Smoking CessationNCT04620915
Construal Level as a Novel Pathway for Affect Regulation and Cancer Control
A study testing High-level construal, Down-regulation of craving for cigarettes and Up-regulation of goal energization in people with Smoking Cessation and Smoking Reduction, run by University of Oregon at 2 sites in United States.
Trial summary
The objective of the proposed research is to conduct a longitudinal experiment on the neurocognitive pathways and individual differences in high-level construal for affect regulation and smoking cessation. The population is adult smokers aged 25-55 who have tried and failed to quit and who are experiencing poverty. Read more about this study
- Who is it for?
- Ages 25 to 55 years
- Conditions the study is for
- Smoking Cessation, Smoking Reduction, Cancer
- What is being tested?
- High-level construal, Down-regulation of craving for cigarettes and Up-regulation of goal energization
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 300 participants
- Where
- 2 sitesUnited States
- Study dates
- 11 Oct 2021to 5 Nov 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 25 to 55 years
- All sexes
- No healthy volunteers
- Adult
Who may be able to join
- Low-SES
- Persistent smokers: cigarette smokers (at least 10 cigarettes/day for at least 1 year)
- Want to quit but have tried and failed at least once
- Income-to-needs ratio (INR) is less than 2.0, meaning that their household income adjusted for household size is below 200% of the federal poverty line
- Ages 25-55
- Scan Exclusion Criteria:
Show all 15Show fewer
- Metal implants (e.g., braces, permanent retainers, pins)
- Metal fragments, pacemakers or other electronic medical implants
- Claustrophobia
- Weight ˃ 550 lbs.
- Women who are pregnant or believe they might be pregnant
- People in this population are likely to have some comorbid psychiatric, substance use, and/or other health disorders that might pose a challenge to retention and intervention compliance. Such comorbidities are inherent to the population of interest (persistent smokers) so they will not be exclusionary criteria; instead, we will gather information about psychiatric, substance use, and medical comorbidities on intake so that we can monitor and report any associations with attrition, compliance, and effects of the experimental conditions.
- E-cigarette use is acceptable - it is not an exclusionary criterion - but it will be recorded and covaried as appropriate in the analyses.
- To increase the homogeneity of the sample in terms of cessation aids, we require that all participants use pharmacological cessation aids such as nicotine replacement therapy (NRT). This inclusion criterion also more realistically models how cessation happens in vivo, as medical care providers often recommend adding pharmacological assistance such as NRT to quit programs. We will provide patches or gum (e.g., Nicoderm) to participants who cannot afford. Participants who want or are able to provide their own NRT will be included as long as they agree to continue using NRT for the duration of the training period. We will monitor NRT use weekly to ensure compliance with this inclusion criterion.
- No exclusions will be made on gender, race, or ethnicity, so the sample will reflect the demographic profile of the United States. Eligible participants will be scheduled for the Zoom pre-session.
Who cannot join
None listed.
Trial locations and contacts
2 sites in 1 country.
United States2 sites
University of Oregon, Lewis Integrative Sciences Building
Eugene, Oregon, 97403
University of Oregon, Social and Affective Neuroscience Laboratory
Eugene, Oregon, 97403
About this study
Official title: High-level Construal as a Novel Pathway for Affect Regulation and Cancer Control
The objective of the proposed research is to conduct a longitudinal experiment on the neurocognitive pathways and individual differences in high-level construal for affect regulation and smoking cessation. The population is adult smokers aged 25-55 who have tried and failed to quit and who are experiencing poverty. The primary endpoints are (a) the similarity in neural representation of high-level construal to one of two candidate pathways, (b) the presence of meaningful individual differences in the neural representation of high-level construal, and (c) as a secondary endpoint, the effect size of the high-level construal condition on smoking as measured by cigarettes per day.
Each of these endpoints corresponds to a specific null hypothesis. The null hypothesis for the first endpoint is that high-level construal is not significantly different in its neural representation from down-regulation of craving, which would suggest that high-level construal does not operate through distinct mechanisms from traditional treatments. The null hypothesis for the second endpoint is that the between-subjects variability in the neural representation of construal level does not significantly relate to relevant individual differences measures (e.g., traits, task behavior), which would suggest that individual differences are not meaningfully related to outcomes. Finally, the null hypothesis for the secondary endpoint is that the magnitude of the effect of high-level construal on smoking as measured by reductions in average cigarettes per day is not significantly greater than in the other conditions, which would suggest that the efficacy of the high-level construal condition is not significantly greater than a standard text-messaging intervention.
The primary endpoints will be assessed at baseline and change from pre-to-post training (8 weeks).
Read the detailed description
OVERVIEW:
The proposed work will achieve the three specific aims (two confirmatory, one exploratory) in the context of a 3-arm translational experiment. Assessments of neurocognitive mechanisms of high-level construal, as well as of two candidate pathways, will be completed at baseline and endpoint sessions. The 300 participants enrolled in the study will complete a multimodal battery that will assess neural, behavioral, and self-report indices relating to the three processes of interest - construal level, down-regulation of craving, and up-regulation of goal energization - and then are randomized to one of three experimental conditions related to those processes. This design is highly advantageous because it allows for the establishment of the mechanisms of the construal-level intervention, to compare them with the mechanisms of the other two processes, and to test whether, and to what extent, our potentially novel affect regulation strategy engages and alters those mechanisms (Aim 1); and to identify individual differences in the effects of that novel strategy (high-level construal) on patterns of brain activation, affect regulation, and cessation outcomes (Aim 2). Though the translational experiment design is not intended to be an intervention per se (because the evidence base does not yet support a full-scale trial and materials for such an intervention still need to be developed), the investigators will nonetheless quantify the effect size of high-level construal on changes in smoking so future RCTs have that information and can be adequately powered to detect an effect.
ASSIGNMENT OF PARTICIPANTS TO CONDITION:
Participants will be randomly assigned to a condition using the randomizer function in the RedCap participant tracking and management software. This assignment will happen only after participants are screened, consented, enrolled, and complete the baseline session. In other words, all 300 participants will be treated in exactly the same way through the end of the baseline session, and only at that point will RedCap be used to assign participants to their condition. All participants will have equal probability of being assigned to the conditions (i.e., 33.33% chance of assignment to each). The study coordinator will know which participant is enrolled in each condition, but researchers involved in data analysis (i.e., Drs. Berkman, Fujita, Chavez, and Weston, as well as the graduate students) as well as the research assistants who interact with the participants will be blind to condition during data gathering and analysis.
METHODS FOR SAMPLE SIZE CALCULATION AND DATA ANALYSIS:
The method for selecting the sample size was based on a power analysis of the least sensitive test - Aim 2. The key statistical tests for the three aims are as follows. For Aim 1, the test of neural similarity between conditions is essentially a paired-samples t-test on similarity scores (e.g., pattern correlations calculated within subjects). This is a high-powered comparison because the covariance within subjects of the scores is high. For Aim 2, the individual difference analyses are between-subjects correlations and regression (or partial regression or logistic regression) coefficients relating neural similarity to affect regulation scores, responses to trait and individual difference surveys, and smoking behavior as measured by cigarettes per day. This family of test has relatively low power because it is entirely between subjects. For Exploratory Aim 3, the key test is the condition-by-time interaction (i.e., differences among the groups in change in smoking behavior from pre-to-post training). This test is a within-between (sometimes called "mixed") ANOVA analysis that is more powerful that the individual difference analyses for Aim 2 but less powerful than the fully within-subjects tests for Aim 1.
INTERVENTION CONTENT:
The content for all three training arms is a set of brief (<160 character) messages designed to enable participants to practice one specific affect regulation strategy (experimental arms). In brief, all messages in the experimental arms are generated by a large group of mTurk workers who are smokers; the process of message generation and validation has already begun. During the award period the investigators will add even more messages to the corpus and validate them. In the high-level construal condition, workers compose messages that encourage thinking about purpose of quitting and future goals (e.g., "What would quitting mean to you and your future?"). In the down-regulation of craving condition, workers compose messages that encourage effortful inhibitory or attentional control of cravings (e.g., "When you feel an urge to smoke, think about the health consequences"). And in the up-regulation of goal energization condition, workers compose messages that tie one specific core value (which the mTurk worker ranked as within his or her top three core values) to the goal of quitting (e.g., for the core value of "family", a message might be, "Quitting will help you model a healthy lifestyle for your family"). The content for the up-regulation of goal energization condition is matched to participants' own top three core values.
INTERVENTION DELIVERY:
All participants receive text messages and complete biweekly online "booster" sessions for 8 weeks.
Beginning on their quit date, participants will be sent messages via SMS text messaging 5 times each day for 28 consecutive days, then 4 times each day for the following 28 days. The investigators chose to increase the messaging frequency in the first month of cessation given the higher likelihood of relapse during this period. The order of the messages will be pseudo-randomized such that each message will be seen no more than three times across the 8-week training period, separated by at least 10 days. The timing of the messages will be adjusted for each participant to be evenly spaced starting at wake-up and ending 15 minutes before bedtime and adjusting for weekday/weekend differences. Participants will reply to each message and use a 5-point scale to rate its perceived helpfulness. Participants can also text "SOS" to the system at any point to initiate support via text if they feel tempted to smoke. Daily text messaging is an ideal delivery format for this training because it allows for in vivo participant contact at moments when smoking decisions are being made. Text messaging has very high adoption rates in the United States even among underserved communities that are typically difficult to sample densely for extended durations, and low SES users are comfortable receiving texts throughout the day. The investigators have used text messaging for experience sampling and for theory-based intervention in a community sample (see Preliminary Studies 5 and 6). Participants will provide their mobile phone number at the baseline session; those without a text message-enabled phone or those who do not wish to use their own, will be provided a prepaid phone at the end of the baseline session.
In addition to the text messaging, participants will complete biweekly online "booster" sessions using Qualtrics with a custom, personalized link sent to the participant via email and text. The booster sessions are designed to reinforce the active interventions (high-level construal, goal energization, down-regulation of craving) and provide opportunities to practice the assigned affect regulation strategy. In the sessions, participants will be reminded of their assigned strategy and write brief responses to specific prompts (e.g., "What are two specific ways that quitting now will change your future life?", "Why is quitting important to you today?", and "What are two ways you can change how you think to reduce your craving for cigarettes?"). Participants will also generate triggers to smoking (situations or cues) and practice using down-regulation of craving when they see those triggers. This exercise helps form the habit of deploying the strategy in everyday life. Not all participants have computer access, so, as in previous studies, participants will be provided access in the lab and the research team will work with the local library system to ensure all study sites are accessible from their computers.
BOOSTER COMPLETION AND RETENTION:
Dr. Berkman is currently using similar "booster" sessions, which are programmed in and are delivered via Qualtrics, in a current translational experiment on healthy eating (R01 CA211224). The automated reminders and links, which can be sent via email and text messaging depending on participant preference, greatly increase completion of the boosters. Together with the reminders, graded incentives (e.g., a monetary bonus for completing >90% of the boosters during the study) have greatly increased completion of the at-home booster sessions.
- Conditions
- Smoking Cessation, Smoking Reduction, Cancer
- Being tested
- High-level construal, Down-regulation of craving for cigarettes, Up-regulation of goal energization
- Keywords
- Smoking, Construal level, Cigarettes, Quitting
- Medical subject headings
- Smoking Cessation, Smoking Reduction, Neoplasms, Smoking
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
High-level construalBehavioural
In the high-level construal condition, participants will be sent messages asking them to consider why they are quitting ("What are your main reasons for quitting?") and to imagine what their lives will look like in the future if they succeed ("What would quitting mean to you and your family's future?"; Yeager et al., 2014). The corpus for this condition is 100 messages composed by a large independent sample of mTurk workers who are smokers and validated by a team of RAs trained to 0.8 reliability on ratings of high-level construal. To meet criteria for inclusion, a message must be rated as significantly closer to high-level (vs. low-level) on a rating scale of construal level.
In addition to the texting, participants will complete biweekly online "booster" sessions using Qualtrics with a custom, personalized link sent to the participant via email and text.
Down-regulation of craving for cigarettesBehavioural
In the down-regulation of craving condition, participants will be sent messages that encourage inhibitory control of cravings for cigarettes (e.g., using cognitive reappraisal or attentional control) and that provide strategies to do so (e.g., "When you feel an urge to smoke, think about the health consequences"). The corpus for this condition is 100 messages composed by a large, independent sample of mTurk smokers and validated by a team of RAs trained to 0.8 reliability on ratings of plausibility AND effortful cognitive inhibition or control.
In addition to the texting, participants will complete biweekly online "booster" sessions using Qualtrics with a custom, personalized link sent to the participant via email and text.
Up-regulation of goal energizationBehavioural
In the up-regulation of goal energization condition, participants will be sent messages that encourage them to consider the core values that drive their desire to quit smoking. These messages will name a specific core value that the participant rated in the top three (of 19) during the baseline session, and will draw a connection between quitting and the core value. For example, a message for a person who nominated "family" as one of her top three core values might read, "Quitting will help you model a healthy lifestyle for your family." This intervention is grounded in robust theory and evidence supporting Self-Affirmation Theory. The corpus for this condition is 100 messages composed by a large, independent sample of mTurk smokers and validated by a team of RAs trained to 0.8 reliability in correctly identifying to which core value the message is tied.
In addition to the texting, participants will complete biweekly online "booster" sessions using Qualtrics.
| Study group | Role | What they receive |
|---|---|---|
| High-level construal | Experimental | Participants will be sent messages asking them to imagine what their lives will look like in the future if they succeed ("What would quitting mean to you and your family's future?"; Yeager et al., 2014). Receives: Behavioral: High-level construal |
| Effortful down-regulation of craving for cigarettes | Experimental | Participants will be sent messages that encourage inhibitory control of cravings for cigarettes (e.g., using cognitive reappraisal or attentional control) and that provide strategies to do so (e.g., "When you feel an urge to smoke, think about the health consequences"). Receives: Behavioral: Down-regulation of craving for cigarettes |
| Up-regulation of goal energization | Experimental | Participants will be sent messages that encourage them to consider the core values that drive their desire to quit smoking. Receives: Behavioral: Up-regulation of goal energization |
What is being measured
The primary outcome is the main question the study is designed to answer.
Aim 1: Neural similarity at baseline among the proposed psychological mechanisms
Neural similarity as indexed by Pearson's correlations derived from the similarity matrices produced by Representational Similarity Analysis. The correlation is among the vectorized 3D images representing the patterns of BASELINE functional neural activity related to (a) high-level construal, (b) down-regulation, and (c) up-regulation of goal energization. There will be 3 correlations in total (a with b, a with c, and b with c).
Measured: At baseline
Aim 1: Neural similarity in pre-post change among the proposed psychological mechanisms
Neural similarity as indexed by Pearson's correlations derived from the similarity matrices produced by Representational Similarity Analysis. The correlation is among the vectorized 3D images representing the patterns of PRE-TO-POST CHANGE in the functional neural activity related to (a) high-level construal, (b) down-regulation, and (c) up-regulation of goal energization. There will be 3 correlations in total (a with b, a with c, and b with c).
Measured: 56 days after the baseline session
Aim 2: Correlation of pattern representation of high-level construal with survey measure
Correlation between the similarity matrices produced by Representational Similarity Analysis and the self-report measures assessed at baseline. The measure is the Pearson's correlation between (a) the vectorized 3D image representing the patterns of baseline functional neural activity related to high-level construal and (b) the Levels of Personal Agency Questionnaire. The Outcome is the Pearson's r between (a) and (b).
Measured: Within two weeks of enrollment
Aim 2: Degree of prediction success of change in smoking from surveys
Cross-validated machine learning (ML) prediction of endpoint (56-day) smoking quantity in terms of cigarettes per day based on responses to baseline responses to the Levels of Personal Agency Questionnaire. Degree of prediction will be expressed in Pearson's r correlation between (a) actual # of cigarettes per day at endpoint and (b) ML-predicted # of cigarettes per day.
Measured: 56 days after the baseline session
Aim 2: Prediction success of change in smoking from task data
Cross-validated machine learning prediction of endpoint (56-day) smoking quantity in terms of cigarettes per day based on responses to behavioral performance on the Construal Level Task as measured by the difference in response time in milliseconds between in the high- and low-level conditions. Degree of prediction will be expressed in Pearson's r correlation units.
Measured: 56 days after the baseline session
Aim 2: Prediction of craving ratings from multivariate representations of high-level construal
Cross-validated machine learning prediction of baseline craving ratings during reactivity to personalized cigarette smoking cues based on multivariate neural representation of high-level construal. Ratings are on a 1 to 5 scale from "no craving" to "extreme craving". Degree of prediction will be expressed in Pearson's r units. Higher r values indicate better prediction of craving ratings.
Measured: Within two weeks of enrollment
Secondary outcomes (2)
Aim 3: Effect size of high-level construal on smoking at endpoint
Difference in baseline-to-endpoint change in cigarettes per day among the three conditions.
Measured: 56 days after the baseline session
Aim 3: Time-series of the effect size of high-level construal on smoking across the training period
Trajectory of the group difference of change in cigarettes per day from the baseline assessment.
Measured: Inclusive of days 1-56 of the training period
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Nov 2020
- Study start11 Oct 2021
- Primary completion20 Aug 2025
- Study completion5 Nov 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (97)Papers the sponsor has linked to this study.
- Other trials for Smoking CessationStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Basic science
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Triple blind
- Who is masked
- Participant, Care provider, Outcomes assessor
- Enrolment
- 300 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Oregon
- Sponsor type
- University, hospital or other
- Collaborators
- Ohio State University
- Responsible party
- Principal investigator, Elliot Berkman, University of Oregon
- Investigators
- Elliot T Berkman, Ph.D., Principal investigator, University of Oregon
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04620915
- Sponsor's protocol ID
- EPCS27942
- Status last verified
- Jul 2026
- First submitted
- 27 Apr 2020
- Last updated
- 21 Jul 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Armitage CJ. Efficacy of a brief worksite intervention to reduce smoking: the roles of behavioral and implementation intentions. J Occup Health Psychol. 2007 Oct;12(4):376-90. doi: 10.1037/1076-8998.12.4.376.
PubMed 17953496Bakermans-Kranenburg MJ, van IJzendoorn MH. The hidden efficacy of interventions: genexenvironment experiments from a differential susceptibility perspective. Annu Rev Psychol. 2015 Jan 3;66:381-409. doi: 10.1146/annurev-psych-010814-015407. Epub 2014 Aug 11.
PubMed 25148854Barratt, E.S. (1994). Impulsiveness and Aggression. In Monahan, J., and H.J. Steadman (Eds.), Violence and Mental Disorder: Developments in Risk Assessment (pp. 61-79). University of Chicago Press, Chicago, IL.
SRNT Subcommittee on Biochemical Verification. Biochemical verification of tobacco use and cessation. Nicotine Tob Res. 2002 May;4(2):149-59. doi: 10.1080/14622200210123581. No abstract available.
PubMed 12028847Benowitz NL, Kuyt F, Jacob P 3rd. Influence of nicotine on cardiovascular and hormonal effects of cigarette smoking. Clin Pharmacol Ther. 1984 Jul;36(1):74-81. doi: 10.1038/clpt.1984.142.
PubMed 6734053Berkman ET, Dickenson J, Falk EB, Lieberman MD. Using SMS text messaging to assess moderators of smoking reduction: Validating a new tool for ecological measurement of health behaviors. Health Psychol. 2011 Mar;30(2):186-94. doi: 10.1037/a0022201.
PubMed 21401252Berkman ET, Falk EB. Beyond Brain Mapping: Using Neural Measures to Predict Real-World Outcomes. Curr Dir Psychol Sci. 2013 Feb;22(1):45-50. doi: 10.1177/0963721412469394.
PubMed 24478540Giuliani NR, Berkman ET. Craving is an Affective State and Its Regulation Can Be Understood in Terms of the Extended Process Model of Emotion Regulation. Psychol Inq. 2015;26(1):48-53. doi: 10.1080/1047840X.2015.955072. No abstract available.
PubMed 25780321Berkman ET, Lieberman MD. Using Neuroscience to Broaden Emotion Regulation: Theoretical and Methodological Considerations. Soc Personal Psychol Compass. 2009 Jul 1;3(4):475-493. doi: 10.1111/j.1751-9004.2009.00186.x.
PubMed 24052803Berkman ET, Livingston JL, Kahn LE. Finding the "self" in self-regulation: The identity-value model. Psychol Inq. 2017;28(2-3):77-98. doi: 10.1080/1047840X.2017.1323463. Epub 2017 Aug 18.
PubMed 30774280Berkman ET, Falk EB, Lieberman MD. In the trenches of real-world self-control: neural correlates of breaking the link between craving and smoking. Psychol Sci. 2011 Apr;22(4):498-506. doi: 10.1177/0956797611400918. Epub 2011 Mar 4.
PubMed 21378368Berkman ET, Kahn LE, Merchant JS. Training-induced changes in inhibitory control network activity. J Neurosci. 2014 Jan 1;34(1):149-57. doi: 10.1523/JNEUROSCI.3564-13.2014.
PubMed 24381276Berridge KC, Robinson TE. Parsing reward. Trends Neurosci. 2003 Sep;26(9):507-13. doi: 10.1016/S0166-2236(03)00233-9.
PubMed 12948663Brewer JA, Elwafi HM, Davis JH. Craving to quit: psychological models and neurobiological mechanisms of mindfulness training as treatment for addictions. Psychol Addict Behav. 2013 Jun;27(2):366-79. doi: 10.1037/a0028490. Epub 2012 May 28.
PubMed 22642859Buhle JT, Silvers JA, Wager TD, Lopez R, Onyemekwu C, Kober H, Weber J, Ochsner KN. Cognitive reappraisal of emotion: a meta-analysis of human neuroimaging studies. Cereb Cortex. 2014 Nov;24(11):2981-90. doi: 10.1093/cercor/bht154. Epub 2013 Jun 13.
PubMed 23765157
Study at a glance
From the registry record, last updated by the sponsor on 21 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- High-level Construal as a Novel Pathway for Affect Regulation and Cancer Control
- ClinicalTrials.gov ID
- NCT04620915
- Acronym / sponsor ID
- EPCS27942
- Conditions
- Smoking Cessation, Smoking Reduction, Cancer
- Keywords
- Smoking, Construal level, Cigarettes, Quitting
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 300 participants (actual)
- Lead sponsor
- University of OregonUniversity, hospital or other
- Collaborators
- Ohio State University
- Study start
- 11 Oct 2021 (actual)
- Primary completion
- 20 Aug 2025 (actual)
- Study completion
- 5 Nov 2025 (actual)
- First posted
- 9 Nov 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The objective of the proposed research is to conduct a longitudinal experiment on the neurocognitive pathways and individual differences in high-level construal for affect regulation and smoking cessation. The population is adult smokers aged 25-55 who have tried and failed to quit and who are experiencing poverty. The primary endpoints are (a) the similarity in neural representation of high-level construal to one of two candidate pathways, (b) the presence of meaningful individual differences in the neural representation of high-level construal, and (c) as a secondary endpoint, the effect size of the high-level construal condition on smoking as measured by cigarettes per day.
Each of these endpoints corresponds to a specific null hypothesis. The null hypothesis for the first endpoint is that high-level construal is not significantly different in its neural representation from down-regulation of craving, which would suggest that high-level construal does not operate through distinct mechanisms from traditional treatments. The null hypothesis for the second endpoint is that the between-subjects variability in the neural representation of construal level does not significantly relate to relevant individual differences measures (e.g., traits, task behavior), which would suggest that individual differences are not meaningfully related to outcomes. Finally, the null hypothesis for the secondary endpoint is that the magnitude of the effect of high-level construal on smoking as measured by reductions in average cigarettes per day is not significantly greater than in the other conditions, which would suggest that the efficacy of the high-level construal condition is not significantly greater than a standard text-messaging intervention.
The primary endpoints will be assessed at baseline and change from pre-to-post training (8 weeks).
Detailed description
OVERVIEW:
The proposed work will achieve the three specific aims (two confirmatory, one exploratory) in the context of a 3-arm translational experiment. Assessments of neurocognitive mechanisms of high-level construal, as well as of two candidate pathways, will be completed at baseline and endpoint sessions. The 300 participants enrolled in the study will complete a multimodal battery that will assess neural, behavioral, and self-report indices relating to the three processes of interest - construal level, down-regulation of craving, and up-regulation of goal energization - and then are randomized to one of three experimental conditions related to those processes. This design is highly advantageous because it allows for the establishment of the mechanisms of the construal-level intervention, to compare them with the mechanisms of the other two processes, and to test whether, and to what extent, our potentially novel affect regulation strategy engages and alters those mechanisms (Aim 1); and to identify individual differences in the effects of that novel strategy (high-level construal) on patterns of brain activation, affect regulation, and cessation outcomes (Aim 2). Though the translational experiment design is not intended to be an intervention per se (because the evidence base does not yet support a full-scale trial and materials for such an intervention still need to be developed), the investigators will nonetheless quantify the effect size of high-level construal on changes in smoking so future RCTs have that information and can be adequately powered to detect an effect.
ASSIGNMENT OF PARTICIPANTS TO CONDITION:
Participants will be randomly assigned to a condition using the randomizer function in the RedCap participant tracking and management software. This assignment will happen only after participants are screened, consented, enrolled, and complete the baseline session. In other words, all 300 participants will be treated in exactly the same way through the end of the baseline session, and only at that point will RedCap be used to assign participants to their condition. All participants will have equal probability of being assigned to the conditions (i.e., 33.33% chance of assignment to each). The study coordinator will know which participant is enrolled in each condition, but researchers involved in data analysis (i.e., Drs. Berkman, Fujita, Chavez, and Weston, as well as the graduate students) as well as the research assistants who interact with the participants will be blind to condition during data gathering and analysis.
METHODS FOR SAMPLE SIZE CALCULATION AND DATA ANALYSIS:
The method for selecting the sample size was based on a power analysis of the least sensitive test - Aim 2. The key statistical tests for the three aims are as follows. For Aim 1, the test of neural similarity between conditions is essentially a paired-samples t-test on similarity scores (e.g., pattern correlations calculated within subjects). This is a high-powered comparison because the covariance within subjects of the scores is high. For Aim 2, the individual difference analyses are between-subjects correlations and regression (or partial regression or logistic regression) coefficients relating neural similarity to affect regulation scores, responses to trait and individual difference surveys, and smoking behavior as measured by cigarettes per day. This family of test has relatively low power because it is entirely between subjects. For Exploratory Aim 3, the key test is the condition-by-time interaction (i.e., differences among the groups in change in smoking behavior from pre-to-post training). This test is a within-between (sometimes called "mixed") ANOVA analysis that is more powerful that the individual difference analyses for Aim 2 but less powerful than the fully within-subjects tests for Aim 1.
INTERVENTION CONTENT:
The content for all three training arms is a set of brief (<160 character) messages designed to enable participants to practice one specific affect regulation strategy (experimental arms). In brief, all messages in the experimental arms are generated by a large group of mTurk workers who are smokers; the process of message generation and validation has already begun. During the award period the investigators will add even more messages to the corpus and validate them. In the high-level construal condition, workers compose messages that encourage thinking about purpose of quitting and future goals (e.g., "What would quitting mean to you and your future?"). In the down-regulation of craving condition, workers compose messages that encourage effortful inhibitory or attentional control of cravings (e.g., "When you feel an urge to smoke, think about the health consequences"). And in the up-regulation of goal energization condition, workers compose messages that tie one specific core value (which the mTurk worker ranked as within his or her top three core values) to the goal of quitting (e.g., for the core value of "family", a message might be, "Quitting will help you model a healthy lifestyle for your family"). The content for the up-regulation of goal energization condition is matched to participants' own top three core values.
INTERVENTION DELIVERY:
All participants receive text messages and complete biweekly online "booster" sessions for 8 weeks.
Beginning on their quit date, participants will be sent messages via SMS text messaging 5 times each day for 28 consecutive days, then 4 times each day for the following 28 days. The investigators chose to increase the messaging frequency in the first month of cessation given the higher likelihood of relapse during this period. The order of the messages will be pseudo-randomized such that each message will be seen no more than three times across the 8-week training period, separated by at least 10 days. The timing of the messages will be adjusted for each participant to be evenly spaced starting at wake-up and ending 15 minutes before bedtime and adjusting for weekday/weekend differences. Participants will reply to each message and use a 5-point scale to rate its perceived helpfulness. Participants can also text "SOS" to the system at any point to initiate support via text if they feel tempted to smoke. Daily text messaging is an ideal delivery format for this training because it allows for in vivo participant contact at moments when smoking decisions are being made. Text messaging has very high adoption rates in the United States even among underserved communities that are typically difficult to sample densely for extended durations, and low SES users are comfortable receiving texts throughout the day. The investigators have used text messaging for experience sampling and for theory-based intervention in a community sample (see Preliminary Studies 5 and 6). Participants will provide their mobile phone number at the baseline session; those without a text message-enabled phone or those who do not wish to use their own, will be provided a prepaid phone at the end of the baseline session.
In addition to the text messaging, participants will complete biweekly online "booster" sessions using Qualtrics with a custom, personalized link sent to the participant via email and text. The booster sessions are designed to reinforce the active interventions (high-level construal, goal energization, down-regulation of craving) and provide opportunities to practice the assigned affect regulation strategy. In the sessions, participants will be reminded of their assigned strategy and write brief responses to specific prompts (e.g., "What are two specific ways that quitting now will change your future life?", "Why is quitting important to you today?", and "What are two ways you can change how you think to reduce your craving for cigarettes?"). Participants will also generate triggers to smoking (situations or cues) and practice using down-regulation of craving when they see those triggers. This exercise helps form the habit of deploying the strategy in everyday life. Not all participants have computer access, so, as in previous studies, participants will be provided access in the lab and the research team will work with the local library system to ensure all study sites are accessible from their computers.
BOOSTER COMPLETION AND RETENTION:
Dr. Berkman is currently using similar "booster" sessions, which are programmed in and are delivered via Qualtrics, in a current translational experiment on healthy eating (R01 CA211224). The automated reminders and links, which can be sent via email and text messaging depending on participant preference, greatly increase completion of the boosters. Together with the reminders, graded incentives (e.g., a monetary bonus for completing >90% of the boosters during the study) have greatly increased completion of the at-home booster sessions.
Study design
- Primary purpose
- Basic science
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Triple blind (participant, care provider, outcomes assessor)
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| High-level construal | Experimental | Behavioral: High-level construalParticipants will be sent messages asking them to imagine what their lives will look like in the future if they succeed ("What would quitting mean to you and your family's future?"; Yeager et al., 2014). |
| Effortful down-regulation of craving for cigarettes | Experimental | Behavioral: Down-regulation of craving for cigarettesParticipants will be sent messages that encourage inhibitory control of cravings for cigarettes (e.g., using cognitive reappraisal or attentional control) and that provide strategies to do so (e.g., "When you feel an urge to smoke, think about the health consequences"). |
| Up-regulation of goal energization | Experimental | Behavioral: Up-regulation of goal energizationParticipants will be sent messages that encourage them to consider the core values that drive their desire to quit smoking. |
Who may qualify
- Ages
- 25 to 55 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult
Key inclusion criteria (15 listed)
- Low-SES
- Persistent smokers: cigarette smokers (at least 10 cigarettes/day for at least 1 year)
- Want to quit but have tried and failed at least once
- Income-to-needs ratio (INR) is less than 2.0, meaning that their household income adjusted for household size is below 200% of the federal poverty line
- Ages 25-55
Key exclusion criteria (0 listed)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| High-level construalIn the high-level construal condition, participants will be sent messages asking them to consider why they are quitting ("What are your main reasons for quitting?") and to imagine what their lives will look like in the future if they succeed ("What would quitting mean to you and your family's future?"; Yeager et al., 2014). The corpus for this condition is 100 messages composed by a large independent sample of mTurk workers who are smokers and validated by a team of RAs trained to 0.8 reliability on ratings of high-level construal. To meet criteria for inclusion, a message must be rated as significantly closer to high-level (vs. low-level) on a rating scale of construal level. In addition to the texting, participants will complete biweekly online "booster" sessions using Qualtrics with a custom, personalized link sent to the participant via email and text. | Behavioural | High-level construal |
| Down-regulation of craving for cigarettesIn the down-regulation of craving condition, participants will be sent messages that encourage inhibitory control of cravings for cigarettes (e.g., using cognitive reappraisal or attentional control) and that provide strategies to do so (e.g., "When you feel an urge to smoke, think about the health consequences"). The corpus for this condition is 100 messages composed by a large, independent sample of mTurk smokers and validated by a team of RAs trained to 0.8 reliability on ratings of plausibility AND effortful cognitive inhibition or control. In addition to the texting, participants will complete biweekly online "booster" sessions using Qualtrics with a custom, personalized link sent to the participant via email and text. | Behavioural | Effortful down-regulation of craving for cigarettes |
| Up-regulation of goal energizationIn the up-regulation of goal energization condition, participants will be sent messages that encourage them to consider the core values that drive their desire to quit smoking. These messages will name a specific core value that the participant rated in the top three (of 19) during the baseline session, and will draw a connection between quitting and the core value. For example, a message for a person who nominated "family" as one of her top three core values might read, "Quitting will help you model a healthy lifestyle for your family." This intervention is grounded in robust theory and evidence supporting Self-Affirmation Theory. The corpus for this condition is 100 messages composed by a large, independent sample of mTurk smokers and validated by a team of RAs trained to 0.8 reliability in correctly identifying to which core value the message is tied. In addition to the texting, participants will complete biweekly online "booster" sessions using Qualtrics. | Behavioural | Up-regulation of goal energization |
Primary outcome
Aim 1: Neural similarity at baseline among the proposed psychological mechanisms
Time frame: At baseline
Neural similarity as indexed by Pearson's correlations derived from the similarity matrices produced by Representational Similarity Analysis. The correlation is among the vectorized 3D images representing the patterns of BASELINE functional neural activity related to (a) high-level construal, (b) down-regulation, and (c) up-regulation of goal energization. There will be 3 correlations in total (a with b, a with c, and b with c).
Aim 1: Neural similarity in pre-post change among the proposed psychological mechanisms
Time frame: 56 days after the baseline session
Neural similarity as indexed by Pearson's correlations derived from the similarity matrices produced by Representational Similarity Analysis. The correlation is among the vectorized 3D images representing the patterns of PRE-TO-POST CHANGE in the functional neural activity related to (a) high-level construal, (b) down-regulation, and (c) up-regulation of goal energization. There will be 3 correlations in total (a with b, a with c, and b with c).
Aim 2: Correlation of pattern representation of high-level construal with survey measure
Time frame: Within two weeks of enrollment
Correlation between the similarity matrices produced by Representational Similarity Analysis and the self-report measures assessed at baseline. The measure is the Pearson's correlation between (a) the vectorized 3D image representing the patterns of baseline functional neural activity related to high-level construal and (b) the Levels of Personal Agency Questionnaire. The Outcome is the Pearson's r between (a) and (b).
Aim 2: Degree of prediction success of change in smoking from surveys
Time frame: 56 days after the baseline session
Cross-validated machine learning (ML) prediction of endpoint (56-day) smoking quantity in terms of cigarettes per day based on responses to baseline responses to the Levels of Personal Agency Questionnaire. Degree of prediction will be expressed in Pearson's r correlation between (a) actual # of cigarettes per day at endpoint and (b) ML-predicted # of cigarettes per day.
Aim 2: Prediction success of change in smoking from task data
Time frame: 56 days after the baseline session
Cross-validated machine learning prediction of endpoint (56-day) smoking quantity in terms of cigarettes per day based on responses to behavioral performance on the Construal Level Task as measured by the difference in response time in milliseconds between in the high- and low-level conditions. Degree of prediction will be expressed in Pearson's r correlation units.
Aim 2: Prediction of craving ratings from multivariate representations of high-level construal
Time frame: Within two weeks of enrollment
Cross-validated machine learning prediction of baseline craving ratings during reactivity to personalized cigarette smoking cues based on multivariate neural representation of high-level construal. Ratings are on a 1 to 5 scale from "no craving" to "extreme craving". Degree of prediction will be expressed in Pearson's r units. Higher r values indicate better prediction of craving ratings.
2 secondary outcomes
Aim 3: Effect size of high-level construal on smoking at endpoint
Time frame: 56 days after the baseline session
Aim 3: Time-series of the effect size of high-level construal on smoking across the training period
Time frame: Inclusive of days 1-56 of the training period
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Jul 2026.
- Background: PubMed 17953496Armitage CJ. Efficacy of a brief worksite intervention to reduce smoking: the roles of behavioral and implementation intentions. J Occup Health Psychol. 2007 Oct;12(4):376-90. doi: 10.1037/1076-8998.12.4.376.
- Background: PubMed 25148854Bakermans-Kranenburg MJ, van IJzendoorn MH. The hidden efficacy of interventions: genexenvironment experiments from a differential susceptibility perspective. Annu Rev Psychol. 2015 Jan 3;66:381-409. doi: 10.1146/annurev-psych-010814-015407. Epub 2014 Aug 11.
- BackgroundBarratt, E.S. (1994). Impulsiveness and Aggression. In Monahan, J., and H.J. Steadman (Eds.), Violence and Mental Disorder: Developments in Risk Assessment (pp. 61-79). University of Chicago Press, Chicago, IL.
- Background: PubMed 12028847SRNT Subcommittee on Biochemical Verification. Biochemical verification of tobacco use and cessation. Nicotine Tob Res. 2002 May;4(2):149-59. doi: 10.1080/14622200210123581. No abstract available.
- Background: PubMed 6734053Benowitz NL, Kuyt F, Jacob P 3rd. Influence of nicotine on cardiovascular and hormonal effects of cigarette smoking. Clin Pharmacol Ther. 1984 Jul;36(1):74-81. doi: 10.1038/clpt.1984.142.
- Background: PubMed 21401252Berkman ET, Dickenson J, Falk EB, Lieberman MD. Using SMS text messaging to assess moderators of smoking reduction: Validating a new tool for ecological measurement of health behaviors. Health Psychol. 2011 Mar;30(2):186-94. doi: 10.1037/a0022201.
- Background: PubMed 24478540Berkman ET, Falk EB. Beyond Brain Mapping: Using Neural Measures to Predict Real-World Outcomes. Curr Dir Psychol Sci. 2013 Feb;22(1):45-50. doi: 10.1177/0963721412469394.
- Background: PubMed 25780321Giuliani NR, Berkman ET. Craving is an Affective State and Its Regulation Can Be Understood in Terms of the Extended Process Model of Emotion Regulation. Psychol Inq. 2015;26(1):48-53. doi: 10.1080/1047840X.2015.955072. No abstract available.
- Background: PubMed 24052803Berkman ET, Lieberman MD. Using Neuroscience to Broaden Emotion Regulation: Theoretical and Methodological Considerations. Soc Personal Psychol Compass. 2009 Jul 1;3(4):475-493. doi: 10.1111/j.1751-9004.2009.00186.x.
- Background: PubMed 30774280Berkman ET, Livingston JL, Kahn LE. Finding the "self" in self-regulation: The identity-value model. Psychol Inq. 2017;28(2-3):77-98. doi: 10.1080/1047840X.2017.1323463. Epub 2017 Aug 18.
- Background: PubMed 21378368Berkman ET, Falk EB, Lieberman MD. In the trenches of real-world self-control: neural correlates of breaking the link between craving and smoking. Psychol Sci. 2011 Apr;22(4):498-506. doi: 10.1177/0956797611400918. Epub 2011 Mar 4.
- Background: PubMed 24381276Berkman ET, Kahn LE, Merchant JS. Training-induced changes in inhibitory control network activity. J Neurosci. 2014 Jan 1;34(1):149-57. doi: 10.1523/JNEUROSCI.3564-13.2014.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Elliot T Berkman, Ph.D. principal investigator
University of Oregon
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing High-level construal, Down-regulation of craving for cigarettes and Up-regulation of goal energization in people with Smoking Cessation and Smoking Reduction, run by University of Oregon at 2 sites in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 15 inclusion and 0 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 21 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Aim 1: Neural similarity at baseline among the proposed psychological mechanisms (time frame: At baseline). The study lists 6 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04620915, which also lists 97 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 21 Jul 2026.