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

Created on 19 Sep 2026

Authors

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

Published in

JMIR mHealth and uHealth. Volume 14. Pages e64278. Sep 18, 2026. Epub Sep 18, 2026.

Abstract

Relaxation-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.
This 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.
We 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.
Eleven 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 (F1,17=17.02, P<.001). No difference was observed in delay in response to video prompts. However, within each group, participant perceptions were not fully reflected in performance. Some participants in the high-benefit group showed decreased video watching after surgery but still reported feeling engaged with the intervention. Interview data revealed that "intentional use" behavior-where users actively seek content to manage symptoms independent of prompts-distinguished these participants. Those who developed intentional use were able to practice relaxation techniques without the app and resume app engagement following contextual disruptions.
This 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.

PMID:
42759031
Bibliographic data and abstract were imported from PubMed on 19 Sep 2026.

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