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Common Data Types in Public Health Research

Data Types

Quantitative Data

  • Quantitative data is measurable, often used for comparisons, and involves counting of people, behaviors, conditions, or other discrete events (Wang, 2013).
  • Quantitative data uses numbers to determine the what, who, when, and where of health-related events (Wang, 2013).
  • Examples of quantitative data include: age, weight, temperature, or the number of people suffering from diabetes.

Qualitative Data

  • Qualitative data is a broad category of data that can include almost any non-numerical data.
  • Qualitative data uses words to describe a particular health-related event (Romano).
  • This data can be observed, but not measured.
  • Involves observing people in selected places and listening to discover how they feel and why they might feel that way (Wang, 2013).
  • Examples of qualitative data include: male/female, smoker/non-smoker, or questionnaire response (agree, disagree, neutral).
  • Example of qualitative data from a health care setting includes (Curry, Nembhard, & Bradley, 2009):
    • Measuring organizational change.
    • Measures of clinical leadership in implementing evidence-based guidelines.
    • Patient perceptions of quality of care.

Data Sources

Primary Data Sources

  • Primary data analysis in which the same individual or team of researchers designs, collects, and analyzes the data, for the purpose of answering a research question (Koziol & Arthur, nd).

Advantages to Using Primary Data

  • You collect exactly the data elements that you need to answer your research question (Romano).
  • You can test an intervention, such as an experimental drug or an educational program, in the purest way (a double-blind randomized controlled trial (Romano).
  • You control the data collection process, so you can ensure data quality, minimize the number of missing values, and assess the reliability of your instruments (Romano).

Secondary Data Sources

  • Existing data collected for another purposes, that you use to answer your research question (Romano).

Advantages of Working with Secondary Data

  • Large samples
  • Can provide population estimates : for example state data can be combined across states to get national estimates (Shaheen, Pan, & Mukherjee).
  • Less expensive to collect than primary data (Romano)
  • It takes less time to collect secondary data (Romano).
  • You may not need to worry about informed consent, human subjects restriction (Romano).

Issues in Using Secondary Data

  • Study design and data collection already completed (Koziol & Arthur, nd).
  • Data may not facilitate particular research question o Information regarding study design and data collection procedures may be scarce.
  • Data may potentially lack depth (the greater the breadth the harder it is to measure any one construct in depth) (Koziol & Arthur, nd).
  • Certain fields or departments (e.g., experimental programs) may place less value on secondary data analysis (Koziol & Arthur, nd).
  • Often requires special techniques to analyze statistically the data.