Lifespan Development. Tara L. Kuther

with pictures and links, yet most people are unable to report what they have viewed, even immediately after viewing it (Vraga, Bode, & Troller-Renfree, 2016). A researcher who employs physiological measures might use an infant’s pupil dilation as a measure of interest (Wetzel, Buttelmann, Schieler, & Widmann, 2016). An advantage of physiological measures is they do not rely on verbal reports and generally cannot be faked. A challenge to physiological measures is that, although physiological responses can be recorded, they may be difficult to interpret. For example, excitement and anger may both cause an increase in heart rate. Physiological measures of brain activity are a particularly promising source of data, as discussed in the Brain and Biological Influences on Development feature. Data collection methods are summarized in Table 1.6.

      Research Designs

      There are many steps in conducting research. In addition to determining the research question and deciding what information to collect, scientists must choose a research design—a technique for conducting the research study.

      Case Study

      A case study is an in-depth examination of a single person (or small group of individuals). It is conducted by gathering information from many sources, such as through observations, interviews, and conversations with family, friends, and others who know the individual. A case study may include samples or interpretations of a person’s writing, such as poetry or journal entries, artwork, and other creations. A case study provides a rich description of a person’s life and influences on his or her development. It is often employed to study individuals who have unique and unusual experiences, abilities, or disorders. Conclusions drawn from a case study may shed light on an individual’s development but may not be generalized or applied to others. Case studies can be a source of hypotheses to examine in large-scale research.

Table 1.6

      Correlational Research

      Are children with high self-esteem more likely to excel at school? Are older adults with more friends happier than those with few? Are college students who work part-time less likely to graduate? All of these questions can be studied with correlational research, which permits researchers to examine relations among measured characteristics, behaviors, and events. For example, in one study, scientists examined the relationship between physical fitness and academic performance in middle school students and found that children with higher aerobic capacity scored higher on achievement tests than did children with poorer aerobic capacity (Bass, Brown, Laurson, & Coleman, 2013). Note that this correlation does not tell us why aerobic capacity was associated with academic achievement. Correlational research cannot answer this question because it simply describes relationships that exist among variables; it does not enable us to reach conclusions about the causes of those relationships. It is likely that other variables influence both a child’s aerobic ability and achievement (e.g., health), but correlation does not enable us to determine the causes for behavior—for that we need an experiment.

      Researchers experimentally manipulate which children play with violent video games to determine their effect on behavior.

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      Experimental Research

      Scientists who seek to test hypotheses about causal relationships, such as whether media exposure influences behavior or whether hearing particular types of music influences mood, employ experimental research. An experiment is a procedure that uses control to determine causal relationships among variables. Specifically, one or more variables thought to influence a behavior of interest are changed, or manipulated, while other variables are held constant. Researchers can then examine how the changing variable influences the behavior under study. If the behavior changes as the variable changes, this suggests that the variable caused the change in the behavior.

      Brain and Biological Influences on Development

      Methods of Studying the Brain

      Description

      Modern brain imaging techniques enable us to measure brain activity as individuals think and solve problems.

      Phanie / Alamy Stock Photo

      What parts of the brain are active when we solve problems or feel emotions? How does the brain change with development? Until recently, the brain was a mystery. Over the past hundred years, researchers have devised several ways of studying brain activity that have increased our understanding of how the brain functions and how it develops.

      The earliest instrument created to measure brain activity was the electroencephalogram, first used with humans in the 1920s (Collura, 1993). Electroencephalography (EEG) measures electrical activity patterns produced by the brain via electrodes placed on the scalp. Researchers study fluctuations in activity that occur when participants are presented with stimuli or when they sleep. EEG recordings measure electrical activity in the brain, but they do not provide information about the location of activity.

      Not until the invention of positron emission tomography (PET) in the early 1950s did researchers obtain the first glimpse of the inner workings of the brain (Portnow, Vaillancourt, & Okun, 2013). Researchers inject a small dose of radioactive material into the participant’s bloodstream and detected by the PET scan. The radioactive material enables researchers to monitor the flow of blood. Blood flows more readily to active areas of the brain, and the resulting images can illustrate what parts of the brain are active as participants view stimuli and solve problems. Developed in 1971, computerized tomography, known as the CT scan, produces X-ray images of brain structures (Cierniak, 2011). A movable X-ray unit rotates around a person’s head as it records images of the brain (Herman, 2009). The images are then combined to make a three-dimensional picture of the person’s brain, providing images of bone, brain vasculature, and tissue. CT scans can provide researchers with information about the density of brain structures to illustrate, for example, how the thickness of the cortex changes with development.

      Functional magnetic resonance imaging (fMRI) measures brain activity by monitoring changes in blood flow in the brain (Bandettini, 2012). Developed in the 1990s, MRI machines house a powerful magnet that uses radio waves and to measure blood oxygen level. Active areas of the brain require more oxygen-rich blood. Like PET scans, fMRI enables researchers to determine what parts of the brain are active as individuals complete cognitive tasks. However, fMRI images are much more detailed than PET scans. An important advantage of fMRI over PET scans is that it does not rely on radioactive molecules, which can only be administered a few times before becoming unsafe.

      Another imaging process, called diffusion tensor imaging (DTI), uses an MRI machine to track how water molecules move in and around the fibers connecting different parts of the brain (Soares, Marques, Alves, & Sousa, 2013). DTI gauges the thickness and density of the brain’s connections, permitting researchers to measure the brain’s white matter and determine changes that occur with development and with age-related illnesses, such as Alzheimer’s disease.

      What Do You Think?

      If you were going to study the brain, which measure would you choose and why? What type of information would you obtain from your chosen measure? Identify a research question that your measure might help you answer.

      For example, Gentile, Bender, and Anderson (2017) examined the effect of playing violent video games on children’s