Evidence map›Paper›PMID 29998820›Full record

ArticleBJPsych open2018

Creating boundaries to empower digital health technology.

Honor Hsin, John Torous

Abstract read
In one paragraph

Article in BJPsych open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Digitalization in Medicine: Are German Medical Students Well Prepared for the Future?International journal of environmental research and public health · 2022
    Article
  3. Review
  4. Article
  5. Article
  6. Review
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

2 authors.

Honor HsinClinical Psychiatrist,Verily Life Sciences,South San Francisco,California,USA.
John TorousClinical Psychiatrist,Departments of Psychiatry and Clinical Informatics,Beth Israel Deaconess Medical Center,Harvard Medical School,Boston,Massachusetts,USA.

Funding

Digital Phenotyping for Computational Models of Relapse Prediction in Early Course PsychosisK23MH116130 · NIMH · BETH ISRAEL DEACONESS MEDICAL CENTER · PI TOROUS, JOHN · 2018 to 2021
$872k
6 · The paper itself

Abstract

SummaryThe potential of digital health tools such as smartphones and sensors to increase access to and enhance delivery of healthcare is well known. However, a lack of regulation and delineation between those technologies seeking to offer direct clinical diagnostics and treatments and those involving clinical care enhancements or direct-to-consumer resources has led to patient and clinician confusion about the appropriate use and role of digital health. Here, we propose that creating boundaries and better defining the scope of digital health technology will advance the field through matching the right use cases with the right tools. We further propose that ethical clinicians, as stewards of standard of care, are well suited to uphold these boundaries and to safeguard best practices in digital health.Declaration of interestH.H. is an employee of Verily Life Sciences and owns equity in this company. The views expressed here are those of the authors and are not official views of Verily Life Sciences.

Indexed as

digitalmHealthpsychiatrySmartphones

Identifiers

PMID29998820
PMCPMC6060491

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.