Evidence map›Paper›PMID 30609978›Full record

Trial reportJMIR mHealth and uHealth2019

Impact of Personal Health Records and Wearables on Health Outcomes and Patient Response: Three-Arm Randomized Controlled Trial.

Jeong-Whun Kim, Borim Ryu, Seoyoon Cho, Eunyoung Heo, Yoojung Kim, Joongseek Lee, Se Young Jung, Sooyoung Yoo

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03200223 (A Study of the Management of the Patient's Disease Based on the Life Log Data of Patient With Lifestyle-related Diseases Through a Wearable Device and Mobile App), which is not on this map. Cited by 39 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 6 pooled it
–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.

NCT03200223 naterminatednot on this map

A Study of the Management of the Patient's Disease Based on the Life Log Data of Patient With Lifestyle-related Diseases Through a Wearable Device and Mobile App

TypeinterventionalSponsorSeoul National University HospitalRan2017 to 2018Enrolled60ConditionsObesity, Life Style Induced IllnessArmsPersonalized healthcare service
3 · Its place in the literature

Who cites it

39 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
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  7. Trial
  8. Guidelines for rigor and reproducibility of heart rate variability within human cardiovascular research.American journal of physiology. Heart and circulatory physiology · 2026
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  15. NurseVerse: nursing in the metaverse era.Frontiers in medicine · 2025
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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

8 authors.

Jeong-Whun Kim *Department of Otorhinolaryngology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.ORCID 0000-0003-4858-3316
Borim Ryu *Office of eHealth Research and Businesses, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.ORCID 0000-0002-2000-4565
Seoyoon ChoOffice of eHealth Research and Businesses, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.ORCID 0000-0002-7027-0781
Eunyoung HeoOffice of eHealth Research and Businesses, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.ORCID 0000-0003-0866-8331
Yoojung KimGraduate School of Convergence Science and Technology, Seoul National University, Suwon, Republic of Korea.ORCID 0000-0002-4078-5848
Joongseek LeeGraduate School of Convergence Science and Technology, Seoul National University, Suwon, Republic of Korea.ORCID 0000-0003-2376-3046
Se Young JungOffice of eHealth Research and Businesses, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.ORCID 0000-0001-9946-8807
Sooyoung YooOffice of eHealth Research and Businesses, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.ORCID 0000-0001-8620-4925

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough using the technologies for a variety of chronic health conditions such as personal health record (PHR) is reported to be acceptable and useful, there is a lack of evidence on the associations between the use of the technologies and the change of health outcome and patients' response to a digital health app.

objectiveThis study aimed to examine the impact of the use of PHR and wearables on health outcome improvement and sustained use of the health app that can be associated with patient engagement.

methodsWe developed an Android-based mobile phone app and used a wristband-type activity tracker (Samsung Charm) to collect data on health-related daily activities from individual patients. Dietary record, daily step counts, sleep log, subjective stress amount, blood pressure, and weight values were recorded. We conducted a prospective randomized clinical trial across 4 weeks on those diagnosed with obstructive sleep apnea (OSA) who had visited the outpatient clinic of Seoul National University Bundang Hospital. The trial randomly assigned 60 patients to 3 subgroups including 2 intervention groups: (1) mobile app and wearable device users (n=20), (2) mobile app-only users (n=20), and (3) controls (n=20). The primary outcome measure was weight change. Body weights before and after the trial were recorded and analyzed during clinic visits. Changes in OSA-related respiratory parameters such as respiratory disturbance, apnea-hypopnea, and oxygenation desaturation indexes and snoring comprised the secondary outcome and were analyzed for each participant.

resultsWe collected the individual data for each group during the trial, specifically anthropometric measurement and laboratory test results for health outcomes, and the app usage logs for patient response were collected and analyzed. The body weight showed a significant reduction in the 2 intervention groups after intervention, and the mobile app-only group showed more weight loss compared with the controls (P=.01). There were no significant changes in sleep-related health outcomes. From a patient response point of view, the average daily step counts (8165 steps) from the app plus wearable group were significantly higher than those (6034 steps) from the app-only group because they collected step count data from different devices (P=.02). The average rate of data collection was not different in physical activity (P=.99), food intake (P=.98), sleep (P=.95), stress (P=.70), and weight (P=.90) in the app plus wearable and app-only groups, respectively.

conclusionsWe tried to integrate PHR data that allow clinicians and patients to share lifelog data with the clinical workflow to support lifestyle interventions. Our results suggest that a PHR-based intervention may be successful in losing body weight and improvement in lifestyle behavior.

trial registrationClinicalTrials.gov NCT03200223; https://clinicaltrials.gov/ct2/show/NCT03200223 (Archived by WebCite at http://www.webcitation.org/74baZmnCX).

Indexed as

AdultBody Mass IndexFemaleHealth Records, PersonalHealth Services AccessibilityHumansMaleMiddle AgedMobile ApplicationsOutcome Assessment, Health CarePatient Acceptance of Health CareProspective StudiesRepublic of KoreaSleep Apnea, ObstructiveWearable Electronic Devicesdelivery of health careelectronic health recordlifestylemobile healthpersonal health recordsleep apnea, obstructive

Identifiers

PMID30609978
PMCPMC6682299

What OpenQuestion holds

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LicenceCC BY
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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.