Using Mobile Technology to Improve Self-Regulation

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.

Inclusion criteria:

- Age 18-50 years

- Understand English sufficiently to provide informed consent

- 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