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Personalized Digital Interventions for Behavior Change: Insights from the MoM App Study

  • Fawad Taj*
  • , Michel Klein
  • , Aart van Halteren
  • *Corresponding author for this work
  • Vrije Universiteit Amsterdam
  • Koninklijke Philips N.V.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

This study evaluates the effectiveness of the digital intervention delivered using the MoM mobile app. The app uses different behavior as change techniques to bring about change via an explicit model of motivation as a mechanism of action for physical activity behavior. For a two-arm, single-blind experimental trial, 41 participants were randomly assigned to intervention (n = 20) and control (n = 21) groups. The Intervention group participants used a model-based personalized and adaptive app (MoM) for 40 days. Control participants used the same app without the motivation model, which was neither fully personalized nor adaptive. 9 days of baseline data and 40 days of treatment period data were collected for both intervention and control groups. Based on the linear mixed effect model, participants in the intervention group demonstrated more significant increases in steps per day (95% CI = 873.97–3497.19 p = 0.001) compared to their baseline. Still, changes in daily steps between-groups are not so significantly different. At the same time, enjoyment is the most related motive (95%, CI = 71.87–1339.14 p = 0.029) for calculating reward prediction error and increasing daily physical activity. Using an explicit model for the targeted determinant increases the effectiveness and gives more control to design personalized and adaptive interventions.
Original languageEnglish
Title of host publicationPersuasive Technology - 20th International Conference, PERSUASIVE 2025, Proceedings
EditorsKhin Than Win, Raian Ali, Evangelos Karapanos, George A. Papadopoulos, Kiemute Oyibo, Elena Vlahu-Gjorgievska
PublisherSpringer Science and Business Media Deutschland GmbH
Pages46-58
Number of pages13
Volume15711 LNCS
ISBN (Print)9783031949586
DOIs
Publication statusPublished - 2025
Event20th International Conference on Persuasive Technology, PERSUASIVE 2025 - Limassol, Cyprus
Duration: 5 May 20257 May 2025

Publication series

NameLecture Notes in Computer Science
Volume15711 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Persuasive Technology, PERSUASIVE 2025
Country/TerritoryCyprus
CityLimassol
Period05/05/202507/05/2025

Keywords

  • behavior change systems
  • cognitive modeling
  • digital health behavior
  • dopamine reward system
  • mhealth
  • motivation model
  • persuasive technologies

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