Which research design can control for practice effects cohort effects and dropping out?
|
A cohort effect is a research result that occurs because of the characteristics of the cohort being studied. A cohort is any group that shares common historical or social experiences, like their year of birth. Cohort effects are a concern for researchers in fields such as sociology, epidemiology, and psychology. Show
Key Takeaways: Cohort Effect
Cohort DefinitionA cohort is a group of people who share a particular characteristic. Typically, the shared characteristic is a life event that took place in a particular time period, like birth or high school graduation. The most commonly studied cohorts are age-related (e.g. individuals who share a birth year or generational designation). Additional examples of cohorts include:
A cohort is any group that shares common historical or social experiences, like their year of birth. Cohort Effect DefinitionThe impact of the characteristics of a cohort on the results of a research study is called a cohort effect. While the factors that make a group of people a cohort may seem broad and therefore have little to do with each individual member of the group, the characteristics the group have in common may influence findings in a research context. This is because different cohorts’ characteristics vary over time due to their shared experiences, even if those experiences were very general. Psychological studies tend to focus on birth or generational cohorts. Such cohorts share common life experiences and experience similar social trends. For example, the historical events, arts and popular culture, political realities, economic conditions, and moral climate experienced by Millennials growing up were much different than those experienced by Baby Boomers. In other words, generational and birth cohorts develop in different sociocultural contexts, which can have an influence on the outcomes of research. Say a researcher wanted to see how easily people learned how to play a new mobile game featuring artificial intelligence. She decided to conduct a research study and recruited participants that ranged in age from 20 to 80 years old. Her findings showed that while the younger participants had an easy time learning how to play the game, the older participants had much more difficulty. The researcher could conclude that older people are less capable of learning to play the game than younger people. However, the research findings could also be the result of cohort effects in that older participants would have far less exposure to mobile devices than younger participants, potentially making it more difficult for them to learn how to play the new game. Thus, cohort effects are important to take into account in research. Cross-Sectional vs. Longitudinal ResearchCohort effects are a particular issue in studies that employ cross-sectional methods. In cross-sectional studies, researchers collect and compare data from participants in two or more age-related cohorts at a single point in time. For example, a researcher might collect information on attitudes towards gender equality in the workplace from people in their 20s, 40s, 60s, and 80s. The researcher might find that those in the 20-year-old group are more open to gender equality at work than those in the 80-year-old group. The researcher could conclude that as one ages they become less open to gender equality, but the results could also be the consequence of a cohort effect—the 80-year-old group had very different historical experiences than the 20-year-old group and, as a result, values gender equality differently. In cross-sectional studies of birth or generational cohorts it is difficult to discern whether a finding is the result of the aging process or if it is due to the differences between the various cohorts studied. The only way to guard against cohort effects when investigating the way people change over time is to perform a longitudinal study. In longitudinal studies, researchers collect data from a single set of participants over time. So, a researcher might collect information on attitudes towards gender equality in the workplace in 2019 from a group of 20 year olds, and then ask the participants the same questions when they are 40 (in 2039) and again when they are 60 (in 2059). The advantage of the longitudinal method is that by studying a group of people across time, change can be observed directly, ensuring there is no concern that cohort effects will compromise the research outcomes. On the other hand, longitudinal studies are expensive and time consuming, so researchers are more likely to use cross-sectional methods. With a cross-sectional design, comparisons among different age groups can be made quickly and efficiently, however, it is always possible that cohort effects have influenced a cross-sectional study’s findings. Examples of the Cohort EffectPsychological researchers have utilized cross-sectional and longitudinal studies to measure changes in personality traits over time. For example, a cross-sectional study of a group of participants ranging in age from 16 to 91 found that older adults were more agreeable and conscientious than younger adults. In explaining the limitations of their study, however, the researchers wrote that they couldn’t be certain if their findings were due to the effects of development over the lifespan or the result of cohort effects. In fact, there is research that indicates cohort effects play a role in personality differences. For example, a study published in the journal Personality and Individual Differences, the researcher utilized past research measuring extraversion in American college students to compare levels of this trait in birth cohorts from 1966 to 1993. The results showed a large increase in extraversion over time, showing the effect that birth cohort can have on personality. Sources
What type of research do researchers use to help reduce cohort effects?The only way to guard against cohort effects when investigating the way people change over time is to perform a longitudinal study. In longitudinal studies, researchers collect data from a single set of participants over time.
Which study design involves the possibility of cohort effects?Cross-sectional studies are studies that involve participants in different cohorts. Cross-sectional studies are especially susceptible to the cohort effect because they involve participants from different cohorts.
Which research design allows you to identify age effects cohort effects and time of measurement effects?Sequential designs are developmental research designs that include elements of both cross-sectional and longitudinal studies; they are configured in ways to address confounds between age, cohort, and time of measurement.
What type of research design assesses multiple cohorts over time?Cross-sequential designs combine aspects of both cross-sectional and longitudinal designs. They are also known as sequential, mixed, and accelerated longitudinal designs. This design is when multiple age groups or cohorts are studied over time.
|
