research studies developmental psychology

Research Methods in Developmental Psychology

Angela Lukowski and Helen Milojevich

Learning Objectives

• Describe different research methods used to study infant and child development
• Discuss different research designs, as well as their strengths and limitations
• Report on the unique challenges associated with conducting developmental research

Introduction

A group of children were playing hide-and-seek in the yard. Pilar raced to her hiding spot as her six-year-old cousin, Lucas, loudly counted, “… six, seven, eight, nine, ten! Ready or not, here I come!”. Pilar let out a small giggle as Lucas ran over to find her – in the exact location where he had found his sister a short time before. At first glance, this behavior is puzzling: why would Pilar hide in exactly the same location where someone else was just found? Whereas older children and adults realize that it is likely best to hide in locations that have not been searched previously, young children do not have the same cognitive sophistication. But why not… and when do these abilities first develop?

Developmental psychologists investigate questions like these using research methods that are tailored to the particular capabilities of the infants and children being studied. Importantly, research in developmental psychology is more than simply examining how children behave during games of hide-and-seek – the results obtained from developmental research have been used to inform best practices in parenting, education, and policy.

This module describes different research techniques that are used to study psychological phenomena in infants and children, research designs that are used to examine age-related changes in developmental processes and changes over time, and unique challenges and special issues associated with conducting research with infants and children.

Research Methods

Infants and children—especially younger children—cannot be studied using the same research methods used in studies with adults. Researchers, therefore, have developed many creative ways to collect information about infant and child development. In this section, we highlight some of the methods that have been used by researchers who study infants and older children, separating them into three distinct categories: involuntary or obligatory responses , voluntary responses , and psychophysiological responses . We will also discuss other methods such as the use of surveys and questionnaires. At the end of this section, we give an example of how interview techniques can be used to study the beliefs and perceptions of older children and adults – a method that cannot be used with infants or very young children.

Involuntary or obligatory responses

One of the primary challenges in studying very young infants is that they have limited motor control – they cannot hold their heads up for short amounts of time, much less grab an interesting toy, play the piano, or turn a door knob. As a result, infants cannot actively engage with the environment in the same way as older children and adults. For this reason, developmental scientists have designed research methods that assess involuntary or obligatory responses. These are behaviors in which people engage without much conscious thought or effort. For example, think about the last time you heard your name at a party – you likely turned your head to see who was talking without even thinking about it. Infants and young children also demonstrate involuntary responses to stimuli in the environment. When infants hear the voice of their mother, for instance, their heart rate increases – whereas if they hear the voice of a stranger, their heart rate decreases (Kisilevsky et al., 2003). Researchers study involuntary behaviors to better understand what infants know about the world around them.

One research method that capitalizes on involuntary or obligatory responses is a procedure known as habituation . In habituation studies, infants are presented with a stimulus such as a photograph of a face over and over again until they become bored with it. When infants become bored, they look away from the picture. If infants are then shown a new picture–such as a photograph of a different face– their interest returns and they look at the new picture. This is a phenomenon known as dishabituation . Habituation procedures work because infants generally look longer at novel stimuli relative to items that are familiar to them. This research technique takes advantage of involuntary or obligatory responses because infants are constantly looking around and observing their environments; they do not have to be taught to engage with the world in this way.

One classic habituation study was conducted by Baillargeon and colleagues (1985). These researchers were interested in the concept of object permanence , or the understanding that objects exist even when they cannot be seen or heard. For example, you know your toothbrush exists even though you are probably not able to see it right this second. To investigate object permanence in 5-month-old infants, the researchers used a violation of expectation paradigm . The researchers first habituated infants to an opaque screen that moved back and forth like a drawbridge (using the same procedure you just learned about in the previous paragraph). Once the infants were bored with the moving screen, they were shown two different scenarios to test their understanding of physical events. In both of these test scenarios, an opaque box was placed behind the moving screen. What differed between these two scenarios, however, was whether they confirmed or violated the solidity principle – the idea that two solid objects cannot occupy the same space at the same time. In the possible scenario, infants watched as the moving drawbridge stopped when it hit the opaque box (as would be expected based on the solidity principle). In the impossible scenario, the drawbridge appeared to move right through the space that was occupied by the opaque box! This impossible scenario violates the solidity principle in the same way as if you got out of your chair and walked through a wall, reappearing on the other side.

The results of this study revealed that infants looked longer at the impossible test event than at the possible test event. The authors suggested that the infants reacted in this way because they were surprised – the demonstration went against their expectation that two solids cannot move through one another. The findings indicated that 5-month-old infants understood that the box continued to exist even when they could not see it. Subsequent studies indicated that 3½- and 4½-month-old infants also demonstrate object permanence under similar test conditions (Baillargeon, 1987). These findings are notable because they suggest that infants understand object permanence much earlier than had been reported previously in research examining voluntary responses (although see more recent research by Cashon & Cohen, 2000).

Voluntary responses

As infants and children age, researchers are increasingly able to study their understanding of the world through their voluntary responses. Voluntary responses are behaviors that a person completes by choice. For example, think about how you act when you go to the grocery store: you select whether to use a shopping cart or a basket, you decide which sections of the store to walk through, and you choose whether to stick to your grocery list or splurge on a treat. Importantly, these behaviors are completely up to you (and are under your control). Although they do not do a lot of grocery shopping, infants and children also have voluntary control over their actions. Children, for instance, choose which toys to play with.

Researchers study the voluntary responses of infants and young children in many ways. For example, developmental scientists study recall memory in infants and young children by looking at voluntary responses. Recall memory is memory of past events or episodes, such as what you did yesterday afternoon or on your last birthday. Whereas older children and adults are simply asked to talk about their past experiences, recall memory has to be studied in a different way in infants and very young children who cannot discuss the past using language. To study memory in these subjects researchers use a behavioral method known as e licited imitation (Lukowski & Milojevich, in press).

In the elicited imitation procedure, infants play with toys that are designed in the lab to be unlike the kinds of things infants usually have at home. These toys (or event sequences, as researchers call them) can be put together in a certain way to produce an outcome that infants commonly enjoy. One of these events is called Find the Surprise. As shown in Figure 1, this toy has a door on the front that is held in place by a latch – and a small plastic figure is hidden on the inside. During the first part of the study, infants play with the toy in whichever way they want for a few minutes. The researcher then shows the infant how make the toy work by (1) flipping the latch out of the way and (2) opening the door, revealing the plastic toy inside. The infant is allowed to play with the toy again either immediately after the demonstration or after a longer delay. As the infant plays, the researcher records whether the infant finds the surprise using the same procedure that was demonstrated.

Use of the elicited imitation procedure has taught developmental scientists a lot about how recall memory develops. For example, we now know that 6-month-old infants remember one step of a 3-step sequence for 24 hours (Barr, Dowden, & Hayne, 1996; Collie & Hayne, 1999). Nine-month-olds remember the individual steps that make up a 2-step event sequence for 1 month, but only 50% of infants remember to do the first step of the sequence before the second (Bauer, Wiebe, Carver, Waters, & Nelson, 2003; Bauer, Wiebe, Waters, & Bangston, 2001; Carver & Bauer, 1999). When children are 20 months old, they remember the individual steps and temporal order of 4-step events for at least 12 months – the longest delay that has been tested to date (Bauer, Wenner, Dropik, & Wewerka, 2000).

Psychophysiology

Behavioral studies have taught us important information about what infants and children know about the world. Research on behavior alone, however, cannot tell scientists how brain development or biological changes impact (or are impacted by) behavior. For this reason, researchers may also record psychophysiological data, such as measures of heart rate, hormone levels, or brain activity. These measures may be recorded by themselves or in combination with behavioral data to better understand the bidirectional relations between biology and behavior.

One manner of understanding associations between brain development and behavioral advances is through the recording of event-related potentials , or ERPs. ERPs are recorded by fitting a research participant with a stretchy cap that contains many small sensors or electrodes. These electrodes record tiny electrical currents on the scalp of the participant in response to the presentation of particular stimuli, such as a picture or a sound (for additional information on recording ERPs from infants and children, see DeBoer, Scott, & Nelson, 2005). The recorded responses are then amplified thousands of times using specialized equipment so that they look like squiggly lines with peaks and valleys. Some of these brain responses have been linked to psychological phenomena. For example, researchers have identified a negative peak in the recorded waveform that they have called the N170 (Bentin, Allison, Puce, Perez, & McCarthy, 2010). The peak is named in this way because it is negative (hence the N) and because it occurs about 140ms to 170ms after a stimulus is presented (hence the 170). This peak is particularly sensitive to the presentation of faces, as it is commonly more negative when participants are presented with photographs of faces rather than with photographs of objects. In this way, researchers are able to identify brain activity associated with real world thinking and behavior.

The use of ERPs has provided important insight as to how infants and children understand the world around them. In one study (Webb, Dawson, Bernier, & Panagiotides, 2006), researchers examined face and object processing in children with autism spectrum disorders, those with developmental delays, and those who were typically developing. The children wore electrode caps and had their brain activity recorded as they watched still photographs of faces (of their mother or of a stranger) and objects (including those that were familiar or unfamiliar to them). The researchers examined differences in face and object processing by group by observing a component of the brainwave they called the prN170 (because it was believed to be a precursor to the adult N170). Their results showed that the height of the prN170 peak (commonly called the amplitude ) did not differ when faces or objects were presented to typically developing children. When considering children with autism, however, the peaks were higher when objects were presented relative to when faces were shown. Differences were also found in how long it took the brain to reach the negative peak (commonly called the latency of the response). Whereas the peak was reached more quickly when typically developing children were presented with faces relative to objects, the opposite was true for children with autism. These findings suggest that children with autism are in some way processing faces differently than typically developing children (and, as reported in the manuscript, children with more general developmental delays).

Parent-report questionnaires

Developmental science has come a long way in assessing various aspects of infant and child development through behavior and psychophysiology – and new advances are happening every day. In many ways, however, the very youngest of research participants are still quite limited in the information they can provide about their own development. As such, researchers often ask the people who know infants and children best – commonly, their parents or guardians – to complete surveys or questionnaires about various aspects of their lives. These parent-report data can be analyzed by themselves or in combination with any collected behavioral or psychophysiological data.

One commonly used parent-report questionnaire is the Child Behavior Checklist (CBCL; Achenbach & Rescorla, 2000). Parents complete the preschooler version of this questionnaire by answering questions about child strengths, behavior problems, and disabilities, among other things. The responses provided by parents are used to identify whether the child has any behavioral issues, such as sleep difficulties, aggressive behaviors, depression, or attention deficit/hyperactivity problems.

A recent study used the CBCL-Preschool questionnaire (Achenbach & Rescorla, 2000) to examine preschooler functioning in relation to levels of stress experienced by their mothers while they were pregnant (Ronald, Pennell, & Whitehouse, 2011). Almost 3,000 pregnant women were recruited into the study during their pregnancy and were interviewed about their stressful life experiences. Later, when their children were 2 years old, mothers completed the CBCL-Preschool questionnaire. The results of the study showed that higher levels of maternal stress during pregnancy (such as a divorce or moving to a new house) were associated with increased attention deficit/hyperactivity problems in children over 2 years later. These findings suggest that stressful events experienced during prenatal development may be associated with problematic child behavioral functioning years later – although additional research is needed.

Interview techniques

Whereas infants and very young children are unable to talk about their own thoughts and behaviors, older children and adults are commonly asked to use language to discuss their thoughts and knowledge about the world. In fact, these verbal report paradigms are among the most widely used in psychological research. For instance, a researcher might present a child with a vignette or short story describing a moral dilemma, and the child would be asked to give their own thoughts and beliefs (Walrath, 2011). For example, children might react to the following:

“Mr. Kohut’s wife is sick and only one medication can save her life. The medicine is extremely expensive and Mr. Kohut cannot afford it. The druggist will not lower the price. What should Mr. Kohut do, and why?”

Children can provide written or verbal answers to these types of scenarios. They can also offer their perspectives on issues ranging from attitudes towards drug use to the experience of fear while falling asleep to their memories of getting lost in public places – the possibilities are endless. Verbal reports such as interviews and surveys allow children to describe their own experience of the world.

Research Design

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 themselves, 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, Lukowski, & Bauer, 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.

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.

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, 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.

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 four-year research study would provide information about 8 years of developmental time by enrolling children ranging in age from two to ten 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.

Challenges Associated with Conducting Developmental Research

The previous sections describe research tools to assess development in infancy and early childhood, as well as the ways that research designs can be used to track age-related changes and development over time. Before you begin conducting developmental research, however, you must also be aware that testing infants and children comes with its own unique set of challenges. In the final section of this module, we review some of the main issues that are encountered when conducting research with the youngest of human participants. In particular, we focus our discussion on ethical concerns, recruitment issues, and participant attrition.

Ethical concerns

As a student of psychological science, you may already know that  Institutional Review Boards (IRBs) review and approve of all research projects that are conducted at universities, hospitals, and other institutions. An IRB is typically a panel of experts who read and evaluate proposals for research. IRB members want to ensure that the proposed research will be carried out ethically and that the potential benefits of the research outweigh the risks and harm for participants. What you may not know though, is that the IRB considers some groups of participants to be more vulnerable or at-risk than others. Whereas university students are generally not viewed as vulnerable or at-risk, infants and young children commonly fall into this category. What makes infants and young children more vulnerable during research than young adults? One reason infants and young children are perceived as being at increased risk is due to their limited cognitive capabilities, which makes them unable to state their willingness to participate in research or tell researchers when they would like to drop out of a study. For these reasons, infants and young children require special accommodations as they participate in the research process.

When thinking about special accommodations in developmental research, consider the informed consent process. If you have ever participated in psychological research, you may know through your own experience that adults commonly sign an informed consent statement (a contract stating that they agree to participate in research) after learning about a study. As part of this process, participants are informed of the procedures to be used in the research, along with any expected risks or benefits. Infants and young children cannot verbally indicate their willingness to participate, much less understand the balance of potential risks and benefits. As such, researchers are oftentimes required to obtain written informed consent from the parent or legal guardian of the child participant, an adult who is almost always present as the study is conducted. In fact, children are not asked to indicate whether they would like to be involved in a study at all (a process known as assent ) until they are approximately seven years old. Because infants and young children also cannot easily indicate if they would like to discontinue their participation in a study, researchers must be sensitive to changes in the state of the participant (determining whether a child is too tired or upset to continue) as well as to parent desires (in some cases, parents might want to discontinue their involvement in the research). As in adult studies, researchers must always strive to protect the rights and well-being of the minor participants and their parents when conducting developmental science.

Recruitment

An additional challenge in developmental science is participant recruitment. Recruiting university students to participate in adult studies is typically easy. Many colleges and universities offer extra credit for participation in research and have locations such as bulletin boards and school newspapers where research can be advertised. Unfortunately, young children cannot be recruited by making announcements in Introduction to Psychology courses, by posting ads on campuses, or through online platforms such as  Amazon Mechanical Turk . Given these limitations, how do researchers go about finding infants and young children to be in their studies?

The answer to this question varies along multiple dimensions. Researchers must consider the number of participants they need and the financial resources available to them, among other things. Location may also be an important consideration. Researchers who need large numbers of infants and children may attempt to do so by obtaining infant birth records from the state, county, or province in which they reside. Some areas make this information publicly available for free, whereas birth records must be purchased in other areas (and in some locations birth records may be entirely unavailable as a recruitment tool). If birth records are available, researchers can use the obtained information to call families by phone or mail them letters describing possible research opportunities. All is not lost if this recruitment strategy is unavailable, however. Researchers can choose to pay a recruitment agency to contact and recruit families for them. Although these methods tend to be quick and effective, they can also be quite expensive. More economical recruitment options include posting advertisements and fliers in locations frequented by families, such as mommy-and-me classes, local malls, and preschools or day care centers. Researchers can also utilize online social media outlets like Facebook, which allows users to post recruitment advertisements for a small fee. Of course, each of these different recruitment techniques requires IRB approval.

Another important consideration when conducting research with infants and young children is attrition . Although attrition is quite common in longitudinal research in particular, it is also problematic in developmental science more generally, as studies with infants and young children tend to have higher attrition rates than studies with adults. For example, high attrition rates in ERP studies oftentimes result from the demands of the task: infants are required to sit still and have a tight, wet cap placed on their heads before watching still photographs on a computer screen in a dark, quiet room. In other cases, attrition may be due to motivation (or a lack thereof). Whereas adults may be motivated to participate in research in order to receive money or extra course credit, infants and young children are not as easily enticed. In addition, infants and young children are more likely to tire easily, become fussy, and lose interest in the study procedures than are adults. For these reasons, research studies should be designed to be as short as possible – it is likely better to break up a large study into multiple short sessions rather than cram all of the tasks into one long visit to the lab. Researchers should also allow time for breaks in their study protocols so that infants can rest or have snacks as needed. Happy, comfortable participants provide the best data.

Conclusions

Child development is a fascinating field of study – but care must be taken to ensure that researchers use appropriate methods to examine infant and child behavior, use the correct experimental design to answer their questions, and be aware of the special challenges that are part-and-parcel of developmental research. After reading this module, you should have a solid understanding of these various issues and be ready to think more critically about research questions that interest you. For example, when considering our initial example of hide-and-seek behaviors in preschoolers, you might ask questions about what other factors might contribute to hiding behaviors in children. Do children with older siblings hide in locations that were previously searched less often than children without siblings? What other abilities are associated with the development of hiding skills? Do children who use more sophisticated hiding strategies as preschoolers do better on other tests of cognitive functioning in high school? Many interesting questions remain to be examined by future generations of developmental scientists – maybe you will make one of the next big discoveries!

Discussion Questions

• Why is it important to conduct research on infants and children?
• What are some possible benefits and limitations of the various research methods discussed in this module?
• Why is it important to examine cohort effects in developmental research?
• Think about additional challenges or unique issues that might be experienced by developmental scientists. How would they handle the challenges and issues you’ve addressed?
• Work with your peers to design a study to identify whether children who were good hiders as preschoolers are more cognitively advanced in high school. What research design would you use and why? What are the advantages and limitations of the design you selected?

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Research Methods in Developmental Psychology by Angela Lukowski and Helen Milojevich is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Behaviors in which individuals engage that do not require much conscious thought or effort.

Behaviors that a person has control over and completes by choice.

Recording of biological measures (such as heart rate and hormone levels) and neurological responses (such as brain activity) that may be associated with observable behaviors.

A research method in which participants are asked to report on their experiences using language, commonly by engaging in conversation with a researcher (participants may also be asked to record their responses in writing).

The use of thinking to direct muscles and limbs to perform a desired action.

When participants demonstrated decreased attention (through looking or listening behavior) to repeatedly-presented stimuli.

When participants demonstrated increased attention (through looking or listening behavior) to a new stimulus after having been habituated to a different stimulus.

The understanding that objects continue to exist even when they cannot be directly observed (e.g., that a pen continues to exist even when it is hidden under a piece of paper).

A research method in which infants are expected to respond in a particular way because one of two conditions violates or goes against what they should expect based on their everyday experiences (e.g., it violates our expectations that Wile E. Coyote runs off a cliff but does not immediately fall to the ground below).

The idea that two solid masses should not be able to move through one another.

The process of remembering discrete episodes or events from the past, including encoding, consolidation and storage, and retrieval.

A behavioral method used to examine recall memory in infants and young children.

When one variable is likely both cause and consequence of another variable.

The recording of participant brain activity using a stretchy cap with small electrodes or sensors as participants engage in a particular task (commonly viewing photographs or listening to auditory stimuli).

Research methods that require participants to report on their experiences, thoughts, feelings, etc., using language.

A short story that presents a situation that participants are asked to respond to.

The specific tools and techniques used by researchers to collect information.

The strategy (or “blueprint”) for deciding how to collect and analyze research information.

A research design used to examine behavior in the same participants over short (months) or long (decades) periods of time.

A research design used to examine behavior in participants of different ages who are tested at the same point in time.

When a participant drops out, or fails to complete, all parts of a study.

When participants get better at a task over time by “practicing” it through repeated assessments instead of due to actual developmental change (practice effects can be particularly problematic in longitudinal and sequential research designs).

When research findings differ for participants of the same age tested at different points in historical time.

A research design that includes elements of cross-sectional and longitudinal research designs. Similar to cross-sectional designs, sequential research designs include participants of different ages within one study; similar to longitudinal designs, participants of different ages are followed over time.

A committee that reviews and approves research procedures involving human participants and animal subjects to ensure that the research is conducted in accordance with federal, institutional, and ethical guidelines.

The process of getting permission from adults for themselves and their children to take part in research.

When minor participants are asked to indicate their willingness to participate in a study. This is usually obtained from participants who are at least 7 years old, in addition to parent or guardian consent.

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Developmental Psychology is the scientific study of mind and behavior from the perspective of change across the entire lifespan. In the present chapter, we provide a comprehensive and modern view on current topics particularly relevant when teaching Developmental Psychology. We start with the attempt to derive a contemporary definition of development and Developmental Psychology. Over historical time, perspectives on development changed. These different perspectives were regularly challenged, and we discuss some of the questions of scientific dispute such as the influence of nature and nurture on the development of an individual from a contemporary perspective. The perspectives often resulted in larger theoretical constructs. We will not describe individual theories comprehensively but rather focus on general issues of theoretical approaches and highlight one recent approach, the dynamic systems theories. Theories need to be supported by empirical evidence. Accordingly, we will briefly describe the major research designs used to measure developmental change. We will conclude the chapter with a focus on one topic particularly relevant when teaching Developmental Psychology, the development of communication, and discuss further topics that can potentially be included in a Developmental Psychology curriculum and describe some ideas on how to teach them. In all, we intend to provide a contemporary overview of the scientific study of developmental change.

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Daum, M.M., Manfredi, M. (2022). Developmental Psychology. In: Zumbach, J., Bernstein, D., Narciss, S., Marsico, G. (eds) International Handbook of Psychology Learning and Teaching. Springer International Handbooks of Education. Springer, Cham. https://doi.org/10.1007/978-3-030-26248-8_13-2

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Research in Developmental Psychology

What you’ll learn to do: examine how to do research in lifespan development.

How do we know what changes and stays the same (and when and why) in lifespan development? We rely on research that utilizes the scientific method so that we can have confidence in the findings. How data are collected may vary by age group and by the type of information sought. The developmental design (for example, following individuals as they age over time or comparing individuals of different ages at one point in time) will affect the data and the conclusions that can be drawn from them about actual age changes. What do you think are the particular challenges or issues in conducting developmental research, such as with infants and children? Read on to learn more.

Learning outcomes

• Explain how the scientific method is used in researching development
• Compare various types and objectives of developmental research
• Describe methods for collecting research data (including observation, survey, case study, content analysis, and secondary content analysis)
• Explain correlational research
• Describe the value of experimental research
• Compare the advantages and disadvantages of developmental research designs (cross-sectional, longitudinal, and sequential)
• Describe challenges associated with conducting research in lifespan development

Research in Lifespan Development

How do we know what we know.

An important part of learning any science is having a basic knowledge of the techniques used in gathering information. The hallmark of scientific investigation is that of following a set of procedures designed to keep questioning or skepticism alive while describing, explaining, or testing any phenomenon. Not long ago a friend said to me that he did not trust academicians or researchers because they always seem to change their story. That, however, is exactly what science is all about; it involves continuously renewing our understanding of the subjects in question and an ongoing investigation of how and why events occur. Science is a vehicle for going on a never-ending journey. In the area of development, we have seen changes in recommendations for nutrition, in explanations of psychological states as people age, and in parenting advice. So think of learning about human development as a lifelong endeavor.

Personal Knowledge

How do we know what we know? Take a moment to write down two things that you know about childhood. Okay. Now, how do you know? Chances are you know these things based on your own history (experiential reality), what others have told you, or cultural ideas (agreement reality) (Seccombe and Warner, 2004). There are several problems with personal inquiry or drawing conclusions based on our personal experiences.

Our assumptions very often guide our perceptions, consequently, when we believe something, we tend to see it even if it is not there. Have you heard the saying, “seeing is believing”? Well, the truth is just the opposite: believing is seeing. This problem may just be a result of cognitive ‘blinders’ or it may be part of a more conscious attempt to support our own views. Confirmation bias is the tendency to look for evidence that we are right and in so doing, we ignore contradictory evidence.

Philosopher Karl Popper suggested that the distinction between that which is scientific and that which is unscientific is that science is falsifiable; scientific inquiry involves attempts to reject or refute a theory or set of assumptions (Thornton, 2005). A theory that cannot be falsified is not scientific. And much of what we do in personal inquiry involves drawing conclusions based on what we have personally experienced or validating our own experience by discussing what we think is true with others who share the same views.

Science offers a more systematic way to make comparisons and guard against bias. One technique used to avoid sampling bias is to select participants for a study in a random way. This means using a technique to ensure that all members have an equal chance of being selected. Simple random sampling may involve using a set of random numbers as a guide in determining who is to be selected. For example, if we have a list of 400 people and wish to randomly select a smaller group or sample to be studied, we use a list of random numbers and select the case that corresponds with that number (Case 39, 3, 217, etc.). This is preferable to asking only those individuals with whom we are familiar to participate in a study; if we conveniently chose only people we know, we know nothing about those who had no opportunity to be selected. There are many more elaborate techniques that can be used to obtain samples that represent the composition of the population we are studying. But even though a randomly selected representative sample is preferable, it is not always used because of costs and other limitations. As a consumer of research, however, you should know how the sample was obtained and keep this in mind when interpreting results. It is possible that what was found was limited to that sample or similar individuals and not generalizable to everyone else.

Scientific Methods

The particular method used to conduct research may vary by discipline and since lifespan development is multidisciplinary, more than one method may be used to study human development. One method of scientific investigation involves the following steps:

• Determining a research question
• Reviewing previous studies addressing the topic in question (known as a literature review)
• Determining a method of gathering information
• Conducting the study
• Interpreting the results
• Drawing conclusions; stating limitations of the study and suggestions for future research
• Making the findings available to others (both to share information and to have the work scrutinized by others)

The findings of these scientific studies can then be used by others as they explore the area of interest. Through this process, a literature or knowledge base is established. This model of scientific investigation presents research as a linear process guided by a specific research question. And it typically involves quantitative research , which relies on numerical data or using statistics to understand and report what has been studied.

Another model of research, referred to as qualitative research, may involve steps such as these:

• Begin with a broad area of interest and a research question
• Gain entrance into a group to be researched
• Gather field notes about the setting, the people, the structure, the activities, or other areas of interest
• Ask open-ended, broad “grand tour” types of questions when interviewing subjects
• Modify research questions as the study continues
• Note patterns or consistencies
• Explore new areas deemed important by the people being observed
• Report findings

In this type of research, theoretical ideas are “grounded” in the experiences of the participants. The researcher is the student and the people in the setting are the teachers as they inform the researcher of their world (Glazer & Strauss, 1967). Researchers should be aware of their own biases and assumptions, acknowledge them, and bracket them in efforts to keep them from limiting accuracy in reporting. Sometimes qualitative studies are used initially to explore a topic and more quantitative studies are used to test or explain what was first described.

A good way to become more familiar with these scientific research methods, both quantitative and qualitative, is to look at journal articles, which are written in sections that follow these steps in the scientific process. Most psychological articles and many papers in the social sciences follow the writing guidelines and format dictated by the  American Psychological Association  (APA). In general, the structure follows: abstract (summary of the article), introduction or literature review, methods explaining how the study was conducted, results of the study, discussion and interpretation of findings, and references.

Link to Learning

Brené Brown is a bestselling author and social work professor at the University of Houston. She conducts grounded theory research by collecting qualitative data from large numbers of participants. In Brené Brown’s TED Talk The Power of Vulnerability , Brown refers to herself as a storyteller-researcher as she explains her research process and summarizes her results.

Research Methods and Objectives

The main categories of psychological research are descriptive, correlational, and experimental research. Research studies that do not test specific relationships between variables are called  descriptive, or qualitative, studies . These studies are used to describe general or specific behaviors and attributes that are observed and measured. In the early stages of research, it might be difficult to form a hypothesis, especially when there is not any existing literature in the area. In these situations designing an experiment would be premature, as the question of interest is not yet clearly defined as a hypothesis. Often a researcher will begin with a non-experimental approach, such as a descriptive study, to gather more information about the topic before designing an experiment or correlational study to address a specific hypothesis. Some examples of descriptive questions include:

• “How much time do parents spend with their children?”
• “How many times per week do couples have intercourse?”
• “When is marital satisfaction greatest?”

The main types of descriptive studies include observation, case studies, surveys, and content analysis (which we’ll examine further in the module). Descriptive research is distinct from  correlational research , in which psychologists formally test whether a relationship exists between two or more variables.  Experimental research  goes a step further beyond descriptive and correlational research and randomly assigns people to different conditions, using hypothesis testing to make inferences about how these conditions affect behavior. Some experimental research includes explanatory studies, which are efforts to answer the question “why” such as:

• “Why have rates of divorce leveled off?”
• “Why are teen pregnancy rates down?”
• “Why has the average life expectancy increased?”

Evaluation research is designed to assess the effectiveness of policies or programs. For instance, research might be designed to study the effectiveness of safety programs implemented in schools for installing car seats or fitting bicycle helmets. Do children who have been exposed to the safety programs wear their helmets? Do parents use car seats properly? If not, why not?

Research Methods

We have just learned about some of the various models and objectives of research in lifespan development. Now we’ll dig deeper to understand the methods and techniques used to describe, explain, or evaluate behavior.

All types of research methods have unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. While this allows for results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records. While this can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control over how or what kind of data was collected.

Types of Descriptive Research

Observation.

Observational studies , also called naturalistic observation, involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play in a park, or behind a one-way glass while children are at play in a laboratory playroom. The researcher may follow a checklist and record the frequency and duration of events (perhaps how many conflicts occur among 2-year-olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.). The researcher may be a participant or a non-participant. What would be the strengths of being a participant? What would be the weaknesses?

In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. One weakness of self-report studies is that what people do and what they say they do are often very different. A major weakness of observational studies is that they do not allow the researcher to explain causal relationships. Yet, observational studies are useful and widely used when studying children. It is important to remember that most people tend to change their behavior when they know they are being watched (known as the Hawthorne effect ) and children may not survey well.

Case Studies

Case studies  involve exploring a single case or situation in great detail. Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation. Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation. And they are often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment. Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions. However, the findings from case studies cannot be generalized or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison. (Read The Man Who Mistook His Wife for a Hat by Dr. Oliver Sacks as a good example of the case study approach.)

Surveys  are familiar to most people because they are so widely used. Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online. A survey involves asking a standard set of questions to a group of subjects. In a highly structured survey, subjects are forced to choose from a response set such as “strongly disagree, disagree, undecided, agree, strongly agree”; or “0, 1-5, 6-10, etc.” Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many variables in a relatively short period of time. Surveys typically yield surface information on a wide variety of factors, but may not allow for an in-depth understanding of human behavior.

Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices. However, they are based on self-report, or what people say they do rather than on observation, and this can limit accuracy. Validity refers to accuracy and reliability refers to consistency in responses to tests and other measures; great care is taken to ensure the validity and reliability of surveys.

Content Analysis

Content analysis  involves looking at media such as old texts, pictures, commercials, lyrics, or other materials to explore patterns or themes in culture. An example of content analysis is the classic history of childhood by Aries (1962) called “Centuries of Childhood” or the analysis of television commercials for sexual or violent content or for ageism. Passages in text or television programs can be randomly selected for analysis as well. Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.

Secondary content analysis, or archival research, involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices, or preferences. There are a number of data sets available to those who wish to conduct this type of research. The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study. And unfortunately, the researcher is limited to the questions asked and data collected originally.

Correlational and Experimental Research

Correlational research.

When scientists passively observe and measure phenomena it is called correlational research . Here, researchers do not intervene and change behavior, as they do in experiments. In correlational research, the goal is to identify patterns of relationships, but not cause and effect. Importantly, with correlational research, you can examine only two variables at a time, no more and no less.

So, what if you wanted to test whether spending money on others is related to happiness, but you don’t have $20 to give to each participant in order to have them spend it for your experiment? You could use a correlational design—which is exactly what Professor Elizabeth Dunn (2008) at the University of British Columbia did when she conducted research on spending and happiness. She asked people how much of their income they spent on others or donated to charity, and later she asked them how happy they were. Do you think these two variables were related? Yes, they were! The more money people reported spending on others, the happier they were.

Understanding Correlation

With a positive correlation , the two variables go up or down together. In a scatterplot, the dots form a pattern that extends from the bottom left to the upper right (just as they do in Figure 1). The r value for a positive correlation is indicated by a positive number (although, the positive sign is usually omitted). Here, the r value is .81. For the example above, the direction of the association is positive. This means that people who perceived the past month as being good reported feeling happier, whereas people who perceived the month as being bad reported feeling less happy.

A negative correlation is one in which the two variables move in opposite directions. That is, as one variable goes up, the other goes down. Figure 2 shows the association between the average height of males in a country (y-axis) and the pathogen prevalence (or commonness of disease; x-axis) of that country. In this scatterplot, each dot represents a country. Notice how the dots extend from the top left to the bottom right. What does this mean in real-world terms? It means that people are shorter in parts of the world where there is more disease. The r-value for a negative correlation is indicated by a negative number—that is, it has a minus (–) sign in front of it. Here, it is –.83.

Experimental Research

Experiments  are designed to test  hypotheses  (or specific statements about the relationship between  variables ) in a controlled setting in an effort to explain how certain factors or events produce outcomes. A variable is anything that changes in value. Concepts are operationalized  or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study. For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of marital satisfaction. What is something measurable that would indicate some level of marital satisfaction? Would it be the amount of time couples spend together each day? Or eye contact during a discussion about money? Or maybe a subject’s score on a marital satisfaction scale? Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction. What do you think? These are the kinds of considerations researchers must make when working through the design.

The experimental method is the only research method that can measure cause and effect relationships between variables. Three conditions must be met in order to establish cause and effect. Experimental designs are useful in meeting these conditions:

• The independent and dependent variables must be related.  In other words, when one is altered, the other changes in response. The independent variable is something altered or introduced by the researcher; sometimes thought of as the treatment or intervention. The dependent variable is the outcome or the factor affected by the introduction of the independent variable; the dependent variable  depends on the independent variable. For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.
• The cause must come before the effect.  Experiments measure subjects on the dependent variable before exposing them to the independent variable (establishing a baseline). So we would measure the subjects’ level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels. (Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these methods.)
• The cause must be isolated.  The researcher must ensure that no outside, perhaps unknown variables, are actually causing the effect we see. The experimental design helps make this possible. In an experiment, we would make sure that our subjects’ diets were held constant throughout the exercise program. Otherwise, the diet might really be creating a change in stress level rather than exercise.

A basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the  experimental group or the control group . Ideally, to prevent bias, the participants would be blind to their condition (not aware of which group they are in) and the researchers would also be blind to each participant’s condition (referred to as “ double blind “). The experimental group is the group that is going to be exposed to an independent variable or condition the researcher is introducing as a potential cause of an event. The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable. This helps address the placebo effect, which is that a group may expect changes to happen just by participating. After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred. If so, we are in a better position to suggest that the independent variable caused the change in the dependent variable . The basic experimental model looks like this:

The major advantage of the experimental design is that of helping to establish cause and effect relationships. A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting.

Developmental Research Designs

Now you know about some tools used to conduct research about human development. Remember,  research methods  are 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. Developmental research designs are techniques used particularly in lifespan development research. When we are trying to describe development and change, the research designs become especially important because we are interested in what changes and what stays the same with age. These techniques try to examine how age, cohort, gender, and social class impact development.

Cross-sectional designs

The majority of developmental studies use cross-sectional designs because they are less time-consuming and less expensive than other developmental designs. Cross-sectional research designs are used to examine behavior in participants of different ages who are tested at the same point in time. Let’s suppose that researchers are interested in the relationship between intelligence and aging. They might have a hypothesis (an educated guess, based on theory or observations) that intelligence declines as people get older. The researchers might choose to give a certain intelligence test to individuals who are 20 years old, individuals who are 50 years old, and individuals who are 80 years old at the same time and compare the data from each age group. This research is cross-sectional in design because the researchers plan to examine the intelligence scores of individuals of different ages within the same study at the same time; they are taking a “cross-section” of people at one point in time. Let’s say that the comparisons find that the 80-year-old adults score lower on the intelligence test than the 50-year-old adults, and the 50-year-old adults score lower on the intelligence test than the 20-year-old adults. Based on these data, the researchers might conclude that individuals become less intelligent as they get older. Would that be a valid (accurate) interpretation of the results?

No, that would not be a valid conclusion because the researchers did not follow individuals as they aged from 20 to 50 to 80 years old. One of the primary limitations of cross-sectional research is that the results yield information about age differences  not necessarily changes with age or over time. That is, although the study described above can show that in 2010, the 80-year-olds scored lower on the intelligence test than the 50-year-olds, and the 50-year-olds scored lower on the intelligence test than the 20-year-olds, the data used to come up with this conclusion were collected from different individuals (or groups of individuals). It could be, for instance, that when these 20-year-olds get older (50 and eventually 80), they will still score just as high on the intelligence test as they did at age 20. In a similar way, maybe the 80-year-olds would have scored relatively low on the intelligence test even at ages 50 and 20; the researchers don’t know for certain because they did not follow the same individuals as they got older.

It is also possible that the differences found between the age groups are not due to age, per se, but due to cohort effects. The 80-year-olds in this 2010 research grew up during a particular time and experienced certain events as a group. They were born in 1930 and are part of the Traditional or Silent Generation. The 50-year-olds were born in 1960 and are members of the Baby Boomer cohort. The 20-year-olds were born in 1990 and are part of the Millennial or Gen Y Generation. What kinds of things did each of these cohorts experience that the others did not experience or at least not in the same ways?

You may have come up with many differences between these cohorts’ experiences, such as living through certain wars, political and social movements, economic conditions, advances in technology, changes in health and nutrition standards, etc. There may be particular cohort differences that could especially influence their performance on intelligence tests, such as education level and use of computers. That is, many of those born in 1930 probably did not complete high school; those born in 1960 may have high school degrees, on average, but the majority did not attain college degrees; the young adults are probably current college students. And this is not even considering additional factors such as gender, race, or socioeconomic status. The young adults are used to taking tests on computers, but the members of the other two cohorts did not grow up with computers and may not be as comfortable if the intelligence test is administered on computers. These factors could have been a factor in the research results.

Another disadvantage of cross-sectional research is that it is limited to one time of measurement. Data are collected at one point in time and it’s possible that something could have happened in that year in history that affected all of the participants, although possibly each cohort may have been affected differently. Just think about the mindsets of participants in research that was conducted in the United States right after the terrorist attacks on September 11, 2001.

Longitudinal research designs

Longitudinal   research involves beginning with a group of people who may be of the same age and background (cohort) and measuring them repeatedly over a long period of time. One of the benefits of this type of research is that people can be followed through time and be compared with themselves when they were younger; therefore changes with age over time are measured. What would be the advantages and disadvantages of longitudinal research? Problems with this type of research include being expensive, taking a long time, and subjects dropping out over time. Think about the film, 63 Up , part of the Up Series mentioned earlier, which is an example of following individuals over time. In the videos, filmed every seven years, you see how people change physically, emotionally, and socially through time; and some remain the same in certain ways, too. But many of the participants really disliked being part of the project and repeatedly threatened to quit; one disappeared for several years; another died before her 63rd year. Would you want to be interviewed every seven years? Would you want to have it made public for all to watch?   

Longitudinal research designs are used to examine behavior in the same individuals over time. For instance, with our example of studying intelligence and aging, a researcher might conduct a longitudinal study to examine whether 20-year-olds become less intelligent with age over time. To this end, a researcher might give an intelligence test to individuals when they are 20 years old, again when they are 50 years old, and then again when they are 80 years old. This study is longitudinal in nature because the researcher plans to study the same individuals as they age. Based on these data, the pattern of intelligence and age might look different than from the cross-sectional research; it might be found that participants’ intelligence scores are higher at age 50 than at age 20 and then remain stable or decline a little by age 80. How can that be when cross-sectional research revealed declines in intelligence with age?

Since longitudinal research happens over a period of time (which could be short term, as in months, but is often longer, as in years), there is a risk of attrition. Attrition occurs when participants fail to complete all portions of a study. Participants may move, change their phone numbers, die, 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. There is also something known as  selective attrition— this means that certain groups of individuals may tend to drop out. It is often the least healthy, least educated, and lower socioeconomic participants who tend to drop out over time. That means that the remaining participants may no longer be representative of the whole population, as they are, in general, healthier, better educated, and have more money. This could be a factor in why our hypothetical research found a more optimistic picture of intelligence and aging as the years went by. What can researchers do about selective attrition? At each time of testing, they could randomly recruit more participants from the same cohort as the original members, to replace those who have dropped out.

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). So our participants may have become familiar with the intelligence test each time (and with the computerized testing administration). Another limitation of longitudinal research is that the data are limited to only one cohort.

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 research includes participants of different ages. This research design is also distinct from those that have been discussed previously in that individuals of different ages are enrolled into a study at various points in time to examine age-related changes, development within the same individuals as they age, and to account for the possibility of cohort and/or time of measurement effects. In 1965, K. Warner Schaie described particular sequential designs: cross-sequential, cohort sequential, and time-sequential. The differences between them depended on which variables were focused on for analyses of the data (data could be viewed in terms of multiple cross-sectional designs or multiple longitudinal designs or multiple cohort designs). Ideally, by comparing results from the different types of analyses, the effects of age, cohort, and time in history could be separated out.

Challenges Conducting Developmental Research

The previous sections describe research tools to assess development across the lifespan, as well as the ways that research designs can be used to track age-related changes and development over time. Before you begin conducting developmental research, however, you must also be aware that testing individuals of certain ages (such as infants and children) or making comparisons across ages (such as children compared to teens) comes with its own unique set of challenges. In the final section of this module, let’s look at some of the main issues that are encountered when conducting developmental research, namely ethical concerns, recruitment issues, and participant attrition.

Ethical Concerns

You may already know that Institutional Review Boards (IRBs) must review and approve all research projects that are conducted at universities, hospitals, and other institutions (each broad discipline or field, such as psychology or social work, often has its own code of ethics that must also be followed, regardless of institutional affiliation). An IRB is typically a panel of experts who read and evaluate proposals for research. IRB members want to ensure that the proposed research will be carried out ethically and that the potential benefits of the research outweigh the risks and potential harm (psychological as well as physical harm) for participants.

What you may not know though, is that the IRB considers some groups of participants to be more vulnerable or at-risk than others. Whereas university students are generally not viewed as vulnerable or at-risk, infants and young children commonly fall into this category. What makes infants and young children more vulnerable during research than young adults? One reason infants and young children are perceived as being at increased risk is due to their limited cognitive capabilities, which makes them unable to state their willingness to participate in research or tell researchers when they would like to drop out of a study. For these reasons, infants and young children require special accommodations as they participate in the research process. Similar issues and accommodations would apply to adults who are deemed to be of limited cognitive capabilities.

When thinking about special accommodations in developmental research, consider the informed consent process. If you have ever participated in scientific research, you may know through your own experience that adults commonly sign an informed consent statement (a contract stating that they agree to participate in research) after learning about a study. As part of this process, participants are informed of the procedures to be used in the research, along with any expected risks or benefits. Infants and young children cannot verbally indicate their willingness to participate, much less understand the balance of potential risks and benefits. As such, researchers are oftentimes required to obtain written informed consent from the parent or legal guardian of the child participant, an adult who is almost always present as the study is conducted. In fact, children are not asked to indicate whether they would like to be involved in a study at all (a process known as assent) until they are approximately seven years old. Because infants and young children cannot easily indicate if they would like to discontinue their participation in a study, researchers must be sensitive to changes in the state of the participant (determining whether a child is too tired or upset to continue) as well as to parent desires (in some cases, parents might want to discontinue their involvement in the research). As in adult studies, researchers must always strive to protect the rights and well-being of the minor participants and their parents when conducting developmental research.

Recruitment

An additional challenge in developmental science is participant recruitment. Recruiting university students to participate in adult studies is typically easy.  Unfortunately, young children cannot be recruited in this way. Given these limitations, how do researchers go about finding infants and young children to be in their studies?

The answer to this question varies along multiple dimensions. Researchers must consider the number of participants they need and the financial resources available to them, among other things. Location may also be an important consideration. Researchers who need large numbers of infants and children may attempt to recruit them by obtaining infant birth records from the state, county, or province in which they reside. Researchers can choose to pay a recruitment agency to contact and recruit families for them.  More economical recruitment options include posting advertisements and fliers in locations frequented by families, such as mommy-and-me classes, local malls, and preschools or daycare centers. Researchers can also utilize online social media outlets like Facebook, which allows users to post recruitment advertisements for a small fee. Of course, each of these different recruitment techniques requires IRB approval. And if children are recruited and/or tested in school settings, permission would need to be obtained ahead of time from teachers, schools, and school districts (as well as informed consent from parents or guardians).

And what about the recruitment of adults? While it is easy to recruit young college students to participate in research, some would argue that it is too easy and that college students are samples of convenience. They are not randomly selected from the wider population, and they may not represent all young adults in our society (this was particularly true in the past with certain cohorts, as college students tended to be mainly white males of high socioeconomic status). In fact, in the early research on aging, this type of convenience sample was compared with another type of convenience sample—young college students tended to be compared with residents of nursing homes! Fortunately, it didn’t take long for researchers to realize that older adults in nursing homes are not representative of the older population; they tend to be the oldest and sickest (physically and/or psychologically). Those initial studies probably painted an overly negative view of aging, as young adults in college were being compared to older adults who were not healthy, had not been in school nor taken tests in many decades, and probably did not graduate high school, let alone college. As we can see, recruitment and random sampling can be significant issues in research with adults, as well as infants and children. For instance, how and where would you recruit middle-aged adults to participate in your research?

Another important consideration when conducting research with infants and young children is attrition . Although attrition is quite common in longitudinal research in particular (see the previous section on longitudinal designs for an example of high attrition rates and selective attrition in lifespan developmental research), it is also problematic in developmental science more generally, as studies with infants and young children tend to have higher attrition rates than studies with adults.  Infants and young children are more likely to tire easily, become fussy, and lose interest in the study procedures than are adults. For these reasons, research studies should be designed to be as short as possible – it is likely better to break up a large study into multiple short sessions rather than cram all of the tasks into one long visit to the lab. Researchers should also allow time for breaks in their study protocols so that infants can rest or have snacks as needed. Happy, comfortable participants provide the best data.

Conclusions

Lifespan development is a fascinating field of study – but care must be taken to ensure that researchers use appropriate methods to examine human behavior, use the correct experimental design to answer their questions, and be aware of the special challenges that are part-and-parcel of developmental research. After reading this module, you should have a solid understanding of these various issues and be ready to think more critically about research questions that interest you. For example, what types of questions do you have about lifespan development? What types of research would you like to conduct? Many interesting questions remain to be examined by future generations of developmental scientists – maybe you will make one of the next big discoveries!

Lifespan development is the scientific study of how and why people change or remain the same over time. As we are beginning to see, lifespan development involves multiple domains and many ages and stages that are important in and of themselves, but that are also interdependent and dynamic and need to be viewed holistically. There are many influences on lifespan development at individual and societal levels (including genetics); cultural, generational, economic, and historical contexts are often significant. And how developmental research is designed and data are collected, analyzed, and interpreted can affect what is discovered about human development across the lifespan.

Lifespan Development Copyright © 2020 by Julie Lazzara is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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Developmental Psychology 101: Theories, Stages, & Research

You can imagine how vast this field of psychology is if it has to cover the whole of life, from birth through death.

Just like any other area of psychology, it has created exciting debates and given rise to fascinating case studies.

In recent years, developmental psychology has shifted to incorporate positive psychology paradigms to create a holistic lifespan approach. As an example, the knowledge gained from positive psychology can enhance the development of children in education.

In this article, you will learn a lot about different aspects of developmental psychology, including how it first emerged in history and famous theories and models.

Before you continue, we thought you might like to download our three Positive Psychology Exercises for free . These science-based exercises explore fundamental aspects of positive psychology, including strengths, values, and self-compassion, and will give you the tools to enhance the wellbeing of your clients, students, or employees.

This Article Contains:

What is developmental psychology, 4 popular theories, stages, & models, 2 questions and research topics, fascinating case studies & research findings, a look at positive developmental psychology, applying developmental psychology in education, resources from positivepsychology.com, a take-home message.

Human beings change drastically over our lifetime.

The American Psychological Association (2020) defines developmental psychology as the study of physical, mental, and behavioral changes, from conception through old age.

Developmental psychology investigates biological, genetic, neurological, psychosocial, cultural, and environmental factors of human growth (Burman, 2017).

Over the years, developmental psychology has been influenced by numerous theories and models in varied branches of psychology (Burman, 2017).

History of developmental psychology

Developmental psychology first appeared as an area of study in the late 19th century (Baltes, Lindenberger, & Staudinger, 2007). Developmental psychology focused initially on child and adolescent development, and was concerned about children’s minds and learning (Hall, 1883).

There are several key figures in developmental psychology. In 1877, the famous evolutionary biologist Charles Darwin undertook the first study of developmental psychology on innate communication forms. Not long after, physiologist William Preyer (1888) published a book on the abilities of an infant.

The 1900s saw many significant people dominating the developmental psychology field with their detailed theories of development: Sigmund Freud (1923, 1961), Jean Piaget (1928), Erik Erikson (1959), Lev Vygotsky (1978), John Bowlby (1958), and Albert Bandura (1977).

By the 1920s, the scope of developmental psychology had begun to include adult development and the aging process (Thompson, 2016).

In more recent years, it has broadened further to include prenatal development (Brandon et al., 2009). Developmental psychology is now understood to encompass the complete lifespan (Baltes et al., 2007).

Each of these models has contributed to the understanding of the process of human development and growth.

Furthermore, each theory and model focuses on different aspects of development: social, emotional, psychosexual, behavioral, attachment, social learning, and many more.

Here are some of the most popular models of development that have heavily contributed to the field of developmental psychology.

1. Bowlby’s attachment styles

The seminal work of psychologist John Bowlby (1958) showcased his interest in children’s social development. Bowlby (1969, 1973, 1980) developed the most famous theory of social development, known as attachment theory .

Bowlby (1969) hypothesized that the need to form attachments is innate, embedded in all humans for survival and essential for children’s development. This instinctive bond helps ensure that children are cared for by their parent or caregiver (Bowlby, 1969, 1973, 1980).

Bowlby’s original attachment work was developed further by one of his students, Mary Ainsworth. She proposed several attachment styles between the child and the caregiver (Ainsworth & Bell, 1970).

This theory clearly illustrates the importance of attachment styles to a child’s future development. Consistent and stable caregiving results in a secure attachment style (Ainsworth, Blehar, Waters, & Wall, 1978). In contrast, unstable and insecure caregiving results in several negative attachment styles: ambivalent, avoidant, or disorganized (Ainsworth & Bell, 1970; Main & Solomon, 1986).

Bowlby’s theory does not consider peer group influence or how it can shape children’s personality and development (Harris, 1998).

2. Piaget’s stage theory

Jean Piaget was a French psychologist highly interested in child development. He was interested in children’s thinking and how they acquire, construct, and use their knowledge (Piaget, 1951).

Piaget’s (1951) four-stage theory of cognitive development sequences a child’s intellectual development. According to this theory, all children move through these four stages of development in the same order (Simatwa, 2010).

The sensorimotor stage is from birth to two years old. Behaviors are triggered by sensory stimuli and limited to simple motor responses. If an object is removed from the child’s vision, they think it no longer exists (Piaget, 1936).

The pre-operational stage occurs between two and six years old. The child learns language but cannot mentally manipulate information or understand concrete logic (Wadsworth, 1971).

The concrete operational stage takes place from 7 to 11 years old. Children begin to think more logically about factual events. Abstract or hypothetical concepts are still difficult to understand in this stage (Wadsworth, 1971).

In the formal operational stage from 12 years to adulthood, abstract thought and skills arise (Piaget, 1936).

Piaget did not consider other factors that might affect these stages or a child’s progress through them. Biological maturation and interaction with the environment can determine the rate of cognitive development in children (Papalia & Feldman, 2011). Individual differences can also dictate a child’s progress (Berger, 2014).

3. Freud’s psychosexual development theory

One of the most influential developmental theories, which encompassed psychosexual stages of development, was developed by Austrian psychiatrist Sigmund Freud (Fisher & Greenberg, 1996).

Freud concluded that childhood experiences and unconscious desires influence behavior after witnessing his female patients experiencing physical symptoms and distress with no physical cause (Breuer & Freud, 1957).

According to Freud’s psychosexual theory, child development occurs in a series of stages, each focused on different pleasure areas of the body. During each stage, the child encounters conflicts, which play a significant role in development (Silverman, 2017).

Freud’s theory of psychosexual development includes the oral, anal, phallic, latent, and genital stages. His theory suggests that the energy of the libido is focused on these different erogenous zones at each specific stage (Silverman, 2017).

Freud concluded that the successful completion of each stage leads to healthy adult development. He also suggested that a failure to progress through a stage causes fixation and developmental difficulties, such as nail biting (oral fixation) or obsessive tidiness (anal fixation; Silverman, 2017).

Freud considered personality to be formed in childhood as a child passes through these stages. Criticisms of Freud’s theory of psychosexual development include its failure to consider that personality can change and grow over an entire lifetime. Freud believed that early experiences played the most significant role in shaping development (Silverman, 2017).

4. Bandura’s social learning theory

American psychologist Albert Bandura proposed the social learning theory (Bandura, Ross, & Ross, 1961). Bandura did not believe that classical or operant conditioning was enough to explain learned behavior because some behaviors of children are never reinforced (Bandura, 1986). He believed that children observe, imitate, and model the behaviors and reactions of others (Bandura, 1977).

Bandura suggested that observation is critical in learning. Further, the observation does not have to be of a live actor, such as in the Bobo doll experiment (Bandura, 1986). Bandura et al. (1961) considered that learning and modeling can also occur from listening to verbal instructions on behavior performance.

Bandura’s (1977) social theory posits that both environmental and cognitive factors interact to influence development.

Bandura’s developmental theory has been criticized for not considering biological factors or children’s autonomic nervous system responses (Kevin, 1995).

Overview of theories of development – Khan Academy

Developmental psychology has given rise to many debatable questions and research topics. Here are two of the most commonly discussed.

1. Nature vs nurture debate

One of the oldest debates in the field of developmental psychology has been between nature and nurture (Levitt, 2013).

Is human development a result of hereditary factors (genes), or is it influenced by the environment (school, family, relationships, peers, community, culture)?

The polarized position of developmental psychologists of the past has now changed. The nature/nurture question now concerns the relationship between the innateness of an attribute and the environmental effects on that attribute (Nesterak, 2015).

The field of epigenetics  describes how behavioral and environmental influences affect the expression of genes (Kubota, Miyake, & Hirasawa, 2012).

Many severe mental health disorders have a hereditary component. Yet, the environment and behavior, such as improved diet, reduced stress, physical activity, and a positive mindset, can determine whether this health condition is ever expressed (Śmigielski, Jagannath, Rössler, Walitza, & Grünblatt, 2020).

When considering classic models of developmental psychology, such as Piaget’s schema theory and Freud’s psychosexual theory, you’ll see that they both perceive development to be set in stone and unchangeable by the environment.

Contemporary developmental psychology theories take a different approach. They stress the importance of multiple levels of organization over the course of human development (Lomas, Hefferon, & Ivtzan, 2016).

2. Theory of mind

Theory of mind allows us to understand that others have different intentions, beliefs, desires, perceptions, behaviors, and emotions (American Psychological Association, 2020).

It was first identified by research by Premack and Woodruff (1978) and considered to be a natural developmental stage of progression for all children. Starting around the ages of four or five, children begin to think about the thoughts and feelings of others. This shows an emergence of the theory of mind (Wellman & Liu, 2004).

However, the ability of all individuals to achieve and maintain this critical skill at the same level is debatable.

Children diagnosed with autism exhibit a deficit in the theory of mind (Baron-Cohen, Leslie, & Frith, 1985).

Individuals with depression (psychotic and non-psychotic) are significantly impaired in theory of mind tasks (Wang, Wang, Chen, Zhu, & Wang, 2008).

People with social anxiety disorder have also been found to show less accuracy in decoding the mental states of others (Washburn, Wilson, Roes, Rnic, & Harkness, 2016).

Further research has shown that the theory of mind changes with aging. This suggests a developmental lifespan process for this concept (Meinhardt-Injac, Daum, & Meinhardt, 2020).

1. Little Albert

The small child who was the focus of the experiments of behavioral psychologists Watson and Rayner (1920) was referred to as ‘Little Albert.’ These experiments were essential landmarks in developmental psychology and showed how an emotionally stable child can be conditioned to develop a phobia.

Albert was exposed to several neutral stimuli including cotton wool, masks, a white rat, rabbit, monkey, and dog. Albert showed no initial fear to these stimuli.

When a loud noise was coupled with the initially neutral stimulus, Albert became very distressed and developed a phobia of the object, which extended to any similar object as well.

This experiment highlights the importance of environmental factors in the development of behaviors in children.

2. David Reimer

At the age of eight months, David Reimer lost his penis in a circumcision operation that went wrong. His worried parents consulted a psychologist, who advised them to raise David as a girl.

David’s young age meant he knew nothing about this. He went through the process of hormonal treatment and gender reassignment. At the age of 14, David found out the truth and wanted to reverse the gender reassignment process to become a boy again. He had always felt like a boy until this time, even though he was socialized and brought up as a girl (Colapinto, 2006).

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Contemporary theories of developmental psychology often encompass a holistic approach and a more positive approach to development.

Positive psychology has intersected with developmental disciplines in areas such as parenting, education, youth, and aging (Lomas et al., 2016).

These paradigms can all be grouped together under the umbrella of positive developmental psychology. This fresh approach to development focuses on the wellbeing aspects of development, while systematically bringing them together (Lomas, et al., 2016).

• Positive parenting is the approach to children’s wellbeing by focusing on the role of parents and caregivers (Latham, 1994).
• Positive education looks at flourishing in the context of school (Seligman, Ernst, Gillham, Reivich, & Linkins, 2009).
• Positive youth development is the productive and constructive focus on adolescence and early adulthood to enhance young people’s strengths and promote positive outcomes (Larson, 2000).
• Positive aging , also known as healthy aging, focuses on the positivity of aging as a healthy, normal stage of life (Vaillant, 2004).

Much of the empirical and theoretical work connected to positive developmental psychology has been going on for years, even before the emergence of positive psychology itself (Lomas et al., 2016).

We recommend this related article Applying Positive Psychology in Schools & Education: Your Ultimate Guide for further reading.

In the classroom, developmental psychology considers children’s psychological, emotional, and intellectual characteristics according to their developmental stage.

A report on the top 20 principles of psychology in the classroom, from pre-kindergarten to high school, was published by the American Psychological Association in 2015. The report also advised how teachers can respond to these principles in the classroom setting.

The top 5 principles and teacher responses are outlined in the table below.

There are many valuable resources to help you foster positive development no matter whether you’re working with young children, teenagers, or adults.

To help get you started, check out the following free resources from around our blog.

• Adopt A Growth Mindset This exercise helps clients recognize instances of fixed mindset in their thinking and actions and replace them with thoughts and behaviors more supportive of a growth mindset.
• Childhood Frustrations This worksheet provides a space for clients to document key challenges experienced during childhood, together with their emotional and behavioral responses.
• What I Want to Be This worksheet helps children identify behaviors and emotions they would like to display and select an opportunity in the future to behave in this ideal way.
• 17 Positive Psychology Exercises If you’re looking for more science-based ways to help others enhance their wellbeing, this signature collection contains 17 validated positive psychology tools for practitioners. Use them to help others flourish and thrive.
• Developmental Psychology Courses If you are interested in a career in Developmental Psychology , we suggest 15 of the best courses in this article.

17 Top-Rated Positive Psychology Exercises for Practitioners

Expand your arsenal and impact with these 17 Positive Psychology Exercises [PDF] , scientifically designed to promote human flourishing, meaning, and wellbeing.

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Earlier developmental psychology models and theories were focused on specific areas, such as attachment, psychosexual, cognitive, and social learning. Although informative, they did not take in differing perspectives and were fixed paradigms.

We’ve now come to understand that development is not fixed. Individual differences take place in development, and the factors that can affect development are many. It is ever changing throughout life.

The modern-day approach to developmental psychology includes sub-fields of positive psychology. It brings these differing disciplines together to form an overarching positive developmental psychology paradigm.

Developmental psychology has helped us gain a considerable understanding of children’s motivations, social and emotional contexts, and their strengths and weaknesses.

This knowledge is essential for educators to create rich learning environments for students to help them develop positively and ultimately flourish to their full potential.

We hope you enjoyed reading this article. Don’t forget to download our three Positive Psychology Exercises for free .

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Developmental Research Designs

Sometimes, especially in developmental research, the researcher is interested in examining changes over time and will need to consider a research design that will capture these changes. Remember,  research methods  are tools that are used to collect information, while r esearch design  is the strategy or blueprint for deciding how to collect and analyze information. Research design dictates which methods are used and how. There are three types of developmental research designs: cross-sectional, longitudinal, and sequential.

Video 2.9.1.  Developmental Research Design  summarizes the benefits of challenges of the three developmental design models.

Cross-Sectional Designs

The majority of developmental studies use cross-sectional designs because they are less time-consuming and less expensive than other developmental designs.  Cross-sectional research  designs are used to examine behavior in participants of different ages who are tested at the same point in time. Let’s suppose that researchers are interested in the relationship between intelligence and aging. They might have a hypothesis that intelligence declines as people get older. The researchers might choose to give a particular intelligence test to individuals who are 20 years old, individuals who are 50 years old, and individuals who are 80 years old at the same time and compare the data from each age group. This research is cross-sectional in design because the researchers plan to examine the intelligence scores of individuals of different ages within the same study at the same time; they are taking a “cross-section” of people at one point in time. Let’s say that the comparisons find that the 80-year-old adults score lower on the intelligence test than the 50-year-old adults, and the 50-year-old adults score lower on the intelligence test than the 20-year-old adults. Based on these data, the researchers might conclude that individuals become less intelligent as they get older. Would that be a valid (accurate) interpretation of the results?

Figure 2.9.1. Example of cross-sectional research design

No, that would not be a valid conclusion because the researchers did not follow individuals as they aged from 20 to 50 to 80 years old. One of the primary limitations of cross-sectional research is that the results yield information about age  differences  not necessarily  changes  over time. That is, although the study described above can show that the 80-year-olds scored lower on the intelligence test than the 50-year-olds, and the 50-year-olds scored lower than the 20-year-olds, the data used for this conclusion were collected from different individuals (or groups). It could be, for instance, that when these 20-year-olds get older, they will still score just as high on the intelligence test as they did at age 20. Similarly, maybe the 80-year-olds would have scored relatively low on the intelligence test when they were young; the researchers don’t know for certain because they did not follow the same individuals as they got older.

With each cohort being members of a different generation, it is also possible that the differences found between the groups are not due to age, per se, but due to cohort effects. Differences between these cohorts’ IQ results could be due to differences in life experiences specific to their generation, such as differences in education, economic conditions, advances in technology, or changes in health and nutrition standards, and not due to age-related changes.

Another disadvantage of cross-sectional research is that it is limited to one time of measurement. Data are collected at one point in time, and it’s possible that something could have happened in that year in history that affected all of the participants, although possibly each cohort may have been affected differently.

Longitudinal Research Designs

Longitudinal research designs are used to examine behavior in the same individuals over time. For instance, with our example of studying intelligence and aging, a researcher might conduct a longitudinal study to examine whether 20-year-olds become less intelligent with age over time. To this end, a researcher might give an intelligence test to individuals when they are 20 years old, again when they are 50 years old, and then again when they are 80 years old. This study is longitudinal in nature because the researcher plans to study the same individuals as they age. Based on these data, the pattern of intelligence and age might look different than from the cross-sectional research; it might be found that participants’ intelligence scores are higher at age 50 than at age 20 and then remain stable or decline a little by age 80. How can that be when cross-sectional research revealed declines in intelligence with age?

Figure 2.9.2. Example of a longitudinal research design

Since longitudinal research happens over a period of time (which could be short-term, as in months, but is often longer, as in years), there is a risk of attrition.  Attrition  occurs when participants fail to complete all portions of a study. Participants may move, change their phone numbers, die, 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. There is also something known as  selective attrition— this means that certain groups of individuals may tend to drop out. It is often the least healthy, least educated, and lower socioeconomic participants who tend to drop out over time. That means that the remaining participants may no longer be representative of the whole population, as they are, in general, healthier, better educated, and have more money. This could be a factor in why our hypothetical research found a more optimistic picture of intelligence and aging as the years went by. What can researchers do about selective attrition? At each time of testing, they could randomly recruit more participants from the same cohort as the original members to replace those who have dropped out.

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). So our participants may have become familiar with the intelligence test each time (and with the computerized testing administration).

Another limitation of longitudinal research is that the data are limited to only one cohort. As an example, think about how comfortable the participants in the 2010 cohort of 20-year-olds are with computers. Since only one cohort is being studied, there is no way to know if findings would be different from other cohorts. In addition, changes that are found as individuals age over time could be due to age or to time of measurement effects. That is, the participants are tested at different periods in history, so the variables of age and time of measurement could be confounded (mixed up). For example, what if there is a major shift in workplace training and education between 2020 and 2040, and many of the participants experience a lot more formal education in adulthood, which positively impacts their intelligence scores in 2040? Researchers wouldn’t know if the intelligence scores increased due to growing older or due to a more educated workforce over time between measurements.

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 research includes participants of different ages. This research design is also distinct from those that have been discussed previously in that individuals of different ages are enrolled into a study at various points in time to examine age-related changes, development within the same individuals as they age, and to account for the possibility of cohort and/or time of measurement effects

Consider, once again, our example of intelligence and aging. In a study with a sequential design, a researcher might recruit three separate groups of participants (Groups A, B, and C). Group A would be recruited when they are 20 years old in 2010 and would be tested again when they are 50 and 80 years old in 2040 and 2070, respectively (similar in design to the longitudinal study described previously). Group B would be recruited when they are 20 years old in 2040 and would be tested again when they are 50 years old in 2070. Group C would be recruited when they are 20 years old in 2070, and so on.

Figure 2.9.3. Example of sequential research design

Studies with sequential designs are powerful because they allow for both longitudinal and cross-sectional comparisons—changes and/or stability with age over time can be measured and compared with differences between age and cohort groups. This research design also allows for the examination of cohort and time of measurement effects. For example, the researcher could examine the intelligence scores of 20-year-olds at different times in history and different cohorts (follow the yellow diagonal lines in figure 2.9.3). This might be examined by researchers who are interested in sociocultural and historical changes (because we know that lifespan development is multidisciplinary). One way of looking at the usefulness of the various developmental research designs was described by Schaie and Baltes (1975): cross-sectional and longitudinal designs might reveal change patterns while sequential designs might identify developmental origins for the observed change patterns.

Since 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 (if data are collected more frequently than over the 30-year spans in our example) 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.

Comparing Developmental Research Designs

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 2.9.1.  Advantages and disadvantages of different research designs

Candela Citations

• Developmental Research Design. Authored by : Nicole Arduini-Van Hoose. Provided by : Hudson Valley Community College. Retrieved from : https://courses.lumenlearning.com/edpsy/chapter/developmental-research-designs/. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
• Developmental Research Designs. Authored by : Nicole Arduini-Van Hoose. Provided by : Hudson Valley Community College. Retrieved from : https://courses.lumenlearning.com/adolescent/chapter/developmental-research-design/. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike

Educational Psychology Copyright © 2020 by Nicole Arduini-Van Hoose is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Developmental Psychology Topics

Topics for research, papers, and other projects

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

• Childhood Topics
• Adolescence Topics
• Adulthood Topics
• How to Choose
• Tips for Students

Are you looking for a developmental psychology topic for a psychology paper , experiment, or science fair project? Topics you might pick can range from prenatal development to health during the final stages of life.

Developmental psychology is a broad topic that involves studying how people grow and change throughout their whole lifetime. Topics don't just include physical growth but also the emotional, cognitive, and social development that people experience at different stages of their lives.

At a Glance

The following are just a few different topics that might help inspire you. Remember, these are just ideas to help you get started. You might opt to explore one of these areas, or you might think of a related question that interests you as well.

Developmental Psychology Topics on Childhood

• Could packaging nutritious foods in visually appealing ways encourage children to make healthier food choices?
• Do children who listen to music while studying perform better or worse on exams?
• Do students who eat breakfast perform better in school than those who do not eat breakfast?
• Does birth order have an impact on procrastination ? Are first-borns less likely to procrastinate? Are last-borns more likely to put off tasks until the last minute?
• Does teaching infants sign language help or hinder the language acquisition process?
• How do parenting styles impact a child's level of physical activity? Are children raised by parents with permissive or uninvolved parents less active than those raised by parents with authoritative or authoritarian styles?
• How does bullying impact student achievement? Are bullied students more likely to have worse grades than their non-bullied peers?
• Which type of reinforcement works best for getting students to complete their homework: a tangible reward (such as a piece of candy) or social reinforcement (such as offering praise when homework is completed on time)?

Developmental Psychology Topics on Adolescence

• What factors tend to influence the onset of depression in teens and young adults?
• How do peer relationships influence identity formation during adolescence and young adulthood?
• What impact do parent-child relationships have in predicting substance use among teens and young adults?
• How does early substance use during adolescence impact impulsivity and risk-taking during early adulthood?
• How does technology use during adolescence influence social and emotional development?
• How does social media use influence body image among teens?
• What factors contribute to success during the transition from the teen years to early adulthood?
• How do cultural differences impact different aspects of adolescent development?

Developmental Psychology Topics on Adulthood

• Are older adults who rate high in self-efficacy more likely to have a better memory than those with low self-efficacy?
• Do the limits of short-term memory change as we age? How do the limits of short-term memory compare at ages, 15, 25, 45, and 65?
• Do mental games such as word searches, Sudoku, and word matching help elderly adults keep their cognitive skills sharp?
• How do explanations for the behavior of others change as we age? Are younger adults more likely to blame internal factors for events and older adults more likely to blame external variables?

Choosing Developmental Psychology Topics

Developmental psychology is a huge and diverse subject, so picking a topic isn't always easy. Some tips that can help you choose a good developmental psychology topic include:

• Focus on a specific topic : Make sure that your topic isn't too broad to avoid getting overwhelmed by the amount of information available
• Have a clear question or hypothesis : Your research question should be focused and clearly defined
• Do some background research : Spend some time reviewing the existing literature to get a better idea about what you want to cover with your topic
• Consider developmental theories : You might consider analyzing your topic through the lens of a particular theory of developmental psychology
• Check out recent research : Use research databases to find the most recently published research on your topic

Before you start working on any paper, experiment, or science project, the first thing you need to do is understand the rules your instructor has established for the assignment.

Also, be sure to check the official guidelines given by your teacher. If you are not sure about these guidelines, ask your instructor if there are any specific requirements before you get started on your research .

If you are going to actually conduct an experiment , you need to present your idea to your instructor to gain their permission before going forward. In some cases, you might have to also present your plan to your school's Institutional Review Board.

Tips for Researching Developmental Psychology Topics

After you have gotten to move forward with your chosen topic, the next step is to do some background research. This step is essential! If you are writing a paper, the information you find will make up your literature review.

If you are performing an experiment, it will provide background information for the introduction of your lab report . For a psychology science project, this research will help you in your presentation and can help you decide how to best approach your own experiment.

What This Means For You

Choosing a topic for a developmental psychology experiment, paper, or project can be tough! The ideas above can be a great place to start, but you might also consider questions you've had about your own life. Once you have a general idea for your topic, narrow it down, do some background research and talk to your instructor.

Nielsen M, Haun D. Why developmental psychology is incomplete without comparative and cross-cultural perspectives .  Philos Trans R Soc Lond B Biol Sci . 2016;371(1686):20150071. doi:10.1098/rstb.2015.0071

Leite DFB, Padilha MAS, Cecatti JG. Approaching literature review for academic purposes: The Literature Review Checklist .  Clinics (Sao Paulo) . 2019;74:e1403. Published 2019 Nov 25. doi:10.6061/clinics/2019/e1403

Grady C. Institutional review boards: Purpose and challenges .  Chest . 2015;148(5):1148-1155. doi:10.1378/chest.15-0706

Kim WO. Institutional review board (IRB) and ethical issues in clinical research . Korean Journal of Anesthesiology . 2012;62(1):3-12. doi:10.4097/kjae.2012.62.1.3

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Psychological Research

Developmental Research Designs

Sometimes, especially in developmental research, the researcher is interested in examining changes over time and will need to consider a research design that will capture these changes. Remember,  research methods  are tools that are used to collect information, while r esearch design  is the strategy or blueprint for deciding how to collect and analyze information. Research design dictates which methods are used and how. There are three types of developmental research designs: cross-sectional, longitudinal, and sequential.

Video 2.9.1.  Developmental Research Design  summarizes the benefits of challenges of the three developmental design models.

Cross-Sectional Designs

The majority of developmental studies use cross-sectional designs because they are less time-consuming and less expensive than other developmental designs.  Cross-sectional research  designs are used to examine behavior in participants of different ages who are tested at the same point in time. Let’s suppose that researchers are interested in the relationship between intelligence and aging. They might have a hypothesis that intelligence declines as people get older. The researchers might choose to give a particular intelligence test to individuals who are 20 years old, individuals who are 50 years old, and individuals who are 80 years old at the same time and compare the data from each age group. This research is cross-sectional in design because the researchers plan to examine the intelligence scores of individuals of different ages within the same study at the same time; they are taking a “cross-section” of people at one point in time. Let’s say that the comparisons find that the 80-year-old adults score lower on the intelligence test than the 50-year-old adults, and the 50-year-old adults score lower on the intelligence test than the 20-year-old adults. Based on these data, the researchers might conclude that individuals become less intelligent as they get older. Would that be a valid (accurate) interpretation of the results?

Figure 2.9.1. Example of cross-sectional research design

No, that would not be a valid conclusion because the researchers did not follow individuals as they aged from 20 to 50 to 80 years old. One of the primary limitations of cross-sectional research is that the results yield information about age  differences  not necessarily  changes  over time. That is, although the study described above can show that the 80-year-olds scored lower on the intelligence test than the 50-year-olds, and the 50-year-olds scored lower than the 20-year-olds, the data used for this conclusion were collected from different individuals (or groups). It could be, for instance, that when these 20-year-olds get older, they will still score just as high on the intelligence test as they did at age 20. Similarly, maybe the 80-year-olds would have scored relatively low on the intelligence test when they were young; the researchers don’t know for certain because they did not follow the same individuals as they got older.

With each cohort being members of a different generation, it is also possible that the differences found between the groups are not due to age, per se, but due to cohort effects. Differences between these cohorts’ IQ results could be due to differences in life experiences specific to their generation, such as differences in education, economic conditions, advances in technology, or changes in health and nutrition standards, and not due to age-related changes.

Another disadvantage of cross-sectional research is that it is limited to one time of measurement. Data are collected at one point in time, and it’s possible that something could have happened in that year in history that affected all of the participants, although possibly each cohort may have been affected differently.

Longitudinal Research Designs

Longitudinal research designs are used to examine behavior in the same individuals over time. For instance, with our example of studying intelligence and aging, a researcher might conduct a longitudinal study to examine whether 20-year-olds become less intelligent with age over time. To this end, a researcher might give an intelligence test to individuals when they are 20 years old, again when they are 50 years old, and then again when they are 80 years old. This study is longitudinal in nature because the researcher plans to study the same individuals as they age. Based on these data, the pattern of intelligence and age might look different than from the cross-sectional research; it might be found that participants’ intelligence scores are higher at age 50 than at age 20 and then remain stable or decline a little by age 80. How can that be when cross-sectional research revealed declines in intelligence with age?

Figure 2.9.2. Example of a longitudinal research design

Since longitudinal research happens over a period of time (which could be short term, as in months, but is often longer, as in years), there is a risk of attrition.  Attrition  occurs when participants fail to complete all portions of a study. Participants may move, change their phone numbers, die, 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. There is also something known as  selective attrition— this means that certain groups of individuals may tend to drop out. It is often the least healthy, least educated, and lower socioeconomic participants who tend to drop out over time. That means that the remaining participants may no longer be representative of the whole population, as they are, in general, healthier, better educated, and have more money. This could be a factor in why our hypothetical research found a more optimistic picture of intelligence and aging as the years went by. What can researchers do about selective attrition? At each time of testing, they could randomly recruit more participants from the same cohort as the original members to replace those who have dropped out.

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). So our participants may have become familiar with the intelligence test each time (and with the computerized testing administration).

Another limitation of longitudinal research is that the data are limited to only one cohort. As an example, think about how comfortable the participants in the 2010 cohort of 20-year-olds are with computers. Since only one cohort is being studied, there is no way to know if findings would be different from other cohorts. In addition, changes that are found as individuals age over time could be due to age or to time of measurement effects. That is, the participants are tested at different periods in history, so the variables of age and time of measurement could be confounded (mixed up). For example, what if there is a major shift in workplace training and education between 2020 and 2040, and many of the participants experience a lot more formal education in adulthood, which positively impacts their intelligence scores in 2040? Researchers wouldn’t know if the intelligence scores increased due to growing older or due to a more educated workforce over time between measurements.

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 research includes participants of different ages. This research design is also distinct from those that have been discussed previously in that individuals of different ages are enrolled into a study at various points in time to examine age-related changes, development within the same individuals as they age, and to account for the possibility of cohort and/or time of measurement effects

Consider, once again, our example of intelligence and aging. In a study with a sequential design, a researcher might recruit three separate groups of participants (Groups A, B, and C). Group A would be recruited when they are 20 years old in 2010 and would be tested again when they are 50 and 80 years old in 2040 and 2070, respectively (similar in design to the longitudinal study described previously). Group B would be recruited when they are 20 years old in 2040 and would be tested again when they are 50 years old in 2070. Group C would be recruited when they are 20 years old in 2070, and so on.

Figure 2.9.3. Example of sequential research design

Studies with sequential designs are powerful because they allow for both longitudinal and cross-sectional comparisons—changes and/or stability with age over time can be measured and compared with differences between age and cohort groups. This research design also allows for the examination of cohort and time of measurement effects. For example, the researcher could examine the intelligence scores of 20-year-olds at different times in history and different cohorts (follow the yellow diagonal lines in figure 3). This might be examined by researchers who are interested in sociocultural and historical changes (because we know that lifespan development is multidisciplinary). One way of looking at the usefulness of the various developmental research designs was described by Schaie and Baltes (1975): cross-sectional and longitudinal designs might reveal change patterns while sequential designs might identify developmental origins for the observed change patterns.

Since 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 (if data are collected more frequently than over the 30-year spans in our example) 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.

Comparing Developmental Research Designs

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 2.9.1.  Advantages and disadvantages of different research designs

Child Psychology Copyright © 2021 by Nicole Arduini-Van Hoose is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Developmental Psychology Studies: 10 Examples

Discover ten classic developmental psychology experiments that study how children’s self, memory, language, learning and more emerge.

Once upon a time, although it seems barely credible to us now, we were all children.

We gurgled, we cried, we laughed, we explored, we fell down, and we had very little idea about the journey on which we had just embarked.

Barring mishap, over the first few years of our lives we developed memory, language, self-concept, cognitive, social and emotional abilities.

We took our first steps towards our future selves.

Child psychology — or, more broadly, developmental psychology — is not just the study of children, it is the study of you and me and how we came to be this way.

Just as discovering your history can teach you about the future, so developmental psychology shows us what we once were and even what we will become.

Here are 10 classic developmental psychology studies that have illuminated crucial areas of childhood development.

Each one is a piece in the jigsaw puzzle that is ourselves, and each one reminds us, through examining just one piece, how aspects of experience we now take for granted were once so complex.

Click the links for a more extensive description of each developmental psychology experiment.

1. Infant memory develops very early on

Some argue it’s impossible for us to remember anything much from before around two to four years of age.

Others think our memories can go way back – perhaps even to before birth.

The question of infant memory is thorny because it’s hard to test whether adults’ earliest memories are real or imagined.

What psychologists have done, though, is examine the emergence of memory in our first few years with a series of now classic experiments in developmental psychology.

These have found that our memory systems actually work quite well from very early on.

Infants’ memories also seems to work in much the same way as adult memories – it’s just that infant memories are much more fragile.

2. Developmental psychology: when the self emerges

To this day the ‘mirror test’ remains the best developmental psychology experiment yet developed for examining the emergence of self-concept in infants using the mirror test .

Most people look out for number one, themselves, which makes it strange to think that there was ever a time when we had no concept of ‘me’.

A simple study dating from the early 70s suggests that before the age of around two years old we can’t recognise ourselves in the mirror.

Because of this study, and the many variations in developmental psychology that have followed, some claim that it isn’t until our second birthday that our self-concept emerges.

3. How children learn

A classic study of childhood learning suggests true understanding comes from letting go of established preconceptions.

How children revise their understanding of the world is one of the most fascinating areas of developmental psychology.

But it is not just relevant to children; we all have to take on new concepts from time-to-time – even though they may not be as profound as the origin of the species.

It’s tempting to think that learning is largely about memory – especially since in the bad old days of education learning was largely accomplished by rote.

However, the idea of ‘mental models’ suggests children create, and then test, mental models of the way the world works in order to build up our understanding, and that is how children learn.

4. Attachment styles in developmental psychology

Attachment styles analyse how people respond to threats and problems in their personal relationships.

People who find relationships difficult often become unable to participate in the ordinary give-and-take of everyday life.

They may become hostile towards others, have problems in education as well as a greater chance of developing psychiatric disorders later in life.

These difficulties sometimes have their roots in the most important early relationships, evidenced in attachment styles.

It’s no wonder that developmental psychologists are so interested in the first relationships we build with our primary caregivers.

These attachment styles are likely to prove a vital influence on all our future relationships, including those with our spouse, our workmates and our own children.

While you can’t blame everything on your parents, early relationship attachment styles are like a template that we take forward with us in life.

5. Infants imitate others when only weeks old

One of the most basic forms of social behaviour is copying another person.

Although imitation is something we adults take for granted, it’s actually a pretty demanding process for a young infant.

At the heart of imitation is understanding the difference between yourself and others – something that famous Swiss child psychologist Jean Piaget thought didn’t emerge immediately in infants.

Consequently, he argued that infants could not imitate others until they were 8 to 12 months of age.

However, now some researchers think tiny infants who are between 12- and 21-days-old can imitate others.

6. When children can simulate other minds

Theory of mind is when we can put ourselves in other people’s shoes to try and imagine their thoughts, intentions and possible actions.

Without the ability to simulate what other people are thinking we would be lost in the social world.

The emergence of theory of mind in children is a vital developmental milestone; some psychologists think that a failure to develop a theory of mind is a central component of autism.

Some developmental psychology experiments suggest that at about 4- to 6-years old a range of remarkable skills start to emerge in young children that are vital for their successful functioning in society.

They begin to understand that others can hold false beliefs, they themselves can lie, and that others can lie to them — they have a theory of mind.

7. Object permanence in developmental psychology

Object permanence , or object constancy, in developmental psychology is understanding that things continue to exist, even if you cannot seem them.

Research in developmental psychology has found that infants as young as 3.5 months seem to have a basic grasp of object permanence.

It appears that young infants are not necessarily trapped in a world of shapes which have little meaning for them.

Instead, they seem to be intuitive physicists who can carry out rudimentary reasoning about physical concepts like gravity, inertia and object permanence.

8. How infants learn their first word

An infant’s very first step in their year-long developmental journey to their first word is perhaps their most impressive.

This first step is discriminating and categorising the basic sound components of the language they are hearing.

To get an idea how hard this might be think about listening to someone speaking a language you don’t understand.

Foreign languages can sound like continuous streams of noise in which it’s very hard to pick up where one word starts and another word begins.

Research in developmental psychology finds that until about 11 months of age infants are masters of discriminating phonemes used in all different types of languages.

But after 11 months infants settle down with one set of phonemes for their first language, and lose the ability to discriminate the phonemes from other languages.

9. Play and developmental psychology

The pioneering developmental psychologist Lev Vygotsky thought that, in the preschool years, play is the leading source of development.

Through play children learn and practice many basic social skills.

They develop a sense of self, learn to interact with other children, how to make friends, how to lie and how to role-play.

The classic developmental psychology study of how play develops in children was carried out by Mildred Parten in the late 1920s at the Institute of Child Development in Minnesota ( Parten, 1933 ).

She closely observed children between the ages of 2 and 5 years and categorised the types of play.

She found six different types of play , ranging from solitary, through associative to cooperative

10. Piaget’s developmental psychology theory

Jean Piaget was a developmental psychologist whose four-stage theory, published in 1936, has proved extremely influential.

Piaget’s four stages of development theory  has the dubious claim to fame of being one of the most criticised psychological theories ever.

From the sensorimotor stage, through the pre-operational stage, the concrete operational stage and the formal operational stage, his theory attempts to describe how childhood development progresses.

However, Piaget’s experiments and theories about how children build up their knowledge of the world have faced endless challenges, many of them justified.

Read on about them here .

Author: Jeremy Dean

Psychologist, Jeremy Dean, PhD is the founder and author of PsyBlog. He holds a doctorate in psychology from University College London and two other advanced degrees in psychology. He has been writing about scientific research on PsyBlog since 2004. He is also the author of the book "Making Habits, Breaking Habits" (Da Capo, 2013) and several ebooks. View all posts by Jeremy Dean

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How to study developmental psychology: methods, designs & tools

Every person goes through a development during his life. A physical development, but also a social, emotional, cognitive, and intellectual development. Researchers in developmental psychology examines the various stages of life, from baby to schoolchild, to adolescent, to adult and finally to the elderly. They look at how and why people do the things they do. Observing people’s behavior is a good method for this.

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What is developmental psychology?

Developmental psychology is a scientific discipline that explores how individuals change and grow across their lifespan, focusing on the physical, cognitive, emotional, and social aspects of development. It examines how various factors, such as genetics, environment, and experiences, shape and influence an individual's development from infancy to adulthood. 

By studying developmental processes, researchers gain insights into typical and atypical patterns of human behavior, contributing to our understanding of human development and informing interventions to support healthy development.

Studying changes across the lifespan

Not only the observable actions are studied, but also how people perceive themselves and the world, how they think and fantasize and which feelings and desires they experience. Moreover, it is not only about the development of an individual researchers look at, but also about the development of interactions between people and about the development of relationships and groups.

The knowledge that arises from these studies can make a difference in areas such as youth health care, education, in policy formulation, or it can contribute to solutions for societal challenges. After all, while most people follow common patterns in their development, others reach developmental milestones at a different pace. Research in developmental psychology is designed to help all people reach their full potential.

Research methods to study developmental psychology

Besides behavioral observation, as mentioned above, there are other additional ways to scrutinize the development of humans and answer your research questions. For example, think of:

• Controlled experiments, such as the Still Face Experiment or Piaget’s conservation tasks
• In-depth interviews
• Self-reports or surveys, such as the Social Skills Questionnaire (SSQ) or the Minnesota Multiphasic Personality Inventory (MMPI)
• Correlational studies
• Archival research

In the Noldus Webinar about Research tools in Developmental Psychology , we explain how our research tools can be used to study behavior. Curious? Watch the webinar on demand now!

Since developmental psychology is all about time and how things change over the course of life, it is important to combine the above mentioned methods with a longitudinal or cross-sectional research design. For example, you can conduct a longitudinal experiment or a cross-sectional survey.

See more research examples of Developmental Psychology .

Longitudinal versus cross-sectional research design

The main idea behind longitudinal research is that you take one group of people – all of the same age – and study them over some period of time. This could be weeks, months, or even years. This way, you can investigate changes in individuals over time by comparing one person’s data at several moments in time. 

It brings you in-depth data and a high internal validity. The disadvantages are that this is very time-consuming and the chance that participants drop out is high.

Instead, you can do a cross-sectional study. In this case, you compare groups of people of different ages at one point of time. This is a much quicker way of doing research, you get fast results, and you do not have to worry about people dropping out. 

However, it is possible that cohort effects will appear. The differences found in one group may be caused by age, or because people in a particular group grew up under different circumstances or were exposed to different influences.

Equipment available for developmental psychology research

There is quite a few equipment available to gather data in the best possible way. Things to consider when you set up a study for answering your research questions are for example:

Do you want to go on site to gather data, or is a laboratory setting more suitable?

A perfect solution for the first option is to use a portable lab . This way, all equipment needed is packed in a suitcase, which you can carry around, put in the back of your car, or even take with you on a plane trip. 

It is easy to set up and enables you to gather data from participants while they behave in their natural environment, such as their own home.

To be able to control all kind of settings or circumstances for your experiment or if you need a lot of additional hardware to measure your data with and you do not want to be dragging all this stuff back and forth, a stationary observation lab is more suitable. 

It can be equipped with cameras, microphones, a one-way mirror to observe participants unobtrusively, data acquisition systems , eye-trackers , and much more. All the equipment is built in and integrates nicely, making it a smoothly running lab. 

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However, building a lab is not just about the hardware, you also need software to facilitate your data collection. To choose which software fits best, something to consider is:

Will your dataset mostly exist of qualitative or quantitative data?

A software system such as Viso is particularly suitable to gather qualitative data. This audio and video recording system enables you to control multiple cameras from different angles and to zoom in on certain situations.

In the picture below, you can see an example. One camera is pointed at the parent’s face, the second on the child, and the third one on both parent and child, providing an overview of the situation.

Besides, in Viso you can predefine relevant behaviors you want to study and annotate these during or after your observations or recording sessions. You can play back the recorded sessions immediately afterwards, without any downtime.

To be able to analyze your data quantitatively, you need a software tool such as The Observer XT . This is a manual event recorder for detailed annotations and analysis. 

With use of more detailed coding schemes, you can create a log of annotated behaviors, thus providing insight on length and frequency of the behavior and then analyze these behaviors in a descriptive or numerical way. The analysis options make The Observer XT a unique tool.

In addition, The Observer XT is a powerful tool, which allows you to integrate different kinds of data streams, such as facial expressions , eye tracking, and physiology . Making your experimental data richer.

Also read: how to make coding behavioral data more fun.

To finish, there is a third important element that you should take into account in your study setup and choice of equipment:

Are your participants able to describe their feelings in spoken words?

If your research includes children, especially babies, they may not be able to let you know how they feel or what there are thinking by putting it into words or answering a survey question. To be able to measure some of these feelings and emotions in another way, you can assess their non-verbal behavior.

A quantitative tool to measure non-verbal behavior from facial expressions is for example FaceReader . Based on Action Units in the face, FaceReader determines six basic emotions, as well as valence and arousal. Especially for infants ranging in age from 6 to 24 months old, Baby FaceReader is available.

Put it all together in one clear overview

There are many ways to conduct your research in developmental psychology and available tools to support you in this. In order to put everything together in an orderly manner, we have developed an interactive pdf. Check it out at your convenience at: https://www.noldus.com/noldus-product-portfolio-psychology.pdf .

• Webinar ‘Research in Developmental Psychology’: https://www.noldus.com/webinars#developmentalpsychology
• Still Face Experiment: https://www.youtube.com/watch?v=apzXGEbZht0
• Piaget’s conservation tasks: https://www.youtube.com/watch?v=gnArvcWaH6I
• Research methods in developmental psychology: https://www.youtube.com/watch?v=P3sWPGMg-9U
• Theories of Development: Research Methods: https://www.youtube.com/watch?v=F_HTEYwa0UI
• Must-reads on psychology and behavioral coding

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How Do Psychologists Decide What to Study?

Personal perspective: psychological research is sometimes, but not always, “me-search.".

Posted May 14, 2024 | Reviewed by Ray Parker

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• It is sometimes assumed that the personal concerns of the researcher guide psychological research.
• Research topics often evolve from curiosity about how everyday life works.
• Connecting new research to existing bodies of research is essential.

There is an old saying among psychological scientists that “Research is me-search.” This means, of course, that people, including psychologists, are drawn to topics that have deep relevance to issues in their own lives.

This old saying certainly rings true as I watch my undergraduate students select topics for their capstone senior research projects: The too-thin young woman who wants to study eating disorders, the student of color who is interested in racism , the child of divorce who desperately wishes to understand how a marriage ending in divorce affects children.

Given that I am best known for my work on creepiness and gossip, this old truism about “me-search” stalks and haunts me whenever I do a media interview about my research on either of these topics. The interviewer always wants to know what it is, exactly, that enticed me to devote years of my life to studying such a thing. There seems to be an assumption that I have a personal story to tell about a lifetime of being plagued by gossip or about my fear that I am chronically creeping other people out.

I will let the discerning reader draw their own conclusions about my interest in creepiness, but my interest in gossip does have an identifiable point of origin that is a bit more mundane than one might expect.

Research Ideas Can Be Inspired by Everyday Life

One day, about 25 years ago, I was standing in a long, slow-moving line at a grocery store. As it happened, my progress was stalled right next to a magazine rack rife with tabloids full of scandalous stories about movie stars, politicians, and assorted other celebrities.

For the first time in my life, I really looked at these publications and found myself wondering how they all stayed in business. Who reads all of this stuff? Why do we care so much about the private lives of individuals who we will never meet? I pondered this during my drive to the office after I left the store. I remember posing questions about the allure of these magazines to the first psychologist colleague I encountered when I got to work, and our ensuing conversation fanned the flames of my interest even further.

Being a good academic, my first impulse was to turn to the scientific literature to see what experts on gossip had been able to uncover. I was stunned by what I found, or more accurately, by what I did not find. There were a few studies in which anthropologists hung out in villages in random cultures and reported on what they heard people talking about when they gossiped and some intriguing anthropological theories about the origin of gossip.

However, I was unable to find anything in the way of actual experiments done by social psychologists on how gossip works. This is extraordinary: Until the dawn of the 21 st century, a universal human activity that lies at the heart of social life had been largely ignored by scientists whose stated mission was to understand human social interaction.

As an experimental social psychologist, I found the implied challenge irresistible. And so, with the help of some of my students, I embarked on a series of experiments on the psychology of gossip. I am proud to say that an interest in gossip spread like wildfire throughout the research community and that the study of gossip is now a thriving enterprise in the field of social psychology and related social sciences.

Thus, some research ideas do indeed spring directly from questions that arise through observing everyday life or from personal concerns faced by the researcher. However, this is not the only way in which research questions are formulated, and I will explore this in another post.

Frank McAndrew, Ph.D., is the Cornelia H. Dudley Professor of Psychology at Knox College.

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The crystallization of memory: Study reveals how practice forms new memory pathways in the brain

A new study led by UCLA Health has shown that repetitive practice not only is helpful in improving skills but also leads to profound changes in the brain's memory pathways.

The research, published in the journal Nature and co-led by Rockefeller University, sought to unravel how the brain's ability to retain and process information, known as working memory, improves through training.

To test this, researchers tasked mice with identifying and recalling a sequence of odors over the course of two weeks. Researchers then tracked neural activity in the animals as they practiced the task by using a novel, custom-built microscope that can image cellular activity in up to 73,000 neurons simultaneously throughout the cortex.

The study revealed a transformation in the working memory circuits located in the secondary motor cortex as the mice repeated the task through time. As the mice were first learning the task, the memory representations were unstable. However, after repeatedly practicing the task, the memory patterns began to solidify or "crystalize," said corresponding author and UCLA Health neurologist Dr. Peyman Golshani.

"If one imagines that each neuron in the brain is sounding a different note, the melody that the brain is generating when it is doing the task was changing from day to day, but then became more and more refined and similar as animals kept practicing the task," Golshani said.

These changes give insights into why performance becomes more accurate and automatic following repetitive practice.

"This insight not only advances our understanding of learning and memory but also has implications for addressing memory-related disorders," Golshani said.

The work was performed by Dr. Arash Bellafard, project scientist at UCLA in close collaboration with Dr. Alipasha Vaziri's group at Rockefeller University.

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Materials provided by University of California - Los Angeles Health Sciences . Original written by Will Houston. Note: Content may be edited for style and length.

Journal Reference :

• Arash Bellafard, Ghazal Namvar, Jonathan C. Kao, Alipasha Vaziri, Peyman Golshani. Volatile working memory representations crystallize with practice . Nature , 2024; DOI: 10.1038/s41586-024-07425-w

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SYSTEMATIC REVIEW article

The role of counseling for non-traditional students in formal higher education: a scoping review provisionally accepted.

• 1 Department of Pedagogy and Primary Education, National and Kapodistrian University of Athens, Greece

The final, formatted version of the article will be published soon.

Since the mid-20th century, the number of adult students enrolled in formal higher education (HE) programs has significantly increased. The profile of non-traditional students differs significantly from that of traditional students in terms of their characteristics, learning methods, obstacles and challenges, motivations for learning, and conditions for effective learning. Unlike traditional students, adult students often balance family, work, and educational responsibilities, necessitating a more nuanced approach to support and guidance. However, most HE institutions primarily serve the needs of traditional student populations, which results in limited support available to adult students. This scoping review aimed to explore and map the existing literature on the role of adult (or non-traditional) students counseling in the context of formal HE. We focused on literature related to academic advising for non-traditional students in formal HE, restricting our search to both empirical and non-empirical articles published in peer-reviewed journals between 2010 and 2022. Employing Arksey and O'Malley's scoping review method and the PRISMA-ScR Checklist, we searched four databases (EBSCOhost, Crossref, Semantic Scholar, and ERIC), supplemented by a manual search. Of the 1,330 articles identified and screened, 25 studies met the eligibility criteria. Our review included 17 empirical and eight non-empirical studies, with the majority conducted in the USA (21 of 25). Thematic analysis revealed five key research areas (or themes): academic advising practices, perceptions of advising, technology, and advising, advising models, and academic success. The most common research theme, advising practices for adult (undergraduate and doctoral) students, constituted 52% of the studies (n=13). Drawing from our analysis, we discuss current trends and future development in advising non-traditional students within formal HE settings. The added value of academic advising for adult students is explored, and any potential gaps in research literature knowledge are identified.

Keywords: Academic advising, Counseling, non-traditional students, adult students, higher education

Received: 25 Dec 2023; Accepted: 16 May 2024.

Copyright: © 2024 Stamou, Tsoli and Babalis. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Ms. Panagiota Stamou, National and Kapodistrian University of Athens, Department of Pedagogy and Primary Education, Athens, Greece

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Video games can have a positive impact on children—if designed with the right features, says new study

New research finds that digital games can contribute to the well-being of children, but game producers must design games to support positive outcomes.

Video games can contribute to and support the well-being of children if they are designed with the needs of children in mind, according to new research from UNICEF Innocenti and collaborating institutions, including New York University.

The report, the second in the Responsible Innovation in Technology for Children (RITEC) project, establishes that digital gaming companies and game designers can and should support the well-being of children through the games they produce and demonstrates that digital play has a particularly positive impact on children’s autonomy, competence, creativity, and identity when it responds to their deep interests, needs and desires. The project was co-founded by UNICEF and the LEGO Group and is funded by the LEGO Foundation.

NYU Steinhardt Professor Jan L. Plass led one of three studies appearing in the report. To understand the effect of digital play on children’s well-being, Plass and his colleagues implemented a 10-week intervention involving digital games including Lego Builder’s Journey and Rocket League with 255 children ages 8 through 12 years old. Among their findings, US children with a greater need for belonging relayed more positive feelings toward their social and parental relationships and an improved sense of autonomy. In Chile, children reported greater autonomy and improved parental relationships. In South Africa, the digital play generally supported well-being for all children.

“Many parents are concerned about screen time for their children, and this is the first study investigating the effect of digital play on well-being for this age group in the US, Chile, and South Africa,” said Plass, founding director of the Consortium for Research and Evaluation of Advanced Technology in Education (CREATE) Lab at NYU.

In addition to the experimental research led by Plass, observational research was conducted in the homes of 50 families over a 14-month period with children ages 6 through 12 in Australia, Cyprus, South Africa, and the UK. Lab-based research measured heart rate, eye tracking, facial expressions, and galvanic skin response (changes in sweat gland activity) of 69 children, ages 7 though 12, playing digital games in Australia.

The three studies found that games can support children’s senses of autonomy, competence, creativity, and identity, as well as help them regulate emotions and build relationships. But in order to support one or more of these aspects of well-being, games should consider certain features. For example, to support children’s sense of autonomy, a game could put them in control, allow them to make decisions about gameplay and encourage them to develop their own strategies to progress. Or to support creativity, a game could allow children to freely explore and solve problems or create their own characters or narratives.

“For decades, people have often assumed that playing video games is somehow bad for children, undermining their well-being. But our new study paints a far more complex picture—one in which these games can actually contribute to children’s well-being and positively support them as they grow up,” said Bo Viktor Nylund, director of UNICEF Innocenti.

Anna Rafferty, vice president of Digital Consumer Engagement, the LEGO Group, said: “This exciting research from UNICEF and leading academics shows that safe and inclusive digital play can have a profoundly positive impact on children’s lives. We’re proud to be partnering with like-minded organisations to understand how digital experiences can be designed in a way that puts children’s well-being first. These findings will empower responsible businesses to create a digital future where children are safe, nurtured and equipped to thrive.”

“The finding that digital play can enhance child well-being and meet children’s psychological needs, such as the need for connections to others, is especially important at a time when we are concerned about children’s mental health,” added Plass.

Said Nylund: “This research helps us understand not only how video games can impact the well-being of children, but also helps the producers and designers of these games understand what elements they can include to support children. We hope they will consider these findings as they design the games our children will be playing in the future.”

Also included in the RITEC project is the Joan Ganz Cooney Center; the Young & Resilient Research Centre at Western Sydney University; the Graduate Center, City University of New York; the University of Sheffield; and the Australian Centre of Excellence for the Digital Child.

The findings will be followed later this year by the launch of a guide to assist businesses to incorporate these findings into the games they design.

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