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In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
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Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
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Multicellular organisms employ a variety of ways for cells to communicate with each other. Gap junctions are specialized proteins that form pores between neighboring cells in animals, connecting the cytoplasm between the two, and allowing for the exchange of molecules and ions. They are found in a wide range of invertebrate and vertebrate species, mediate numerous functions including cell differentiation and development, and are associated with numerous human diseases, including cardiac and...
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The cytoplasm of adjacent animal cells can exchange small molecules, ions, and secondary messengers via the communication channels which form the gap junctions. These junctions comprise a few hundred to thousands of molecular channels, each made of two halves, called the connexon hemichannel. A connexon is a hexamer of six transmembrane connexin proteins, which assemble radially, thus forming a pore or channel in the center. One connexon hemichannel docks with a corresponding connexon on the...
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Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
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Opportunities for computer support for systematic reviewing - a gap analysis.

Linh Hoang1, Jodi Schneider1

  • 1University of Illinois at Urbana-Champaign, Champaign IL 61820, USA.

Transforming Digital Worlds : 13Th International Conference, Iconference 2018, Sheffield, UK, March 25-28, 2018, Proceedings. International Conference on Transforming Digital Worlds (13Th : 2018 : Sheffield, England)
|January 15, 2019
PubMed
Summary
This summary is machine-generated.

Computer support can streamline systematic reviews, a key research synthesis method. Identifying current challenges and opportunities can improve efficiency and quality in evidence synthesis.

Keywords:
Gap analysisInterview studyMeta-analysisSystematic review

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Area of Science:

  • Health Informatics
  • Information Science
  • Evidence Synthesis Methodologies

Background:

  • Systematic reviews synthesize available evidence for research questions.
  • Conducting systematic reviews is time-intensive and requires substantial effort.
  • Computer support is continually evolving to aid systematic review processes.

Purpose of the Study:

  • Identify current gaps and opportunities for computer support in systematic reviews.
  • Understand the technical challenges faced by systematic reviewers.
  • Explore how computer support can enhance the efficiency and quality of systematic reviews.

Main Methods:

  • Qualitative study involving interviews with experienced systematic reviewers.
  • Diverse fields represented to capture a broad range of experiences.
  • Analysis of current computer support usage and identified technical challenges.

Main Results:

  • Systematic reviewers face specific technical problems and challenges.
  • Current use of computer support varies among reviewers.
  • Gaps exist in how technology can be leveraged for systematic review efficiency.

Conclusions:

  • Computer support has significant potential to accelerate systematic review processes.
  • Future research should focus on developing targeted computer support solutions.
  • Improving computer support can maintain or enhance the quality of systematic reviews.