Using Mobile Technology to Improve Self-Regulation

• Sponsor: Dartmouth-Hitchcock Medical Center (Other)
• Overall Status: Completed
• CT.gov ID: NCT03774433
• Collaborator: National Institutes of Health (NIH) (NIH), National Institute on Drug Abuse (NIDA) (NIH)
• Enrollment: 114
• Location: 1
• Arm: 1
• Actual Duration (Months): 16
• Patients Per Site Per Month: 7.1

Study Details

Study Description

Brief 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 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.

Condition or Disease	Intervention/Treatment	Phase
Self-regulation; Binge Eating; Smoking	Behavioral: Laddr	N/A

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

• Study Type: Interventional
• Actual Enrollment: 114 participants
• Allocation: N/A
• Intervention Model: Single Group Assignment
• Masking: None (Open Label)
• Primary Purpose: Basic Science
• 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
• Actual Study Start Date: Feb 27, 2019
• Actual Primary Completion Date: Jun 29, 2020
• Actual Study Completion Date: Jun 29, 2020

Arms and Interventions

Arm

Intervention/Treatment

Experimental: Laddr All participants in the study will be invited to use Laddr, described in the intervention section.

Behavioral: Laddr; 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.

Outcome Measures

Primary Outcome Measures

1. Rate of Binge Eating Episodes [Binge Eating Sample Only] [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.

2. Rate of Smoking Episodes [Smoking Sample Only] [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.

Eligibility Criteria

Criteria

• Ages Eligible for Study: 18 Years to 50 Years
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: No

Inclusion criteria:

• 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

• 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

Exclusion criteria:

• 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)

• 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

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Center for Technology and Behavioral Health, Dartmouth College	Lebanon	New Hampshire	United States	03766

Sponsors and Collaborators

• Dartmouth-Hitchcock Medical Center
• National Institutes of Health (NIH)
• National Institute on Drug Abuse (NIDA)

Investigators

• Principal Investigator: Lisa A Marsch, PhD, Dartmouth College

Study Documents (Full-Text)

• Study Protocol and Statistical Analysis Plan - Jul 11, 2019

More Information

Publications

None provided.

• Responsible Party: Lisa A. Marsch, Andrew G. Wallace Professor; Director, Center for Technology and Behavioral Health, Dartmouth-Hitchcock Medical Center
• ClinicalTrials.gov Identifier: NCT03774433
• Other Study ID Numbers: 4UH3DA041713-04 D19035; UH3DA041713
• First Posted: Dec 13, 2018
• Last Update Posted: Aug 24, 2021
• Last Verified: Jul 1, 2021

• Individual Participant Data (IPD) Sharing Statement: Yes
• Plan to Share IPD: Yes
• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No
• Keywords provided by Lisa A. Marsch, Andrew G. Wallace Professor; Director, Center for Technology and Behavioral Health, Dartmouth-Hitchcock Medical Center: self-regulation; binge eating; smoking; ecological momentary assessment; mobile sensing; mHealth
• Additional relevant MeSH terms: Bulimia; Binge-Eating Disorder

Study Results

Participant Flow

Recruitment Details	Participants were recruited from online (e.g., Craigslist, Facebook, Google AdWords) between 2/27/19 and 6/29/20.

Arm/Group Title	Laddr
Arm/Group Description	All participants in the study will be invited to use Laddr, described in the intervention section. Laddr: 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.
Period Title: Overall Study
STARTED	114
COMPLETED	100
NOT COMPLETED	14

Baseline Characteristics

Arm/Group Title	Laddr
Arm/Group Description	All participants in the study will be invited to use Laddr, described in the intervention section. Laddr: 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.
Overall Participants	114
Age (Count of Participants)
<=18 years	0 0%
Between 18 and 65 years	114 100%
>=65 years	0 0%
Age (years) [Mean (Full Range) ]
Mean (Full Range) [years]	33.83
Sex: Female, Male (Count of Participants)
Female	65 57%
Male	49 43%
Ethnicity (NIH/OMB) (Count of Participants)
Hispanic or Latino	9 7.9%
Not Hispanic or Latino	105 92.1%
Unknown or Not Reported	0 0%
Race (NIH/OMB) (Count of Participants)
American Indian or Alaska Native	0 0%
Asian	7 6.1%
Native Hawaiian or Other Pacific Islander	0 0%
Black or African American	14 12.3%
White	83 72.8%
More than one race	1 0.9%
Unknown or Not Reported	9 7.9%
Region of Enrollment (Count of Participants)
United States	114 100%

Outcome Measures

1. Primary Outcome

Title	Rate of Binge Eating Episodes [Binge Eating Sample Only]
Description	[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.
Time Frame	28 days

Outcome Measure Data

Analysis Population Description

Participants included completed >10% (at least 12) EMAs.

Arm/Group Title	Laddr
Arm/Group Description	All participants in the study will be invited to use Laddr, described in the intervention section. Laddr: 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.
Measure Participants	50
week 1 (self-reported overeating behavior)	0.256 (0.437)
week 2 (self-reported overeating behavior)	0.210 (0.408)
week 3 (self-reported overeating behavior)	0.219 (0.414)
week 4 (self-reported overeating behavior)	0.205 (0.404)
week 1 (self-reported lost control behavior)	0.170 (0.376)
week 2 (self-reported lost control behavior)	0.167 (0.373)
week 3 (self-reported lost control behavior)	0.135 (0.312)
week 4 (self-reported lost control behavior)	0.148 (0.355)

2. Primary Outcome

Title	Rate of Smoking Episodes [Smoking Sample Only]
Description	[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.
Time Frame	28 days

Outcome Measure Data

Analysis Population Description

Participants included completed >10% (at least 12) EMAs.

Arm/Group Title	Laddr
Arm/Group Description	All participants in the study will be invited to use Laddr, described in the intervention section. Laddr: 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.
Measure Participants	50
Week 1 (self-reported smoking of more than zero cigarettes)	0.841 (0.366)
Week 2 (self-reported smoking of more than zero cigarettes)	0.706 (0.456)
Week 3 (self-reported smoking of more than zero cigarettes)	0.640 (0.480)
Week 4 (self-reported smoking of more than zero cigarettes)	0.606 (0.489)

Adverse Events

Time Frame	Adverse event data were collected between the Baseline and the Follow-Up Assessment. After a participant completed the Baseline Assessment, they would start their 28-day study period. At the end of their 28-day study period, they completed one Follow-Up Assessment.
Arm/Group Title	Laddr
Arm/Group Description	All participants in the study will be invited to use Laddr, described in the intervention section. Laddr: 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.
All Cause Mortality
	Laddr
	Affected / at Risk (%)	# Events
Total	0/114 (0%)
Serious Adverse Events
	Laddr
	Affected / at Risk (%)	# Events
Total	1/114 (0.9%)
Injury, poisoning and procedural complications
Facial Fractures	1/114 (0.9%)
Other (Not Including Serious) Adverse Events
	Laddr
	Affected / at Risk (%)	# Events
Total	1/114 (0.9%)
Blood and lymphatic system disorders
Deep Vein Thrombosis	1/114 (0.9%)

Limitations/Caveats

[Not Specified]

More Information

Certain Agreements

Principal Investigators are NOT employed by the organization sponsoring the study.

There is NOT an agreement between Principal Investigators and the Sponsor (or its agents) that restricts the PI's rights to discuss or publish trial results after the trial is completed.