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Related Experiment Videos

Language as research data: application of computer content analysis in nursing research.

A W Kelly1, A M Sime

  • 1Mayo Center for Nursing, Mayo Clinic, Rochester, Minnesota.

ANS. Advances in Nursing Science
|April 1, 1990
PubMed
Summary

The Minnesota Contextual Content Analysis (MCCA) provides a systematic, computer-assisted method for analyzing client statements in nursing research. This approach enhances data reduction, coding reliability, and statistical comparison for richer insights into linguistic communications.

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Area of Science:

  • Nursing Research
  • Qualitative Data Analysis
  • Health Informatics

Background:

  • Client statements are crucial nursing research data.
  • Traditional analysis methods are labor-intensive and pose coding reliability challenges.
  • Adapting traditional methods for group comparisons is difficult.

Purpose of the Study:

  • To introduce the Minnesota Contextual Content Analysis (MCCA) as a computer-assisted tool.
  • To provide a systematic approach for categorizing and reducing qualitative nursing data.
  • To enhance the interpretation of manifest and latent meanings in client communications.

Main Methods:

  • Utilizes the Minnesota Contextual Content Analysis (MCCA) program.
  • Employs a computer-assisted approach for systematic data categorization and reduction.

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  • Scores social context and emphasized ideas as variables for statistical analysis.

    • Main Results:

    • Ensures coding reliability even with large datasets and multiple variables.
    • Facilitates the use of statistical procedures to refine meaning interpretation.
    • Enables comprehensive analysis of the entire text of communications.

    Conclusions:

    • The MCCA offers a rigorous method for nurse researchers.
    • It aids in overcoming the limitations of traditional qualitative data analysis.
    • Enhances the utilization of language as valuable research data in nursing.