Obesity, ChildhoodBRAKENCT05456516
Study of Brain, Reward, and Kids' Eating
A study testing Food Rating in people with Obesity, Childhood and Eating Behavior, run by Penn State University at 1 site in United States.
Trial summary
Children from rural communities are at greater risk for obesity than children from more urban communities. However, some children are resilient to obesity despite greater exposure to obesogenic influences in rural communities (e.g., fewer community-level physical activity or healthy eating resources). Read more about this study
- Who is it for?
- Ages 8 to 10 yearsHealthy volunteers can take part
- Conditions the study is for
- Obesity, Childhood, Eating Behavior
- What is being tested?
- Food Rating
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 76 participants
- Where
- 1 siteUnited States
- Study dates
- 10 Jan 2023to 30 Dec 2024
- Phase
- Interventional
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
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 8 to 10 years
- All sexes
- Healthy volunteers accepted
- Child
Who may be able to join
None listed.
Who cannot join
- They are not within the age requirements (< than 8 years old or > than 10 years-old at baseline).
- If they are taking cold or allergy medication, or other medications known to influence cognitive function, taste, appetite, or blood flow.
- don't speak English.
- are colorblind.
- has a learning disability, ADHD, language delays, autism or other neurological or psychological conditions.
- has a pre-existing medical condition such as type I or type II diabetes, rheumatoid arthritis, Cushing's syndrome, Down's syndrome, severe lactose intolerance, Prader-Willi syndrome, HIV, cancer, renal failure, or cerebral palsy.
Show all 9Show fewer
- is allergic to foods or ingredients used in the study.
- Parent Exclusion Criteria:
- the parent is unable to attend the study visits
Trial locations and contacts
1 site in 1 country.
United States1 site
Chandlee Laboratory
University Park, Pennsylvania, 16802
About this study
Official title: Neurocognitive and Behavioral Factors That Promote Resiliency to Pediatric Obesity
Children from rural communities are at greater risk for obesity than children from more urban communities. However, some children are resilient to obesity despite greater exposure to obesogenic influences in rural communities (e.g., fewer community-level physical activity or healthy eating resources). Identifying factors that promote this resiliency could inform obesity prevention. Eating habits are learned through reinforcement (e.g., hedonic, familial environment), the process through which environmental food cues become valued and influence behavior. Therefore, understanding individual differences in reinforcement learning is essential to uncovering the causes of obesity. Preclinical models have identified two reinforcement learning phenotypes that may have translational importance for understanding excess consumption in humans: 1) goal-tracking-environmental cues have predictive value; and 2) sign-tracking-environmental cues have predictive and hedonic value (i.e., incentive salience). Sign-tracking is associated with poorer attentional control, greater impulsivity, and lower prefrontal cortex (PFC) engagement in response to reward cues. This parallels neurocognitive deficits observed in pediatric obesity (i.e., worse impulsivity, lower PFC food cue reactivity). The proposed research aims to determine if reinforcement learning phenotype (i.e., sign- and goal-tracking) is 1) associated with adiposity due to its influence on neural food cue reactivity, 2) associated with reward-driven overconsumption and meal intake due to its influence on eating behaviors; and 3) associated with changes in adiposity over 1 year. The investigators hypothesize that goal-tracking will promote resiliency to obesity due to: 1) reduced attribution of incentive salience and greater PFC engagement to food cues; and 2) reduced reward-driven overconsumption. Finally, the investigators hypothesize reinforcement learning phenotype will be associated due to its influence on eating behaviors associated with overconsumption (e.g., larger bites, faster bite rat and eating sped). To test this hypothesis, the investigators will enroll 76, 8-10-year-old children, half with healthy weight and half with obesity based on Centers for Disease Control definitions. Methods will include computer tasks to assess reinforcement learning, dual x-ray absorptiometry to assess adiposity, and neural food cue reactivity from functional near-infrared spectroscopy (fNIRS).
- Conditions
- Obesity, Childhood, Eating Behavior
- Being tested
- Food Rating
- Keywords
- reinforcement learning, fNIRS, food-cue reactivity
- Medical subject headings
- Pediatric Obesity, Feeding Behavior
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Food RatingBehavioural
Children will rate foods on taste, health, and desire to eat. The order in which they rate the food characteristics is randomly assigned and counter-balanced across participants
| Study group | Role | What they receive |
|---|---|---|
| All participants | Other | There is only 1 arm in this study Receives: Behavioral: Food Rating |
What is being measured
The primary outcome is the main question the study is designed to answer.
Child Body Mass Index
child height and weight will be measured
Measured: baseline and 1 year follow-up
Body Composition
The BodPod uses air displacement plethysmography to assess body composition including fat mass and fat-free mass in children
Measured: baseline and 1-year follow-up
Food Intake in Grams During a Standard Meal
Intake in grams from standard meal
Measured: baseline and 1-year follow-up
Food Intake in kcal During a Standard Meal
Intake in kcal during a standard meal
Measured: baseline and 1-year follow-up
Food Intake in Grams During a Snack Buffet When Not Hungry
Intake in grams during a snack buffet using a standard eating in the absence of hunger paradigm (i.e., non-homeostatic intake)
Measured: baseline
Food Intake in kcal During a Snack Buffet When Not Hungry
Intake in kcal during a snack buffet using a standard eating in the absence of hunger paradigm (i.e., non-homeostatic intake)
Measured: baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Jul 2022
- Study start10 Jan 2023
- Primary completion30 Dec 2024
- Study completion30 Dec 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Publications (6)Papers the sponsor has linked to this study.
- Other trials for Obesity, ChildhoodStudies of the same condition, open and under way.
- More trials run by Penn State UniversityThe sponsor's other registered studies.
- 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
- Prevention
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 76 participants (actual)
Sponsor and investigators
- Lead sponsor
- Penn State University
- Sponsor type
- University, hospital or other
- Collaborators
- National Center for Advancing Translational Sciences (NCATS)
- Responsible party
- Principal investigator, Alaina Pearce, Penn State University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05456516
- Sponsor's protocol ID
- STUDY00020463
- Other IDs
- KL2TR002015
- Acronym
- BRAKE
- Status last verified
- Mar 2026
- First submitted
- 6 Jul 2022
- Last updated
- 13 Apr 2026
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: All protocols, methods, and data obtained from this project will be made publicly available following the National Institutes of Health's FAIR principles on Open Science Framework or other sites for data sharing. The final dataset will be published with a persistent identifier to ensure that the dataset will be Findable even if the hosting platforms change. Rich meta-data will be published to ensure the data are Accessible. Where possible, meta-data will use formal and searchable language and terms based on common ontologies so that the data are Interoperable. In order to ensure Reusability, meta-data will include detailed information about the protocols and methods following scientific community standards. Data intended for broader use will be free of identifiers that would permit linkages to individual research participants and variables that could lead to deductive disclosure of individual subjects.
Publications
Pearce AL, Adise S, Roberts NJ, White C, Geier CF, Keller KL. Individual differences in the influence of taste and health impact successful dietary self-control: A mouse tracking food choice study in children. Physiol Behav. 2020 Sep 1;223:112990. doi: 10.1016/j.physbeh.2020.112990. Epub 2020 Jun 4.
PubMed 32505786Pearce AL, Cevallos MC, Romano O, Daoud E, Keller KL. Child meal microstructure and eating behaviors: A systematic review. Appetite. 2022 Jan 1;168:105752. doi: 10.1016/j.appet.2021.105752. Epub 2021 Oct 16.
PubMed 34662600Fuchs BA, Roberts NJ, Adise S, Pearce AL, Geier CF, White C, Oravecz Z, Keller KL. Decision-Making Processes Related to Perseveration Are Indirectly Associated With Weight Status in Children Through Laboratory-Assessed Energy Intake. Front Psychol. 2021 Aug 18;12:652595. doi: 10.3389/fpsyg.2021.652595. eCollection 2021.
PubMed 34489782Rangel A. Regulation of dietary choice by the decision-making circuitry. Nat Neurosci. 2013 Dec;16(12):1717-24. doi: 10.1038/nn.3561. Epub 2013 Nov 22.
PubMed 24270272van Meer F, Charbonnier L, Smeets PA. Food Decision-Making: Effects of Weight Status and Age. Curr Diab Rep. 2016 Sep;16(9):84. doi: 10.1007/s11892-016-0773-z.
PubMed 27473844Colaizzi JM, Flagel SB, Joyner MA, Gearhardt AN, Stewart JL, Paulus MP. Mapping sign-tracking and goal-tracking onto human behaviors. Neurosci Biobehav Rev. 2020 Apr;111:84-94. doi: 10.1016/j.neubiorev.2020.01.018. Epub 2020 Jan 20.
PubMed 31972203
Study at a glance
From the registry record, last updated by the sponsor on 13 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Neurocognitive and Behavioral Factors That Promote Resiliency to Pediatric Obesity
- ClinicalTrials.gov ID
- NCT05456516
- Acronym / sponsor ID
- BRAKE / STUDY00020463
- Conditions
- Obesity, Childhood, Eating Behavior
- Keywords
- reinforcement learning, fNIRS, food-cue reactivity
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 76 participants (actual)
- Lead sponsor
- Penn State UniversityUniversity, hospital or other
- Collaborators
- National Center for Advancing Translational Sciences (NCATS)
- Study start
- 10 Jan 2023 (actual)
- Primary completion
- 30 Dec 2024 (actual)
- Study completion
- 30 Dec 2024 (actual)
- First posted
- 13 Jul 2022 (actual)
- Results
- Posted 13 Apr 2026
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Children from rural communities are at greater risk for obesity than children from more urban communities. However, some children are resilient to obesity despite greater exposure to obesogenic influences in rural communities (e.g., fewer community-level physical activity or healthy eating resources). Identifying factors that promote this resiliency could inform obesity prevention. Eating habits are learned through reinforcement (e.g., hedonic, familial environment), the process through which environmental food cues become valued and influence behavior. Therefore, understanding individual differences in reinforcement learning is essential to uncovering the causes of obesity. Preclinical models have identified two reinforcement learning phenotypes that may have translational importance for understanding excess consumption in humans: 1) goal-tracking-environmental cues have predictive value; and 2) sign-tracking-environmental cues have predictive and hedonic value (i.e., incentive salience). Sign-tracking is associated with poorer attentional control, greater impulsivity, and lower prefrontal cortex (PFC) engagement in response to reward cues. This parallels neurocognitive deficits observed in pediatric obesity (i.e., worse impulsivity, lower PFC food cue reactivity). The proposed research aims to determine if reinforcement learning phenotype (i.e., sign- and goal-tracking) is 1) associated with adiposity due to its influence on neural food cue reactivity, 2) associated with reward-driven overconsumption and meal intake due to its influence on eating behaviors; and 3) associated with changes in adiposity over 1 year. The investigators hypothesize that goal-tracking will promote resiliency to obesity due to: 1) reduced attribution of incentive salience and greater PFC engagement to food cues; and 2) reduced reward-driven overconsumption. Finally, the investigators hypothesize reinforcement learning phenotype will be associated due to its influence on eating behaviors associated with overconsumption (e.g., larger bites, faster bite rat and eating sped). To test this hypothesis, the investigators will enroll 76, 8-10-year-old children, half with healthy weight and half with obesity based on Centers for Disease Control definitions. Methods will include computer tasks to assess reinforcement learning, dual x-ray absorptiometry to assess adiposity, and neural food cue reactivity from functional near-infrared spectroscopy (fNIRS).
Study design
- Primary purpose
- Prevention
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| All participants | Other | Behavioral: Food RatingThere is only 1 arm in this study |
Who may qualify
- Ages
- 8 to 10 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child
Key inclusion criteria (0 listed)
Key exclusion criteria (9 listed)
- They are not within the age requirements (< than 8 years old or > than 10 years-old at baseline).
- If they are taking cold or allergy medication, or other medications known to influence cognitive function, taste, appetite, or blood flow.
- don't speak English.
- are colorblind.
- has a learning disability, ADHD, language delays, autism or other neurological or psychological conditions.
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 |
|---|---|---|
| Food RatingChildren will rate foods on taste, health, and desire to eat. The order in which they rate the food characteristics is randomly assigned and counter-balanced across participants | Behavioural | All participants |
Primary outcome
Child Body Mass Index
Time frame: baseline and 1 year follow-up
child height and weight will be measured
Body Composition
Time frame: baseline and 1-year follow-up
The BodPod uses air displacement plethysmography to assess body composition including fat mass and fat-free mass in children
Food Intake in Grams During a Standard Meal
Time frame: baseline and 1-year follow-up
Intake in grams from standard meal
Food Intake in kcal During a Standard Meal
Time frame: baseline and 1-year follow-up
Intake in kcal during a standard meal
Food Intake in Grams During a Snack Buffet When Not Hungry
Time frame: baseline
Intake in grams during a snack buffet using a standard eating in the absence of hunger paradigm (i.e., non-homeostatic intake)
Food Intake in kcal During a Snack Buffet When Not Hungry
Time frame: baseline
Intake in kcal during a snack buffet using a standard eating in the absence of hunger paradigm (i.e., non-homeostatic intake)
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Apr 2026.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Background: PubMed 32505786Pearce AL, Adise S, Roberts NJ, White C, Geier CF, Keller KL. Individual differences in the influence of taste and health impact successful dietary self-control: A mouse tracking food choice study in children. Physiol Behav. 2020 Sep 1;223:112990. doi: 10.1016/j.physbeh.2020.112990. Epub 2020 Jun 4.
- Background: PubMed 34662600Pearce AL, Cevallos MC, Romano O, Daoud E, Keller KL. Child meal microstructure and eating behaviors: A systematic review. Appetite. 2022 Jan 1;168:105752. doi: 10.1016/j.appet.2021.105752. Epub 2021 Oct 16.
- Background: PubMed 34489782Fuchs BA, Roberts NJ, Adise S, Pearce AL, Geier CF, White C, Oravecz Z, Keller KL. Decision-Making Processes Related to Perseveration Are Indirectly Associated With Weight Status in Children Through Laboratory-Assessed Energy Intake. Front Psychol. 2021 Aug 18;12:652595. doi: 10.3389/fpsyg.2021.652595. eCollection 2021.
- Background: PubMed 24270272Rangel A. Regulation of dietary choice by the decision-making circuitry. Nat Neurosci. 2013 Dec;16(12):1717-24. doi: 10.1038/nn.3561. Epub 2013 Nov 22.
- Background: PubMed 27473844van Meer F, Charbonnier L, Smeets PA. Food Decision-Making: Effects of Weight Status and Age. Curr Diab Rep. 2016 Sep;16(9):84. doi: 10.1007/s11892-016-0773-z.
- Background: PubMed 31972203Colaizzi JM, Flagel SB, Joyner MA, Gearhardt AN, Stewart JL, Paulus MP. Mapping sign-tracking and goal-tracking onto human behaviors. Neurosci Biobehav Rev. 2020 Apr;111:84-94. doi: 10.1016/j.neubiorev.2020.01.018. Epub 2020 Jan 20.
- Individual participant dataSharing planned: Yes. All protocols, methods, and data obtained from this project will be made publicly available following the National Institutes of Health's FAIR principles on Open Science Framework or other sites for data sharing. The final dataset will be published with a persistent identifier to ensure that the dataset will be Findable even if the hosting platforms change. Rich meta-data will be published to ensure the data are Accessible. Where possible, meta-data will use formal and searchable language and terms based on common ontologies so that the data are Interoperable. In order to ensure Reusability, meta-data will include detailed information about the protocols and methods following scientific community standards. Data intended for broader use will be free of identifiers that would permit linkages to individual research participants and variables that could lead to deductive disclosure of individual subjects.
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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.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Food Rating in people with Obesity, Childhood and Eating Behavior, run by Penn State University 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 0 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 13 Apr 2026. 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?
Yes. Results are posted in the registry (first posted 13 Apr 2026). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
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?
Child Body Mass Index (time frame: baseline and 1 year follow-up). 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 NCT05456516, which also lists 6 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 13 Apr 2026.