ArticleDigital health
Co-creation with research participants to inform the design of electronic informed consent.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 13 citations in OpenAlex.
- Time for Clarity in Exploring the Evidence and Key Concepts of Human-Centered Design in Digital Health Care: Protocol for a Scoping Review.JMIR research protocols · 2025Article
- Participatory Research in Clinical Studies: An Innovative Approach to Co-creating Nutritional and Physical Activity Recommendations for Older Adults With Sarcopenia (FOOP-Sarc Project).Health expectations : an international journal of public participation in health care and health policy · 2025Article
- Testing and Practical Implementation of a User-Friendly Personalized and Long-Term Electronic Informed Consent Prototype in Clinical Research: Mixed Methods Study.Journal of medical Internet research · 2023Article
- Informing a European guidance framework on electronic informed consent in clinical research: a qualitative study.BMC health services research · 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
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aimed to provide recommendations for a personalized electronic informed consent interface that is adapted to research participants' needs and could enable a longitudinal interaction between the participants and the research team. Methods: The co-creation process consisted of three co-creation workshops, one focus group discussion, and four semi-structured interviews. In total, 24 participants, who had taken part in four disparate clinical studies in Belgium, were involved. Descriptive statistics and qualitative content analysis were applied to analyze the survey data and audio recordings. Results: Varying perceptions on the type and amount of information described in an informed consent form were reported. Other findings were related to the structure and presentation of information, setting preferences for data sharing, and electronically signing new informed consent versions. Regarding the long-term interaction, most of the participants wanted to receive progress updates, including the results, of the study in which they had taken part. They proposed to receive a notification, preferably via email, in case new information is made available on the electronic informed consent interface. Conclusions: To optimally support the design of an electronic informed consent interface, it is key to understand the research participants' needs. Study findings suggest that an electronic informed consent interface may be a promising technological application to interactively provide study-related information and to keep participants informed during and after the clinical study.
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.