Overweight and ObesityNCT03557710
Devaluing Foods to Change Eating Behavior
A study of Overweight and Obesity and Cancer, run by University of Oregon at 1 site in United States.
Trial summary
Excessive eating of energy-dense foods and obesity are risk factors for a range of cancers. There are programs to reduce intake of these foods and weight loss, but the effects of the programs rarely last. Read more about this study
- Who is it for?
- Ages 18 to 60 yearsHealthy volunteers can take part
- Conditions the study is for
- Overweight and Obesity, Cancer
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 253 participants
- Where
- 1 siteUnited States
- Study dates
- 1 May 2018to 30 Jun 2023
- 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 18 to 60 years
- All sexes
- Healthy volunteers accepted
- Adult
Who may be able to join
- overweight to obese range (BMI 25-35)
Who cannot join
- 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 who have been diagnosed with past or current medical, psychiatric, neurological, eating disorders, or are taking psychotropic medications
Show all 9Show fewer
- urine screen to exclude participants who are acutely intoxicated
- screen for handedness
- Beyond these criteria, participants will be recruited without exclusions based on gender, race, or ethnicity, so our sample will reflect the diversity in the local population (Lane County, Oregon) with regard to gender, race, and ethnicity.
Trial locations and contacts
1 site in 1 country.
United States1 site
University of Oregon, Lewis Integrative Sciences Building
Eugene, Oregon, 97403
About this study
Official title: Devaluing Energy-dense Foods for Cancer-control: Translational Neuroscience
Excessive eating of energy-dense foods and obesity are risk factors for a range of cancers. There are programs to reduce intake of these foods and weight loss, but the effects of the programs rarely last. This project tests whether altering the value of cancer-risk foods can create lasting change, and uses neuroimaging to compare the efficacy of two programs to engage the valuation system on a neural level. Results will establish the pathways through which the programs work and suggest specific treatments for individuals based on a personalized profile.
Read the detailed description
Obesity and intake of certain foods increase cancer risk, but the most common treatment (behavioral weight loss programs) rarely produces lasting weight loss and eating behavior change, apparently because caloric restriction increases the reward value of food and prompts energy-sparing adaptations. Interventions that reduce the implicit valuation of cancer-risk foods (e.g., red meats, refined sugar) may be more effective. Emerging data suggest that behavioral response training and cognitive reappraisal training reduce valuation of such foods, which leads to decrease intake of these foods and weight loss. Internalized incentive value is reflected in a ventromedial prefrontal cortex (vmPFC) / orbitofrontal cortex valuation system, which encodes the implicit reward value of food and is central to a reinforcement cycle that perpetuates unhealthy eating. Thus, the vmPFC valuation system is a promising target for intervention because changes to the system might disrupt the unhealthy reinforcement cycle. Interestingly, various interventions influence the vmPFC through distinct pathways. Behavioral training alters motor input to valuation regions, whereas cognitive training relies on lateral prefrontal "top-down" regions. The proposed translational neuroscience experiment will compare the efficacy with which two novel treatments cause lasting change in food valuation, and whether a composite of theory-based baseline individual differences in relevant processes (such as response tendencies and cognitive styles) moderate treatment effects. We will randomize 300 overweight/obese adults who are at risk for eating- and obesity-related cancers to behavioral response training toward healthy foods and away from cancer-risk foods, a cognitive reappraisal intervention focused on cancer-risk foods, or non-food inhibitory control training. Aim 1 compares the efficacy and mechanisms of action of these two interventions to reduce valuation of cancer-risk foods relative to the active control condition, using neural, behavioral, self-report, and physiological measures of the process and outcomes. Aim 2 is to establish the temporal pattern and durability of the effects across time; food intake and habits, body fat, BMI, and waist-to-hip ratio will be measured pre, post, and at 3-, 6-, and 12-month follow-up. Aim 3 uses machine learning to build and validate a low-cost, easy-to-administer composite that predicts whether and for how long an individual is likely to respond to intervention, and to which treatment. We hypothesize that self-report measures specifically related to valuation (e.g., willingness-to-pay) and to intervention-specific pathways to valuation (e.g., behavioral response tendencies, cognitive style) will predict differential response. Discovering these individual differences will provide a practical, low-cost tool to help interventionists "match" a given person to an effective treatment for that person. This project is very innovative because no study has directly compared the distinct and common effects of these treatments on valuation, used brain imaging to study the mechanism of effects, tested whether these interventions produce a lasting change in food valuation and body fat, or built and validated a composite that moderates response.
- Conditions
- Overweight and Obesity, Cancer
- Being tested
- Devaluing energy-dense foods for cancer-control
- Keywords
- eating, overweight, obesity, cancer risk, translational neuroscience, cognitive reappraisal, functional magnetic resonance imaging (fMRI), vmPFC, inhibitory control, valuation
- Medical subject headings
- Overweight, Obesity, Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Devaluing energy-dense foods for cancer-controlBehavioural
Also called Devaluing foods to change eating behavior
A 3-arm randomized controlled trial experiment study over 12 months. At baseline, participants will complete behavioral, neural, and self-report measures related to food, specifically measures of food valuation and of the proximal neural systems hypothesized to be linked to each of the 2 experimental arms. We will also measure food intake and body composition at baseline. Then participants will be randomized to one of 3 arms (2 experimental + 1 active control) for 8 30-min sessions to occur twice weekly at the University of Oregon for 30 days. At endpoint (~1 month following baseline), all behavioral, neural, and self-report measures will be reassessed, as will eating, habit, and body composition measures. Follow-ups at 3, 6, and 12 months will assess all measures except neuroimaging.
| Study group | Role | What they receive |
|---|---|---|
| Behavioral Response Training | Experimental | In Arm 1 of Devaluing energy-dense foods for cancer-control, participants will complete computer delivered versions of the stop-signal, go/no-go, and dot-probe training tasks in 8 30-min biweekly visits to the lab, with breaks between training blocks in which participants sit with their eyes closed to allow consolidation of learning. Participants will also complete a weekly 15-min training task online from home. Total training time = 345 min. Training will involve 100 images of cancer risk foods that participants regularly eat, including red and processed meats; high-sugar foods; heavily salted, smoked, and pickled foods; fries, chips, and snacks with trans-fats, and 100 images of healthy foods that participants rate as palatable, including vegetables, fruits, nuts, and whole grains. Receives: Behavioral: Devaluing energy-dense foods for cancer-control |
| Cognitive Reappraisal Training | Experimental | Arm 2 of the Devaluing energy-dense foods for cancer-control intervention will be delivered via computer-assisted in-person training. Between baseline and endpoint sessions, participants will practice reappraisal on a computer, under close supervision of a facilitator, in 8 30-min twice-weekly individual sessions. During sessions, participants will practice cognitive reappraisal to reduce the value of cancer risk foods. Participants will also practice reappraisal of cancer risk foods on a computer at home, twice weekly for 15 minutes, for a total intervention time of contact of 345 minutes. The facilitator will review homework completed by participants and offer corrective feedback. The home practice is intended to promote generalization of use of this skill in the natural environment. Receives: Behavioral: Devaluing energy-dense foods for cancer-control |
| Generic Response Training | Active comparator | In Arm 3 (active control) of the Devaluing energy-dense foods for cancer-control intervention will be identical in duration and contact time to the behavioral response training described above (345 min total), but will involve nonfood images (birds and flowers), as described in the pilot trial. Participants will be informed that this intervention is designed to improve response inhibition, which should lead to eating change and weight loss given that impulsivity increases the risk for overeating, ensuring the credibility of the control arm. Receives: Behavioral: Devaluing energy-dense foods for cancer-control |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change from Baseline Food Intake at 1 month using dietary assessment tool
Assessed with the Automated Self-Administered 24-Hour (ASA24) Dietary Assessment Tool The National Cancer Institutes's standard self-assessment instrument to comprehensively measure food intake.
Measured: baseline, 1 month
Change from Baseline Food Intake at 1 month, Self-Report Questionnaire
Food-Frequency Questionnaire modified to include cancer risk foods
Measured: baseline, 1 month
Secondary outcomes (19)
Change from Baseline Body Fat Percent at 1 month
Assessed with a BodPod (body pod) air displacement system
Measured: baseline, 1 month
Change from Baseline Body Mass Index at 1 month
Index of body composition based on height and weight
Measured: baseline, 1 month
Change from Baseline Waist-to-Hip Ratio at 1 month
Index of body morphology based on external measurements
Measured: baseline, 1 month
Change from Baseline Food Approach and Avoidance Behavior at 1 month, Self-Report Questionnaire 2
Barratt Impulsivity self-report questionnaire, measuring the construct of impulsivity. There are three subscales: Attentional impulsivity (8 items), motor impulsivity (10 items) non-planning impulsivity (12 items). Participants respond to each item on a 1-to-4 Likert scale and scores are averaged within subscales (yielding three 1-to-4 average scores) then averaged across the three subscales to yield one 1-to-4 overall score. Higher scores indicate higher impulsivity, which is a worse outcome.
Measured: baseline, 1 month
Change from Baseline Food Approach and Avoidance Behavior at 1 month, Self-Report Questionnaire 3
Restraint Scale self-report questionnaire. This questionnaire measures the construct of dietary restraint. There are 2 subscales: concern for dieting and weight fluctuations. Participants answer 6 questions about concern for dieting (1-to-5) that are averaged to create a 1-to-5 score on dieting concern. Dieting concern is expected to be u-shaped in terms of better or worse, where no concern or extreme concern is worse and moderate concern is better. Participants answer 4 questions about weight fluctuations (1-to-5) that are averaged to create a 1-to-5 score for weight fluctuation. Great fluctuation is a worse outcome.
Measured: baseline, 1 month
Change from Baseline Cognitive Tendencies at 1 month, Self-Report Questionnaire 1
Need for Cognition self-report questionnaire, which measures the construct of cognitive engagement and enjoyment of thinking. Participants complete 18 items on a 9-point Likert scale (-4 to +4) and scores are averaged across all items to create a single score that ranges from -4 to +4. Higher scores indicate a better outcome, indicating more enjoyment of thinking processes.
Measured: baseline, 1 month
Change from Baseline Cognitive Tendencies at 1 month, Self-Report Questionnaire 2
Craving Regulation Scale self-report questionnaire, which measures the construct of self-regulation of food cravings. There are 24 items total, with 4 items within each of 6 subscales: avoidance of temptation, controlling temptations, distraction, suppression, goal/rule setting, and goal deliberation. Responses are on a 1-to-5 Likert scale and averaged within subscales to create 6 1-to-5 average ratings. Those six averages are also averaged to create an overall score. Greater scores indicate better self-regulation of craving, which is a desired outcome.
Measured: baseline, 1 month
Change from Baseline Food-related Habitual Behavior at 1 month, Self-report Questionnaire 1
Food version of the Self-Report Habit Index self-report questionnaire. This measures the construct of habitual eating of healthy and unhealthy foods. The scale contains two subscales: healthy foods and unhealthy foods. Each subscale contains 12 items, and responses are on a 1-to-5 Likert scale. Responses are averaged within each subscale to create 1-to-5 average ratings for habitual eating of healthy and unhealthy foods, respectively. The subscales are reported separately and not combined. Greater numbers indicate more habitual eating, so lower averages on the unhealthy subscale and higher averages on the healthy subscale indicate a better outcome.
Measured: baseline, 1 month
Change from Baseline Cancer Risk and Healthy Food Craving and Valuation at 1 month, Self-report Questionnaire 2
Food Craving Inventory self-report questionnaire measuring craving and valuation in dollars per serving of cancer risk and healthy foods. There are 28 items on each subscale (one for craving and one for valuation), and the items are averaged within each subscale. The range of the craving scale is 1-5 (i.e., average of 28 1-to-5 Likert ratings) and the range of the valuation scale is 1-4 (i.e., average of 28 1-to-4 Likert ratings). The subscales are reported separately and not combined. Greater numbers indicate more craving / value of the unhealthy foods, so lower numbers indicate a better outcome.
Measured: baseline, 1 month
Change from Baseline Behavioral Response Biases Toward and Away from Cancer Risk and Healthy Foods at 1 month, Behavioral marker, Task 1
Performance on a standard inhibitory control task (Stop-Signal) with personal risk cues
Measured: baseline, 1 month
Change from Baseline Behavioral Response Biases Toward and Away from Cancer Risk and Healthy Foods at 1 month, Behavioral marker, Task 2
Performance on a standard inhibitory control task (Go/No-Go) with personal risk cues
Measured: baseline, 1 month
Change from Baseline Cognitive Reappraisal of Food at 1 month, Behavioral marker
Performance on a Regulation of Craving Task for Food
Measured: baseline, 1 month
Change from Baseline Valuation of Subjective Value of Various Foods at 1 month, Behavioral marker
Performance on Willingness-to-Pay Task - Food
Measured: baseline, 1 month
Change from Baseline Habitual Response to Food at 1 month, Behavioral marker
Performance on Speeded Cue-Behavior Association Task
Measured: baseline, 1 month
Change from Baseline Behavioral Response Biases Toward and Away from Cancer Risk and Healthy Foods at 1 month, Neural marker, Task 1
Premotor, basal ganglia, dorsal cingulate, and Thalamus Activity during standard inhibitory control task (Stop-Signal) with personal risk cues
Measured: baseline, 1 month
Change from Baseline Behavioral Response Biases Toward and Away from Cancer Risk and Healthy Foods at 1 month, Neural marker, Task 2
Premotor, basal ganglia, dorsal cingulate, and Thalamus Activity during standard inhibitory control task (Go/No-Go) with personal risk cues
Measured: baseline, 1 month
Change from Baseline Cognitive Reappraisal of Food at 1 month, Neural marker
Dorsolateral Prefrontal Cortex and ventrolateral Prefrontal Cortex activity during Regulation of Craving Task for Food
Measured: baseline, 1 month
Change from Baseline Habitual Response to Food at 1 month, Neural marker
Shift from ventral to dorsal striatum activity during Speeded Cue-Behavior Association Task
Measured: baseline, 1 month
Change from Baseline Valuation of Subjective Value of Various Foods at 1 month, Neural marker
Ventromedial prefrontal cortex activity during the Willingness-to-Pay Task - Food
Measured: baseline, 1 month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Jun 2018
- Study start1 May 2018
- Primary completion1 May 2023
- Study completion30 Jun 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (17)Papers the sponsor has linked to this study.
- Other trials for Overweight and ObesityStudies 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
- Treatment
- Allocation
- Randomised
- Intervention model
- Factorial
- Model description
- Quantify the degree to which cognitive and behavioral interventions alter the valuation of cancer-risk foods relative to an active control. We will recruit 300 overweight/obese adults who are at risk for eating- and obesity-related cancers and randomize them to a (a) behavioral response training toward low cancer-risk foods and away from high cancer-risk foods, (b) cognitive reappraisal intervention focused on cancer-risk foods (experimental arms), or (c) non-food inhibitory control training (active control arm). Valuation, our primary mediating process as implicated in the incentive sensitization model, will be measured using behavioral economics tasks and functional magnetic resonance imaging (fMRI) of the vmPFC at pre- and posttraining. Proximal, intervention-specific mediators will also be indexed with fMRI. A final analysis will compare the potency of the intervention-specific neural systems to alter valuation via connectivity to vmPFC.
- Masking
- None (open label)
- Enrolment
- 253 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Oregon
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Elliot Berkman, Ph.D., Principal investigator, University of Oregon
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03557710
- Sponsor's protocol ID
- EPCS24327
- Status last verified
- Nov 2022
- First submitted
- 12 Sep 2017
- Last updated
- 14 Aug 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Berkman ET, Burklund L, Lieberman MD. Inhibitory spillover: intentional motor inhibition produces incidental limbic inhibition via right inferior frontal cortex. Neuroimage. 2009 Aug 15;47(2):705-12. doi: 10.1016/j.neuroimage.2009.04.084. Epub 2009 May 6.
PubMed 19426813Berkman 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 24478540Berkman 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 24381276Giuliani NR, Calcott RD, Berkman ET. Piece of cake. Cognitive reappraisal of food craving. Appetite. 2013 May;64:56-61. doi: 10.1016/j.appet.2012.12.020. Epub 2013 Jan 9.
PubMed 23313699Giuliani NR, Mann T, Tomiyama AJ, Berkman ET. Neural systems underlying the reappraisal of personally craved foods. J Cogn Neurosci. 2014 Jul;26(7):1390-402. doi: 10.1162/jocn_a_00563. Epub 2014 Jan 6.
PubMed 24392892Giuliani NR, Tomiyama AJ, Mann T, Berkman ET. Prediction of daily food intake as a function of measurement modality and restriction status. Psychosom Med. 2015 Jun;77(5):583-90. doi: 10.1097/PSY.0000000000000187.
PubMed 25984820Stice E, Burger K, Yokum S. Caloric deprivation increases responsivity of attention and reward brain regions to intake, anticipated intake, and images of palatable foods. Neuroimage. 2013 Feb 15;67:322-30. doi: 10.1016/j.neuroimage.2012.11.028. Epub 2012 Nov 28.
PubMed 23201365Stice E, Lawrence NS, Kemps E, Veling H. Training motor responses to food: A novel treatment for obesity targeting implicit processes. Clin Psychol Rev. 2016 Nov;49:16-27. doi: 10.1016/j.cpr.2016.06.005. Epub 2016 Jul 21.
PubMed 27498406Stice E, Marti CN, Spoor S, Presnell K, Shaw H. Dissonance and healthy weight eating disorder prevention programs: long-term effects from a randomized efficacy trial. J Consult Clin Psychol. 2008 Apr;76(2):329-40. doi: 10.1037/0022-006X.76.2.329.
PubMed 18377128Stice E, Presnell K, Gau J, Shaw H. Testing mediators of intervention effects in randomized controlled trials: An evaluation of two eating disorder prevention programs. J Consult Clin Psychol. 2007 Feb;75(1):20-32. doi: 10.1037/0022-006X.75.1.20.
PubMed 17295560Stice E, Rohde P, Durant S, Shaw H. A preliminary trial of a prototype Internet dissonance-based eating disorder prevention program for young women with body image concerns. J Consult Clin Psychol. 2012 Oct;80(5):907-16. doi: 10.1037/a0028016. Epub 2012 Apr 16.
PubMed 22506791Stice E, Rohde P, Gau J, Shaw H. An effectiveness trial of a dissonance-based eating disorder prevention program for high-risk adolescent girls. J Consult Clin Psychol. 2009 Oct;77(5):825-34. doi: 10.1037/a0016132.
PubMed 19803563Stice E, Rohde P, Shaw H, Gau J. An effectiveness trial of a selected dissonance-based eating disorder prevention program for female high school students: Long-term effects. J Consult Clin Psychol. 2011 Aug;79(4):500-8. doi: 10.1037/a0024351.
PubMed 21707136Stice E, Yokum S, Burger K, Rohde P, Shaw H, Gau JM. A pilot randomized trial of a cognitive reappraisal obesity prevention program. Physiol Behav. 2015 Jan;138:124-32. doi: 10.1016/j.physbeh.2014.10.022. Epub 2014 Oct 30.
PubMed 25447334
Study at a glance
From the registry record, last updated by the sponsor on 14 Aug 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Devaluing Energy-dense Foods for Cancer-control: Translational Neuroscience
- ClinicalTrials.gov ID
- NCT03557710
- Acronym / sponsor ID
- EPCS24327
- Conditions
- Overweight and Obesity, Cancer
- Keywords
- eating, overweight, obesity, cancer risk, translational neuroscience, cognitive reappraisal, functional magnetic resonance imaging (fMRI), vmPFC
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 253 participants (actual)
- Lead sponsor
- University of OregonUniversity, hospital or other
- Study start
- 1 May 2018 (actual)
- Primary completion
- 1 May 2023 (actual)
- Study completion
- 30 Jun 2023 (actual)
- First posted
- 15 Jun 2018 (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.
Excessive eating of energy-dense foods and obesity are risk factors for a range of cancers. There are programs to reduce intake of these foods and weight loss, but the effects of the programs rarely last. This project tests whether altering the value of cancer-risk foods can create lasting change, and uses neuroimaging to compare the efficacy of two programs to engage the valuation system on a neural level. Results will establish the pathways through which the programs work and suggest specific treatments for individuals based on a personalized profile.
Detailed description
Obesity and intake of certain foods increase cancer risk, but the most common treatment (behavioral weight loss programs) rarely produces lasting weight loss and eating behavior change, apparently because caloric restriction increases the reward value of food and prompts energy-sparing adaptations. Interventions that reduce the implicit valuation of cancer-risk foods (e.g., red meats, refined sugar) may be more effective. Emerging data suggest that behavioral response training and cognitive reappraisal training reduce valuation of such foods, which leads to decrease intake of these foods and weight loss. Internalized incentive value is reflected in a ventromedial prefrontal cortex (vmPFC) / orbitofrontal cortex valuation system, which encodes the implicit reward value of food and is central to a reinforcement cycle that perpetuates unhealthy eating. Thus, the vmPFC valuation system is a promising target for intervention because changes to the system might disrupt the unhealthy reinforcement cycle. Interestingly, various interventions influence the vmPFC through distinct pathways. Behavioral training alters motor input to valuation regions, whereas cognitive training relies on lateral prefrontal "top-down" regions. The proposed translational neuroscience experiment will compare the efficacy with which two novel treatments cause lasting change in food valuation, and whether a composite of theory-based baseline individual differences in relevant processes (such as response tendencies and cognitive styles) moderate treatment effects. We will randomize 300 overweight/obese adults who are at risk for eating- and obesity-related cancers to behavioral response training toward healthy foods and away from cancer-risk foods, a cognitive reappraisal intervention focused on cancer-risk foods, or non-food inhibitory control training. Aim 1 compares the efficacy and mechanisms of action of these two interventions to reduce valuation of cancer-risk foods relative to the active control condition, using neural, behavioral, self-report, and physiological measures of the process and outcomes. Aim 2 is to establish the temporal pattern and durability of the effects across time; food intake and habits, body fat, BMI, and waist-to-hip ratio will be measured pre, post, and at 3-, 6-, and 12-month follow-up. Aim 3 uses machine learning to build and validate a low-cost, easy-to-administer composite that predicts whether and for how long an individual is likely to respond to intervention, and to which treatment. We hypothesize that self-report measures specifically related to valuation (e.g., willingness-to-pay) and to intervention-specific pathways to valuation (e.g., behavioral response tendencies, cognitive style) will predict differential response. Discovering these individual differences will provide a practical, low-cost tool to help interventionists "match" a given person to an effective treatment for that person. This project is very innovative because no study has directly compared the distinct and common effects of these treatments on valuation, used brain imaging to study the mechanism of effects, tested whether these interventions produce a lasting change in food valuation and body fat, or built and validated a composite that moderates response.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Factorial
- Masking
- None (open label)
- Number of arms
- 3
- Model description
- Quantify the degree to which cognitive and behavioral interventions alter the valuation of cancer-risk foods relative to an active control. We will recruit 300 overweight/obese adults who are at risk for eating- and obesity-related cancers and randomize them to a (a) behavioral response training toward low cancer-risk foods and away from high cancer-risk foods, (b) cognitive reappraisal intervention focused on cancer-risk foods (experimental arms), or (c) non-food inhibitory control training (active control arm). Valuation, our primary mediating process as implicated in the incentive sensitization model, will be measured using behavioral economics tasks and functional magnetic resonance imaging (fMRI) of the vmPFC at pre- and posttraining. Proximal, intervention-specific mediators will also be indexed with fMRI. A final analysis will compare the potency of the intervention-specific neural systems to alter valuation via connectivity to vmPFC.
| Arm | Type | Receives |
|---|---|---|
| Behavioral Response Training | Experimental | Behavioral: Devaluing energy-dense foods for cancer-controlIn Arm 1 of Devaluing energy-dense foods for cancer-control, participants will complete computer delivered versions of the stop-signal, go/no-go, and dot-probe training tasks in 8 30-min biweekly visits to the lab, with breaks between training blocks in which participants sit with their eyes closed to allow consolidation of learning. Participants will also complete a weekly 15-min training task online from home. Total training time = 345 min. Training will involve 100 images of cancer risk foods that participants regularly eat, including red and processed meats; high-sugar foods; heavily salted, smoked, and pickled foods; fries, chips, and snacks with trans-fats, and 100 images of healthy foods that participants rate as palatable, including vegetables, fruits, nuts, and whole grains. |
| Cognitive Reappraisal Training | Experimental | Behavioral: Devaluing energy-dense foods for cancer-controlArm 2 of the Devaluing energy-dense foods for cancer-control intervention will be delivered via computer-assisted in-person training. Between baseline and endpoint sessions, participants will practice reappraisal on a computer, under close supervision of a facilitator, in 8 30-min twice-weekly individual sessions. During sessions, participants will practice cognitive reappraisal to reduce the value of cancer risk foods. Participants will also practice reappraisal of cancer risk foods on a computer at home, twice weekly for 15 minutes, for a total intervention time of contact of 345 minutes. The facilitator will review homework completed by participants and offer corrective feedback. The home practice is intended to promote generalization of use of this skill in the natural environment. |
| Generic Response Training | Active comparator | Behavioral: Devaluing energy-dense foods for cancer-controlIn Arm 3 (active control) of the Devaluing energy-dense foods for cancer-control intervention will be identical in duration and contact time to the behavioral response training described above (345 min total), but will involve nonfood images (birds and flowers), as described in the pilot trial. Participants will be informed that this intervention is designed to improve response inhibition, which should lead to eating change and weight loss given that impulsivity increases the risk for overeating, ensuring the credibility of the control arm. |
Who may qualify
- Ages
- 18 to 60 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
Key inclusion criteria (1 listed)
- overweight to obese range (BMI 25-35)
Key exclusion criteria (9 listed)
- 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
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 |
|---|---|---|
| Devaluing energy-dense foods for cancer-controlAlso: Devaluing foods to change eating behaviorA 3-arm randomized controlled trial experiment study over 12 months. At baseline, participants will complete behavioral, neural, and self-report measures related to food, specifically measures of food valuation and of the proximal neural systems hypothesized to be linked to each of the 2 experimental arms. We will also measure food intake and body composition at baseline. Then participants will be randomized to one of 3 arms (2 experimental + 1 active control) for 8 30-min sessions to occur twice weekly at the University of Oregon for 30 days. At endpoint (~1 month following baseline), all behavioral, neural, and self-report measures will be reassessed, as will eating, habit, and body composition measures. Follow-ups at 3, 6, and 12 months will assess all measures except neuroimaging. | Behavioural | Behavioral Response Training, Cognitive Reappraisal Training, Generic Response Training |
Primary outcome
Change from Baseline Food Intake at 1 month using dietary assessment tool
Time frame: baseline, 1 month
Assessed with the Automated Self-Administered 24-Hour (ASA24) Dietary Assessment Tool The National Cancer Institutes's standard self-assessment instrument to comprehensively measure food intake.
Change from Baseline Food Intake at 1 month, Self-Report Questionnaire
Time frame: baseline, 1 month
Food-Frequency Questionnaire modified to include cancer risk foods
19 secondary outcomes
Change from Baseline Body Fat Percent at 1 month
Time frame: baseline, 1 month
Change from Baseline Body Mass Index at 1 month
Time frame: baseline, 1 month
Change from Baseline Waist-to-Hip Ratio at 1 month
Time frame: baseline, 1 month
Change from Baseline Food Approach and Avoidance Behavior at 1 month, Self-Report Questionnaire 2
Time frame: baseline, 1 month
Change from Baseline Food Approach and Avoidance Behavior at 1 month, Self-Report Questionnaire 3
Time frame: baseline, 1 month
Change from Baseline Cognitive Tendencies at 1 month, Self-Report Questionnaire 1
Time frame: baseline, 1 month
Change from Baseline Cognitive Tendencies at 1 month, Self-Report Questionnaire 2
Time frame: baseline, 1 month
Change from Baseline Food-related Habitual Behavior at 1 month, Self-report Questionnaire 1
Time frame: baseline, 1 month
Change from Baseline Cancer Risk and Healthy Food Craving and Valuation at 1 month, Self-report Questionnaire 2
Time frame: baseline, 1 month
Change from Baseline Behavioral Response Biases Toward and Away from Cancer Risk and Healthy Foods at 1 month, Behavioral marker, Task 1
Time frame: baseline, 1 month
Change from Baseline Behavioral Response Biases Toward and Away from Cancer Risk and Healthy Foods at 1 month, Behavioral marker, Task 2
Time frame: baseline, 1 month
Change from Baseline Cognitive Reappraisal of Food at 1 month, Behavioral marker
Time frame: baseline, 1 month
Change from Baseline Valuation of Subjective Value of Various Foods at 1 month, Behavioral marker
Time frame: baseline, 1 month
Change from Baseline Habitual Response to Food at 1 month, Behavioral marker
Time frame: baseline, 1 month
Change from Baseline Behavioral Response Biases Toward and Away from Cancer Risk and Healthy Foods at 1 month, Neural marker, Task 1
Time frame: baseline, 1 month
Change from Baseline Behavioral Response Biases Toward and Away from Cancer Risk and Healthy Foods at 1 month, Neural marker, Task 2
Time frame: baseline, 1 month
Change from Baseline Cognitive Reappraisal of Food at 1 month, Neural marker
Time frame: baseline, 1 month
Change from Baseline Habitual Response to Food at 1 month, Neural marker
Time frame: baseline, 1 month
Change from Baseline Valuation of Subjective Value of Various Foods at 1 month, Neural marker
Time frame: baseline, 1 month
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 14 Aug 2023.
- Background: PubMed 19426813Berkman ET, Burklund L, Lieberman MD. Inhibitory spillover: intentional motor inhibition produces incidental limbic inhibition via right inferior frontal cortex. Neuroimage. 2009 Aug 15;47(2):705-12. doi: 10.1016/j.neuroimage.2009.04.084. Epub 2009 May 6.
- 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 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.
- Background: PubMed 23313699Giuliani NR, Calcott RD, Berkman ET. Piece of cake. Cognitive reappraisal of food craving. Appetite. 2013 May;64:56-61. doi: 10.1016/j.appet.2012.12.020. Epub 2013 Jan 9.
- Background: PubMed 24392892Giuliani NR, Mann T, Tomiyama AJ, Berkman ET. Neural systems underlying the reappraisal of personally craved foods. J Cogn Neurosci. 2014 Jul;26(7):1390-402. doi: 10.1162/jocn_a_00563. Epub 2014 Jan 6.
- Background: PubMed 25984820Giuliani NR, Tomiyama AJ, Mann T, Berkman ET. Prediction of daily food intake as a function of measurement modality and restriction status. Psychosom Med. 2015 Jun;77(5):583-90. doi: 10.1097/PSY.0000000000000187.
- Background: PubMed 23201365Stice E, Burger K, Yokum S. Caloric deprivation increases responsivity of attention and reward brain regions to intake, anticipated intake, and images of palatable foods. Neuroimage. 2013 Feb 15;67:322-30. doi: 10.1016/j.neuroimage.2012.11.028. Epub 2012 Nov 28.
- Background: PubMed 27498406Stice E, Lawrence NS, Kemps E, Veling H. Training motor responses to food: A novel treatment for obesity targeting implicit processes. Clin Psychol Rev. 2016 Nov;49:16-27. doi: 10.1016/j.cpr.2016.06.005. Epub 2016 Jul 21.
- Background: PubMed 18377128Stice E, Marti CN, Spoor S, Presnell K, Shaw H. Dissonance and healthy weight eating disorder prevention programs: long-term effects from a randomized efficacy trial. J Consult Clin Psychol. 2008 Apr;76(2):329-40. doi: 10.1037/0022-006X.76.2.329.
- Background: PubMed 17295560Stice E, Presnell K, Gau J, Shaw H. Testing mediators of intervention effects in randomized controlled trials: An evaluation of two eating disorder prevention programs. J Consult Clin Psychol. 2007 Feb;75(1):20-32. doi: 10.1037/0022-006X.75.1.20.
- Background: PubMed 22506791Stice E, Rohde P, Durant S, Shaw H. A preliminary trial of a prototype Internet dissonance-based eating disorder prevention program for young women with body image concerns. J Consult Clin Psychol. 2012 Oct;80(5):907-16. doi: 10.1037/a0028016. Epub 2012 Apr 16.
- Social and Affective Neuroscience (SAN) Laboratory websiteLink provided by the sponsor.
- Description: Study recruitment websiteLink provided by the sponsor.
- Individual participant dataSharing planned: No
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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 Berkman, Ph.D. principal investigator
University of Oregon
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study of Overweight and Obesity and Cancer, run by University of Oregon at 1 site 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 1 inclusion and 9 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 14 Aug 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site 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?
Change from Baseline Food Intake at 1 month using dietary assessment tool (time frame: baseline, 1 month). The study lists 2 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 NCT03557710, which also lists 17 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 14 Aug 2023.