Using Mobile Technology to Improve Self-Regulation
Condition: Self-regulation; Binge Eating; Smoking
MeSH terms: Bulimia; Binge-Eating Disorder
Study type: Interventional

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.
    

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.
    

Intervention name(s): Laddr
Intervention type(s): Behavioral
Intervention description(s): 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.
Intervention model: Single Group Assignment
Masking: None (Open Label)
Primary purpose: Basic Science
Keywords: self-regulation; binge eating; smoking; ecological momentary assessment; mobile sensing; mHealth