Ecological Validity in Psychology: Definition & Examples

ecological validity in psychology, explained below

Ecological validity is a subset of external validity, specifically focusing on the extent to which behaviors observed and recorded in a study can be expected to occur in real-world settings (Nestor & Schutt, 2018).

To grasp the concept better, think about a study on eating habits conducted in a laboratory with measured portions . The controlled environment of a lab, with allocated meals, differs drastically from a typical day for most people.

Therefore, even if the study presents robust data about people’s eating habits under these specific circumstances, it has limited ecological validity. It may not accurately indicate how people would eat in their own homes and routine conditions. The essence here is how well the study emulates real-life situations. 

Ecological Validity Definition in Psychology

Ecological validity is defined in the below quote from the Encyclopedia of Social Psychology (Baumeister & Vohs, 2007):

“Ecological validity is the extent to which research findings would generalize to settings typical of everyday life.”

Maintaining ecological validity is a critical consideration in research designs (Hammersley, 2019). Failing to consider this can limit the generalizability of the findings and their application to real-world scenarios. The best research designs aim to balance internal and external validity, including ecological validity, while acknowledging the trade-offs between control and realism.

High Ecological Validity Examples

1. Studying Shopping Habits
A researcher could observe consumer behavior during a Black Friday sale in a large retail store. Observing customers’ decision-making processes, reactions to discounts, crowd navigation, and purchase patterns in this real-world retail environment provides a high ecological validity as it accurately reflects behaviors in a natural shopping scenario.

2. Classroom Learning
Let’s consider a longitudinal study that observes students’ note-taking habits during actual classes over a semester. The researchers could investigate how these habits relate to performance on tests. This study would possess excellent ecological validity since it reflects real classroom conditions instead of contrived lab settings (Monahan, 2013).

3. Internet Use
A researcher interested in studying online behavior could install software to track participants’ internet usage over several months. These data, reflecting the participants’ actual browsing patterns, website preferences, and time spent online, provide a high degree of ecological validity (Boase, 2013).

4. Workplace Dynamics
For example, researchers studying teamwork and collaboration could observe an existing team in a corporation working on a long-term project. By observing real interactions, conflicts, problem-solving, and workflow in a natural work environment, the study maintains strong ecological validity.

5. Physical Activity
A two-week study using fitness trackers to accurately record participants’ daily physical activity levels, sleep patterns, and heart rates would have stronger ecological validity compared to research relying solely on participants’ memory or honesty in self-report surveys. Such direct monitoring reflects actual behavior and routines, eliminating possible false reporting (Troiano, 2017).

Low Ecological Validity Examples

1. A Memory Test
Laboratory studies often use tasks which aren’t representative of real-world memory usage. For example, a study might ask participants to memorize a random sequence of ten numbers and recall them after a certain time period. This scenario has low ecological validity because it isolates memory from its everyday context where people usually remember meaningful information like phone numbers or addresses in a familiar sequence.

2. A Sleep Study
A study that investigates sleep patterns by having participants sleep in a lab under unfamiliar conditions, connected to various machines to monitor their sleep, has low ecological validity. This scenario varies substantially from how we naturally sleep in our comfortable, familiar home environment. Consequently, data collected this way may not accurately represent usual sleep patterns and could be influenced by factors such as anxiety or discomfort in the lab environment.

3. Emotional Response Study
Let’s consider a research study that uses images or videos to elicit emotional responses from participants in a controlled laboratory setting. This study may have low ecological validity as it doesn’t account for complex, nuanced emotional/stress responses that occur in real-life situations that are often influenced by a variety of unpredictable elements, personal relationships, or specific contexts (Coan et al., 2019).

4. Food Preference Study
Research that seeks to understand people’s food preferences by offering food samples in a lab may also have low ecological validity. People’s food choices in the real world can be influenced by factors such as ambiance, company, mood, and cultural preferences – factors which a controlled lab environment can’t replicate.

5. Group Dynamics Study
A study of group dynamics in a work team would have low ecological validity if it involved only strangers working together in a one-off, contrived task. A more ecologically valid study may observe established work teams over some time as they work on meaningful, long-term projects.

Limitations of Ecological Validity

As crucial as ecological validity is in research, it does have its set of limitations that one needs to be aware of.

  1. Time Constraints: Studies with a high degree of ecological validity often demand much more time, effort, and resources than controlled laboratory studies (Nestor & Schutt, 2018). Researchers must manage unpredictable variables that naturally occur in real-world contexts, necessitating a higher degree of flexibility during the data collection process.
  2. Need for Control: Maintaining control over confounding variables becomes much more complex outside of a laboratory setting (Kazdin, 2010). In natural environments, countless factors could influence the results.
  3. Struggles to Determine Cause and Effect: The more control you have over your dependent and independent variables, the more you can infer cause and effect. This is why experiments (which have lower ecological validity) tend to be able to infer causality while observational studies (which tend to have higher ecological validity) are merely descriptive. I discussed this in detail in my recent article on experimental vs observational studies.
  4. Generalizability: Results from studies with high ecological validity can sometimes lack generalizability. This happens because these studies are conducted in specific real-world settings – the behaviors observed might not be applicable to different contexts (Shadish, et al., 2011). 
  5. Ethical Concerns: Ethical considerations might often limit what can be examined in real-world settings, making it challenging to observe certain behaviors in their natural environments, for example, emotions after traumatic events, or reactions to sensitive topics (Kenny, 2019).

While ecological validity offers valuable insights, it’s crucial to interpret results with an understanding of these limitations. 

Ecological Validity vs External Validity

Ecological validity is a sub-type of external validity. As Andrade (2018) argues:

“External validity examines whether the study findings can be generalized to other contexts. Ecological validity examines, specifically, whether the study findings can be generalized to real-life settings; thus ecological validity is a subtype of external validity.” (Andrade, 2018, p., 498)

External validity is the extent to which results of a study can be generalized to other contexts, including different settings, people, and times.

This type of validity answers the question:

Can we apply the findings of this study beyond the specific conditions under which the research was conducted? (Mook, 2010).

For instance, if an experimental medication was successfully tested in a controlled laboratory environment with a specific age group, external validity would assess the likelihood of its effectiveness in a broader demographic and in various environments.

Ecological validity is a more specific term. It specifically addresses the realism of the research setting and procedures, assessing if the conditions of a study are reflective of real-world circumstances.

Consider a study on group dynamics conducted within an office setting with actual coworkers versus a simulated office setting with strangers acting as coworkers. The former would have higher ecological validity due to its more natural environment and interactions.

Therefore, while external validity looks at the scope of generalization, ecological validity focuses on the truthfulness of the methodology to real-life situations (Bortoli, 2018).

Ecological Validity vs Mundane Realism

Ecological validity and mundane realism are two crucial dimensions of validity in the realm of psychological research, each possessing its unique characteristics and implications (Nestor & Schutt, 2018).

Ecological validity refers to the degree to which the behaviors observed in a research setting reflect the behaviors that occur in natural settings. Emphasizing the relationship between conditions of the study and real-world situations, it regards the extent to which a study’s findings can be applied to everyday life (Kazdin, 2010).

Mundane realism, on the other hand, is a form of ecological validity that focuses more strictly on the surface resemblance between the research scenario and situations people might encounter in their everyday lives (Aronson, 2013).

Mundane realism relates to the physical and superficial characteristics of the research environment.

For example, a laboratory study of people’s behavior at a virtual workplace, using a realistic workplace setting with actual office equipment, would count as a study with high mundane realism. Its focus is the extent to which the experimental situation, materials, and tasks are similar to circumstances people encounter in real life.

Both ecological validity and mundane realism strive to increase the applicability of research findings to real-world scenarios, but they do so with different orientations. Ecological validity focuses on the functional relationship of the behavior—how well the research behavior predicts real-world behavior—whereas mundane realism is concerned with the superficial similar features of the experiment and the real-world situation (Bargh, 2002).

References

Andrade, C. (2018). Internal, external, and ecological validity in research design, conduct, and evaluation. Indian journal of psychological medicine, 40(5), 498-499.

Aronson, E., Wilson T.D., Akert R.M. (2013). Social Psychology (8th Edition). London: Prentice Hall.

Bargh, J. A. (2002). Losing Consciousness: Automatic Influences on Consumer Judgment, Behavior, and Motivation. Journal of Consumer Research, 29(3), 280-285. doi: https://doi.org/10.1086/341577

Baumeister, R. F. & Vohs, K. D. (2007). Encyclopedia of social psychology. New York: Sage.

Boase, J., & Ling, R. (2013). Measuring mobile phone use: Self-report versus log data. Journal of Computer-Mediated Communication, 18(4), 508-519. doi: https://doi.org/10.1111/jcc4.12021

Coan, J. A., Schaefer, H. S., & Davidson, R. J. (2006). Lending a hand: Social regulation of the neural response to threat. Psychological science, 17(12), 1032-1039. doi: https://doi.org/10.1111/j.1467-9280.2006.01832.x

Gehl, J. (2010). Cities for People. Island Press.

Hammersley, M. (2019). Reflections on Linguistic Repertoire: Revolutionary Science, Breaching Experiments and Ecological Validity. Qualitative Research, 19(1), 7–22. doi:10.1177/1468794118765086

Kazdin, A. E. (2021). Research design in clinical psychology. Cambridge: Cambridge University Press.

Kenny, D. A. (2019). Enhancing validity in psychological research. The American Psychologist, 74(9), 1018–1028. https://doi.org/10.1037/amp0000531

Monahan, T., McArdle, G., & Bertolotto, M. (2013). Virtual reality for collaborative e-learning. Computers & Education, 60(1), 1-15. Doi: https://doi.org/10.1016/j.compedu.2006.12.008

Mook, D. G. (2010). Classic experiments in psychology. Westport, Conn.: Greenwood Press.

Nestor, P. G., & Schutt, R. K. (2018). Research methods in psychology: Investigating human behavior. New York: Sage Publications.

Oldham, G. R., & Fried, Y. (2016). Job design research and theory: Past, present and future. Organizational behavior and human decision processes, 136, 20-35. doi: https://doi.org/10.1016/j.obhdp.2016.05.002

Shadish, W. R., Cook, T. D., & Campbell, D. T. (2011). Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton Mifflin.

Troiano, R. P., Berrigan, D., Dodd, K. W., Masse, L. C., Tilert, T., & McDowell, M. (2008). Physical activity in the United States measured by accelerometer. Medicine and science in sports and exercise, 40(1), 181.

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Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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