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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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Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
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Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
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Purpose of Health Records I01:11

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The vital purpose of health records is to provide a complete and accurate account of a patient's medical history, including communication, diagnostic and therapeutic orders, care planning, research, and quality review.
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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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The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
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Meta-research studies should improve and evaluate their own data sharing practices.

Ioana A Cristea1, Florian Naudet2, Laura Caquelin2

  • 1Department of Brain and Behavioral Sciences, University of Pavia, Piazza Botta 11, 27100 Pavia, Italy; IRCCS Mondino Foundation, Pavia, Italy.

Journal of Clinical Epidemiology
|May 27, 2022
PubMed
Summary

Metaresearchers must improve data sharing practices. This study highlights benefits, barriers, and offers recommendations for enhancing data accessibility in metaresearch, contrasting it with clinical research.

Keywords:
Data sharingMeta-analysisMetaresearchOpen ScienceReporting guidelinesReproducibilitySecondary data

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Area of Science:

  • Scientific research methodology
  • Data science
  • Research ethics

Background:

  • Data sharing is crucial for scientific reproducibility and data reuse.
  • Metaresearch, which relies on existing data, has historically received less attention regarding its own data sharing practices compared to clinical research.
  • Metaresearchers have an ethical obligation to improve and evaluate data sharing, including their own.

Purpose of the Study:

  • To contrast data sharing practices, benefits, and barriers in metaresearch versus clinical research.
  • To identify inadequate and pervasive data sharing issues within metaresearch.
  • To provide concrete recommendations for improving data sharing in metaresearch.

Main Methods:

  • Comparative analysis of data sharing in metaresearch and clinical research.
  • Examination of benefits and barriers specific to metaresearch data sharing.
  • Review of current data sharing practices and their adequacy.

Main Results:

  • Significant disparities exist in the focus and practices of data sharing between metaresearch and clinical research.
  • Metaresearch faces unique challenges and benefits concerning data sharing.
  • Current data sharing practices in metaresearch are often inadequate.

Conclusions:

  • Metaresearchers must prioritize and enhance their data sharing practices.
  • Implementing tailored recommendations can improve data accessibility and reproducibility in metaresearch.
  • Ethical considerations necessitate robust data sharing protocols for all scientific fields.