ReviewMethods in molecular biology (Clifton, N.J.)2021
Changing Health-Related Behaviors 6: Analysis, Interpretation, and Application of Big Data.
Review in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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0 citing papers in PubMed.
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Authors and funding
2 authors.
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Abstract
The behavior of individuals can affect both their own health and the health of those around them. Furthermore, the behavior of healthcare providers obviously affects the health of those receiving the care. In both of these cases, and in spite of its known benefits, behavior change is difficult for most people. To make change easier, big data can provide insight through an objective and nonjudgmental perspective. It may also help make specific, individualized, evidence-based recommendations for effective change. We provide a historical perspective on data and health and then describe the value of adding big data systems and how they are implemented. We discuss some of the sources of big data and how it is collected. We also review the additional challenges for analysis, interpretation, and application of big data that require specific technologies. We end with a summary of current uses of big data for behavior change and suggestions for additional approaches, which may be of benefit.
Indexed as
Identifiers
33871868What 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.