NATURAL EXPERIMENTS
TYPES OF EXPERIMENT:
LABORATORY, FIELD EXPERIMENTS, NATURAL AND QUASI-EXPERIMENTS
Laboratory, field, natural and quasi-experiments all investigate relationships between variables by comparing groups of scores. Still, there are also significant differences between different types of experiments, such as how respected they are.
Laboratory experiments fulfil all the criteria of an actual experiment but have problems with external validity.
Field experiments are true but don't occur in a controlled environment or have random allocation of participants.
Natural and quasi-experiments cannot prove or disprove causation with the same confidence as a lab experiment.
Natural experiments don't manipulate the IV; they observe changes in a naturally occurring IV.
Quasi-experiments don't randomly allocate participants to conditions.
NATURAL EXPERIMENTS
Be cautious not to be misled by the term "natural experiment." It might conjure images of conducting research amidst badgers and beavers in a forest clearing, but the "natural" aspect refers to the nature of the independent variable (IV) rather than the physical setting of the experiment. When we speak of a natural experiment, the IV is observed in its naturally occurring state rather than being directly manipulated by the researcher. For instance, in studying the impact of stress levels between individuals who have experienced an earthquake and those who haven't, the occurrence of the earthquake is the IV that is naturally varied, beyond the researcher's control. Natural experiments can unfold in any environment or context, distinct from field experiments characterized by their naturalistic settings.
In a natural experiment, the researcher does not actively manipulate the independent variable (IV). Instead, the researcher observes variations in the IV that occur naturally, recognizing that some IVs cannot be ethically manipulated. For instance, in studying the impacts of privation, Hodges and Tizard examined children who had experienced different upbringing scenarios—adoption, staying in an orphanage, or returning to their biological parents. These conditions represent naturally varying IVs. Manipulating such variables, such as by orchestrating the adoption of some children, keeping others in an orphanage, or sending others back to their biological families, would have been ethically impermissible.
All natural experiments have quasi-features; in other words, participants cannot be randomly allocated to conditions.
ADVANTAGES
Very similar to field experiments, natural experiments have their own set of advantages and disadvantages. The biggest advantage of a natural experiment is that it allows researchers to study the effects of independent variables (IVs) that are impossible or unethical to manipulate in a controlled setting. Another advantage is high external validity: because the IV arises naturally from real-life circumstances and has not been artificially created by researchers, the results are more likely to apply to other real-life groups and situations.
DISADVANTAGES
Natural experiments deviate from the criteria of a true experiment because the independent variable (IV) is not manipulated. Without manipulation, researchers lose the ability to control extraneous variables or randomly assign participants to conditions. A prime example of this is the study conducted by Hodges and Tizard on institutionalized children who were placed in children's homes from as young as four months of age. When the children were four, some had returned to their original homes while others were adopted. This study had three naturally occurring independent variables: returning home and staying at the institution or being adopted. The results indicated that adopted children fared better than other groups. However, since the IVs could not be manipulated due to ethical concerns, such as randomly allocating children to conditions like adoption, returning home, or staying at the institution, the researchers could not ascertain whether adoption can overcome privation. Factors such as the children's demeanour or behaviour may have influenced people choosing them for adoption. Researchers cannot control extraneous variables or randomly allocate participants to conditions without manipulation.
Moreover, because the IV is not manipulated, researchers have to study the conditions of the IV as they occur naturally. In other words, they must make do with the participants that present themselves, regardless of participant variables. This immensely lowers internal validity and makes it hard to draw confident conclusions about cause and effect. The use of retrospective data collected for other purposes may introduce inaccuracies, incompleteness, or difficulties in access. For these reasons, some people don't regard natural experiments as proper experiments at all.
ETHICS: Natural experiments present unique ethical challenges due to their reliance on uncontrolled external events. These challenges include ensuring equitable representation, interpreting results within the context of pre-existing inequalities, and managing inadvertent ethical complexities. Ethical considerations also extend to post-hoc analysis, longitudinal responsibilities, community impact, and public or private data use. Researchers must navigate these issues carefully, balancing scientific inquiry with respect for individual privacy, community sensitivities, and the broader societal implications of their work. Ethical rigour in natural experiments demands a nuanced approach to study design, data interpretation, and dissemination of findings, ensuring that research contributes positively to knowledge without compromising ethical standards.
EXAMPLES:
Oregon Health Insurance Experiment:
This study leveraged the Oregon Medicaid lottery, where some low-income individuals received Medicaid coverage while others did not due to limited slots. Researchers analyzed the impact of Medicaid coverage on various health outcomes, healthcare utilization, financial strain, and overall well-being. The study used a randomized controlled design, with individuals selected through a lottery system.
Reference: Finkelstein, A., Taubman, S., Wright, B., Bernstein, M., Gruber, J., Newhouse, J. P., Allen, H., Baicker, K., Oregon Health Study Group. (2012). The Oregon Health Insurance Experiment: Evidence from the First Year. Quarterly Journal of Economics, 127(3), 1057–1106.
Impact of Hurricane Katrina on Birth Outcomes:
This study examined the effects of Hurricane Katrina on birth outcomes by comparing data from areas affected by the hurricane to unaffected areas. Researchers investigated various birth outcomes such as low birth weight, preterm birth, and infant mortality rates. The study found significant adverse effects on birth outcomes in areas affected by the hurricane.
Reference: Currie, J., Rossin-Slater, M. (2013). Weathering the Storm: Hurricanes and Birth Outcomes. Journal of Health Economics, 32(3), 487–503.
Effect of Smoking Bans on Heart Attacks:
This study investigated the impact of smoking bans on the incidence of heart attacks by comparing data from areas with and without smoking bans. Researchers analysed hospital admissions for heart attacks before and after the implementation of smoking bans and found a significant decrease in heart attack rates following the bans.
Reference: Bartecchi, C. E., MacKenzie, T. D., Schrier, R. W. (2006). The Effects of Cigarette Smoking on Dose-Response and Magnitude of Glomerular Filtration Reductions with Advanced Age. Journal of the American Society of Nephrology, 17(6), 158S-163S
By the way, AQA only refers to between-subject quasi-experiments in the examination and specification, so just learn about this type if needs be.
ETHICS: Quasi-experiments may be chosen when it would be unethical to randomly assign participants to conditions, mainly when providing or withholding treatment could pose ethical concerns.
ADVANTAGES: Because the independent variable is manipulated before the dependent variable is measured, quasi-experimental research eliminates the directionality problem. External validity is usually higher than most true experiments involving real-world interventions rather than artificial laboratory settings. Plus, quasis allows for better control of confounding variables. Quasi-experiments may also be preferred when accurate experimental designs are impractical or too costly to implement. For researchers with limited funding or resources, conducting an accurate experimental study may be unfeasible due to financial constraints or logistical challenges. Additionally, recruiting and designing experimental interventions for sufficient subjects can be labour-intensive and time-consuming, making quasi-experimental designs a more practical option in some cases.
DISADVANTAGES:
Participants not randomly assigned: Because participants aren't randomly assigned, the groups being compared in a quasi-experiment may differ in ways other than the studied variable. These additional differences, known as confounding variables, can affect the outcomes and make it challenging to attribute any observed effects solely to the independent variable.
Experimental status: Quasi-experiments sit somewhere between correlational studies and true experiments in terms of their experimental status. Here's what that means:
Correlational studies: These studies observe the relationship between variables but do not involve experimental manipulation. They look at how variables naturally co-vary.
True experiments: Researchers manipulate the independent variable and randomly assign participants to conditions, allowing for stronger causal inferences.
Quasi-experiments: Quasi-experiments involve some degree of experimental manipulation, similar to true experiments, but lack random assignment. This makes them more controlled than correlational studies but less rigorous than true experiments in establishing causality. Therefore, they fall somewhere between the two regarding their experimental status.
