Evidence map›Paper›PMID 31972852›Full record

ArticleNursing research

Mobile Health Technology for Pediatric Symptom Monitoring: A Feasibility Study.

Jacqueline Vaughn, Siddharth Gollarahalli, Ryan J Shaw, Sharron Docherty, Qing Yang, Chandni Malhotra, Erika Summers-Goeckerman, Nirmish Shah

Abstract read
In one paragraph

Article in Nursing research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Development of an electronic system for self/proxy symptom tracking alongside children with cancer and their caregivers: a co-design exemplar.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
    Article
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Article
  7. Article
  8. Continuous timely monitoring of core temperature with two wearable devices in pediatric patients undergoing chemotherapy for cancer - a comparison study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
    Observational
  9. Review
  10. Review
  11. Article
  12. Seriously ill pediatric patient, parent, and clinician perspectives on visualizing symptom data.Journal of the American Medical Informatics Association : JAMIA · 2021
    Article
  13. Article
  14. 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

8 authors.

Jacqueline VaughnJacqueline Vaughn, BSN, RN, CHSE, is PhD Candidate, Duke University School of Nursing, Durham, North Carolina. Ryan J. Shaw, PhD, RN, is Associate Professor, Duke University School of Nursing, Durham, North Carolina. Sharron Docherty, PhD PNP-BC, FAAN, is Associate Professor, Duke University School of Nursing, Durham, North Carolina. Qing Yang, PhD, is Assistant Professor, Duke University School of Nursing, Durham, North Carolina. Sid Gollarahalli, BA, is Clinical Research Specialist, Duke Health, Durham, North Carolina. Chandni Malhotra, BS, is Undergraduate Research Assistant, Department of Statistics, North Carolina State University, Raleigh. Erika Summers-Goeckerman, MSN, RN, CPNP-AC, is Pediatric Blood and Marrow Transplant Nurse Practitioner, Hematology-Oncology, Duke Health, Durham, North Carolina. Nirmish Shah, MD, is Assistant Professor of Medicine, Hematology-Oncology, Duke Health, Durham, North Carolina.
Siddharth Gollarahalli
Ryan J Shaw
Sharron Docherty
Qing Yang
Chandni Malhotra
Erika Summers-Goeckerman
Nirmish Shah

Funding

Technology-Mediated Symptom Management in Pediatric Blood and Marrow Transplant CareF31NR018100 · NINR · DUKE UNIVERSITY · PI VAUGHN, JACQUELINE · 2018 to 2019
$79k
NINR NIH HHS F31 NR018100
6 · The paper itself

Abstract

backgroundPediatric blood and marrow transplant (PBMT) patients experience significant symptom distress. Mobile health (mHealth) technologies can be leveraged to improve understanding of the patient's symptom experience by providing continuous, real-time, in situ, patient-generated symptom data. This rich data stream can subsequently enhance symptom management strategies. However, limited research has been conducted in this area.

objectivesThis pilot study seeks to (a) explore the feasibility of integrating mHealth technologies to monitor symptom data for PBMT patients and (b) evaluate the study design, measures, and procedures.

methodsAn exploratory longitudinal design was employed to assess the feasibility of monitoring 10 PBMT patients' symptoms using data from two mHealth technologies: (a) a smartphone mHealth application (app) to collect symptom data and (b) a wearable tracking device (Apple watch) to collect physiological data. Feasibility was measured as usability and acceptability. Monthly patient interviews and an end-of-study feasibility survey were employed and analyzed to further understand reasons for sustained interest in and attrition from the study.

resultsOverall usability of the wearable was 51%, and app was 56%. Children reported devices were easy to use and acceptable. The study demonstrated acceptability with an enrollment rate of 83% and an attrition rate of 30%, with 70% of the children remaining in the study for at least 40 days. DISCUSSION: This pilot study is among the first to explore the feasibility of using mobile technologies to longitudinally obtain patient-generated symptom data to enhance understanding of the PBMT symptom experience. In addition, it will improve our understanding of how these data present, interact, and cluster together throughout the posttransplant period.

Indexed as

Biomedical TechnologyPediatricsSmartphoneSymptom AssessmentTelemedicineWearable Electronic DevicesAdolescentBone MarrowChildFeasibility StudiesFemaleHumansLongitudinal StudiesMalePatient CompliancePilot Projects

Identifiers

PMID31972852
PMCPMC7256218

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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.