Research Considerations
- When conducting research, psychologists must consider factors that influence the quality and trustworthiness of their findings.
- These considerations help ensure that the results are valid, reliable, and applicable to real-world situations.
Research considerations are critical for evaluating the quality of a study. They help determine if the findings are trustworthy and applicable beyond the specific research context.
Validity
- Validity refers to the extent to which a study measures what it claims to measure. There are several types of validity:
Internal Validity
- Definition: The degree to which the results of a study are due to the manipulation of the independent variable and not other factors.
- Application: High internal validity means the study is well-controlled, with minimal confounding variables.
In Loftus and Palmer's (1974) study, internal validity was ensured by controlling the wording of questions to isolate its effect on memory distortion.
External Validity
- Definition: The extent to which the findings can be generalized beyond the study sample.
- Application: High external validity means the results are applicable to other populations, settings, or times.
Loftus and Palmer's findings on memory distortion may have limited external validity if the sample (college students) does not represent the broader population.
Content Validity
- Definition: The extent to which a test or measure covers the entire range of the concept being studied.
- Application: Ensures that all aspects of the concept are represented.
Loftus and Palmer's study focused on the influence of leading questions but did not address other factors affecting memory, such as stress or time elapsed since the event.
Face Validity
- Definition: The extent to which a test appears to measure what it claims to measure.
- Application: Relies on subjective judgment and is often assessed by experts or participants.
A questionnaire on anxiety has face validity if participants recognize the questions as relevant to anxiety.
Construct Validity
- Definition: The degree to which a test measures the theoretical construct it is intended to measure.
- Application: Requires evidence that the test correlates with other measures of the same construct.
A new intelligence test has construct validity if it correlates with established IQ tests.
TipWhen evaluating a study, consider which types of validity are most relevant. For example, internal validity is crucial for experiments, while external validity is key for field studies.
Reliability
- Reliability refers to the consistency of a study's results.
If a study is replicated and yields the same results, we can assume it is reliable.
NoteReliability does not guarantee validity. A study can be reliable but not valid if it consistently measures the wrong concept.
AnalogyThink of validity and reliability like a dart and a dart board.
- If the bullseye is consistently hit, it is valid and reliable.
- If the bullseye consistently hits the outer areas, it is reliable but not valid.
Generalizability
- Generalizability refers to the extent to which findings can be applied to other populations, contexts, or cultures.
Populations
- Definition: The degree to which results apply to groups beyond the study sample.
- Application: Studies with diverse samples are more generalizable.
- A study on memory using only college students may not generalize to older adults.
- The use of college students in the sample may limit the generalizability of the findings to other age groups or populations.
Contexts
- Definition: The extent to which findings apply to different settings or situations.
- Application: Studies conducted in artificial environments may lack ecological validity.
- Laboratory studies may not generalize to real-world settings.
- The artificial setting of the experiment may limit its ecological validity, as real-life eyewitness situations are more complex and emotionally charged.
Cultures
- Definition: The applicability of findings across different cultural groups.
- Application: Cross-cultural research enhances generalizability.
