Working Memory Training on Delay Discounting Among Cigarette Smokers

Not Applicable

Completed

Conditions: Tobacco Use Disorder/Cigarette Smoking

Interventions: Behavioral: Working Memory Training (Active Intervention) + Behavioral Intervention
Behavioral: Control Training (CT) + Behavioral Intervention

Registration Number: NCT05210608

Lead Sponsor: University of Kansas Medical Center

Brief Summary: Despite widespread awareness of significant negative health consequences, cigarette smoking remains the leading cause of preventable morbidity and mortality in the US (Creamer et al., 2019; Jamal, 2018). Moreover, the highest rate of smoking and heaviest burden of smoking-related illness occurs among low-socioeconomic status (SES) individuals relative to higher SES groups (Businelle et al., 2010; Clegg et al., 2009). Low SES individuals are also 40% less likely to succeed in quitting smoking when they attempt to do so (National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health, 2014). One potential explanation for the disparity in rate of smoking and successful quit attempts may be differences in individual rates of delay discounting (DD), i.e., the degree to which rewards loses their value as the delays to their receipt increase (Odum, 2011). A proposed way to reduce steep DD and, potentially, substance use has been computer training for working memory, which has shown favorable results in a sample of individuals with stimulant dependence (Bickel et al., 2011) and substance use broadly (Felton et al., 2019), with the latter even showing decreases in cigarette smoking in a subset of the sample.

Detailed Description: The highest rate of smoking and heaviest burden of smoking-related illness occurs among low-SES individuals (Businelle et al., 2010; Clegg et al., 2009). One explanation for this disparity may be differences in individual rates of DD, which have been showed to be reduced with working memory training. (Bickel et al., 2011; Felton et al., 2019). Given the low cost of administering working memory training, such an intervention may be favorable for low-SES populations to improve smoking cessation outcomes.

DD has significant associations with:

Cigarette smoking (smokers tend to have higher rates of DD compared to non-smokers; Bickel et al., 1999);

Smoking treatment outcome (individuals who remained smoke free after a smoking cessation intervention had lower DD compared to those who didn't; González-Roz et al., 2019; Krishnan-Sarin et al., 2007; MacKillop \& Kahler, 2009; Yoon et al., 2007); SES (individuals with lower education and income have higher DD rates compared to those who are more educated and affluent; de Wit et al., 2007; Reimers et al., 2009).

An innovative way to reduce DD that has been proposed is via working memory (WM) training. WM refers to one's capacity to hold information while engaging in complex mental tasks, including reasoning, comprehension, and learning (Baddeley, 2010). Previous research has shown that DD and WM correlate negatively (Shamosh et al., 2008), that individuals with higher DD rates show neural deficits in WM (Herting et al., 2010), and that acute nicotine abstinence is associated with WM deficits (Mendrek et al., 2006; Patterson et al., 2010). Furthermore, previous studies targeting WM to reduce DD have shown favorable results in a sample of individuals with stimulant dependence (Bickel et al., 2011) and substance use broadly (Felton et al., 2019), with the latter even showing decreases in cigarette smoking in a subset of the sample.

Although previous research has shown WM training to reduce DD (which would support H3), and cigarette use in a small subsample, the hypotheses of this study are largely exploratory. However, given the theoretical connections between DD, SES, and WM, it is expected that the hypotheses of this project will be supported.

The performance of this project may advance our knowledge of the relevant clinical targets for smoking cessation in low-SES individuals. In particular, this project is expected to shed light on DD as the putative mechanism in smoking for low-SES individuals and the durability of reductions in smoking as a result of reductions in DD through WM training.

Despite the evidence for some successful techniques for reducing DD, little of this work has been translated into intervention approaches to target clinical outcomes. This application seeks to capitalize on the emerging literatures indicating (1) WM training may be an effective and efficient way to reduce DD, and (2) DD is associated with SES, cigarette smoking, and treatment outcomes. Though WM training has been successfully implemented in laboratory-controlled experiments to reduce DD, we are not aware of any interventions for clinical disorders that specifically seek to do so and potentially enhance treatment outcomes.

The development of effective, theoretically coherent interventions addressing cigarette smoking is imperative, particularly interventions that would be feasible, efficacious, and acceptable in low-SES individuals. The proposed research is an innovative approach that capitalizes on previous findings showing reductions in delay discounting and even cigarette smoking. If working memory training is found to improve smoking cessation outcomes as a function of reductions in delay discounting, the project results could be helpful in future development of low-cost interventions for cigarette smoking.

Recruitment & Eligibility

Status: COMPLETED

Sex: All

Target Recruitment: 13

Inclusion Criteria

Not provided

Exclusion Criteria

Not provided

Study & Design

Study Type: INTERVENTIONAL

Study Design: SINGLE_GROUP

Arm && Interventions

Group	Intervention	Description
Working Memory Training (Active Training) + Behavioral Intervention	Working Memory Training (Active Intervention) + Behavioral Intervention	Participants will be randomized to complete 10 sessions of a Working Memory Training. All participants will receive behavioral activation (a behavioral intervention for smoking cessation) and nicotine patches.
Control Training (CT) + Behavioral Intervention	Control Training (CT) + Behavioral Intervention	Participants will be randomized to complete 10 sessions of a Control Condition Memory Training. All participants will receive behavioral activation (a behavioral intervention for smoking cessation) and nicotine patches.

Primary Outcome Measures

Name	Time	Method
Delay Discounting	Baseline, Post-treatment, 1 month follow up	Delay Discounting (DD) was measured via an established computerized binary choice task in which participants choose between an amount of money available immediately and larger amount of money available after a specified delay (1 day to 25 years). A computerized algorithm adjusts the immediately available reward across seven trials to determine an indifference point (k) for each amount/delay pairing. Indifference points are then used to calculate a rate of delay discounting for a $50, $200, $1,000 "larger later" sum. Larger scores mean greater delay discounting. While there is no strict minimum or maximum k-value, but in practical research settings, typical k-values often range from close to 0 for individuals who discount delayed rewards very slowly to values above 1 for those who heavily discount delayed rewards. There is no strict lower or upper bound, but values can be extremely high (above 1) if an individual very strongly prefers immediate rewards.
Timeline Follow-Back (TLFB): Number of Total Cigarettes Smoked Per Week	Baseline, Post-treatment, 1 month follow up	The Timeline Follow-Back (TLFB) for cigarette smoking is a self-report method used to assess an individual's smoking behavior over a specified period and specified as one week for this study. In this method, individuals are guided to recall their daily cigarette use by referencing events, routines, and cues that help them accurately track their smoking patterns. They are asked to document the number of cigarettes smoked each day, which provides a detailed, day-by-day account of their smoking habits. This data was then be summed to give a weekly total cigarettes smoked per week. The TLFB approach is valued for its reliability and ability to capture fluctuations in smoking behavior over time.
Carbon Monoxide Levels	Baseline, Post-treatment, 1 month follow up	Participant reports of abstinence will be verified by expired carbon monoxide (\< 6 ppm cutoff for stated abstinence). CO levels are collected via a CO monitor.
Working Memory	Baseline, Post-treatment, 1 month follow up	Working memory was assessed by adding the scores of 3 different working memory measures: 1) the total achievement score in the Tower of Hanoi, 2) the total recall score of the Hopkins Verbal Learning Test- Revised and 3) the total scaled score of the Letter Number Sequencing. These measures are commonly used to assess working memory. In this study, the composite score of all measures ranged between 36 and 89 with higher scores representing greater working memory,