ReviewInnovations in clinical neuroscience
Implementing Digital Technologies in Clinical Trials: Lessons Learned.
Review in Innovations in clinical neuroscience. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed.
- Article
- Addressing the need for standardization of symptomatic medication documentation in Parkinson's disease clinical research: A call to action.Journal of Parkinson's disease · 2025Review
- Continuous Monitoring of Head Turns: Compliance, Kinematics, and Reliability of Wearable Sensing.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2025Article
- Using digital tools in clinical, health and social care research: a mixed-methods study of UK stakeholders.BMJ open · 2024Article
- Decentralisation in Clinical Trials and Patient Centricity: Benefits and Challenges.Pharmaceutical medicine · 2024Review
- Remote monitoring of cognition in cirrhosis and encephalopathy: future opportunity and challenge.Metabolic brain disease · 2023Review
- Digital Solutions Observed in Clinical Trials: A Formative Feasibility Scoping Review.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
- Editorial: The use of digital technologies in the promotion of children's health.Frontiers in pediatrics · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multiple digital health technologies have been evaluated across clinical development programs, including external, wearable, implantable, and ingestible devices and sensors, along with digital mobile health applications (apps) that are accessible via users' personal electronic devices (e.g., smartphones, tablets, and computers). Several of these technologies have been incorporated into our ongoing neurology and respiratory clinical development programs. Based on our experience, one of the greatest potential benefits of digital health technologies is the ability to collect objective and/or biological data continuously or at regular intervals outside of office visits during a patient's normal daily activities to provide additional efficacy and safety information, versus data capture from traditional episodic, time point-based office visits. Many challenges encountered with digital health technologies can be successfully addressed by providing the appropriate training to staff and patients, ensuring availability of appropriate infrastructure support, and conducting pilot studies before scaling up to larger trials. Overall, our experience with digital health technologies demonstrated their potential to increase the amount of objective data collected in clinical trials, expand patient access to trials, and facilitate further improvement of clinical outcomes.
Indexed as
Identifiers
35958972PMC9341314What 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.