ArticlePsychopharmacology2020
Effort-based decision making varies by smoking status.
Article in Psychopharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 6 citations in OpenAlex.
- Neurobehavioral differences in value-based decision making between people with cocaine use disorder and controls.Experimental and clinical psychopharmacology · 2026Article
- Effort and substance use: differentiating tobacco use through reinforcement learning of effort based decision making.Journal of computational neuroscience · 2026Article
- An Exploratory Study of an fMRI Reward-Learning Paradigm in Developing Adolescents.Children (Basel, Switzerland) · 2026Article
- Effort and Substance Use: Differentiating Tobacco Use Through Reinforcement Learning of Effort Based Decision Making.Research square · 2026Article
- Greater fatigue is more strongly associated with reduced reward sensitivity in the long-term phase of coronavirus disease (COVID-19) than in the early phase.Brain, behavior, & immunity - health · 2025Article
- Substance use disorder severity is associated with sensitivity to effort-related decision-making constraints.Psychopharmacology · 2025Article
- Neurobiological foundations and clinical relevance of effort-based decision-making.Brain imaging and behavior · 2024Review
- Effort-related decision making and cannabis use among college students.Experimental and clinical psychopharmacology · 2023Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
rationaleA reduced willingness to perform effort based on the magnitude and probability of potential rewards has been associated with diminished dopamine function and may be relevant to chronic drug use.
objectivesHere, we investigated the influence of smoking status on effort-based decisions. We hypothesized that smokers would make fewer high-effort selections than ex-smokers and never-smokers.
methodsCurrent smokers (n = 25), ex-smokers (≥ 1 year quit, n = 23), and never-smokers (n = 19) completed the Effort Expenditure for Rewards Task in which participants select between low-effort and high-effort options to receive monetary rewards at varying levels of reward magnitude, probability and expected value.
resultsOverall, participants selected more high-effort options as potential reward magnitude and expected value increased. Smokers did not make fewer high-effort selections overall, but smokers were less sensitive to the changes in magnitude, probability, and expected value compared to never-smokers. Smokers were also less sensitive to the changes in probability and expected value, but not magnitude, compared to ex-smokers. Among smokers and ex-smokers, less nicotine dependence was associated with an increased likelihood of high-effort selections.
conclusionsThese results demonstrate the relevance of smoking status to effort-based decisions and suggest that smokers have diminished sensitivity to nondrug reward value. Among ex-smokers, greater pre-existing sensitivity to reward value may have been conducive to smoking cessation, or sensitivity was improved by smoking cessation. Future prospective studies can investigate whether effort-related decision making is predictive of smoking initiation or cessation success. IMPLICATIONS: Willingness to perform effort to achieve a goal and sensitivity to changes in reward value are important aspects of motivation. These results showed that smokers have decreased sensitivity to changes in effort-related reward probability and expected value compared to ex-smokers and never-smokers. Potentially, improved sensitivity to rewards among ex-smokers may be a cause or consequence of smoking cessation. These findings may help explain why some smokers are able to achieve long-term abstinence.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.