Evidence map›Paper›PMID 42759031›Full record

ArticleJMIR mHealth and uHealth2026

Engagement With a Relaxation-Based Mobile Health Intervention for Perioperative Anxiety: Prospective Longitudinal Cohort Mixed Methods Study.

Xinghui Yan, Afton L Hassett, Jennifer F Waljee, Mark W Newman, Sun Young Park, Rongqi Bei, Noelle E Carlozzi

Abstract read
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

What it found

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2 · The registry

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Xinghui YanSchool of Information, University of Michigan, Ann Arbor, MI, United States.ORCID https://orcid.org/0000-0003-0431-152X
Afton L HassettChronic Pain & Fatigue Research Center, Department of Anesthesiology, University of Michigan, Ann Arbor, MI, United States.ORCID https://orcid.org/0000-0003-2982-484X
Jennifer F WaljeeDepartment of Surgery, Michigan Medicine, Ann Arbor, MI, United States.ORCID https://orcid.org/0000-0001-5956-8467
Mark W NewmanSchool of Information, University of Michigan, Ann Arbor, MI, United States.ORCID https://orcid.org/0000-0001-7186-1383
Sun Young ParkSchool of Information, University of Michigan, Ann Arbor, MI, United States.ORCID https://orcid.org/0000-0001-8666-1800
Rongqi BeiSchool of Information, University of Michigan, Ann Arbor, MI, United States.ORCID https://orcid.org/0000-0003-1342-1771
Noelle E CarlozziCenter for Clinical Outcomes Development and Application (CODA), Departments of Physical Medicine and Rehabilitation, and Surgery, University of Michigan, Ann Arbor, MI, United States.ORCID https://orcid.org/0000-0003-0439-9429

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRelaxation-based mobile health (mHealth) interventions hold strong potential to address perioperative anxiety and pain management in a scalable manner. However, there is limited research on how surgical patients engage with these interventions and what aspects may be most helpful.

objectiveThis study had 3 goals: (1) explore how users interact with a relaxation-based mHealth intervention during the perioperative period; (2) understand how user performance and perceptions relate to perceived benefits; and (3) identify design considerations to enhance user engagement and behavior change outcomes in mHealth interventions.

methodsWe conducted a prospective longitudinal cohort, mixed methods study to evaluate user engagement with MiCarePath, a relaxation-based mHealth intervention. A total of 19 perioperative patients (mean age 41.3 years; 14/19, 74%, female) undergoing elective surgery and reporting sometimes-to-always anxiety were enrolled using 3 recruitment methods. Participants used the app from 10 days before surgery to 4 weeks after surgery. We collected quantitative data on video engagement metrics (eg, duration of watching, response rate to video prompts) and ecological momentary assessments of anxiety and pain. Concurrently, we conducted semistructured, data-prompted interviews at 3 time points to assess user perceptions. These data were integrated using descriptive statistics, repeated-measures ANOVA, and qualitative thematic analysis to examine the relationship between user performance and perceived benefits.

resultsEleven participants reported developing or improving relaxation-based self-management strategies (high benefit), whereas 8 reported little benefit from the intervention. The high-benefit group showed significantly greater total watching time (difference 223.8 minutes, 95% CI 95.54-366.46 minutes, P<.001), higher adherence to video prompts (73.45% vs 34.60%, P<.001), and greater perceived helpfulness of the content (79.80% vs 25.50%, P<.001) compared with the low-benefit group. A significant group-by-time interaction effect was observed for engagement (F

conclusionsThis study explored user engagement with a relaxation-based mHealth intervention for perioperative care, advancing the literature by integrating user perceptions and performance for digital anxiety and pain management. Results indicate that perceived benefit may not always be reflected in user performance. Intentional use emerges as a promising indicator of effective mHealth engagement in perioperative care. Future designs should aim to foster intentional use through features such as reflection prompts and adaptive notifications. Future work should also develop computational models to detect intentional use and evaluate adaptive interventions in larger cohorts.

Indexed as

AnxietyRelaxation TherapyAdultCohort StudiesDigital HealthFemaleHumansLongitudinal StudiesMaleMiddle AgedMobile ApplicationsPerioperative PeriodProspective StudiesQualitative ResearchSurveys and QuestionnairesTelemedicinemHealth interventionmindfulnesspain managementperioperative anxietyrelaxationuser engagement

Identifiers

PMID42759031
PMCPMC13633465

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Registered trials

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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.