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Related Concept Videos

Archival Research01:40

Archival Research

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Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
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Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
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Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
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Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
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Data Collection I01:30

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Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
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The scientific method provides the foundation for any research. It is the most reliable and objective of all forms of gaining knowledge and guides in applying research-based evidence in practice and conducting future research.
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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
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Data Management: The First Step in Reproducible Research.

Soundarya Soundararajan1, Sukhdev Mishra1

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Implementing robust data management is crucial for reproducibility in occupational health research. Effective data management enhances organization, transparency, quality, and collaboration for scientific endeavors.

Keywords:
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Area of Science:

  • Occupational Health Research
  • Scientific Data Management

Background:

  • Reproducibility is a key goal in scientific research, particularly within occupational health.
  • Data management is fundamental to achieving research reproducibility and integrity.

Purpose of the Study:

  • To outline best practices for data management in occupational health research.
  • To highlight the role of data management in enhancing research reproducibility, transparency, and collaboration.

Main Methods:

  • Discussion of data organization and preparation strategies.
  • Explanation of how data management supports interoperability and accessibility.
  • Guidance on data storage, dissemination, and data management planning.

Main Results:

  • Organized data management improves research transparency and quality.
  • Effective data management facilitates scientific collaboration and data sharing.
  • Structured data management plans are essential for reproducible research.

Conclusions:

  • Adopting comprehensive data management practices is vital for advancing occupational health research.
  • Proper data handling ensures the reliability and accessibility of research findings.
  • Data management plans should be an integral part of all research projects.