Research methodology

Understanding Research Methodology

  • Research methodology section provides critical details about the study design and execution.

  • Functions as a recipe, enabling replication of the study by outlining:

    • Sample selection

    • Setting for data collection.

Sampling in Research

  • Key Concept: Population vs. Sample

    • Population: Entire group of individuals with common characteristics (e.g., diabetics).

    • Sample: A subset chosen for the study due to impracticality of studying the entire population.

  • Accessible Population Example:

    • Diabetics on insulin from a specific endocrinology practice.

  • Understanding Inclusion and Exclusion Criteria:

    • Inclusion Criteria: Characteristics that qualify participants for the study (e.g., age, health conditions).

    • Exclusion Criteria: Characteristics that disqualify participants to ensure clarity in outcome data (e.g., preexisting conditions).

Sampling Plan Considerations

  • How to recruit participants:

    • Methods include word-of-mouth, posters, emails.

  • Sample Size:

    • Important for validity; must aim for a sufficient number of participants (ideally, a minimum of 30 for quantitative studies).

    • Power analysis can help determine the minimum needed size for detecting differences among variables.

Types of Sampling

Probability Sampling

  • Ensures every individual has an equal chance of selection.

    • Simple Random Sampling: Selection via random methods such as drawing names.

    • Stratified Random Sampling: Involves dividing the population into subgroups and sampling from each.

    • Cluster Sampling: Random samples taken from increasingly narrow groups (e.g., states to counties).

    • Systematic Sampling: Selecting every nth individual from a list.

Non-probability Sampling

  • Not all individuals have an equal chance of selection; often more convenient.

    • Convenience Sampling: Using readily available individuals.

    • Snowball Sampling: Participants identify other potential participants, useful in hard-to-reach populations.

    • Quota Sampling: Sampling aimed to ensure representation of specific subgroups based on known characteristics.

    • Purposeful Sampling: Selecting participants based on the researcher’s judgment (e.g., specific health conditions).

Research Ethics and Institutional Review Board (IRB)

  • IRB ensures safety and ethical standards in research.

    • Examines consent validity, participant protection, and study rationale.

  • Ethical considerations dictate how to conduct and report studies with participant risk management.

Setting of Data Collection

  • The physical location where data is gathered (e.g., labs, homes, online).

  • Rationale for settings should consider participant safety, privacy, and comfort.

  • It is crucial to choose neutral locations to avoid emotional or physical risks (e.g., not conducting domestic abuse studies at home).

Data Collection Techniques and Considerations

  • Data collection must align with the study's goals, with feasibility in mind.

  • Types of data include:

    • Primary data (newly collected).

    • Secondary data (existing data used for analysis).

    • Historical data (archived materials).

  • Measurement errors can occur, categorized as:

    • Random Errors: Non-patterned discrepancies.

    • Systematic Errors: Consistent inaccuracies due to poorly constructed measurement tools.

  • Use of validated tools: Reliability and validity of tools should be confirmed within articles.