Cohort Effect

A cohort refers to a group of individuals who share a common demographic characteristic or life experience within a specific timeframe.

In plain English, this is a group of people who “grew up” or experienced a major life event together.

While we often think of cohorts as generations, such as Baby Boomers or Gen Z, the term applies to any group linked by timing. Common examples of cohorts include:

• Students attending the same university during a specific decade.

• Individuals who entered the workforce during a global recession.

• New parents who navigated the first year of child-rearing in 2020.

Because these groups share a distinct cultural and historical background, they often develop unique behaviors or attitudes.

This shared history creates a confounding variable, which is an outside factor that can unintentionally influence the results of an experiment.

A cohort effect occurs when research findings are heavily influenced by the fact that the participants all lived through this same specific era or time period.

Examples

Behavioral and Philosophical Worldviews

Generations often develop distinct “philosophies of life” based on the economic climate of their upbringing.

• The “Make-Do” Philosophy: People born in the 1930s lived through food rationing and global conflict. This created a lifelong habit of repairing items and conserving resources.

• The “Disposable” Philosophy: Those born in the 1980s matured during rapid financial and technological growth. This cohort is more likely to view products as replaceable.

• Trust and Reciprocity: In economic games, older cohorts show higher levels of reciprocity. This is the social norm of responding to a positive action with another positive action.

Handedness and Cultural Pressure

Hatta and Kawakami (1995) looked at handedness, which is the natural preference for using one hand over the other. They compared Japanese students from 1973 to a new sample in 1993.

The later group had significantly more left-handed and ambidextrous (able to use both hands equally) females.

The researchers concluded that Western media made non-right-handedness more acceptable. This shift reduced parental pressure to “correct” left-handed children.

Personality and Locus of Control

Meta-analyses show that more recent cohorts in the United States score higher in narcissism, which is an inflated sense of self-importance.

Additionally, there has been a shift toward an external locus of control. This is the belief that outside forces, rather than personal effort, determine one’s success.

These changes reflect shifting cultural values rather than a fundamental change in human nature.

Cross-Sectional Challenge

Most researchers begin with a cross-sectional design, a method where different age groups are compared at one single point in time.

While this approach is efficient and cost-effective, it frequently suffers from confounding variables. A confounding variable is an outside influence that changes the results of an experiment unexpectedly.

In these studies, age is “confounded” with the era of birth.

Variations in the data might simply reflect the distinct educational or social environments of each generation.

Even if researchers match participants on social backgrounds, one group may have experienced a unique historical event.

This distortion makes it difficult to claim that getting older is the true cause of any observed change.

Intelligence and Education

If a cross sectional study finds that 70-year-olds have lower IQ scores than 20-year-olds, is intelligence naturally declining?

Not necessarily.

This difference often reflects educational attainment, which is the highest level of formal schooling an individual completes.

Older cohorts frequently had fewer opportunities for higher education than younger generations. Thus, the IQ gap may reflect schooling quality rather than cognitive decay.

Longitudinal Research

To solve these issues, psychologists use longitudinal research.

This involves testing the same group of individuals repeatedly over many years.

By tracking the same people, researchers eliminate generational differences.

For example, a study might measure a person’s diet at age 20, 30, and 40. This reveals true developmental changes because the cohort remains constant.

Longitudinal design support life course theories, which suggest that human development is a cumulative result of belonging to a specific cohort.

Sequential Method

To overcome the limitations of simpler methods, researchers often turn to sequential research.

This is a hybrid method that combines the strengths of both cross-sectional and longitudinal approaches.

By examining several different age groups at multiple points in time, scientists can finally separate the effects of aging from the influence of history.

How Sequential Designs Work

The sequential (cross-longitudinal) method begins like a cross-sectional study. Researchers first select participants from various age cohorts to compare them immediately.

However, the study then adopts a longitudinal element by retesting those same participants at least once more in the future.

This dual approach allows for empirical validation, or the use of observable evidence to confirm that findings are consistent across different generations.

Case Study: The Development of Self-Esteem

A prominent example of this method is the work of Orth, Trzesniewski, and Robins (2010), who investigated how self-esteem changes across the lifespan.

• Aim: To track the development of self-esteem and determine if changes are related to age or specific generational experiences.

• Procedure: The researchers examined six different age cohorts. They collected self-esteem ratings from these groups at four distinct points: 1986, 1989, 1994, and 2002.

• Findings: The data revealed that self-esteem typically increases from age 25 to age 60. After age 60, however, these ratings tend to decrease.

• Conclusions: By using a sequential design, the researchers identified a clear developmental trend. If they had used a purely longitudinal study, it would have taken decades longer to reach these same conclusions.

Why Strategy Matters

Advanced designs like these reduce the impact of confounding variables.

These are outside factors that can confuse the results of an experiment by providing an alternative explanation for the data.

By using sequential methods, psychologists ensure their findings represent true human growth rather than just a “snapshot” of a specific historical moment.

This rigor allows for a deeper understanding of the life course, which is the sequence of events and roles that individuals occupy as they age.

References

Atingdui, N. (2011). Cohort effect. Encyclopedia of child behavior and development, 389-389.

Cozby, P. C., Bates, S., Krageloh, C., Lacherez, P., & Van Rooy, D. (1977). Methods in behavioral research: Mayfield publishing company Houston, TX.

Dołęga, Z., Jeż, W., & Irzyniec, T. (2014). The cohort effect in studies related to differences in psychosocial functioning of women with Turner syndrome. Endokrynologia Polska, 65(4), 287-294.

Hatta, T., & Kawakami, A. (1995). Patterns of handedness in modern Japanese: a cohort effect shown by re-administration of the HN Handedness Inventory after 20 years. Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale, 49(4), 505.

Haidt, J. (2024). The anxious generation: How the great rewiring of childhood is causing an epidemic of mental illness. Penguin Press.

Keyes, K. M., Utz, R. L., Robinson, W., & Li, G. (2010). What is a cohort effect? Comparison of three statistical methods for modeling cohort effects in obesity prevalence in the United States, 1971–2006. Social science & medicine, 70(7), 1100-1108.

Orth, U., Trzesniewski, K. H., & Robins, R. W. (2010). Self-esteem development from young adulthood to old age: A cohort-sequential longitudinal study. Journal of Personality and Social Psychology, 98(4), 645–658.

Porac, C., & Coren, S. (1979). A test of the validity of offsprings” report of parental handedness. Perceptual and Motor Skills, 49(1), 227-231.

Ryder, N. B. (1985). The cohort as a concept in the study of social change. In Cohort analysis in social research (pp. 9-44): Springer.

Schaie, K. W. (1986). Beyond calendar definitions of age, time, and cohort: The general developmental model revisited. Developmental review, 6(3), 252-277.

Warner Schaie, K. Cohort Sequential Designs (Convergence Analysis). In The Encyclopedia of Clinical Psychology (pp. 1-6).

Willets, R. C. (2004). The cohort effect: insights and explanations. British Actuarial Journal, 10(4), 833-877.

Worden, P. E., & Sherman-Brown, S. (1983). A word-frequency cohort effect in young versus elderly adults” memory for words. Developmental Psychology, 19(4), 521.