Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review
BackgroundJust-In-Time Adaptive Interventions (JITAIs) are interventions designed to deliver timely tailored support by adjusting to changes in users' internal states and external contexts. To accomplish this, JITAIs often apply complex analytic techniques, such as machine learning or Bayesian...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Digital Health |
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| author | Claire R. van Genugten Claire R. van Genugten Melissa S. Y. Thong Melissa S. Y. Thong Melissa S. Y. Thong Wouter van Ballegooijen Wouter van Ballegooijen Wouter van Ballegooijen Annet M. Kleiboer Annet M. Kleiboer Donna Spruijt-Metz Arnout C. Smit Mirjam A. G. Sprangers Mirjam A. G. Sprangers Yannik Terhorst Yannik Terhorst Heleen Riper Heleen Riper Heleen Riper |
| author_facet | Claire R. van Genugten Claire R. van Genugten Melissa S. Y. Thong Melissa S. Y. Thong Melissa S. Y. Thong Wouter van Ballegooijen Wouter van Ballegooijen Wouter van Ballegooijen Annet M. Kleiboer Annet M. Kleiboer Donna Spruijt-Metz Arnout C. Smit Mirjam A. G. Sprangers Mirjam A. G. Sprangers Yannik Terhorst Yannik Terhorst Heleen Riper Heleen Riper Heleen Riper |
| author_sort | Claire R. van Genugten |
| collection | DOAJ |
| description | BackgroundJust-In-Time Adaptive Interventions (JITAIs) are interventions designed to deliver timely tailored support by adjusting to changes in users' internal states and external contexts. To accomplish this, JITAIs often apply complex analytic techniques, such as machine learning or Bayesian algorithms to real- or near-time data acquired from smartphones and other sensors. Given the idiosyncratic, dynamic, and context dependent nature of mental health symptoms, JITAIs hold promise for mental health. However, the development of JITAIs is still in the early stages and is complex due to the multifactorial nature of JITAIs. Considering this complexity, Nahum-Shani et al. developed a conceptual framework for developing and testing JITAIs for health-related problems. This review evaluates the current state of JITAIs in the field of mental health including their alignment with Nahum-Shani et al.'s framework.MethodsNine databases were systematically searched in August 2023. Protocol or empirical studies self-identifying their intervention as a “JITAI” targeting mental health were included in the qualitative synthesis if they were published in peer-reviewed journals and written in English.ResultsOf the 1,419 records initially screened, 9 papers reporting on 5 JITAIs were included (sample size range: 5 to an expected 264). Two JITAIs were for bulimia nervosa, one for depression, one for insomnia, and one for maternal prenatal stress. Although most core components of Nahum-Shani's et al.'s framework were incorporated in the JITAIs, essential elements (e.g., adaptivity and receptivity) within the core components were missing and the core components were only partly substantiated by empirical evidence (e.g., interventions were supported, but the decision rules and points were not). Complex analytical techniques such as data from passive monitoring of individuals' states and contexts were hardly used. Regarding the current state of studies, initial findings on usability, feasibility, and effectiveness appear positive.ConclusionsJITAIs for mental health are still in their early stages of development, with opportunities for improvement in both development and testing. For future development, it is recommended that developers utilize complex analytical techniques that can handle real-or near-time data such as machine learning, passive monitoring, and conduct further research into empirical-based decision rules and points for optimization in terms of enhanced effectiveness and user-engagement. |
| format | Article |
| id | doaj-art-510e1bbe2bdc4f46bb8acec7895e6da3 |
| institution | Kabale University |
| issn | 2673-253X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Digital Health |
| spelling | doaj-art-510e1bbe2bdc4f46bb8acec7895e6da32025-01-28T06:41:25ZengFrontiers Media S.A.Frontiers in Digital Health2673-253X2025-01-01710.3389/fdgth.2025.14601671460167Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic reviewClaire R. van Genugten0Claire R. van Genugten1Melissa S. Y. Thong2Melissa S. Y. Thong3Melissa S. Y. Thong4Wouter van Ballegooijen5Wouter van Ballegooijen6Wouter van Ballegooijen7Annet M. Kleiboer8Annet M. Kleiboer9Donna Spruijt-Metz10Arnout C. Smit11Mirjam A. G. Sprangers12Mirjam A. G. Sprangers13Yannik Terhorst14Yannik Terhorst15Heleen Riper16Heleen Riper17Heleen Riper18Clinical, Neuro-, and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, NetherlandsAmsterdam Public Health, Mental Health, Amsterdam, NetherlandsAmsterdam Public Health, Mental Health, Amsterdam, NetherlandsDepartment of Medical Psychology, Amsterdam UMC Location University of Amsterdam, Amsterdam, NetherlandsUnit of Cancer Survivorship, German Cancer Research Center (DKFZ), Heidelberg, GermanyClinical, Neuro-, and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, NetherlandsAmsterdam Public Health, Mental Health, Amsterdam, NetherlandsDepartment of Psychiatry, Amsterdam UMC, Amsterdam, NetherlandsClinical, Neuro-, and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, NetherlandsAmsterdam Public Health, Mental Health, Amsterdam, NetherlandsCenter for Economic and Social Research, University of California, Los Angeles, CA, United States (emeritus)Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation, University Medical Center Groningen, University of Groningen, Groningen, NetherlandsAmsterdam Public Health, Mental Health, Amsterdam, NetherlandsDepartment of Medical Psychology, Amsterdam UMC Location University of Amsterdam, Amsterdam, NetherlandsDepartment of Psychology, Ludwig Maximilian University of Munich, Munich, GermanyGerman Center for Mental Health (DZPG), Partner Site Munich-Augsburg, Munich, GermanyClinical, Neuro-, and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, NetherlandsAmsterdam Public Health, Mental Health, Amsterdam, NetherlandsDepartment of Psychiatry, Amsterdam UMC, Amsterdam, NetherlandsBackgroundJust-In-Time Adaptive Interventions (JITAIs) are interventions designed to deliver timely tailored support by adjusting to changes in users' internal states and external contexts. To accomplish this, JITAIs often apply complex analytic techniques, such as machine learning or Bayesian algorithms to real- or near-time data acquired from smartphones and other sensors. Given the idiosyncratic, dynamic, and context dependent nature of mental health symptoms, JITAIs hold promise for mental health. However, the development of JITAIs is still in the early stages and is complex due to the multifactorial nature of JITAIs. Considering this complexity, Nahum-Shani et al. developed a conceptual framework for developing and testing JITAIs for health-related problems. This review evaluates the current state of JITAIs in the field of mental health including their alignment with Nahum-Shani et al.'s framework.MethodsNine databases were systematically searched in August 2023. Protocol or empirical studies self-identifying their intervention as a “JITAI” targeting mental health were included in the qualitative synthesis if they were published in peer-reviewed journals and written in English.ResultsOf the 1,419 records initially screened, 9 papers reporting on 5 JITAIs were included (sample size range: 5 to an expected 264). Two JITAIs were for bulimia nervosa, one for depression, one for insomnia, and one for maternal prenatal stress. Although most core components of Nahum-Shani's et al.'s framework were incorporated in the JITAIs, essential elements (e.g., adaptivity and receptivity) within the core components were missing and the core components were only partly substantiated by empirical evidence (e.g., interventions were supported, but the decision rules and points were not). Complex analytical techniques such as data from passive monitoring of individuals' states and contexts were hardly used. Regarding the current state of studies, initial findings on usability, feasibility, and effectiveness appear positive.ConclusionsJITAIs for mental health are still in their early stages of development, with opportunities for improvement in both development and testing. For future development, it is recommended that developers utilize complex analytical techniques that can handle real-or near-time data such as machine learning, passive monitoring, and conduct further research into empirical-based decision rules and points for optimization in terms of enhanced effectiveness and user-engagement.https://www.frontiersin.org/articles/10.3389/fdgth.2025.1460167/fulljust-in-time adaptive interventiondigital mental healthintervention developmentsmartphone interventionJITAI |
| spellingShingle | Claire R. van Genugten Claire R. van Genugten Melissa S. Y. Thong Melissa S. Y. Thong Melissa S. Y. Thong Wouter van Ballegooijen Wouter van Ballegooijen Wouter van Ballegooijen Annet M. Kleiboer Annet M. Kleiboer Donna Spruijt-Metz Arnout C. Smit Mirjam A. G. Sprangers Mirjam A. G. Sprangers Yannik Terhorst Yannik Terhorst Heleen Riper Heleen Riper Heleen Riper Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review Frontiers in Digital Health just-in-time adaptive intervention digital mental health intervention development smartphone intervention JITAI |
| title | Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review |
| title_full | Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review |
| title_fullStr | Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review |
| title_full_unstemmed | Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review |
| title_short | Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review |
| title_sort | beyond the current state of just in time adaptive interventions in mental health a qualitative systematic review |
| topic | just-in-time adaptive intervention digital mental health intervention development smartphone intervention JITAI |
| url | https://www.frontiersin.org/articles/10.3389/fdgth.2025.1460167/full |
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