Evidence map›Paper›PMID 42849895›Full record

ArticleJMIR mHealth and uHealth2026

Integration of Ecological Momentary Assessment and Intervention With Wearable-Based Digital Phenotypes to Treat Anxiety in Young Adults: Mixed Methods Experimental Study.

Hyunsil Song, Yoobin Choi, Jinho Park, Hyunchan Hwang, Jinwoo Kim, Chanmi Park

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In one paragraph

Article in JMIR mHealth and uHealth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Hyunsil SongHAII Corp, Jongno-gu, Republic of Korea.ORCID https://orcid.org/0009-0000-3700-1152
Yoobin ChoiHAII Corp, Jongno-gu, Republic of Korea.ORCID https://orcid.org/0009-0009-6430-5923
Jinho ParkMedical IT Convergence Research Center, Korea Electronics Technology Institute, Seongnam-si, Republic of Korea.ORCID https://orcid.org/0000-0002-1742-6839
Hyunchan HwangChung-Ang University Hospital, Dongjak-gu, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0001-6514-5188
Jinwoo KimHAII Corp, Jongno-gu, Republic of Korea.ORCID https://orcid.org/0000-0002-0162-5446
Chanmi ParkHAII Corp, Jongno-gu, Republic of Korea.ORCID https://orcid.org/0000-0003-1173-9065

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundYoung adults report high levels of anxiety, yet their access to timely treatment remains limited. Mobile-based digital therapeutics, particularly ecological momentary assessment and intervention (EMA/EMI), offer a promising approach to deliver context-responsive care. The integration of wearable-derived digital phenotypes with digital therapeutics may enhance the personalization of feedback in such interventions, but empirical evidence from real-world settings remains scarce.

objectiveThis study examined the real-world applicability and effectiveness of an EMA/EMI-based digital therapeutic, ANZEILAX-Green (HAII Corp), for use in anxiety reduction in young adults and investigated how personalized feedback generated by combining EMA/EMI data with wearable-based digital phenotypes ameliorates symptoms and promotes self-management and user engagement.

methodsAn 8-week exploratory experimental study was conducted with young adults aged 19-39 years. Participants used a smartphone app in which EMA/EMI modules had been integrated with a smartwatch that continuously collected digital phenotyping data, including heart rate, sleep, and activity. Psychological outcomes were assessed using the Generalized Anxiety Disorder 7-item scale (GAD-7) and Patient Health Questionnaire-9 (PHQ-9) at baseline and weeks 2, 4, 6, and 8, and the Rosenberg Self-Esteem Scale (RSES) at baseline and week 8. Quantitative changes were analyzed using paired-samples t tests and repeated-measures ANOVA, and qualitative interviews were thematically analyzed to identify user experience mechanisms and design implications.

resultsIn all, 29 participants were included in the final analysis. Significant improvements were observed in their GAD-7 (mean difference -4.79, 95% CI -6.56 to -3.02; Cohen d=1.03; P<.001), PHQ-9 (mean difference -3.86, 95% CI -5.79 to -1.93; Cohen d=0.76; P<.001), and RSES scores (mean difference +5.21, 95% CI 3.47 to 6.95; Cohen d=1.14; P<.001). Consistent improvements in GAD-7 scores were observed across the assessment points, with statistically significant reductions from week 4 onward. Participants demonstrated high adherence, completing 80% of the EMA/EMI prompts. The digital phenotype showed trends of increased deep sleep and reduced mobility, and sleep indicators were significantly correlated with depressive symptoms. Analysis of the interview findings revealed 5 mechanisms: enhanced self-awareness, data-driven reflection, behavioral change, intrinsic motivation, and extension of treatment into daily life.

conclusionsEMA/EMI-based digital therapeutics integrated with wearable-derived digital phenotypes are feasible and acceptable for use by young adults and were associated with within-group reductions in anxiety, suggesting acceptable efficacy, though this warrants confirmation in a controlled trial. The combination of real-time self-reported assessments of emotional states and passive physiological monitoring enables personalized feedback suited to users' emotional and physiological states. These findings offer empirical and design insights for automated, personalized mental health intervention systems.

Indexed as

AnxietyEcological Momentary AssessmentWearable Electronic DevicesAdultDigital HealthFemaleHumansMalePhenotypePsychometricsSurveys and QuestionnairesYoung Adultacceptance and commitment therapyanxiety disorderdigital phenotypesecological momentary assessmentecological momentary interventionmobile healthwearable data

Identifiers

PMID42849895

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.