Evidence map›Paper›PMID 41069141›Full record

Trial reportJMIR mHealth and uHealth2025

Effect of Mobile Augmented Reality Counseling on Improving Shared Decision-Making in Thoracic Surgery: Randomized Clinical Crossover Trial.

Ying-Shian Chen, Yi-Chen Hsu, Worachate Romalee, Ding-Han Wang, Jennifer Lai, Tsai-Wang Huang, Kuan Hsun Lin

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in JMIR mHealth and uHealth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07062393 (Effect of Mobile Augmented Reality Counseling on Improving Shared Decision-Making in Thoracic Surgery), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07062393 nacompletednot on this map

Effect of Mobile Augmented Reality Counseling on Improving Shared Decision-Making in Thoracic Surgery: A Randomized Clinical Controlled Trial

TypeinterventionalSponsorTri-Service General Hospital (TSGH)Ran2022 to 2023Enrolled47ConditionsLung Cancer PatientsArmsTraditional Counseling → MAR Counseling, MAR Counseling → Traditional Counseling
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Ying-Shian ChenSchool of Medicine, National Defense Medical University, Taipei, Taiwan.ORCID 0000-0002-0442-1086
Yi-Chen HsuCollege of Dentistry, National Yang Ming Chiao Tung University, Taipei, Taiwan.ORCID 0009-0000-0309-5728
Worachate RomaleeCollege of Dentistry, National Yang Ming Chiao Tung University, Taipei, Taiwan.ORCID 0000-0003-3744-4601
Ding-Han WangCollege of Dentistry, National Yang Ming Chiao Tung University, Taipei, Taiwan.ORCID 0000-0003-3314-6113
Jennifer LaiTri-Service General Hospital, National Defense Medical University, Taipei, Taiwan.ORCID 0009-0009-8411-1595
Tsai-Wang HuangDivision of Thoracic Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan.ORCID 0000-0001-8741-9223
Kuan Hsun LinDivision of Thoracic Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan.ORCID 0000-0002-3371-5489

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAugmented reality (AR) superimposes virtual objects onto a real-world environment, allowing users to interact in real time. As AR has become widely used, its integration into smartphones or tablets has enabled mobile augmented reality (MAR) experiences. AR has been adopted in many industries, and the literature has highlighted its applications in academic and clinical settings, particularly in enhancing visualization, communication, and learning.

objectiveThis study investigated the potential of MAR as a mobile health tool to enhance shared decision-making (SDM) in thoracic surgery by increasing patient understanding and engagement during medical consultations.

methodsA randomized crossover clinical trial was conducted at the Tri-Service General Hospital in Taiwan. Participants scheduled for thoracic surgery were enrolled and randomized in a crossover design. The MAR intervention incorporated patient-specific 3D anatomical models that were reconstructed from computed tomography imaging to facilitate understanding and support SDM. The impact of each counseling approach on SDM was evaluated using postintervention questionnaires.

resultsA total of 47 participants were enrolled in this study. After analyzing the data, we found that patients in the MAR group showed significantly higher scores compared to those in the traditional counseling group (P<.001) during the SDM process. Moreover, patients reported higher satisfaction levels and found the visual objects helpful for understanding tumor location and surgical procedures.

conclusionsThis study demonstrated that MAR counseling significantly enhanced patients' comprehension of thoracic conditions and increased their active engagement in the SDM process (P<.001). The integration of patient-specific 3D anatomical models into MAR technology provided an intuitive method for critical medical information. This digital approach not only enhanced personalization in medical communication but also reinforced patient education about their health care conditions. These findings suggest that MAR counseling represents a promising approach for promoting patient-centered care in thoracic surgery and has potential applications across various clinical domains.

trial registrationClinicalTrials.gov NCT07062393; https://clinicaltrials.gov/study/NCT07062393.

Indexed as

Augmented RealityCounselingDecision Making, SharedThoracic Surgical ProceduresAdultAgedCross-Over StudiesFemaleHumansMaleMiddle AgedMobile ApplicationsSurveys and QuestionnairesTaiwan3D modelsmobile augmented realitypatient educationshared decision-makingthoracic surgery

Identifiers

PMID41069141
PMCPMC12661226

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.