Return of the JITAI: Applying a Just-in-Time Adaptive Intervention Framework to the Development of m-Health Solutions for Addictive Behaviors.

Purpose: Lapses are strong indicators of later relapse among individuals with addictive disorders, and thus are an important intervention target. However, lapse behavior has proven resistant to change due to the complex interplay of lapse triggers that are present in everyday life. It could be possi...

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Published in:International Journal of Behavioral Medicine Vol. 24; no. 5; pp. 673 - 683
Main Authors: Goldstein, Stephanie, Evans, Brittney, Flack, Daniel, Juarascio, Adrienne, Manasse, Stephanie, Zhang, Fengqing, Forman, Evan
Format: research tables/charts Journal Article
Published: Springer Nature Oct2017
Online Access:View this record in EBSCOhost
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      dt: Oct2017
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      pub: Springer Nature
      place: New York, New York
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        atl: Return of the JITAI: Applying a Just-in-Time Adaptive Intervention Framework to the Development of m-Health Solutions for Addictive Behaviors.
      aug:
        au:
          Goldstein, Stephanie
          Evans, Brittney
          Flack, Daniel
          Juarascio, Adrienne
          Manasse, Stephanie
          Zhang, Fengqing
          Forman, Evan
        affil: Department of Psychology , Drexel University , 3141 Chestnut Street, Suite 119 Philadelphia 19104 USA
      sug:
        subj:
          Telehealth
          Behavior, Addictive
          Human
          Coping
          Decision Making
      ab: Purpose: Lapses are strong indicators of later relapse among individuals with addictive disorders, and thus are an important intervention target. However, lapse behavior has proven resistant to change due to the complex interplay of lapse triggers that are present in everyday life. It could be possible to prevent lapses before they occur by using m-Health solutions to deliver interventions in real-time. Method: Just-in-time adaptive intervention (JITAI) is an intervention design framework that could be delivered via mobile app to facilitate in-the-moment monitoring of triggers for lapsing, and deliver personalized coping strategies to the user to prevent lapses from occurring. An organized framework is key for successful development of a JITAI. Results: Nahum-Shani and colleagues (2014) set forth six core elements of a JITAI and guidelines for designing each: distal outcomes, proximal outcomes, tailoring variables, decision points, decision rules, and intervention options. The primary aim of this paper is to illustrate the use of this framework as it pertains to developing a JITAI that targets lapse behavior among individuals following a weight control diet. Conclusion: We will detail our approach to various decision points during the development phases, report on preliminary findings where applicable, identify problems that arose during development, and provide recommendations for researchers who are currently undertaking their own JITAI development efforts. Issues such as missing data, the rarity of lapses, advantages/disadvantages of machine learning, and user engagement are discussed.
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      ougenre: Article
    language: English
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