Key features of experiments

Experiments form a core method in psychological research. They allow researchers to investigate cause-and-effect relationships by systematically changing one aspect of a situation and observing the impact on another. This approach helps establish whether one factor directly influences another.

Main components of experiments

• Independent variable (IV) - This is the factor that the researcher deliberately changes or manipulates to see its effect.
• Dependent variable (DV) - This is the outcome that is measured to assess the impact of the IV. It is expected to change as a result of alterations to the IV.
• Experimental groups or conditions - These are the setups where the IV is varied. Participants experience different levels of the IV, allowing comparisons.
• Control group or condition - This provides a baseline for comparison. Here, the IV is not manipulated, or it is set at a standard level, helping to isolate the effect of the IV.

How experiments establish cause and effect

Experiments work by comparing data from experimental groups with data from a control group. Any differences in the DV are assumed to result from the IV, provided other factors that could affect the dependent variable are controlled (kept the same for both groups/conditions).

To ensure fairness and consistency, researchers often use standardised procedures (consistent steps followed in the same way for all participants) and standardised instructions (identical guidance given to everyone). These help give all participants the same experience, reducing bias.

Laboratory experiments

Laboratory experiments take place in a controlled, artificial environment, such as a research room or lab, where the researcher can manage many aspects of the setting. This high level of control is a defining feature, making it easier to isolate the effects of the IV.

Characteristics of laboratory experiments

In these experiments, the researcher regulates elements like temperature, lighting, and noise to ensure consistency. Controls are in place to ensure only the IV is deliberately changed between conditions, while other variables are held constant. This setup allows for precise measurement of the DV and stronger conclusions about cause and effect.

Evaluating laboratory experiments

Laboratory experiments have both advantages and drawbacks, which researchers must consider when interpreting results.

Field experiments

Field experiments occur in natural, everyday environments rather than controlled lab settings. This approach aims to capture more realistic behaviour by studying people in their normal surroundings, such as streets, schools, or workplaces.

Characteristics of field experiments

In these experiments, the IV is still manipulated, and the DV is measured, but the natural setting means some variables cannot be fully controlled. Uncontrolled, situational variables may differ between groups or conditions, making it harder to isolate the IV's effect and draw firm conclusions.

Evaluating field experiments

Field experiments offer unique benefits in terms of realism but come with challenges related to control and ethics.

Examples of experiments in psychological studies

Psychological research often uses experiments to test theories. Below are examples of laboratory and field experiments, broken down using key research terminology to highlight their structure and findings.

Laboratory experiment example: Pozzulo et al. on line-ups

• Aim - This study investigated how different types of line-ups affect identification accuracy.
• Method - Participants viewed video clips in a controlled lab setting, then identified a target person from various line-up formats (e.g., simultaneous or sequential).
• Procedure - The IV was the line-up type, and the DV was identification accuracy. Controls included standardised video presentation and instructions.
• Results - Certain line-up types led to more accurate identifications, showing the IV's impact.
• Conclusions - Findings suggest improvements for real-world eyewitness procedures, though the lab setting may limit generalisability.

Laboratory experiment example: Dement and Kleitman on sleep and dreams

• Aim - This research explored the link between sleep stages and dreaming.
• Method - Participants slept in a controlled lab environment and were woken during either REM (rapid eye movement) sleep or NREM (non-rapid eye movement) sleep.
• Procedure - The IV was the sleep stage at awakening, and the DV was dream recall. Controls included regulated sleep conditions and standardised questioning.
• Results - Dream recall was higher in REM sleep, indicating a causal link.
• Conclusions - The study supported theories about REM sleep's role in dreaming, with high control strengthening cause-and-effect claims.

Field experiment example: Piliavin et al. on subway Samaritans

• Aim - This study examined bystander helping behaviour in a real-world setting.
• Method - Conducted on a New York subway train, researchers staged scenarios with a "victim" collapsing.
• Procedure - The IV included the victim's type (e.g., drunk or ill) and whether a confederate (actor) offered help first. The DV was the rate of helping from passengers. No full controls were possible due to the natural environment.
• Results - Helping rates varied by victim type and model presence, with uncontrolled variables like passenger numbers noted.
• Conclusions - Findings highlighted factors influencing altruism in public, with high ecological validity but ethical concerns due to lack of consent.
• Limitations - Uncontrolled variables reduced reliability, making replication challenging.