Evidence map›Paper›PMID 38222440›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2023

Digital Solutions Observed in Clinical Trials: A Formative Feasibility Scoping Review.

Taylor M Harrison, Sungrim Moon, Liwei Wang, Sunyang Fu, Hongfang Liu

Abstract readScoping Review
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Taylor M HarrisonDepartment of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, USA.
Sungrim MoonDepartment of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, USA.
Liwei WangDepartment of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, USA.
Sunyang FuDepartment of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, USA.
Hongfang LiuDepartment of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Growing digital access accelerates digital transformation of clinical trials where digital solutions (DSs) are increasingly and widely leveraged for improving trial efficiency, effectiveness, and accessibility. Many factors impact DS success including technology barriers, privacy concerns, or user engagement activities. It is unclear how those factors are considered or reported in the literature. Here, we perform a formative feasibility scoping review to identify gaps impacting DS quality and reproducibility in trials. Articles containing digital terms published in English from 2009 to 2022 were collected (n=4,167). 130 articles published between 2016 and 2022 were randomly selected for full-text review. Eligible articles (n=100) were sorted into four identified categories: 16% Education, 59% Intervention, 8% Patient, 17% Treatment. Initial findings about DS trends and reporting practices inform protocol development for a large-scale study urging the generation of fundamental knowledge on reporting standardization, best practice guidelines, and evaluation methodologies related to DS for clinical trials.

Indexed as

Feasibility StudiesClinical Trials as TopicHumansReproducibility of Results

Identifiers

PMID38222440
PMCPMC10785928

What OpenQuestion holds

Textmetadata
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.