ArticleJMIR research protocols2026
Frameworks for Guiding the Selection of Digital Data Collection Tools Used in Clinical Trials: Protocol for a Systematic Review.
Article in JMIR research protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Frameworks for Guiding the Selection of Digital Data Collection Tools Used in Clinical Trials: Protocol for a Systematic Review.JMIR research protocols · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Data collection is an essential aspect of clinical trials because it forms the basis of the scientific analysis that evaluates the performance and safety of interventions. With the wide variety of digital data collection tools available, decision-makers responsible for choosing the appropriate tools for clinical trials must exercise caution. There are numerous challenges that could impact data collection, and a careful selection of tools is necessary to ensure that they effectively support the trial. Therefore, an evidence-based framework is needed to support the selection of an appropriate digital data collection tool in clinical trials. Objective: This systematic review aims to develop an evidence-based framework for the selection of digital data collection tools for clinical trials. Methods: Bibliographic databases including IEEE Xplore, eAIS, PubMed, CINAHL, MEDLINE, Embase, ClinicalTrials.gov, Scopus, and Web of Science will be searched for published articles. Additionally, searches will be performed for publicly available gray literature from reputable institutions such as the United States Food and Drug Administration and World Health Organization. Studies should include a framework that is relevant to selecting digital data collection tools for clinical trials. Two reviewers will independently use Covidence to screen and review the articles to be included. Data related to the selection of digital data collection tools will be extracted. Thematic synthesis will be conducted to develop a new evidence-based framework to select digital data collection tools for clinical trials. Results: The review started in May 2025 and is expected to be completed in December 2025. The searches yielded 9151 studies, which were reduced to 4333 after the removal of duplicates using Covidence. Conclusions: There is a dearth of established frameworks to guide the selection of digital data collection tools for clinical trials. This review aims to develop an evidence-based framework to support technology decision-makers in identifying and selecting tools that are fit-for-purpose, ensuring they meet the specific needs of clinical research settings.
Indexed as
Identifiers
What OpenQuestion holds
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.