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Computerized Response Training Obesity Treatment

Translational Neuroscience: Response Training for Obesity Treatment

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03375853
Acronym
CC
Enrollment
179
Registered
2017-12-18
Start date
2017-07-15
Completion date
2023-09-15
Last updated
2023-09-26

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Feeding and Eating Disorders, Hyperphagia, Obesity

Keywords

Obesity, Dissonance, Response Training, Eating Disorder, Computer-based Training

Brief summary

This project will test whether a food response training intervention produces lasting body fat loss, use objective brain imaging to examine the mechanism of effect of this treatment and investigate the generalizability of the training to non-training foods, and examine factors that should amplify intervention effects to provide a test of the intervention theory. This novel treatment represents a bottom-up implicit training intervention that does not rely on executive control, prolonged caloric deprivation, and expensive clinicians to deliver, like behavioral weight loss treatments that have not produced lasting weight loss. If this computer-based response training intervention produces sustained body fat loss in overweight individuals, it could be easily implemented very broadly at almost no expense, addressing a leading public health problem.

Detailed description

Obesity causes 300,000 US deaths yearly, but most treatments do not result in lasting weight loss. People who show greater brain reward and attention region response, and less inhibitory region response, to high-calorie food images/cues show elevated future weight gain, consistent with the theory that overeating results from a strong approach response to high-calorie food cues paired with a weak inhibitory response. This implies that an intervention that reduces reward and attention region response to such food and increases inhibitory control region response should reduce overeating that is rooted in exposure to pervasive food cues. Computer-based response-inhibition training with high-calorie foods has decreased attentional bias for and intake of the training food, increased inhibitory control, and produced weight loss in overweight participants in 3 proof-of-concept trials, with effects persisting through 6-mo follow-up. A pilot trial found that overweight/obese adults who completed a multi-faceted 4-hr response-inhibition training with high-calorie food images and response-facilitation training with low-calorie food images showed reduced fMRI-assessed reward and attention region response to high-calorie training foods and greater body fat loss than controls who completed a rigorous 4-hr generic response-inhibition/response-facilitation training with non-food images (d=.95), producing a 7% reduction in excess body fat over the 4-wk period. The investigators propose to evaluate a refined and extended version of this response-training intervention. Aim 1: Randomize 180 overweight/obese adults to a 4-wk response training obesity treatment or a generic inhibition training control condition that both include bi-monthly Internet-delivered booster training for a year and a smart phone response training app that can be used when tempted by high-calorie foods, assessing outcomes at pre, post, and at 3-, 6-, and 12-month follow-ups (e.g., % body fat, the primary outcome). Aim 2: Use fMRI to test whether reduced reward and attention region response, and increased inhibitory region response to high-calorie food images used and not used in the response training mediate the effects of the intervention on fat loss. The investigators will also test whether during training participants show acute reductions in reward and attention region response, and increases in inhibitory response to high-calorie training food images to capture the learning process, assess generalizability of the intervention to food images not used in training, and collect behavioral data on mediators. Aim 3: Test whether intervention effects will be stronger for those who show less inhibitory control in response to high-calorie food images, a genetic propensity for greater dopamine signaling in reward circuitry, and greater pretest reward and attention region response, and weaker inhibitory region response to high-calorie food images, based on the theory that response training is more efficacious for those with a strong pre-potent approach tendency to high-calorie foods. During the Covid-19 shelter-at-home order, we will not measure in person only outcomes including BodPod assessments, height and weight measurement for BMI calculation, electrocardiogram (ECG) assessments and fMRI scanning for all participants that have assessments due during this order.

Interventions

BEHAVIORALComputer Based Response Training Weight Loss Intervention

Participants complete four computer based training tasks each visit, over the course of a few lab visits. Participants then perform weekly booster sessions in a more natural home or community environment over the internet using the same computer based training tasks.

BEHAVIORALGeneric Response Training Control Intervention

Participants complete four computer based training tasks each visit, over the course of a few lab visits. Participants then perform weekly booster sessions in a more natural home or community environment over the internet using the same computer based training tasks.

Sponsors

Flinders University
CollaboratorOTHER
University of Exeter
CollaboratorOTHER
Radboud University Medical Center
CollaboratorOTHER
University of Oregon
CollaboratorOTHER
Oregon Research Institute
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
SINGLE (Subject)

Eligibility

Sex/Gender
ALL
Age
18 Years to 38 Years
Healthy volunteers
No

Inclusion criteria

* Body Mass Index Between 25 and 35

Design outcomes

Primary

MeasureTime frameDescription
Body Fat ChangeBaseline, 1 month, 3 months, 6 months, 12 monthsChange in participant's body fat percentage

Secondary

MeasureTime frameDescription
Dietary Restraint, Emotional Eating, and External EatingBaseline, 1 month, 3 months, 6 months, 12 monthsChange in Dietary Restraint, Emotional Eating, and External Eating (aggregate score) as measured by the Dutch Eating Behavior Questionnaire
Change in Disinhibited Eating BehaviorBaseline, 1 month, 3 months, 6 months, 12 monthsChang in Disinhibited Eating as measured by the Three Factor Eating Questionnaire
Change in Eating in the Absence of Hunger BehaviorBaseline, 1 month, 3 months, 6 months, 12 monthsChange in Eating When Not Hungry as measured by the Eating in the Absence of Hunger Questionnaire
Change in Food Addiction BehaviorBaseline, 1 month, 3 months, 6 months, 12 monthsChange in Problematic eating patterns associated with symptoms of addictive behaviors as measured by the Yale Food Addiction Scale
Change in Physical ActivityBaseline, 1 month, 3 months, 6 months, 12 monthsChange in Physical Activity as measured by the Paffenberger Questionnaire
Change in Alcohol Use BehaviorBaseline, 1 month, 3 months, 6 months, 12 monthsChange in Substance use frequency (i.e., number of times per day) for alcohol of participants as measured by the Daily Drinking Questionnaire
Change in Eating Disorder SymptomsBaseline, 1 month, 3 months, 6 months, 12 monthsEating disorder symptoms as measured with the Eating Disorder Diagnostic Interview
Change in Participant Ratings of Unhealthy Food PalatabilityBaseline, 1 monthChange in Participant behavioral response to food pictures, and subjective palatability rating
Change in Participant Ratings of Food Monetary ValueBaseline, 1 monthChange in Participant behavioral response to food pictures, and willingness to pay given dollar amounts (aggregate score) for the pictured food
Change in Food Craving and Liking BehaviorBaseline, 1 month, 3 months, 6 months, 12 monthsChange Participant food craving behaviors as measured by the Food Craving and Liking Scale
Change in Body Mass IndexBaseline, 1 month, 3 months, 6 months, 12 monthsChange in Participant BMI using standard methods of calculation
Change in mean R-Peak AmplitudeBaseline, 1 month, 3 months, 6 months, 12 monthsChange in mean R-Peak Amplitude measured using three-lead ECG using PowerLab 8 Diagnostic Suite
Change in Heart Rate VariabilityBaseline, 1 month, 3 months, 6 months, 12 monthsChange in Heart Rate Variability measured using three-lead ECG using PowerLab 8 Diagnostic Suite
Change in Substance Use BehaviorBaseline, 1 month, 3 months, 6 months, 12 monthsChange in Substance use frequency (i.e., number of times per day) for common recreational drugs of participants as measured by the Daily Drug Taking Questionnaire

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 21, 2026