ClinicalTrials.gg
CompletedNCT04848532REACHUpdated Jun 13, 2025

Problematic Decision-Making and Adolescent Weight Loss

An interventional study of Weight loss treatment in Overweight Adolescents, Overweight or Obesity and Impulsive Behavior, sponsored by Drexel University. Completed at 1 site in United States. Open to participants aged 14 Years to 18 Years. Per ClinicalTrials.gov, last updated 2025-06-13.

Primary conditionObesityRegistry: OverweightReclassifiedWhy we changed it
Registry
Overweight — the first condition term the registry derived for this study.
ClinicalTrials.gg
Obesity
Why
  1. The study's listed conditions name Obesity, a narrower term within Overweight.
Confidence
High: the new condition is named in the study's own listed conditions. Of 351 hand-checked studies reclassified this way, 68% were exactly right and 84% in the right disease family; the registry's first term was right for 5% (measured 2026-10-21). How we classify →
Wrong?
Tell us the study's main condition →

Sponsored by Drexel University · Not applicable, Interventional, and Treatment

Phase
Not applicable
Study type
Interventional
Enrollment
63
Allocation
Not applicable
Ages
14 Years to 18 Years
Sex
All
01

Study summary

This study evaluates the associations between baseline decision-making processes, engagement in problematic dietary practices, and post-intervention weight loss outcomes among adolescents. Results from the study will provide specific direction for what components should comprise future decision-making interventions for adolescents with overweight/obesity.

Read the detailed description

Adolescent overweight and obesity (AOB; i.e., a body mass index (BMI) greater than 85th percentile for age, height, and gender) affects 34.5% of adolescents. Over 80% of obese adolescents will become obese adults and experience increased risk of cardiovascular disease, type 2 diabetes, gallbladder disease, and some forms of cancer. Because of contraindications and hesitations to pursue psychopharmacology or bariatric surgery, behavioral interventions are the first-line treatment for AOB. Unfortunately, adolescent outcomes from pediatric behavioral obesity treatments are poor. In fact, the modal weight loss in behavioral interventions is less than a single BMI point, and many participants lose no weight at all. Outcomes in adolescents are worse than those found in younger children and adults. Notably, the vast majority of existing interventions tested in adolescents are designed for younger children, which may preclude an adolescent's success in these interventions. Successful behavioral AOB interventions may require augmentations that address developmental concerns unique to adolescence. For example, research has shown that, in contrast to younger children, many adolescents are making their own food decisions and are thus more likely to engage in problematic eating behaviors during treatment. As a necessary step towards developing specialized interventions for AOB, it is critical to understand the underlying mechanisms of continued engagement in problematic eating behaviors during AOB interventions.

Three types of problematic eating behaviors are strongly linked (cross-sectionally and longitudinally) with AOB. First, reward-driven overeating (i.e., frequently eating energy-dense foods) results in excess calorie intake, which, in turn, produces adiposity during childhood and adolescence. Second, loss-of-control eating (LOC; the experience of not being able to stop eating once started) is an exceptionally strong predictor of excess weight gain, i.e., an additional 2.4kg per year compared to peers without LOC. Third, rigid dietary restriction involves skipping meals and cutting out food groups for the purposes of weight regulation, but instead results in intense feelings of deprivation. As a result, rigid dietary restriction has the paradoxical effect of calorie overconsumption, excess weight gain, and poor outcomes from pediatric obesity treatment. Taken together, findings indicate that elucidating the drivers of these three problematic eating behaviors is critical to improving AOB treatment outcomes.

An aberrant decision-making framework represents an attractive paradigm for understanding the above-described problematic eating behaviors, especially given that they all run counter to adolescents' intentions and well-being. There are several aberrant decision-making processes endemic to the adolescent developmental period. Three of these processes in particular appear to be directly linked to the three problematic eating behaviors described above. To the extent that aberrant decision-making produces problematic eating behavior, aberrant decision-making can also be hypothesized to predict poor weight loss outcomes. Below, three aberrant decision-making processes and their links to problematic eating behavior are described.

Increased delay discounting. Delay discounting refers to the tendency to discount greater, later rewards in favor of smaller, sooner rewards. A combination of greater sensitivity to reward and slow development of self-regulatory neural processes contributes to especially high discounting rates in some adolescents. Relatively higher discounting rates may produce reward-driven eating, i.e., frequent consumption of energy-dense foods (e.g., high-fat, high sugar foods), while discounting the future reward (e.g., weight loss) that would be derived from forgoing immediate gratification. Indeed, a recent meta-analysis concluded that higher discounting rates were strongly cross-sectionally linked with AOB. Although behavioral weight loss programs discourage consumption of energy-dense foods, psychological strategies for how to prioritize long-term over short-term rewards are not provided. Thus, delay discounting likely contributes to continued reward-driven eating during treatment. However, no studies have tested whether delay discounting predicts reward-driven overeating (and its effect on weight) during AOB treatment.

Affect-driven impulsivity. Affect-driven impulsivity refers to a tendency to choose maladaptive behaviors geared towards the immediate cessation of a negative affective state, despite negative consequences. Affect-driven impulsivity likely drives continued LOC eating during treatment, precluding successful weight loss. Affect-driven impulsivity is a cross-sectional predictor of AOB, but it may be a particularly strong driver of LOC eating because compulsive eating serves the function of reducing distress. Although no studies have compared adolescents with and without LOC on affect-driven impulsivity, adolescents with LOC eating demonstrate overall higher levels of emotional reactivity and emotional eating. LOC eating resulting from affect-driven impulsivity may continue to occur during treatment because little treatment content focuses on skills for tolerating negative affect. Dr. Manasse's work demonstrates that increased affect-driven impulsivity predicts poor outcomes from adult binge eating treatment. However, no studies have examined whether affect-driven impulsivity predicts (1) engagement in LOC during treatment or (2) poor AOB treatment outcomes.

Perseverative decision-making. Perseverative decision-making is characterized by weakened ability to stop engagement in habitual behaviors despite changing contingencies. Highly perseverative decision-making may contribute to repeated engagement in rigid dietary restriction (i.e., setting rigid calorie goals, cutting out specific foods) that increase deprivation. This deprivation, in turn, leads to episodes of overeating that preclude successful caloric restriction. Those who show highly perseverative decision-making continue engaging in this rigid dietary restriction behavior despite the fact that it ultimately delivers the opposite of its intended effect. Indeed, perseverative decision-making and rigid dieting are associated with the presence of LOC eating, and perseveration is cross-sectionally associated with obesity in adolescence. Despite the established links between perseverative decision-making with unhealthy dieting and excess weight, no studies have examined whether perseverative decision-making underlies continued engagement in problematic dietary restriction during treatment and predicts poor outcomes.

To inform the development of tailored intervention approaches, the current study, funded by the National Institutes of Health, aims to elucidate the specific aberrant decision-making processes associated with three problematic eating behaviors and weight loss outcomes. Results from the study will provide specific direction for what components (e.g., strategies for tolerating emotional distress or promoting flexible thinking) should comprise a future decision-making intervention for AOB and for whom (e.g., those with LOC, those who engage in problematic restriction) certain components would be most relevant. Given that LOC eating is a robust predictor of excess weight gain but only 20-30% of those with AOB endorse LOC eating, the study team will oversample individuals with clinically significant LOC, i.e., the study will recruit a total of 80 adolescents (ages 14-18) with overweight/obesity, half of whom (n=40) endorse clinically significant (i.e., at least once weekly) LOC eating and the other half of whom (n=40) endorse subclinical LOC or no LOC. All participants will receive a 16-week group-based, remotely delivered behavioral weight loss intervention and complete a 6-month follow-up. Decision-making measures will be administered at baseline. Problematic eating behaviors and weight will be assessed at all time points.

02

Conditions studied

  • Overweight Adolescents
  • Overweight or Obesity
  • Impulsive Behavior
  • Overeating

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03

In context

Obesity Reclassified

11,522 studies on the registry are indexed under Obesity; 2,033 are open to participants now.

This study's enrollment of 63 is close to the median of 67 across 9,006 interventional studies indexed under Obesity.

Browse Obesity studies →

Lead sponsor

Drexel University is the lead sponsor of 113 studies on the registry; 17 are open to participants now.

Compared within Obesity, this study's primary condition as ClinicalTrials.gg classifies it; the registry's first condition term is Overweight. The counts are of registry records indexed under each term, refreshed daily. How we classify →

04

Who can participate

Ages eligible
14 Years to 18 Years
Sexes eligible
All
Accepts healthy volunteers
No

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  1. Are between 14 and 18 years of age
  2. Have a between the 85th and 99th percentiles for sex and age as determined by the CDC growth charts
  3. Are currently living at home with a parent or guardian
  4. Have at least one parent or guardian who is willing to participate in the study
  5. Are willing to complete baseline assessment tasks
  6. Have a smartphone, are willing to download an app to track food intake and complete surveys on the phone for two seven-day periods throughout the course of the study, and are willing to wear a fitness tracker during these same two week-long periods
  7. Are located in the US and wiling/able to participate in remote intervention and assessments

Exclusion criteria

Exclusion Criteria:

  1. Acute suicide risk
  2. Inability to engage in physical activity (defined as walking two city blocks without stopping)
  3. Have diabetes or a history of bariatric surgery
  4. Current medical or psychiatric condition that may pose a risk to the participant during intervention, cause a change in weight, or limit ability to comply with the program (i.e., bulimia nervosa, substance abuse disorder, psychosis, bipolar I disorder, and/or any condition prohibiting physical activity)
  5. Are pregnant or planning to become pregnant in the next 2 years
  6. Recently began or changed the dose of a medication that can cause significant change in weight
  7. Have experienced weight loss ≥ 5% in the previous 6 months
  8. Are planning to begin in the next 16 months, or are currently participating in, another weight loss treatment or psychotherapy for binge eating and/or weight loss
  9. Are engaging in compensatory vomiting, other severe compensatory behaviors, or more than 12 of any compensatory behaviors in the previous 3 months
  10. Are currently taking medication (e.g., Contrave, Alli, etc.) which is specifically intended for weight loss
Terms in these criteria, in plain language(1)

Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.

BMI (body mass index)

Weight in kilograms divided by height in metres squared. Example: 70 kg and 1.75 m gives 70 ÷ (1.75 × 1.75) ≈ 22.9.

What counts as overweight or obesity differs between countries (some use lower cut-offs), so go by the range the study states.

05

Study design

Phase
Not applicable
Primary purpose
Treatment
Allocation
Not applicable
Intervention model
Single group
Masking
None (open label)
Enrollment
63 participants (actual)

Study arms

  • Experimental
    Adolescent-specific behavioral weight loss treatment

    Behavioral: Weight loss treatment

Interventions

  • BehavioralWeight loss treatment

    The intervention will consist of group-based, weekly or biweekly weight loss coaching (75 minutes per session), which will occur via Zoom videoconferencing software. This intervention is designed to facilitate a 5-10% weight loss and engagement in up to 250 min/week of moderate-to-vigorous physical activity, which is the standard recommendation in lifestyle modification programs for adolescents. Participants will also be asked to download and utilize the smartphone app, Fitbit, to track eating behavior. Weight loss coaches will be experts in lifestyle modification who have graduate degrees in psychology or a related field. Participants will be given guidance on how to reduce your calorie intake (using a balanced deficit diet) and gradually increase your physical activity. Participants will learn to set goals for diet, weight, and physical activity.

    Also known as: Lifestyle modification

06

What researchers measure

Primary outcomes

  1. Percent of 95 percentile BMI

    Time frame: 16 weeks

07

Study locations

1 site
  • Drexel University
    Philadelphia, Pennsylvania 19103, United States
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References and documents

Study documents

PDFs hosted by the registry, ClinicalTrials.gov.

Individual participant data

Plan to share: Undecided

09

Timeline

Tracking since Sep 25, 2026
ElapsedEstimatedEstimated, not yet reachedSimilar studies: half by the dot; the band is the middle halfHalf of similar studies reached it by the dot; the band is the middle half, from a quarter to three quarters

Ran from Feb 2021 to primary completion in Oct 2024, 44 months.

Of 3,680 non-industry interventional studies with no phase under Obesity, half reached primary completion within 23 months of starting (the median), counting those still running; a quarter within 10 and three quarters within 43. This study's 44 months is above that.

Counting every sponsor, half of 3,843 studies reached it within 22 months; a quarter within 10 and three quarters within 42.

How these figures are worked out, and which studies are left out of them.

Registered
Mar 17, 2021
First posted
Apr 19, 2021
StartActual
Feb 3, 2021
Primary completionActual
Oct 15, 2024
CompletionActual
Apr 30, 2025
Last update
Jun 13, 2025
What these dates mean
Start.
When the first participant enrolled; while estimated, when the study expects to open to recruitment.
Primary completion.
When the last participant was examined or treated to collect data for the study's main question, its primary outcome. A study that stopped early gives the date its data collection stopped.
Completion.
When the last participant's last visit took place, for every outcome, secondary ones and side effects included: the end of the study. Often later than primary completion, sometimes the same day.
Actual and Est.
Actual means the registry says the date has happened. Est. (estimated) is a date the sponsor plans or expects. It can still move, and the sponsor is expected to change it to actual once it has passed.
No changes since tracking began. The registry record was last updated on Jun 13, 2025, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT04848532
Lead sponsor
Drexel University
Responsible party
Sponsor
First posted
Apr 19, 2021
Start date
Feb 3, 2021
Primary completion
Oct 15, 2024
Completion
Apr 30, 2025
Last update
Jun 13, 2025

Study contacts

Stephanie Manasse, Ph.D.
principal investigator · Drexel University

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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This study is completed, as verified in Jun 2025. You cannot join it, but the record below documents what was studied.

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