Now you know about some tools used to conduct research with infants and young children. Remember, research methods are the tools that are used to collect information. But it is easy to confuse research methods and research design. Research design is the strategy or blueprint for deciding how to collect and analyze information. Research design dictates which methods are used and how.
Researchers typically focus on two distinct types of comparisons when conducting research with infants and children. The first kind of comparison examines change within individuals. As the name suggests, this type of analysis measures the ways in which a specific person changes (or remains the same) over time. For example, a developmental scientist might be interested in studying the same group of infants at 12 months, 18 months, and 24 months to examine how vocabulary and grammar change over time. This kind of question would be best answered using a longitudinal research design. Another sort of comparison focuses on changes between groups. In this type of analysis, researchers study average changes in behavior between groups of different ages. Returning to the language example, a scientist might study the vocabulary and grammar used by 12-month-olds, 18-month-olds, and 24-month-olds to examine how language abilities change with age. This kind of question would be best answered using a cross-sectional research design.
Longitudinal Research Designs
Longitudinal research designs are used to examine behavior in the same infants and children over time. For example, when considering our example of hide-and-seek behaviors in preschoolers, a researcher might conduct a longitudinal study to examine whether 2-year-olds develop into better hiders over time. To this end, a researcher might observe a group of 2-year-old children playing hide-and-seek with plans to observe them again when they are 4 years old—and again when they are 6 years old. This study is longitudinal in nature because the researcher plans to study the same children as they age. Based on her data, the researcher might conclude that 2-year-olds develop more mature hiding abilities with age. Remember, researchers examine games such as hide- and-seek not because they are interested in the games them- selves, but because they offer clues to how children think, feel, and behave at various ages.
Longitudinal studies may be conducted over the short term (over a span of months, as in Wiebe et al., 2010) or over much longer durations (years or decades, as in Lukowski et al., 2010). For these reasons, longitudinal research designs are optimal for studying stability and change over time. Longitudinal research also has limitations, however. For one, longitudinal studies are expensive: they require that researchers maintain continued contact with participants over time, and they necessitate that scientists have funding to conduct their work over extended durations (from infancy to when participants were 19 years old in Lukowski et al., 2010). An additional risk is attrition. Attrition occurs when participants fail to complete all portions of a study. Participants may move, change their phone numbers, or simply become disinterested in participating over time. Researchers should account for the possibility of attrition by enrolling a larger sample into their study initially, as some participants will likely drop out over time.
The results from longitudinal studies may also be impacted by repeated assessments. Consider how well you would do on a math test if you were given the exact same exam every day for a week. Your performance would likely improve over time—not necessarily because you developed better math abilities, but because you were continuously practicing the same math problems. This phenomenon is known as a practice effect. Practice effects occur when participants become better at a task over time because they have done it again and again; not due to natural psychological development. A final limitation of longitudinal research is that the results may be impacted by cohort effects. Cohort effects occur when the results of the study are affected by the particular point in historical time during which participants are tested. As an example, think about how peer relationships in childhood have likely changed since February 2004—the month and year Facebook was founded. Cohort effects can be problematic in longitudinal research because only one group of participants are tested at one point in time—different findings might be expected if participants of the same ages were tested at different points in historical time.
Figure \(\PageIndex{1}\): Example of longitudinal research design. [This work, “Longitudinal Research Design,” is licensed under CC BY-NC-SA 4.0 by Judy Schmitt. It is a derivative of “Example of longitudinal research design” by Angela Lukowski and Helen Milojevich/Noba, which is licensed under CC BY-NC-SA 4.0.]
Cross-Sectional Designs
Cross-sectional research designs are used to examine behavior in participants of different ages who are tested at the same point in time. When considering our example of hide-and- seek behaviors in children, for example, a researcher might want to examine whether older children more often hide in novel locations (those in which another child in the same game has never hidden before) when compared to younger children. In this case, the researcher might observe 2-, 4-, and 6-year-old children as they play the game (the various age groups represent the “cross sections”). This research is cross-sectional in nature because the researcher plans to examine the behavior of children of different ages within the same study at the same time. Based on her data, the researcher might conclude that 2-year-olds more commonly hide in previously searched locations relative to 6-year-olds.
Cross-sectional designs are useful for many reasons. Because participants of different ages are tested at the same point in time, data collection can proceed at a rapid pace. In addition, because participants are only tested at one point in time, practice effects are not an issue—children do not have the opportunity to become better at the task over time. Cross-sectional designs are also more cost-effective than longitudinal research designs because there is no need to maintain contact with and follow-up on participants over time.
Figure \(\PageIndex{2}\): Example of cross-sectional research design. [This work, “Cross- Sectional Research Design,” is licensed under CC BY-NC-SA 4.0 by Judy Schmitt. It is a derivative of “Example of cross-sectional research design” by Angela Lukowski and Helen Milojevich/Noba, which is licensed under CC BY-NC-SA 4.0.]
One of the primary limitations of cross-sectional research, however, is that the results yield information on age-related change, not development per se. That is, although the study described above can show that 6-year-olds are more advanced in their hiding behavior than 2-year-olds, the data used to come up with this conclusion were collected from different children. It could be, for instance, that this specific sample of 6-year-olds just happened to be particularly clever at hide-and-seek. As such, the researcher cannot conclude that 2-year-olds develop into better hiders with age; she can only state that 6-year-olds, on average, are more sophisticated hiders relative to children 4 years younger.
Sequential Research Designs
Sequential research designs include elements of both longitudinal and cross-sectional research designs. Similar to longitudinal designs, sequential research features participants who are followed over time; similar to cross-sectional designs, sequential work includes participants of different ages. This research design is also distinct from those that have been discussed previously in that children of different ages are enrolled into a study at various points in time to examine age-related changes, assess development within the same individuals as they age, and account for the possibility of cohort effects.
Consider, once again, our example of hide-and-seek behaviors. In a study with a sequential design, a researcher might enroll three separate groups of children (Groups A, B, and C). Children in Group A would be enrolled when they are 2 years old and would be tested again when they are 4 and 6 years old (similar in design to the longitudinal study described previously). Children in Group B would be enrolled when they are 4 years old and would be tested again when they are 6 and 8 years old. Finally, children in Group. C would be enrolled when they are 6 years old and would be tested again when they are 8 and 10 years old.
Figure \(\PageIndex{3}\): Example of sequential research design. [This work, “Sequential Research Design,” is licensed under CC BY-NC-SA 4.0 by Judy Schmitt. It is a derivative of “Example of sequential research design” by Angela Lukowski and Helen Milojevich/Noba, which is licensed under CC BY-NC-SA 4.0.]
Studies with sequential designs are powerful because they allow for both longitudinal and cross-sectional comparisons. This research design also allows for the examination of cohort effects. For example, the researcher could examine the hide- and-seek behavior of 6-year-olds in Groups A, B, and C to determine whether performance differed by group when participants were the same age. If performance differences were found, there would be evidence for a cohort effect. In the hide-and-seek example, this might mean that children from different time periods varied in the amount they giggled or how patient they are when waiting to be found. Sequential designs are also appealing because they allow researchers to learn a lot about development in a relatively short amount of time. In the previous example, a 4-year research study would provide information about 8 years of developmental time by enrolling children ranging in age from 2 to 10 years old.
Because they include elements of longitudinal and cross-sectional designs, sequential research has many of the same strengths and limitations as these other approaches. For example, sequential work may require less time and effort than longitudinal research, but more time and effort than cross-sectional research. Although practice effects may be an issue if participants are asked to complete the same tasks or assessments over time, attrition may be less problematic than what is commonly experienced in longitudinal research since participants may not have to remain involved in the study for such a long period of time.
When considering the best research design to use in their research, scientists think about their main research question and the best way to come up with an answer. A table of advantages and disadvantages for each of the described research designs is provided here to help you as you consider what sorts of studies would be best conducted using each of these different approaches (Table \(\PageIndex{1}\)).
Table \(\PageIndex{1}\):Advantages and Disadvantages of Different Research Designs
Research Design
Disadvantages
Disadvantages
Longitudinal
Examines changes within individuals over time
Provides a developmental analysis
Expensive
Takes a long time
Participant attrition
Possibility of practice effects
Cannot examine cohort effects
Cross-sectional
Examines changes between participants of different ages at the same point in time
Provides information on age-related change
Cannot examine change over time
Cannot examine cohort effects
Sequential
Examines changes within individuals over time
Examines changes between participants of different ages at the
