Researchers often conduct experiments to assess the effectiveness of different tools used to combat mental illnesses. For these tools to be effective, they need to be internal and external valid. Internal validity relates to the effectiveness of the instruments used in the study so that the results they give are reliable and meaningful. In contrast, external validation explores the possibility of applying the findings to real-world situations.
Internal validation is the ability of a study to establish a causal relationship between the issue under investigation and the remedy. It largely depends on the rigor used in selecting and using the instruments and the protocols used in gathering and processing data. A study is valid if the results can adequately explain alternative explanations of the relationship between the variables.
Researchers must take all precautions to ensure that the findings of their study can adequately address all doubts. They can do this by eliminating the confounding factors that make the results questionable. Confounding factors include all the other variables that interact with the subject of the study and have a significant effect on the outcome. In short, the deductions are internally valid if other scholars cannot provide alternative explanations of the results.
Strategies for improving internal validity
The key to producing internally valid results is to design the study in a way that invalidates the alternative hypotheses. One way of doing this is by randomizing the process of selecting participants. Randomization involves the arbitrary selection of the treatment and control groups. This eliminates systemic biases that occur during the selection of the participants. The selection should indiscriminate but still produce a sample that is representative of the population under investigation.
Another method is blinding, which involves the participants and the researcher not knowing the type of treatment they are getting. For instance, one group of participants can get a placebo instead of the actual intervention to avoid biasing their responses to the treatment.
Rigorous protocols can produce reliable outcomes because the researcher adheres to stringent procedures in the use of study instruments and administration of the intervention. The rigor helps reduce variances in the outcome because each group gets a different treatment.
Experimental manipulation involves making an intervention that alters the condition of one of the independent variables. It helps determine if the intervention works or some other variables are influencing the outcome.
Threats to inner validity
Some factors can profoundly affect the outcome of a study and comprise the integrity of the findings. One such factor is confounding, which entails the observation of an outcome that is caused by an independent variable that is not under investigation and that affects the dependent variable. This variable is directly related to the intervention but is not captured by the measurement instruments.
- Maturation is the situation where time becomes a variable in the study. For instance, the outcome of longitudinal studies can be affected by time because the participants have experienced natural changes during the study. Children can grow physically and psychologically while adults can experience cognitive decline. It is hard for researchers to rule out the effects of time on the outcome.
- Testing instruments may alter the outcome of a study. This often happens when the researcher used them to prime the participants to respond in a particular manner. Instrumentation alters the outcome in that it makes the participants respond unnaturally.
- Experimental bias is the situation where the researcher has varying attitudes towards different groups of respondents. This can cause variations in the results. You can avoid experimental bias by applying blinding measures.
- Diffusion refers to a situation where some participants from either the control or the treatment group cross lines through interactions and observation. This can lead to resentment, especially when the control group feels that the experimenters are favoring the treatment group.
- Attrition refers to some participants ceasing to contribute to the study. This creates a biased sample comprising of only those people who remained. Such people may have similar characteristics, such as optimistic worldviews or a high motivation to participate in the study.
- Statistical regression is the tendency of participants with extreme views changing their perspectives over time due to natural behavior rather than intervention.
- Repetitive testing alters the outcome because respondents become increasingly aware of the faculties being assessed with every test.
- Major events can also profoundly affect the respondent’s perspectives on an issue. For instance, natural phenomena or political developments can change people’s perception of reality overnight.
External validation is the potential of the findings to be generalized or applied to other people in similar circumstances and settings. Studies also need to have ecological validity, which refers to the ability of the findings to translate into solutions to real-world problems. Ironically, it is the rigor of the research methods used to achieve inner validity that makes it hard for the findings to have outer validity.
How to improve the chances of achieving external validation
You can improve the relevance of your research by formulating an inclusion and exclusion criteria that clearly define the population under study. Another method is replication, which involves repeating the experiment in a different setting using a new set of instruments. Alternatively, you can by-pass this resource-intensive exercise by conducting a meta-analysis of similar studies. If your results tally with those of similar studies, it is an indication of high external validity.
Always ensure that the participants are experiencing psychological realism. This implies that they view the study as a real-life event. Some of the strategies you can use include creating a cover story linking the experiment to their world. This prevents deviation from normal behavior.
You can also subject experimental data to statistical refinement to increase the validity of the results. This involves using advanced statistical and data analysis tools to create consistency among different datasets. Alternatively, you can do field experiments in the natural environment, such as ethnographic studies. They are easy to replicate because the researcher is fully integrated into the participant’s world.
Threats to outer validity
Certain factors may jeopardize the relevance of your study even if you have applied maximum rigor:
- Situational factors such as location and the number of variables may make it hard to apply the findings to a general population.
- Sample features are characteristics of the participants that cause partial alteration to the results. They make it hard to generalize the findings.
- Selection bias is a situation where the differences in outcomes between the participants reflect the skewed nature of the selection process.
- Pre and post-test effects are results that researchers create by giving tests to the participants. The implication is that the cause and effect relationship found in the study did not exist before the researcher’s intervention, meaning that the results are invalid.
Internal and external validity are critical to conducting successful mental health research, yet their relationship is paradoxical. It is possible to produce internally valid results that are hard to replicate in the real world because the parameters do not reflect how different factors interact in the natural environment. Conversely, you could conduct a field study that is globally applicable but struggle to define the variables. Therefore, it is important to balance between the two extremes so that your results are replicable and relevant to the real world.
What is Random Sampling?
Random sampling is a technique on which each sample has the same probability of being chosen.
What is a Sample Size?
Sample size corresponds to the quantity of data that is available for the study.
What is the Hawthorne Effect?
The Hawthorne effect is when an individual change their behavior when they know they are participating in experiments, clinical trials, or studies.