ArticleEar and hearing
Application of Big Data to Support Evidence-Based Public Health Policy Decision-Making for Hearing.
Article in Ear and hearing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Article
- Data Analytics to Support Policy Making for Noncommunicable Diseases: Scoping Review.Online journal of public health informatics · 2024Article
- The application of artificial intelligence in health policy: a scoping review.BMC health services research · 2023Article
- Article
- Remote Technologies to Enhance Service Delivery for Adults: Clinical Research Perspectives.Seminars in hearing · 2023Review
- Profiling hearing aid users through big data explainable artificial intelligence techniques.Frontiers in neurology · 2022Article
- Analyzing Twitter Data to Evaluate People's Attitudes towards Public Health Policies and Events in the Era of COVID-19.International journal of environmental research and public health · 2021Article
- The everyday acoustic environment and its association with human heart rate: evidence from real-world data logging with hearing aids and wearables.Royal Society open science · 2021Article
- Real-World Hearing Aid Usage Patterns and Smartphone Connectivity.Frontiers in digital health · 2021Article
- Can Haptic Stimulation Enhance Music Perception in Hearing-Impaired Listeners?Frontiers in neuroscience · 2021Review
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
Ideally, public health policies are formulated from scientific data; however, policy-specific data are often unavailable. Big data can generate ecologically-valid, high-quality scientific evidence, and therefore has the potential to change how public health policies are formulated. Here, we discuss the use of big data for developing evidence-based hearing health policies, using data collected and analyzed with a research prototype of a data repository known as EVOTION (EVidence-based management of hearing impairments: public health pOlicy-making based on fusing big data analytics and simulaTION), to illustrate our points. Data in the repository consist of audiometric clinical data, prospective real-world data collected from hearing aids and an app, and responses to questionnaires collected for research purposes. To date, we have used the platform and a synthetic dataset to model the estimated risk of noise-induced hearing loss and have shown novel evidence of ways in which external factors influence hearing aid usage patterns. We contend that this research prototype data repository illustrates the value of using big data for policy-making by providing high-quality evidence that could be used to formulate and evaluate the impact of hearing health care policies.
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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.