Evidence map›Paper›PMID 34524089›Full record

SynthesisJournal of medical Internet research2021

Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review.

Md Mobashir Hasan Shandhi, Jennifer C Goldsack, Kyle Ryan, Alexandra Bennion, Aditya V Kotla, Alina Feng, Yihang Jiang, Will Ke Wang, Tina Hurst, John Patena and 3 more

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 28% of its field
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

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. [Orthopedics and trauma surgery in the digital age].Orthopadie (Heidelberg, Germany) · 2024
    Review
  4. Article
  5. Review
  6. Article
  7. 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

13 authors at 3 institutions in 1 country.

Md Mobashir Hasan ShandhiDepartment of Biomedical Engineering, Duke University, Durham, NC, United States.ORCID 0000-0001-9541-529X
Jennifer C GoldsackDigital Medicine Society, Boston, MA, United States.ORCID 0000-0003-0461-0183
Kyle RyanBig Ideas Lab, Department of Biomedical Engineering, Duke University, Durham, NC, United States.ORCID 0000-0003-0935-8810
Alexandra BennionBig Ideas Lab, Department of Biomedical Engineering, Duke University, Durham, NC, United States.ORCID 0000-0003-0217-1201
Aditya V KotlaBig Ideas Lab, Department of Biomedical Engineering, Duke University, Durham, NC, United States.ORCID 0000-0002-5211-4515
Alina FengBig Ideas Lab, Department of Biomedical Engineering, Duke University, Durham, NC, United States.ORCID 0000-0003-0903-5149
Yihang JiangDepartment of Biomedical Engineering, Duke University, Durham, NC, United States.ORCID 0000-0003-2062-7946
Will Ke WangDepartment of Biomedical Engineering, Duke University, Durham, NC, United States.ORCID 0000-0003-1444-5468
Tina HurstActivinsights Ltd, Cambridgeshire, United Kingdom.ORCID 0000-0001-6688-1451
John PatenaBrown-Lifespan Center for Digital Health, Brown University, Providence, RI, United States.ORCID 0000-0002-4652-1712
Simona CariniDivision of General Internal Medicine, University of California, San Francisco, CA, United States.ORCID 0000-0002-4054-9458
Jeanne ChungDigital Medicine Society, Boston, MA, United States.ORCID 0000-0002-1555-7456
Jessilyn DunnDepartment of Biomedical Engineering, Duke University, Durham, NC, United States.ORCID 0000-0002-3241-8183
Duke University · USBrown University · USUniversity of California, San Francisco · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, ingestibles, and implantables are increasingly used by individuals and clinicians to capture health outcomes or behavioral and physiological characteristics of individuals. Although academia is taking an active role in evaluating digital sensing products, academic contributions to advancing the safe, effective, ethical, and equitable use of digital clinical measures are poorly characterized.

objectiveWe performed a systematic review to characterize the nature of academic research on digital clinical measures and to compare and contrast the types of sensors used and the sources of funding support for specific subareas of this research.

methodsWe conducted a PubMed search using a range of search terms to retrieve peer-reviewed articles reporting US-led academic research on digital clinical measures between January 2019 and February 2021. We screened each publication against specific inclusion and exclusion criteria. We then identified and categorized research studies based on the types of academic research, sensors used, and funding sources. Finally, we compared and contrasted the funding support for these specific subareas of research and sensor types.

resultsThe search retrieved 4240 articles of interest. Following the screening, 295 articles remained for data extraction and categorization. The top five research subareas included operations research (research analysis; n=225, 76%), analytical validation (n=173, 59%), usability and utility (data visualization; n=123, 42%), verification (n=93, 32%), and clinical validation (n=83, 28%). The three most underrepresented areas of research into digital clinical measures were ethics (n=0, 0%), security (n=1, 0.5%), and data rights and governance (n=1, 0.5%). Movement and activity trackers were the most commonly studied sensor type, and physiological (mechanical) sensors were the least frequently studied. We found that government agencies are providing the most funding for research on digital clinical measures (n=192, 65%), followed by independent foundations (n=109, 37%) and industries (n=56, 19%), with the remaining 12% (n=36) of these studies completely unfunded.

conclusionsSpecific subareas of academic research related to digital clinical measures are not keeping pace with the rapid expansion and adoption of digital sensing products. An integrated and coordinated effort is required across academia, academic partners, and academic funders to establish the field of digital clinical measures as an evidence-based field worthy of our trust.

Indexed as

Delivery of Health CareSmartphoneHumansacademic researchbiosensordigital clinical measuresdigital healthdigital measuresfundinghealth outcomes

Identifiers

PMID34524089
PMCPMC8482196
OpenAlexW3201074411

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.