When the behavior of one or more study participants is measured as they age this is called?

Research Over Age and Time
Inside Research: Erika Hoff, Department of Psychology, Florida Atlantic University
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Defining Developmental Terms
Some scientists use the word development as an umbrella term to describe any research that studies humans over time, though this is only one of several relevant terms that also include aging, change over time, maturation, and learning. Each of these terms differs subtly but these distinctions influence specific research designs.

Development primarily refers to changes that occur over the first part of the lifespan, which are often thought of as positive, unidirectional, and cumulative. Development is often used to describe advances in such areas as motor skills, language, and cognition.

Maturation refers to growth and other changes in the body and brain that are associated with underlying genetic information. Therefore, maturation is considered to be relatively automatic and development encompasses both maturation and an individual’s life experience.

Aging refers to changes associated over the latter part of the lifespan and is often linked with loss of function in the areas of motor skills, language, and cognition.

Change over time is a more general way to capture temporal changes that is predominantly due to learning and experience. Scientists debate how to define these terms, but learning is often restricted to changes tied to specific instruction or experiences over relatively short periods of time whereas development and aging are thought to be universal processes impacting all members of a species.

Designs to Study Change Over Age and Time
There are a number of designs that allow researchers to understand causes of differences between individuals of various age groups, or within the same individual over time. Four approaches to developmental research discussed in the textbook are: cross-sectional, longitudinal, cross-sequential, and microgenetic.

Cross-sectional Designs
Cross-sectional research designs are the most common types of studies across age and time. They involve simultaneously assessing two or more different age groups. One challenge is determining the spacing between ages (how wide the gap in days, weeks, months, or even years) and results from past research, theoretical arguments, and your research question should all inform that decision.

Advantages of Cross-Sectional Designs
A main advantage of a cross-sectional design is that it allows researchers to gather information about different age groups in a short period of time. They also offer great ways to discover and document age-related differences associated with certain behaviors.

Disadvantages of Cross-Sectional Designs
Cross-sectional designs do not identify the underlying causes of differences across age groups. Researchers cannot tell whether age, maturation, specific learning experiences, or a combination of the above are the root of the difference. It is also possible that a cohort effect, the result of experiences that impact an entire group of individuals, is at play.

A second limitation of a cross-sectional design is verifying that methods are equally good at measuring behaviors for different age groups in the sample, which is known as having equivalent measures.

Lastly, cross-sectional designs tend to underestimate variability within an age group in order to characterize differences between groups. Because the focus is on differences between ages, it is possible that achievements obtained at specific ages gain greater status than they deserve.

Longitudinal Research Designs
Longitudinal research designs tracks groups of participants over a period of time with two or more assessments of the same individuals at different times. These designs can last any amount of time. Short-term designs tend to be used for infants. Most longitudinal designs are conducted over longer periods of times, often for several months, years, or even decades.

Advantages of Longitudinal Research Designs
One advantage is that longitudinal designs can help researchers understand how processes change in individuals. Another advantage is that these designs generate a lot of data and can allow researchers to explore a wide variety of research questions.

Disadvantages of Longitudinal Research Designs
The main challenge of using a longitudinal design is the cost in time and resources. These studies are much more expensive and take much longer to conduct than a cross-sectional study with the same number of participants.

A second issue is the impact of repeated testing. Much like a within-subjects design, researchers need to assess participants several times in a longitudinal study and this might influence participants.

The third limitation of longitudinal research is that it faces subject attrition. Subject attrition poses two issues: 1. It might lead to insufficient number of participants at the end of the study, which may mean not having enough statistical power. 2. It may result in significant changes to the study over the course of multiple assessments in terms of biases in who drops out. There are methods of minimizing attrition such as providing incentives, although these issues related to participant retention are ones that local IRBs will want to know about.

A fourth disadvantage of longitudinal studies is maintaining research personnel over time. In cases where studies last many years, staff might need to be changed and it is critical that the protocol is kept consistent.

A fifth disadvantage is determining whether the outcomes observed are due to developmental processes or to the timing of data collection that impacted all the participants.

Finally, the quality of a longitudinal study depends greatly on the initial sample and the quality of the measures in the earliest assessments. While these are factors critical to all studies, researchers using a longitudinal design have a much more difficult time recruiting a new sample in the middle of their study.

Cross-sequential Designs
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.

Advantages of Cross-sequential Designs
A key advantage using cross-sequential designs is that it allows researchers to examine multiple age groups in a short period of time, compared to longitudinal designs. It also enables researchers to test for cohort effects, which is often not possible in a usual longitudinal design.

Disadvantages of Cross-sequential Designs
Cross-sequential designs, like longitudinal designs, also face issues of repeated testing and are susceptible to subject attrition. Like cross-sectional designs, they have issues related to having equivalent measures.

Microgenetic Designs
Microgenetic designs aim to capture changes as they occur and attempt to understand mechanisms involved in any observed changes. They often focus on a key transition point or dramatic shift in the behavior of interest. Researchers usually begin observations before this transition point, and make observations until shortly after the transition has stabilized.

Advantages of Microgenetic Methods
One advantage of a microgenetic method is that it may lead to insights about the processes that lead to change. A second advantage is that it allows researchers to examine in detail transitions that occur infrequently.

Disadvantages of Microgenetic Methods
Microgenetic studies are susceptible to repeated testing since participants are observed frequently in a short period of time. Furthermore, because the large numbers of observations, many studies that use a microgenetic design often have a small number of participants and this can influence the representativeness of the sample. Furthermore, small sample sizes can make it difficult to use certain statistical techniques that are common in psychology.

Additional Challenges to Consider in Developmental Designs
Research designs that are used to help scientists understand change over time can be difficult to employ. There are three additional challenges in developmental designs: determining the cause of any observed changes, determining whether the measures used at different times or for different ages are equivalent, and determining the appropriate sample interval.

Determining the Underlying Cause of Change
An important goal of studying change overtime is to determine factors that play important roles in causing those changes. However, changes can be due to age, maturation, learning, specific experiences, and cohort effects. These effects do not always occur independently and can also interact.

Finding Equivalent Measures
From a perspective of creating a well-designed experiment, it would be ideal to use a single assessment to measure a behavior of individuals of different ages. Yet practically, a particular assessment that works best for toddlers may not work so well for young teenagers. A solution to this problem would be to test measures across different ages to find those that provide a reasonable assessment across all different ages.

Determining the Appropriate Sampling Interval
This final issue that confronts researchers examining change over time challenges researchers to determine how frequently they should obtain samples over time. The risk of inadequate sampling is that patterns of change may be mischaracterized or missed altogether. Adolph and Robinson (2011) advocate for frequent sampling, though the appropriateness of their technique involving daily summaries depend on the particular behavior of interest and the resources that you have available.

In which type of study are the effects of age and the effects of time of measurement confounded with one another?

What is the observation of a naturally occurring behavior?

Is development that takes place in clear stages with each stage bringing about behavior that is believed to be qualitatively different from behavior at earlier stages?

Which perspective seeks to identify behavior that is the result?