% of the cases, clearly indicating there is substantial room for improvement. Current work suggests that despite standard interventions, continued substance abuse may result from addictive behaviors governed partly through automatic processes that exert their influence outside conscious control. This is important from a treatment perspective, as we should develop treatments to target implicit processes. Among a number of promising targets for intervention, cognitive biases are important to address as they have been implicated as maintenance factors for addiction. Approach bias, defined as the automatically activated action tendency to approach smoking-related stimuli, is a relatively novel cognitive bias and has been related to failed smoking cessation. A recently developed task for approach bias assessment is the Approach Bias Retraining (ABR), a computerized joystick task increasingly used to measure automatic approach tendencies in addiction research. This clinical trial will evaluate a smoking cessation intervention that integrates standard care with approach bias retraining. Results will provide novel information regarding the potential benefits of engaging implicit cognitive biases as a means to augment traditional smoking cessation therapy. This study has the potential to help individuals attempting to quit smoking and, ultimately, provide unique information about the importance of targeting implicit processes to complement standard care.

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Public field values for ClinicalTrials.gov record NCT03325777, including study identification, conditions, interventions, eligibility (age, sex, healthy volunteer), timeline, and U.S. site list.

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Last update posted Jun 14, 2026 · Synced Sep 2, 2026

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