TM

SI- Threats to Internal and External Validity

I. Understanding Validity

  • Internal Validity: Ensures that observed changes in the dependent variable result only from the manipulation of the independent variable.

  • External Validity: Ensures that research findings can be generalized to other settings, populations, or times.


II. Threats to Internal Validity

  1. History

    • Occurs when uncontrolled events influence outcomes between pretest and posttest.

    • Example: A natural disaster occurring during a stress-reduction intervention.

  2. Maturation

    • Refers to changes in subjects over time unrelated to the study (e.g., aging, fatigue).

    • Particularly problematic in long-term studies.

  3. Attrition (Mortality)

    • Occurs when participants drop out of the study, potentially skewing results.

    • Solution: Plan for sufficient sample size to account for dropouts.

  4. Testing

    • Repeated testing can influence outcomes as subjects learn from previous assessments.

    • Example: Improved posttest scores due to familiarization rather than treatment.

  5. Instrumentation

    • Changes in measurement tools or data collection techniques can affect outcomes.

    • Example: Malfunctioning equipment or altered survey wording.

  6. Statistical Regression

    • Occurs when subjects selected for extreme scores naturally move closer to the mean upon retesting.

    • Solution: Avoid selecting participants solely based on extreme scores.

  7. Selection Bias

    • Results from non-random assignment, causing systematic differences between groups.

    • Solution: Use random assignment to minimize this risk.

  8. Placebo Effect

    • When subjects expect improvement, they may report better outcomes even if the treatment is ineffective.

    • Solution: Use control groups and blinding techniques.


III. Threats to External Validity

  1. Sample to Population Effect

    • Occurs when the sample does not adequately represent the target population.

    • Solution: Ensure diverse and representative sampling.

  2. Description of Experimental Treatment

    • Lack of detailed explanation may hinder replication and limit generalizability.

    • Solution: Clearly describe treatment protocols.

  3. Exposure to Multiple Treatments

    • Participants may encounter multiple variables, making it hard to isolate individual effects.

  4. Hawthorne Effect

    • Subjects alter behavior simply because they know they are being studied.

    • Solution: Include control groups and limit subject awareness of observation.

  5. Researcher Effect

    • The researcher's behavior or characteristics may influence participants.

    • Solution: Standardize procedures and use multiple researchers when possible.

  6. Pretest Effects

    • The act of taking a pretest may influence participants’ responses on subsequent assessments.

    • Solution: Use alternate forms or minimize reliance on pretesting.


IV. Key Takeaways

  • Internal validity ensures that study outcomes are due to the independent variable and not external factors.

  • External validity ensures findings apply beyond the study conditions.

  • Employ strategies such as randomization, clear protocols, and control groups to reduce threats to validity.