Self-regulationNCT03352713
Using Mobile Technology to Better Understand and Measure 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 extent to which we can engage and manipulate putative targets within the self-regulation domain outside of laboratory settings in samples of smokers and overweight/obese individuals with binge eating disorder. Read more about this study
- Who is it for?
- Ages 21 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
- 185 participants
- Where
- 1 siteUnited States
- Study dates
- 11 Jan 2018to 3 Dec 2018
- 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 21 to 50 years
- All sexes
- No healthy volunteers
- Adult
Who may be able to join
- Age 21-50 years
- Understand English sufficiently to provide informed consent
- Use a smartphone (participants without mobile sensing); proficient with using smartphone and comfort wearing devices (participants with mobile sensing)
- Additional inclusion criteria for binge eating sample:
- 27 ≤ BMI ≤ 45 kg/m2
- Have binge eating disorder according to the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) criteria
Show all 10Show fewer
- Non-smoking (defined as no cigarettes in past 12 months-this includes former and never smokers)
- Additional inclusion criteria for smoking sample:
- Smoke 5 or more tobacco cigarettes/day for past year
- 17 ≤ BMI < 27 kg/m2
Who cannot join
- 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 major psychotic disorders (including schizophrenia and bipolar disorder)
- Current use of any medication for psychiatric reasons (including stimulants and mood stabilizers)
- Current use of prescription pain medications (e.g., Vicodin, oxycodone)
Show all 23Show fewer
- Current use of any medication for smoking
- Exceptions: short-acting nicotine replacement therapy (e.g., gum, lozenge, nasal spray, inhaler)
- Will screen out for Wellbutrin or varenicline
- 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) [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) [will not exclude on online/mobile app weight-loss programs]
- Currently on a special diet for a serious health condition
- Additional exclusion criteria for smoking sample:
- Binge eating behavior according to Questionnaire on Eating and Weight Patterns-5 (QEWP-5) ("yes" to Qs 8 and 9 and for Q10, at least one episode per week for three months).
- - QEWP-5 #8: During the past three months, did you ever eat in a short period of time (for example, a two-hour period) what most people would think was an unusually large amount of food? [yes or no]
- - QEWP-5 #9: During the times when you ate an unusually large amount of food, did you ever feel you could not stop eating or control what or how much you were eating? [yes or no]
- - QEWP-5 #10: During the past three months, how often, on average, did you have episodes like this? That is, eating large amounts of food plus the feeling that your eating was out of control? (There may have been some weeks when this did not happen. Just average those in.) [less than one episode per week, five response options for 1 or more episodes per week]
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 2 Non-lab Study: Using Mobile Technology to Better Understand and Measure Self-Regulation
This study will evaluate the extent to which we can engage and manipulate putative targets within the self-regulation domain outside of laboratory settings in samples of smokers and overweight/obese individuals with binge eating disorder. Fifty smokers and 50 overweight/obese individuals with binge eating disorder will be recruited to participate in a non-lab experimental paradigm in which we will leverage our novel mobile behavioral assessment/intervention technology platform. We will measure and modulate engagement of potential self-regulation targets and collect data in real time and in real-world conditions. Mobile sensing will be added to up to 50 additional participants.
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 of 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, we 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. We 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:
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. We will build on Multiple PI Russ Poldrack's pioneering "Cognitive Atlas" ontology to integrate concepts across divergent literatures to develop an "ontology" of self-regulatory processes. Our 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 we can engage and manipulate putative targets 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. We 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 Lisa Marsch) in which we 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 Dave MacKinnon, we will examine cross-assay validity and cross-context and cross-sample reliability of assays. We 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. We 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=100) and overweight/obese persons with binge eating disorder (n=100) (objectively measured smoking in the former sample and binge eating in the latter sample). We will employ our 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 2 non-lab study led by Multiple PI Marsch.
This phase of the study takes what we learned about self-regulation in the first phase and tests it in two samples that are exemplary for "lapses" in self-regulation: individuals who smoke and overweight/obese individuals with binge eating disorder. We expect 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 study is to determine whether we can shift self-regulation for the ultimate goal (in Aim 4) of targeting 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.
12-item Momentary Self-regulation Questionnaire
Self-reported momentary self-regulation assessed by the momentary self-regulation questionnaire four times daily (morning, early afternoon, late afternoon/evening, and night) over a 14-day period. Each item is scored 1 (not at all) to 5 (extremely). The scale is comprised of four subscales: momentary perseverance, momentary sensation seeking, momentary self-judgment, and momentary mindfulness. Each subscale score is calculated by averaging the responses from three of the scale items. Scores on each subscale range from 1 to 5, with higher subscale scores indicating greater momentary reporting of that facet of self-regulation (perseverance, sensation seeking, self-judgment, or mindfulness).
Measured: 14 days
Secondary outcomes (2)
Binge Eating Episodes [Binge Eating Sample Only]
[Binge eating sample only] Self-reported binge eating episodes assessed four times daily (morning, early afternoon, late afternoon/evening, and night) over a 14-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.
Measured: 14 days
Smoking Episodes [Smoking Sample Only]
[Smoking sample only] Self-reported smoking assessed four times daily (morning, early afternoon, late afternoon/evening, and night) over a 14-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.
Measured: 14 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Nov 2017
- Study start11 Jan 2018
- Primary completion29 Nov 2018
- Study completion3 Dec 2018
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 (2)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
- 185 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), University of Memphis, Ohio State University
- 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
- NCT03352713
- Sponsor's protocol ID
- 5UH2DA041713-03 D18029
- Other IDs
- UH2DA041713
- Status last verified
- Dec 2019
- First submitted
- 21 Nov 2017
- Last updated
- 10 Jan 2020
- 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 or other information that could be linked back to an individual participant) will be generated and made available to the research community as a whole. Before 3/22/2018: Informed consent procedures will ensure that participants are aware and opt into the free sharing of this open data set. Participants may consent to participate in the study without consenting to be included in the open data set, in which case their data will be excluded from the open data set. From 3/22/2018 forward: 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
Eisenberg IW, Bissett PG, Canning JR, Dallery J, Enkavi AZ, Whitfield-Gabrieli S, Gonzalez O, Green AI, Greene MA, Kiernan M, Kim SJ, Li J, Lowe MR, Mazza GL, Metcalf SA, Onken L, Parikh SS, Peters E, Prochaska JJ, Scherer EA, Stoeckel LE, Valente MJ, Wu J, Xie H, MacKinnon DP, Marsch LA, Poldrack RA. Applying novel technologies and methods to inform the ontology of self-regulation. Behav Res Ther. 2018 Feb;101:46-57. doi: 10.1016/j.brat.2017.09.014. Epub 2017 Oct 5.
PubMed 29066077Scherer EA, Metcalf SA, Whicker CL, Bartels SM, Grabinski M, Kim SJ, Sweeney MA, Lemley SM, Lavoie H, Xie H, Bissett PG, Dallery J, Kiernan M, Lowe MR, Onken L, Prochaska JJ, Stoeckel LE, Poldrack RA, MacKinnon DP, Marsch LA. Momentary Influences on Self-Regulation in Two Populations With Health Risk Behaviors: Adults Who Smoke and Adults Who Are Overweight and Have Binge-Eating Disorder. Front Digit Health. 2022 Mar 18;4:798895. doi: 10.3389/fdgth.2022.798895. eCollection 2022.
PubMed 35373179
Study at a glance
From the registry record, last updated by the sponsor on 10 Jan 2020. 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 2 Non-lab Study: Using Mobile Technology to Better Understand and Measure Self-Regulation
- ClinicalTrials.gov ID
- NCT03352713
- Acronym / sponsor ID
- 5UH2DA041713-03 D18029
- 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
- 185 participants (actual)
- Lead sponsor
- Dartmouth-Hitchcock Medical CenterUniversity, hospital or other
- Collaborators
- National Institutes of Health (NIH), National Institute on Drug Abuse (NIDA), University of Memphis, Ohio State University
- Study start
- 11 Jan 2018 (actual)
- Primary completion
- 29 Nov 2018 (actual)
- Study completion
- 3 Dec 2018 (actual)
- First posted
- 24 Nov 2017 (actual)
- Results
- Posted 10 Jan 2020
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 extent to which we can engage and manipulate putative targets within the self-regulation domain outside of laboratory settings in samples of smokers and overweight/obese individuals with binge eating disorder. Fifty smokers and 50 overweight/obese individuals with binge eating disorder will be recruited to participate in a non-lab experimental paradigm in which we will leverage our novel mobile behavioral assessment/intervention technology platform. We will measure and modulate engagement of potential self-regulation targets and collect data in real time and in real-world conditions. Mobile sensing will be added to up to 50 additional participants.
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 of 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, we 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. We 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:
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. We will build on Multiple PI Russ Poldrack's pioneering "Cognitive Atlas" ontology to integrate concepts across divergent literatures to develop an "ontology" of self-regulatory processes. Our 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 we can engage and manipulate putative targets 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. We 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 Lisa Marsch) in which we 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 Dave MacKinnon, we will examine cross-assay validity and cross-context and cross-sample reliability of assays. We 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. We 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=100) and overweight/obese persons with binge eating disorder (n=100) (objectively measured smoking in the former sample and binge eating in the latter sample). We will employ our 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 2 non-lab study led by Multiple PI Marsch.
This phase of the study takes what we learned about self-regulation in the first phase and tests it in two samples that are exemplary for "lapses" in self-regulation: individuals who smoke and overweight/obese individuals with binge eating disorder. We expect 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 study is to determine whether we can shift self-regulation for the ultimate goal (in Aim 4) of targeting 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
- 21 to 50 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult
Key inclusion criteria (10 listed)
- Age 21-50 years
- Understand English sufficiently to provide informed consent
- Use a smartphone (participants without mobile sensing); proficient with using smartphone and comfort wearing devices (participants with mobile sensing)
- Additional inclusion criteria for binge eating sample:
- Additional inclusion criteria for smoking sample:
Key exclusion criteria (23 listed)
- 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 major psychotic disorders (including schizophrenia and bipolar disorder)
- Current use of any medication for psychiatric reasons (including stimulants and mood stabilizers)
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
12-item Momentary Self-regulation Questionnaire
Time frame: 14 days
Self-reported momentary self-regulation assessed by the momentary self-regulation questionnaire four times daily (morning, early afternoon, late afternoon/evening, and night) over a 14-day period. Each item is scored 1 (not at all) to 5 (extremely). The scale is comprised of four subscales: momentary perseverance, momentary sensation seeking, momentary self-judgment, and momentary mindfulness. Each subscale score is calculated by averaging the responses from three of the scale items. Scores on each subscale range from 1 to 5, with higher subscale scores indicating greater momentary reporting of that facet of self-regulation (perseverance, sensation seeking, self-judgment, or mindfulness).
2 secondary outcomes
Binge Eating Episodes [Binge Eating Sample Only]
Time frame: 14 days
Smoking Episodes [Smoking Sample Only]
Time frame: 14 days
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 Jan 2020.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Background: PubMed 29066077Eisenberg IW, Bissett PG, Canning JR, Dallery J, Enkavi AZ, Whitfield-Gabrieli S, Gonzalez O, Green AI, Greene MA, Kiernan M, Kim SJ, Li J, Lowe MR, Mazza GL, Metcalf SA, Onken L, Parikh SS, Peters E, Prochaska JJ, Scherer EA, Stoeckel LE, Valente MJ, Wu J, Xie H, MacKinnon DP, Marsch LA, Poldrack RA. Applying novel technologies and methods to inform the ontology of self-regulation. Behav Res Ther. 2018 Feb;101:46-57. doi: 10.1016/j.brat.2017.09.014. Epub 2017 Oct 5.
- Derived from this study: PubMed 35373179Scherer EA, Metcalf SA, Whicker CL, Bartels SM, Grabinski M, Kim SJ, Sweeney MA, Lemley SM, Lavoie H, Xie H, Bissett PG, Dallery J, Kiernan M, Lowe MR, Onken L, Prochaska JJ, Stoeckel LE, Poldrack RA, MacKinnon DP, Marsch LA. Momentary Influences on Self-Regulation in Two Populations With Health Risk Behaviors: Adults Who Smoke and Adults Who Are Overweight and Have Binge-Eating Disorder. Front Digit Health. 2022 Mar 18;4:798895. doi: 10.3389/fdgth.2022.798895. eCollection 2022.
- Individual participant dataSharing planned: Yes. After completion of the study, a de-identified dataset (i.e., stripped of all codes or other information that could be linked back to an individual participant) will be generated and made available to the research community as a whole. Before 3/22/2018: Informed consent procedures will ensure that participants are aware and opt into the free sharing of this open data set. Participants may consent to participate in the study without consenting to be included in the open data set, in which case their data will be excluded from the open data set. From 3/22/2018 forward: 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 10 inclusion and 23 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 10 Jan 2020. 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 10 Jan 2020). 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?
12-item Momentary Self-regulation Questionnaire (time frame: 14 days). 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 NCT03352713, which also lists 2 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 10 Jan 2020.