Self-regulationNCT03774433
Using Mobile Technology to Improve Self-Regulation
A study testing Laddr in people with Self-regulation and Binge Eating, run by Dartmouth-Hitchcock Medical Center at 1 site in United States.
Trial summary
This study will evaluate the degree to which engaging targets produces a desired change in medical regimen adherence (across 4-week interventions) and health behavior among smokers (n=50) and overweight/obese persons with binge eating disorder (n=50) (smoking in the former sample and binge eating in the latter… Read more about this study
- Who is it for?
- Ages 18 to 50 years
- Conditions the study is for
- Self-regulation, Binge Eating, Smoking
- What is being tested?
- Laddr
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 114 participants
- Where
- 1 siteUnited States
- Study dates
- 27 Feb 2019to 29 Jun 2020
- 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 18 to 50 years
- All sexes
- No healthy volunteers
- Adult
Who may be able to join
- Age 18-50 years
- Understand English sufficiently to provide informed consent
- Access to a computer in a setting in which the participant is comfortable providing sensitive information
- Use a smartphone operating system compatible with Laddr
- Additional inclusion criteria for binge eating sample:
- 27 ≤ BMI ≤ 45 kg/m2
Show all 15Show fewer
- Have binge eating disorder according to DSM-5 criteria
- Non-smoking (defined as no cigarettes in past 12 months-this includes former and never smokers)
- Confirmed interest in an eating intervention
- Use a smartphone compatible with Fitbit
- Additional inclusion criteria for smoking sample:
- Smoke 5 or more tobacco cigarettes/day for past year
- 17 ≤ BMI < 27 kg/m2
- Confirmed interest in a smoking quit attempt
- Use a smartphone compatible with the iCO Smokerlyzer
Who cannot join
- Enrolled in Aim 2 study
- Any current substance use disorder
- o Will not exclude based on use of substances
- Currently pregnant or plans to become pregnant in next 3 months
- Lifetime history of mental disorder due to a medical condition
- Lifetime history of major psychotic disorders (including schizophrenia and bipolar disorder)
Show all 25Show fewer
- Current use of prescription pain medications (e.g., Vicodin, oxycodone)
- Current use of any medication for smoking (e.g., Wellbutrin, varenicline)
- o Exceptions: will not screen out for nicotine replacement therapy (e.g., patch, gum, lozenge, nasal spray, inhaler)
- Current use of any medication for weight loss
- Have undergone weight-loss surgery (e.g., gastric bypass, lap band)
- Current nighttime shift work or obstructive sleep apnea
- Note: We will not exclude based on e-cigarette use.
- Additional exclusion criteria for binge eating sample:
- Compensatory behavior (e.g., purging, excessive exercise, fasting)
- o Already excluded as part of the DSM-5 binge eating disorder criteria
- Lost weight in recent past (>10 pounds in past 6 months)
- Currently in a weight-loss program (e.g., Weight Watchers, Jenny Craig)
- o Will ask about, but won't exclude on, online/mobile app weight-loss programs as part of the screener
- Currently on a special diet for a serious health condition
- Currently in therapy with a clinician for binge eating
- Nickel allergy (because Fitbit band contains nickel)
- Additional exclusion criteria for smoking sample:
- Currently in therapy with a clinician for smoking
- Binge eating behavior
Trial locations and contacts
1 site in 1 country.
United States1 site
Center for Technology and Behavioral Health, Dartmouth College
Lebanon, New Hampshire, 03766
About this study
Official title: Applying Novel Technologies and Methods to Inform the Ontology of Self-Regulation - Aim 4 Dartmouth Study: Using Mobile Technology to Improve Self-Regulation
This study will evaluate the degree to which engaging targets produces a desired change in medical regimen adherence (across 4-week interventions) and health behavior among smokers (n=50) and overweight/obese persons with binge eating disorder (n=50) (smoking in the former sample and binge eating in the latter sample). The investigators will employ a novel mobile behavioral assessment/intervention platform to engage targets in these samples, given that (1) it offers self-regulation assessment and behavior change tools via an integrated platform to a wide array of populations, and (2) content within the platform can be quickly modified as needed to better impact targets. This is the fourth and final phase of a study that aims to identify putative mechanisms of behavior change to develop an overarching "ontology" of self-regulatory processes.
This trial builds on NCT03352713.
Read the detailed description
Health risk behavior, including poor diet, physical inactivity, tobacco and other substance use, causes as much as 40% of the illness, suffering, and early death related to chronic diseases. Non-adherence to medical regimens is an important exemplar of the challenges in changing health behavior and its associated impact on health outcomes. Although an array of interventions has been shown to be effective in promoting initiation and maintenance of health behavior change, the mechanisms by which they actually work are infrequently systematically examined. One promising domain of mechanisms to be examined across many populations and types of health behavior is self-regulation. Self-regulation involves identifying one's goals, and maintaining goal-directed behavior. A large scientific literature has identified the role of self-regulation as a potential causal mechanism in promoting health behavior.
Advances in digital technologies have created unprecedented opportunities to assess and modify self-regulation and health behavior. In this project, the investigators plan to use a systematic, empirical process to integrate concepts across the divergent self-regulation literatures to identify putative mechanisms of behavior change to develop an overarching "ontology" of self-regulatory processes.
This multi-year, multi-institution project aims to identify an array of putative psychological and behavioral targets within the self-regulation domain implicated in medical regimen adherence and health behavior. This is in service of developing an "ontology" of self-regulation that will provide structure and integrate concepts across diverse literatures. The investigators aim to examine the relationship between various constructs within the self-regulation domain, the relationship among measures and constructs across multiple levels of analysis, and the extent to which these patterns transcend population and context. The project consists of four primary aims across two phases of funding (UH2 and UH3 phases). Note that Aims 1-3 were conducted under our prior UH2 phase, and the investigators herein include the protocol for Aim 4 to be conducted in the UH3 phase:
Aim 1. Identify an array of putative targets within the self-regulation domain implicated in medical regimen adherence and health behavior across these 3 levels of analysis. The investigators will build on Multiple PI Poldrack's pioneering "Cognitive Atlas" ontology to integrate concepts across divergent literatures to develop an "ontology" of self-regulatory processes. The expert team will catalog tasks in the self-regulation literature, implement tasks via online testing (Mechanical Turk) to rapidly obtain large datasets of self-regulatory function, assess the initial ontology via confirmatory factor analysis and structural equation modeling, and assess and revise the resulting ontology according to neural similarity patterns across tasks (to identify tasks for Aim 2).
Aim 2. Evaluate the extent to which putative targets can be engaged and manipulated within the self-regulation domain both within and outside of laboratory settings. Fifty smokers and 50 overweight/obese persons with binge eating disorder will participate in a lab study (led by Poldrack) to complete the tasks identified under Aim 1. The investigators will experimentally modulate engagement of targets (e.g., stimulus set of highly palatable foods images or tobacco-related images as well as self-regulation interventions). A comparable sampling of 100 persons will participate in a non-lab study (led by Multiple PI Marsch) in which the investigators will leverage our novel mobile-based behavioral assessment/intervention platform to modulate target engagement and collect data in real-world conditions.
Aim 3. Identify or develop measures and methods to permit verification of target engagement within the self-regulation domain. Led by Co-I MacKinnon, the investigators will examine cross-assay validity and cross-context and cross-sample reliability of assays. The investigators will employ discriminant and divergent validation methods and Bayesian modeling to refine an empirically-based ontology of self-regulatory targets (to be used in Aim 4).
Aim 4. The investigators will evaluate the degree to which engaging targets produces a desired change in medical regimen adherence (across 4-week interventions) and health behavior among smokers (n=50 each at Dartmouth and Stanford) and overweight/obese persons with binge eating disorder (n=50 each at Dartmouth and Stanford) (smoking in the former sample and binge eating in the latter sample). The investigators will employ a novel mobile behavioral assessment/intervention platform to engage targets in these samples, given that (1) it offers self-regulation assessment and behavior change tools via an integrated platform to a wide array of populations, and (2) content within the platform can be quickly modified as needed to better impact targets. The proposed project is designed to identify valid and replicable assays of mechanisms of self-regulation across populations to inform an ontology of self-regulation that can ultimately inform development of health behavior interventions of maximal efficacy and potency.
This protocol details the Aim 4 study at Dartmouth led by Multiple PI Marsch.
This phase of the study takes what the investigators learned about self-regulation in the first three phases and applies it in two samples that are exemplary for "lapses" in self-regulation: individuals who smoke and overweight/obese individuals with binge eating disorder. The investigators learned in Aim 2 that many real-world conditions (e.g., temptation, negative affect) may decrease self-regulation, whereas training through the mobile intervention described below may increase self-regulation. The primary purpose of this Aim 4 study is to target self-regulation to impact health behaviors.
- Conditions
- Self-regulation, Binge Eating, Smoking
- Being tested
- Laddr
- Keywords
- self-regulation, binge eating, smoking, ecological momentary assessment, mobile sensing, mHealth
- Medical subject headings
- Self-Control, Bulimia, Smoking
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
LaddrBehavioural
Laddr is an integrated, personalized, web-based self-regulation assessment and behavior change system. It integrates tools that have been shown to be effective for a wide array of behavioral phenomena ranging from substance use and abuse, mental health, risk-taking, chronic pain management, medication adherence, diet, exercise, diabetes and other chronic disease management, and smoking. The organizational structure, functionality and content within Laddr's system centrally embrace these fundamental aspects of behavior change; thus, the Laddr platform is not "diagnosis-specific" but rather enables integrated care for any combination of individuals' goals, needs, and preferences.
| Study group | Role | What they receive |
|---|---|---|
| Laddr | Experimental | All participants in the study will be invited to use Laddr, described in the intervention section. Receives: Behavioral: Laddr |
What is being measured
The primary outcome is the main question the study is designed to answer.
Rate of Binge Eating Episodes [Binge Eating Sample Only]
[Binge eating sample only] Self-reported binge eating episodes are assessed four times daily (morning, early afternoon, late afternoon/evening, and night) over a 28-day period. A binge eating episode is defined as self-reported overeating and loss of control. Overeating is assessed by the question "Since the last prompt, when you ate most recently, did you overeat?" and is scored as 0 (no) or 1 (yes). Loss of control is assessed by the question "When you ate most recently, did you lose control over your eating?" and is scored as 1 (not at all) to 5 (totally), where a 4 or 5 is considered loss of control. We are reporting the mean and standard deviations of the target behavior for each sample by week (i.e., Week 1, Week 2, Week 3, and Week 4). Data were averaged for all assessments each week to calculate the number of binge-eating episodes per week.
Measured: 28 days
Rate of Smoking Episodes [Smoking Sample Only]
[Smoking sample only] Self-reported smoking is assessed four times daily (morning, early afternoon, late afternoon/evening, and night) over a 28-day period. A smoking episode is defined as self-reported smoking of more than zero cigarettes and is assessed by the question "Since the last prompt, how many cigarettes have you smoked?" Participants are asked to input a number into a number field. We are reporting the mean and standard deviations of the target behavior for each sample by week (i.e., Week 1, Week 2, Week 3, and Week 4). Data were averaged for all assessments each week to calculate the number of cigarettes smoked per week.
Measured: 28 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Dec 2018
- Study start27 Feb 2019
- Primary completion29 Jun 2020
- Study completion29 Jun 2020
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 (1)Papers the sponsor has linked to this study.
- Other trials for Self-regulationStudies 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
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 114 participants (actual)
Sponsor and investigators
- Lead sponsor
- Dartmouth-Hitchcock Medical Center
- Sponsor type
- University, hospital or other
- Collaborators
- National Institutes of Health (NIH), National Institute on Drug Abuse (NIDA)
- Responsible party
- Principal investigator, Lisa A. Marsch, Dartmouth-Hitchcock Medical Center
- Investigators
- Lisa A Marsch, PhD, Principal investigator, Dartmouth College
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03774433
- Sponsor's protocol ID
- 4UH3DA041713-04 D19035
- Other IDs
- UH3DA041713
- Status last verified
- Jul 2021
- First submitted
- 11 Dec 2018
- Last updated
- 24 Aug 2021
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: After completion of the study, a de-identified dataset (i.e., stripped of all codes and other information that could be linked back to an individual participant) will be generated and made available to the research community as a whole. Informed consent procedures will ensure that participants are aware that consenting to participate in the study means consenting to inclusion in this open data set.
Publications
Plaitano EG, McNeish D, Bartels SM, Bell K, Dallery J, Grabinski M, Kiernan M, Lavoie HA, Lemley SM, Lowe MR, MacKinnon DP, Metcalf SA, Onken L, Prochaska JJ, Sand CL, Scherer EA, Stoeckel LE, Xie H, Marsch LA. Adherence to a digital therapeutic mediates the relationship between momentary self-regulation and health risk behaviors. Front Digit Health. 2025 Feb 4;7:1467772. doi: 10.3389/fdgth.2025.1467772. eCollection 2025.
PubMed 39981105
Study at a glance
From the registry record, last updated by the sponsor on 24 Aug 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Applying Novel Technologies and Methods to Inform the Ontology of Self-Regulation - Aim 4 Dartmouth Study: Using Mobile Technology to Improve Self-Regulation
- ClinicalTrials.gov ID
- NCT03774433
- Acronym / sponsor ID
- 4UH3DA041713-04 D19035
- Conditions
- Self-regulation, Binge Eating, Smoking
- Keywords
- self-regulation, binge eating, smoking, ecological momentary assessment, mobile sensing, mHealth
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 114 participants (actual)
- Lead sponsor
- Dartmouth-Hitchcock Medical CenterUniversity, hospital or other
- Collaborators
- National Institutes of Health (NIH), National Institute on Drug Abuse (NIDA)
- Study start
- 27 Feb 2019 (actual)
- Primary completion
- 29 Jun 2020 (actual)
- Study completion
- 29 Jun 2020 (actual)
- First posted
- 13 Dec 2018 (actual)
- Results
- Posted 24 Aug 2021
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study will evaluate the degree to which engaging targets produces a desired change in medical regimen adherence (across 4-week interventions) and health behavior among smokers (n=50) and overweight/obese persons with binge eating disorder (n=50) (smoking in the former sample and binge eating in the latter sample). The investigators will employ a novel mobile behavioral assessment/intervention platform to engage targets in these samples, given that (1) it offers self-regulation assessment and behavior change tools via an integrated platform to a wide array of populations, and (2) content within the platform can be quickly modified as needed to better impact targets. This is the fourth and final phase of a study that aims to identify putative mechanisms of behavior change to develop an overarching "ontology" of self-regulatory processes.
This trial builds on NCT03352713.
Detailed description
Health risk behavior, including poor diet, physical inactivity, tobacco and other substance use, causes as much as 40% of the illness, suffering, and early death related to chronic diseases. Non-adherence to medical regimens is an important exemplar of the challenges in changing health behavior and its associated impact on health outcomes. Although an array of interventions has been shown to be effective in promoting initiation and maintenance of health behavior change, the mechanisms by which they actually work are infrequently systematically examined. One promising domain of mechanisms to be examined across many populations and types of health behavior is self-regulation. Self-regulation involves identifying one's goals, and maintaining goal-directed behavior. A large scientific literature has identified the role of self-regulation as a potential causal mechanism in promoting health behavior.
Advances in digital technologies have created unprecedented opportunities to assess and modify self-regulation and health behavior. In this project, the investigators plan to use a systematic, empirical process to integrate concepts across the divergent self-regulation literatures to identify putative mechanisms of behavior change to develop an overarching "ontology" of self-regulatory processes.
This multi-year, multi-institution project aims to identify an array of putative psychological and behavioral targets within the self-regulation domain implicated in medical regimen adherence and health behavior. This is in service of developing an "ontology" of self-regulation that will provide structure and integrate concepts across diverse literatures. The investigators aim to examine the relationship between various constructs within the self-regulation domain, the relationship among measures and constructs across multiple levels of analysis, and the extent to which these patterns transcend population and context. The project consists of four primary aims across two phases of funding (UH2 and UH3 phases). Note that Aims 1-3 were conducted under our prior UH2 phase, and the investigators herein include the protocol for Aim 4 to be conducted in the UH3 phase:
Aim 1. Identify an array of putative targets within the self-regulation domain implicated in medical regimen adherence and health behavior across these 3 levels of analysis. The investigators will build on Multiple PI Poldrack's pioneering "Cognitive Atlas" ontology to integrate concepts across divergent literatures to develop an "ontology" of self-regulatory processes. The expert team will catalog tasks in the self-regulation literature, implement tasks via online testing (Mechanical Turk) to rapidly obtain large datasets of self-regulatory function, assess the initial ontology via confirmatory factor analysis and structural equation modeling, and assess and revise the resulting ontology according to neural similarity patterns across tasks (to identify tasks for Aim 2).
Aim 2. Evaluate the extent to which putative targets can be engaged and manipulated within the self-regulation domain both within and outside of laboratory settings. Fifty smokers and 50 overweight/obese persons with binge eating disorder will participate in a lab study (led by Poldrack) to complete the tasks identified under Aim 1. The investigators will experimentally modulate engagement of targets (e.g., stimulus set of highly palatable foods images or tobacco-related images as well as self-regulation interventions). A comparable sampling of 100 persons will participate in a non-lab study (led by Multiple PI Marsch) in which the investigators will leverage our novel mobile-based behavioral assessment/intervention platform to modulate target engagement and collect data in real-world conditions.
Aim 3. Identify or develop measures and methods to permit verification of target engagement within the self-regulation domain. Led by Co-I MacKinnon, the investigators will examine cross-assay validity and cross-context and cross-sample reliability of assays. The investigators will employ discriminant and divergent validation methods and Bayesian modeling to refine an empirically-based ontology of self-regulatory targets (to be used in Aim 4).
Aim 4. The investigators will evaluate the degree to which engaging targets produces a desired change in medical regimen adherence (across 4-week interventions) and health behavior among smokers (n=50 each at Dartmouth and Stanford) and overweight/obese persons with binge eating disorder (n=50 each at Dartmouth and Stanford) (smoking in the former sample and binge eating in the latter sample). The investigators will employ a novel mobile behavioral assessment/intervention platform to engage targets in these samples, given that (1) it offers self-regulation assessment and behavior change tools via an integrated platform to a wide array of populations, and (2) content within the platform can be quickly modified as needed to better impact targets. The proposed project is designed to identify valid and replicable assays of mechanisms of self-regulation across populations to inform an ontology of self-regulation that can ultimately inform development of health behavior interventions of maximal efficacy and potency.
This protocol details the Aim 4 study at Dartmouth led by Multiple PI Marsch.
This phase of the study takes what the investigators learned about self-regulation in the first three phases and applies it in two samples that are exemplary for "lapses" in self-regulation: individuals who smoke and overweight/obese individuals with binge eating disorder. The investigators learned in Aim 2 that many real-world conditions (e.g., temptation, negative affect) may decrease self-regulation, whereas training through the mobile intervention described below may increase self-regulation. The primary purpose of this Aim 4 study is to target self-regulation to impact health behaviors.
Study design
- Primary purpose
- Basic science
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Laddr | Experimental | Behavioral: LaddrAll participants in the study will be invited to use Laddr, described in the intervention section. |
Who may qualify
- Ages
- 18 to 50 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult
Key inclusion criteria (15 listed)
- Age 18-50 years
- Understand English sufficiently to provide informed consent
- Access to a computer in a setting in which the participant is comfortable providing sensitive information
- Use a smartphone operating system compatible with Laddr
- 27 ≤ BMI ≤ 45 kg/m2
Key exclusion criteria (25 listed)
- Enrolled in Aim 2 study
- Any current substance use disorder
- o Will not exclude based on use of substances
- Currently pregnant or plans to become pregnant in next 3 months
- Lifetime history of mental disorder due to a medical condition
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 |
|---|---|---|
| LaddrLaddr is an integrated, personalized, web-based self-regulation assessment and behavior change system. It integrates tools that have been shown to be effective for a wide array of behavioral phenomena ranging from substance use and abuse, mental health, risk-taking, chronic pain management, medication adherence, diet, exercise, diabetes and other chronic disease management, and smoking. The organizational structure, functionality and content within Laddr's system centrally embrace these fundamental aspects of behavior change; thus, the Laddr platform is not "diagnosis-specific" but rather enables integrated care for any combination of individuals' goals, needs, and preferences. | Behavioural | Laddr |
Primary outcome
Rate of Binge Eating Episodes [Binge Eating Sample Only]
Time frame: 28 days
[Binge eating sample only] Self-reported binge eating episodes are assessed four times daily (morning, early afternoon, late afternoon/evening, and night) over a 28-day period. A binge eating episode is defined as self-reported overeating and loss of control. Overeating is assessed by the question "Since the last prompt, when you ate most recently, did you overeat?" and is scored as 0 (no) or 1 (yes). Loss of control is assessed by the question "When you ate most recently, did you lose control over your eating?" and is scored as 1 (not at all) to 5 (totally), where a 4 or 5 is considered loss of control. We are reporting the mean and standard deviations of the target behavior for each sample by week (i.e., Week 1, Week 2, Week 3, and Week 4). Data were averaged for all assessments each week to calculate the number of binge-eating episodes per week.
Rate of Smoking Episodes [Smoking Sample Only]
Time frame: 28 days
[Smoking sample only] Self-reported smoking is assessed four times daily (morning, early afternoon, late afternoon/evening, and night) over a 28-day period. A smoking episode is defined as self-reported smoking of more than zero cigarettes and is assessed by the question "Since the last prompt, how many cigarettes have you smoked?" Participants are asked to input a number into a number field. We are reporting the mean and standard deviations of the target behavior for each sample by week (i.e., Week 1, Week 2, Week 3, and Week 4). Data were averaged for all assessments each week to calculate the number of cigarettes smoked per week.
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Aug 2021.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Derived from this study: PubMed 39981105Plaitano EG, McNeish D, Bartels SM, Bell K, Dallery J, Grabinski M, Kiernan M, Lavoie HA, Lemley SM, Lowe MR, MacKinnon DP, Metcalf SA, Onken L, Prochaska JJ, Sand CL, Scherer EA, Stoeckel LE, Xie H, Marsch LA. Adherence to a digital therapeutic mediates the relationship between momentary self-regulation and health risk behaviors. Front Digit Health. 2025 Feb 4;7:1467772. doi: 10.3389/fdgth.2025.1467772. eCollection 2025.
- Individual participant dataSharing planned: Yes. After completion of the study, a de-identified dataset (i.e., stripped of all codes and other information that could be linked back to an individual participant) will be generated and made available to the research community as a whole. Informed consent procedures will ensure that participants are aware that consenting to participate in the study means consenting to inclusion in this open data set.
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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.
Lisa A Marsch, PhD principal investigator
Dartmouth College
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Laddr in people with Self-regulation and Binge Eating, run by Dartmouth-Hitchcock Medical Center 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 15 inclusion and 25 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 24 Aug 2021. 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 24 Aug 2021). 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?
Rate of Binge Eating Episodes [Binge Eating Sample Only] (time frame: 28 days). 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 NCT03774433, which also lists 1 linked publication.
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 24 Aug 2021.