ArticleFrontiers in digital health2022
Media and technology usage and attitudes in emergency department patients.
Article in Frontiers in digital health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 9 citations in OpenAlex.
- Technological Strategies for the Patient Experience in Emergency Departments: Scoping Review.JMIR medical informatics · 2026Article
- Striving to make the right decision when seeking emergency care: patients' stories of navigating support alternatives in a digital society, a qualitative study.BMC emergency medicine · 2026Article
- Article
- Plugged-in: a Canadian survey of technology ownership, access, use, and attitudes among emergency department patients.Frontiers in digital health · 2025Article
- Development and validation of the AI dependence scale for Chinese undergraduates and a preliminary exploration.Frontiers in psychology · 2025Article
- Improving pre-exposure prophylaxis uptake among Black women in the United States: insights from conducting public health research within emergency department setting.Frontiers in sociology · 2025Article
- A Pilot of Digital Whiteboards for Improving Patient Satisfaction in the Emergency Department: Nonrandomized Controlled Trial.JMIR formative 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 5 institutions in 1 country.
Funding
Abstract
Introduction: Digital health technologies are increasingly being used in emergency medicine, many of which utilize smartphones and computers. Patient willingness to use these modalities is an important factor in successful implementation. Therefore, this study aimed to assess emergency department (ED) patients' use of and attitudes towards technology. Methods: This was a pooled sub-analysis of ED patients (≥18 years old) that were enrolled in two studies evaluating the ED patient experience in response to novel technological interventions. Participants completed the Media and Technology Usage and Attitudes Scale (MTUAS) that assessed computer and smartphone ownership; frequency of use of phone calls, texting, email, and smartphones; and anxiety and dependence attitudes on these technologies. Results: One hundred and forty-four participants completed the survey. Mean age was 47.2 years (SD 17.94); 61.8% were female; and 61.1% were white. There was high usage of smartphones (93.1%) and computers (74.3%). Participants most frequently used phone calling and texting and least commonly used email. Participants had a positive attitude (mean 3.9/5, SD 0.68) towards the use of these technologies. Discussion: ED patients reported high ownership of smartphones and computers, had a positive attitude towards their use, and had varying frequency with which they used different technologies. Future studies can use this information to inform the development of digital health interventions that utilize technologies that patients find most acceptable.
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.