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Research in Developmental Psychology

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

Desk shown from above, pair of hands seen gesturing towards a graph

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.

question mark

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


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.)

A person is checking off boxes on a paper survey

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

Scatterplot of the association between happiness and ratings of the past month, a positive correlation (r = .81)

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.

Scatterplot showing the association between average male height and pathogen prevalence, a negative correlation (r = –.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?

Text stating that the year of study is 2010 and an experiment looks at cohort A with 20 year olds, cohort B of 50 year olds and cohort C with 80 year olds

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

Middle aged woman holding own photograph of her younger self.

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?

The same person, "Person A" is 20 years old in 2010, 50 years old in 2040, and 80 in 2070.

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.


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?

A tired looking mother closes her eyes and rubs her forehead as her baby cries.

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.


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!

Woman reading to two young children

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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Child health and human development over the lifespan

Joav merrick.

1 National Institute of Child Health and Human Development, Jerusalem, Israel

2 Office of the Medical Director, Health Services, Division for Intellectual and Developmental Disabilities, Ministry of Social Affairs and Social Services, Jerusalem, Israel

3 Division of Pediatrics, Hadassah Hebrew University Medical Center, Mt. Scopus Campus, Jerusalem, Israel

4 Kentucky Children's Hospital, University of Kentucky, Lexington, KY, USA

The topic of child health and human development is a wide area of interest spanning from pregnancy, delivery, childhood, adolescence, adulthood, and end of life. A study of health, development, and well-being over the lifespan.

Before birth through young adulthood there is a wide range of health issues that affect our children, such as general childhood illnesses, eating and obesity, accidents and injuries, and particular stages of life, such as teenage independence. Childs health and pediatrics focus on the well-being of children from conception through adolescence, but human development is a life span issue, so research in childhood does not stop with the end of adolescence, but we need a long-term and lifelong study to observe and understand the development process. Pediatrics is vitally concerned with all aspects of children's growth and development and with the unique opportunity that each child has to achieve their full potential as a healthy adult.

Pediatrics or child health was once not a specific entity, just as adolescence really did not exist as a concept, since all was a part of adult medicine. This field emerged in the nineteenth and early twentieth century as a medical specialty, because of the gradual awareness that the health problems of children were different from those of adults and children's response to illness, medications, and the environment is very depending upon the age of the child.

This uniqueness of children, along with diseases that are particular to this age group, has been responsible for the development of pediatrics as a specialty and for the creation of children's hospitals for the care of children.

Child health research

These same factors have also driven the creation of child health research, but we are still only able to do a few large lifelong studies to see the effects of pregnancy or early childhood on health and well-being in adulthood and older age. Long-term birth cohort studies have been and are conducted in the United Kingdom under the auspices of the Centre for Longitudinal Studies in London, like the National Survey of Health and Development (NSHD) established in 1946, the National Child Development Study (NCDS) established in 1958, the 1970 British Cohort Study (BCS70), and the Millennium Cohort Study (MCS) established in 2000 ( 1 ). In Denmark with the Copenhagen Perinatal Birth Cohort of 9125 individuals born 1959–1961 at the maternity departments of the Copenhagen University Hospital, Rigshospitalet ( 2 ) and the Danish National Birth Cohort 1996–2002 of 101,042 pregnant women recruited in first trimester at first antenatal visit at the general practitioner with 96,986 children resulting from the pregnancies ( 3 ). In the United States the National Institute of Child Health and Human Development has recently also initiated a large prospective life-history study, the National Children's Study, examining the effects of the environment and genetics on the growth, development, and health of children with more than 100,000 children who will be followed up from conception to age 21 years ( 4 ).

Such cohort studies of child health and human development over the lifespan are very important for our understanding of trends in health and well-being, quality of life, and quality of care, which will reveal emerging of “new morbidities” as we have seen over the past 50 years in pediatrics ( 5 ), but such cohort studies are very expensive, huge logistics involved and not always possible to conduct.

Growth and development

A healthy development begins before conception with parental health and their genetic composition and continues on to conception and through the prenatal period. Once delivered, new issues emerge, such as breastfeeding, newborn screening tests, health care appointments, and immunizations. Development constitutes a continuum and a child changes amazingly during the neonatal, newborn period, and early infancy. During this period there are many challenges both for the child, the parents, and the family and before you know it the child enter adolescence and adulthood.

Current issues

CS Mott Children's Hospital at the University of Michigan in Ann Arbor conducts a National Poll on Children's Health in order to monitor the future. In their collaboration with Knowledge Networks in this nationally representative household survey they administer to a randomly selected, group of adult with and without children of about 2000 person that closely resembles the United States population. In 2010, the following overall health concerns for US children in 2010 and the percentage of adults who rate each as a “big problem” included ( 6 ):

  • Childhood obesity, 38%
  • Drug abuse, 30%
  • Smoking, 29%
  • Internet safety, 25%
  • Stress, 24%
  • Bullying, 23%
  • Teen pregnancy, 23%
  • Child abuse and neglect, 21%
  • Alcohol abuse, 20%
  • Not enough opportunities for physical activity, 20%
  • Chemicals in the environment, 18%
  • Sexting, 16%
  • Depression, 15%
  • Sexually transmitted infections, 15%
  • School violence, 13%
  • Asthma, 10%
  • Neighborhood safety, 8%
  • Suicide, 8%

But the perception of the parent does not always portray the view of the child and researchers have therefore become concerned with the children's own perception of health. One study from Portugal ( 7 ) used creative drawing language to identify external factors perceived as negative or positive to health by children. The sample consisted of 130 children in 3rd and 4th classes from four randomly selected schools found that children value healthy food, physical activity, mental health, prevention of inappropriate substance consumption and health and environment. The drawings and comments showed links between diet and physical exercise, and between mental health and interpersonal relationships ( 7 ).


Just a few decades ago, children born with significant congenital anomalies or genetic and metabolic diseases perished at an early age and very few survived into their teens and even less into adulthood. Congenital heart disease, major errors in metabolism, cancer, cystic fibrosis, and many other major diseases were fatal. Because of that many physicians in adult primary care did not have the opportunity to see patients with these problems and thus were unable to learn how to care for them.

With major advancements in medical knowledge, technology, imaging techniques, surgical skills, and pharmaceutical products as well as prosthetic devices, many of these patients now live much longer life and sometimes even close to the average life expectancy for the country at least in the developed world. With that, a new medical care challenge has been created and we have to take a life span approach.

In the Frontier of Child Health and Human Development we would like to provide an academic focal point for the scholarly interdisciplinary study of child life, health, public health, welfare, disability, rehabilitation, intellectual disability, and related aspects of human development over the life span. Research, clinical work, public service activities in the field of child health and human development over the life span will be important topics for this journal.

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Article Contents

Utilizing principles of life-span developmental psychology to study resilience, focus on midlife, future research, acknowledgments, conflict of interest, utilizing principles of life-span developmental psychology to study the complexities of resilience across the adult life span.

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Frank J Infurna, Utilizing Principles of Life-Span Developmental Psychology to Study the Complexities of Resilience Across the Adult Life Span, The Gerontologist , Volume 61, Issue 6, September 2021, Pages 807–818, https://doi.org/10.1093/geront/gnab086

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Life-span developmental psychology includes a broad array of principles that have wide application to studying adult development and aging. Three principles have guided my past, current, and future research: (a) development being a cumulative, lifelong process with no one period taking precedence; (b) multiple processes influence development (e.g., age-, pathology-, nonnormative, and mortality-related processes); and (c) development is multidirectional and multidimensional. This paper elaborates on how these principles have guided my research studying resilience to adversity across the adult life span and how my research aligns with guiding elements of resilience across definitions and literatures. I also discuss my current and future research of applying these principles to studying resilience in midlife, which emphasizes how the defining features of midlife lend themselves to examining resilience, midlife continues to not be well understood, midlife health foreshadows health in old age, and the experience of midlife will evolve in the context of an increasingly diverse society. The last section elaborates on additional directions for future research, such as the promise of intensive longitudinal research designs that incorporate qualitative approaches and examining historical changes in midlife health and well-being. In conclusion, a life-span developmental psychology framework has wide application for elucidating the nature of resilience across the adult life span through the integration of its principles with existing paradigms and research designs that blend contemporary methods with mixed methodology.

Baltes (1987) outlines the theoretical principles that are characteristic of life-span developmental psychology. In this paper, I illustrate how I have used these principles to study resilience to adversity across the adult life span, and elaborate on fruitful avenues for future research in this area.

Three principles of life-span developmental psychology have guided my research: (a) life-span development, (b) multiple processes influencing development, and (c) development is multidirectional and multidimensional. The principle of life-span development signifies that development is a cumulative, lifelong process with no one period in the life span being more important than others and the demands and tasks differing across periods. For example, development in midlife is influenced by early-life conditions ( Ferraro et al., 2016 ) and present-life conditions of work, finances, and intergenerational relationships ( Infurna et al., 2020 ; Lachman, 2004 ). Midlife health behaviors foreshadow health in old age ( Lachman et al., 2015 ).

A second principle that has guided my research is the notion that development reflects a combination of age-, pathology-, nonnormative-, and mortality-related processes ( Birren & Cunningham, 1985 ; Featherman & Petersen, 1986 ). Research on understanding developmental processes in metrics other than chronological age has been around for decades (e.g., terminal drop in cognitive changes; Kleemeier, 1962 ; Riegel & Riegel, 1972 ). This research signifies how development may be better reflected by the onset of a chronic illness, major life stressor, or the years leading up to death than by chronological age ( Featherman & Petersen, 1986 ; Gerstorf & Ram, 2013 ). For example, Gerstorf and colleagues (2008) have demonstrated that developmental changes in subjective well-being may be better characterized by time-to-death than by chronological age. This research signifies that development is a complex and heterogenous process that cannot be explained solely by chronological age. Realigning the time metric in relation to a major life stressor or mortality provides a clearer picture of a homogenous change process. Studying groups of individuals who experienced the same adversity positions researchers to examine between-person differences in change and factors that promote better outcomes and could inform interventions.

The principle of multidimensionality refers to how pertinent domains consist of multiple facets that are interrelated. Multidirectionality includes the notion that developmental changes in outcomes may show differences in their timing or onset of change, direction, and rates of change, or some combination of timing, direction, and rates of change. In the instance of terminal drop, there are between-person differences in its year of onset prior to death and rate of change before and after onset with outcomes showing differences in these parameters (e.g., cognition vs well-being; Gerstorf & Ram, 2013 ; Kleemeier, 1962 ; Riegel & Riegel, 1972 ). Furthermore, subjective well-being consists of life satisfaction, positive affect, and negative affect. Infurna and Luthar (2017a) found cross-domain variability in change in each outcome before and after spousal loss with persons less likely to exhibit resilience in positive and negative affect as compared to life satisfaction. They also observed how positive and negative affect took longer to bounce back following spousal loss as compared to life satisfaction.

The resilience literature has a long history, which has led to many concepts and definitions. Table 1 presents some of the prominent definitions used in the developmental and adult development and aging literatures. Six core elements of resilience emerge across the definitions: (1) exposure to risk or adversity, (2) the response or manifestation of positive adaptation despite encountering risk or adversity, (3) individual variations surrounding response to risk or adversity, (4) protective factors that predict positive adaptation, (5) resilience is a dynamic process that requires methodology to match this notion (e.g., use of contemporary methods of analysis and longitudinal data), and (6) resilience is a multidimensional construct.

Core Definitions of Resilience From Developmental Psychology and Adult Development and Aging Literatures

Note : This list of definitions is not meant to be exhaustive but intended to provide an overview of core elements of resilience.

There are numerous types of risk or adversities that have been studied. Resilience research that originated in developmental psychology primarily focused on children’s resilience in the context of poverty, divorce, maltreatment, or war ( Luthar et al., 2000 ; Masten & Narayan, 2012 ). Adversities examined in the adult development and aging literature include adverse life events (e.g., bereavement, unemployment), chronic stressors (e.g., caregiving for a family member), and clinical trauma (e.g., being involved in a major accident; Jayawickreme et al., 2021 ). These life challenges are uniquely characterized by discrete and, in principle, observable environmental and social changes that precipitate the need for adjustment in identity or life routines ( Dohrenwend, 2006 ; Gray et al., 2004 ). The wide range of adversities that have been studied within a resilience framework is one potential reason why numerous definitions exist.

The second element of resilience is manifestation of positive adaptation despite risk or adversity. Positive adaptation can take different paths or trajectories. Exploration of different pathways has been advanced with the advent of growth mixture modeling (GMM), which is a statistical method of analysis that allows researchers to illuminate discrete trajectories of change ( Grimm et al., 2017 ). Figure 1 illustrates the most commonly observed trajectories, including resilience, recovery, chronic low, and growth ( Infurna & Luthar, 2018 ). Resilience is considered a trajectory of stable, healthy levels of psychological functioning before and after adversity. Recovery is characterized by decrements in psychological functioning because of the adversity followed by a return to near-previous levels. Chronic low is characterized by individuals showing stable, low levels of psychological functioning before and after adversity. Growth encompasses enduring improvements as a result of the adversity ( Infurna & Jayawickreme, 2019 ).

Graphical illustration of the most common trajectories or paths individuals may follow in the years leading up to and following adversity. (A) The four trajectories that have commonly been observed for outcomes centered on psychological functioning where higher levels are indicative of better adjustment, including life satisfaction, positive affect, physical functioning, and perceptions of general health. (B) The four trajectories that have commonly been observed for outcomes centered on symptoms where higher levels reflect poorer adjustment, including depressive symptoms, anxiety, negative affect, and posttraumatic stress symptoms. These trajectories are not exhaustive; other trajectories that have been observed in the literature. Reprinted with permission from Infurna and Luthar (2018).

Graphical illustration of the most common trajectories or paths individuals may follow in the years leading up to and following adversity. ( A ) The four trajectories that have commonly been observed for outcomes centered on psychological functioning where higher levels are indicative of better adjustment, including life satisfaction, positive affect, physical functioning, and perceptions of general health. ( B ) The four trajectories that have commonly been observed for outcomes centered on symptoms where higher levels reflect poorer adjustment, including depressive symptoms, anxiety, negative affect, and posttraumatic stress symptoms. These trajectories are not exhaustive; other trajectories that have been observed in the literature. Reprinted with permission from Infurna and Luthar (2018) .

The third element of resilience involves individual variations in change following adversity. This is exemplified in Figure 2 , which shows large between-person differences in the extent to which spousal loss impacts life satisfaction. The solid black line represents the model-implied average taken from the sample under study and the gray lines represent model-implied changes from a subset of participants. Figure 2 represents a microcosm of Rutter’s (1987) broader consideration of resilience, stating that “Resilience is concerned with individual variations in response to risk. Some people succumb to stress and adversity whereas others overcome life hazards” (p. 317). Such individual variation offers an opportunity to study factors that promote positive outcomes.

Between-person variation in within-person changes of life satisfaction before and after spousal loss. The solid black line represents the model-implied average taken from the sample under study and the gray lines represent model-implied changes from a subset of participants. One can observe that there is a great deal of between-person variation in the extent to which life satisfaction changes before and after spousal loss. Reprinted with permission from Infurna et al. (2017). SOEP = German Socio-Economic Panel Study.

Between-person variation in within-person changes of life satisfaction before and after spousal loss. The solid black line represents the model-implied average taken from the sample under study and the gray lines represent model-implied changes from a subset of participants. One can observe that there is a great deal of between-person variation in the extent to which life satisfaction changes before and after spousal loss. Reprinted with permission from Infurna et al. (2017) . SOEP = German Socio-Economic Panel Study.

Many protective factors have been studied, including adversity severity, sociodemographics, personality factors, control beliefs, and social support. My research has shown that younger age at the time of spousal loss was associated with stronger declines in life satisfaction, but better adaptation in the years thereafter, and in the context of disability, younger age was associated with poorer adaptation. Social support, cognition, and perceived control were key contributors to better adaptation to cancer diagnosis, spousal loss, disability, and unemployment ( Infurna & Luthar, 2017a ; Infurna et al., 2013 , 2016 , 2017 ; Infurna & Wiest, 2018 ).

The fifth component that cuts across definitions of resilience is that resilience is a dynamic process that evolves over time. This fact requires the application of contemporary methods of analysis (e.g., multilevel modeling, GMM) to longitudinal research designs. The resilience literature focusing on adulthood and old age has overwhelmingly used GMM to discern resilience to a wide range of adversities ( Infurna & Luthar, 2016 ). My research in this arena has revealed significant issues that question the validity of existing findings of resilience being the norm, due to an artifact of the methodological approach with research using GMM relying on two key methodological assumptions: homogeneity of variance (86%) and slope variances set to 0 (68%; Infurna & Luthar, 2018 ). These assumptions restrict how much persons’ trajectories differ from one another and variations in how much they change over time. Infurna and Luthar (2016) found that these a priori assumptions inflate the number and percentage of individuals who exhibited a resilient trajectory (for simulation studies, see Diallo et al., 2016 ). The take-home message from our studies was that by applying more justifiable assumptions, estimates of resilience are much lower than that have been reported previously.

A last element to studying resilience is the importance of taking a multidimensional approach. The resilience literature in adulthood and old age has overwhelmingly focused on single outcomes, which inhibits researchers from examining whether pertinent outcomes within and across domains display differential trajectories of change following adversity. Following the principles of multidirectionality and multidimensionality, we used GMM to examine changes in life satisfaction, negative and positive affect, physical functioning, and general health before and after spousal loss ( Infurna & Luthar, 2017a ). Most individuals exhibited a resilient trajectory for life satisfaction (66%), whereas for positive affect (26%) and negative affect (19%), far fewer individuals exhibited resilience. Similarly, fewer individuals showed a resilient trajectory for general health (37%) and physical functioning (29%).

To further examine the multidimensional nature of resilience, a composite total score was created across the five outcomes. We outputted the trajectory membership for each individual and quantified the percentage of individuals who exhibited a resilient trajectory. Only 8% of the 421 participants were resilient in all five outcomes, whereas 20% were not resilient in any of the five outcomes (see also Infurna et al., 2017b ; Luthar et al., 1993 ). These results demonstrate that resilience coexists with deficits across pertinent domains. Infurna and Luthar (2018) observed that over 80% of studies included a single outcome to assess resilience, but this has not prevented researchers from declaring that resilience is the common response to adversity. Mental health and well-being are the most widely studied domains, but other domains, such as physical health, are likely impacted and should be explored further ( Infurna & Luthar, 2018 ).

My research interests have shifted towards applying principles of life-span development to studying resilience in midlife. The age range of midlife is typically 40–65 (±5–10 years; Lachman, 2004 ), with individuals likely spending most of adulthood in midlife. The theory of midlife that immediately comes to mind is Erikson’s (1963) psychosocial stage of generativity versus stagnation. Generativity involves leaving a legacy for others and the need to create or nurture things that will outlast them, which could be pursued through one’s family (raising children and grandchildren), work (mentoring colleagues), or community (volunteering). Stagnation signifies an individual’s failure to achieve these goals or objectives, leading to a sense of being unproductive, not giving back, and being self-centered ( McAdams et al., 1993 ). A lesser discussed stage theory of adult development was developed by Levinson (1986) , who detailed that as individuals transitioned into midlife, their attention shifted to investment in one’s career, family, and other central components, such as friendships, leisure, and community. Midlife was considered a point in the life span where individuals reflected on what they have done and ways to live that best combined their current desires, values, talents, and aspirations ( Levinson, 1986 ).

The late 1990s and early 2000s saw increased interest in the study of midlife as reflected by several edited volumes and burgeoning research through the availability of longitudinal panel surveys. Lachman and James’ (1997) edited volume on multiple paths of midlife development included chapters that covered a wide range of topics, such as development of self and identity, how the experience of midlife differs between men and women, crisis and challenges that are confronted, as well as stability and change in social networks, well-being, and health. The early 2000s saw additional edited volumes on midlife, such as an overview of the Midlife in the United States Study (MIDUS) that has since and continues to provide researchers with a plethora of data to address research questions on midlife development ( Brim et al., 2004 ). The edited volume by Willis and Martin (2005) on applying a life-span perspective to midlife contained important chapters focusing on early life antecedents of development in midlife and how one’s health, well-being, and self/identity in midlife can foreshadow functioning in old age. Whitbourne and Willis (2006) organized an edited volume that focused entirely on the Baby Boomer generation. In the opening preface, the authors highlight how the Baby Boomers are the largest cohort ever to enter midlife in Western society. The various chapters showcase their imposing nature because of their sheer number and ways they will challenge existing norms and policies pertaining to work, family, and health care. An emphasis of this volume was on demographic and theoretical perspectives, physical and mental health changes, psychosocial issues pertaining to self/identity and cognition, and the importance of social relationships and employment.

Another reason for the increase of research on midlife is the number of longitudinal panel surveys that are publicly available. Examples include MIDUS, the Health and Retirement Study, English Longitudinal Study of Ageing, Survey of Health, Ageing, and Retirement in Europe, and the German Socio-Economic Panel. Access to a wealth of cross-national data on persons in midlife makes it easier than ever for researchers to study this period of development. There are several additional reasons why it is important to study middle-aged adults: (a) the defining features of midlife lend themselves to examining resilience, (b) midlife continues to be not well understood, (c) midlife health foreshadows health in old age, and (d) the experience of midlife will evolve in the context of an increasingly diverse society.

Defining Features of Midlife

My colleagues and I recently published a conceptual review of midlife ( Infurna et al., 2020 ) where we conceptualize that midlife consists of four defining features: simultaneous involvement in roles, life transitions, opportunities, and challenges. Involvement in a number of roles symbolizes how middle-aged adults are simultaneously trying to balance commitments in work/career, family, community, and social network engagement, among others. Ahrens and Ryff (2006) found middle-aged adults could be involved with up to eight roles, with the average person engaged in four. A key finding from this study was that more roles were associated with higher well-being. Role engagement likely leads to positive well-being through enhancing one’s resources, social connections, and emotional gratification ( Thoits, 1983 ). The range of significant life transitions in midlife includes career/workforce (e.g., promotions, changing companies, and beginning a new career different than one’s training), marital (e.g., divorce, remarriage), family (e.g., parenthood and grandparenthood), and caregiving responsibilities for an aging family member or spouse/partner, in addition to changes in one’s physical health (e.g., onset of chronic illness) and cognitive abilities ( Lachman et al., 2015 ). Opportunities in midlife include potential peak in career development and earnings, heightened well-being and emotional experiences, control beliefs, and crystallized cognitive abilities ( Galambos et al., 2020 ; Lachman et al., 2015 ).

The core challenges that individuals in midlife are encountering include changing nature of intergenerational dynamics (e.g., raising children, caregiving for aging parents or relatives, and the upsides and downsides of grandparenting) and financial vulnerabilities. One drawback of the tremendous gains in life expectancy seen in the twentieth century is the increasing likelihood of middle-aged adults needing to take on caregiving roles and responsibilities for their aging parents or other relatives. The needs of the aging parent can strain relationships, financial resources, and mental and physical health ( Aneshenshel et al., 1995 ). The nature, pressures, and involvement of raising children have changed due to trends to excel in the classroom and overinvolvement in extracurricular activities ( Ebbert et al., 2019 ). Difficulties in finding long-term stable employment and excessive student loan debt have also led to young adult children moving home in record numbers and potentially being a source of relationship strain ( Fingerman et al., 2020 ).

Financial vulnerabilities refer to how U.S. middle-aged adults are facing a shrinking social and health care safety net that can strain one’s mental and physical health and social network engagement/relationships. For middle-aged adults who are caregiving for an aging parent or relative, there are no paid options for family leave at the federal level; eight states and District of Columbia have paid family leave for caregiving for an aging relative, which can include up to 70% of paid leave for 12 weeks ( Reinhard et al., 2019 ). Oftentimes this is not enough because people who cannot afford to leave work are more likely to be caregivers and may need to decide between caregiving and work. Rising health care costs, coupled with labor market volatility strains household budgets, can further exacerbate mental and physical health declines ( Grande et al., 2013 ).

Midlife Is Not Well Understood

Midlife is considered an ambiguous time in the life span, with no established set of uniform developmental milestones. This has led to views of midlife being a period of stability and developmental inactivity. Much of what is typically discussed about midlife in the general public are myths, such as the midlife crisis or empty nest syndrome; research shows no consistent evidence for these phenomena ( Infurna et al., 2020 ). The myth of the midlife crisis remains because of research on the supposed U-shape curve in well-being. Galambos and colleagues (2020) illustrated that this U-shape curve is a function of cross-sectional data that finds age differences in well-being and confounds age and cohort; when studied using longitudinal data, such a trend no longer remains, with well-being being relatively high and stable across midlife. Without a firm set of milestones, this makes it difficult for researchers to know what to pinpoint in their research on middle-aged adults. The edited volumes and conceptual review discussed above signify that midlife is a developmental period rife with activity where individuals are engaged in numerous roles and may encounter various life transitions, challenges, opportunities, and milestones.

A second reason for midlife continuing to be not well understood is difficulties with recruitment of middle-aged participants. Age-comparative studies often contrast undergrad samples who receive course credits with older adults (aged 65 and older) who are likely retired and have the time to participate. Conversely, individuals in midlife are balancing multiple roles that make it difficult to find time and energy to participate in research studies. Third, middle-aged adults are typically studied in other literatures. For example, there are rich literatures on parenting styles shaping development in childhood and adolescence ( Ebbert et al., 2019 ), intergenerational dynamics ( Fingerman et al., 2020 ), the consequences of parental divorce ( Amato, 2010 ), and career development and workplace influences ( Moen, 2016 ). As discussed above, the advent of publicly available longitudinal panel surveys has been instrumental in bringing to light the importance of explicitly studying individuals in midlife across self/identity, social relationships, cognitive, and health developments, the dynamics of daily life, and physiological and neurological correlates (see Brim et al., 2004 ).

Midlife Health Foreshadows Health in Old Age

Studying midlife positions researchers to effectively study development as a cumulative, lifelong process. An abundance of literature has shown how early-life adversity is associated with health and well-being in midlife and into old age ( Ferraro et al., 2016 ). Empirical evidence also demonstrates that better health in midlife—as indexed by health-promoting behaviors (e.g., physical activity, sleep) and physiology (e.g., blood pressure)—foreshadows better health in old age ( Launer et al., 1995 ; Sabia et al., 2021 ). A long-term consequence of middle-aged adults approaching old age in poorer health in the form of chronic illness, disability, and physical inactivity may be greater health insurance expenses and reliance on family members for caregiving duties ( Infurna et al., 2020 ).

Analogous to this are alarming trends in the health and well-being of middle-aged adults. Recent research from MIDUS shows that U.S. middle-aged adults following the Great Recession are, on average, reporting more health symptoms, daily stress, and poorer psychological well-being than previous cohorts of middle-aged adults ( Almeida et al., 2020 ; Kirsch et al., 2019 ). Several studies using cross-national data from 2002, 2004, and 2012 have shown that compared to middle-aged adults in European and Asian nations, U.S. middle-aged adults, on average, exhibit higher rates of chronic illness and disability ( Avendano et al., 2009 ; Banks et al., 2006 ; Lee et al., 2018 ).

Numerous avenues exist for promoting resilience in midlife and optimizing successful aging. These include interventions focusing on improving physical activity, reducing caregiving-related stress, and improving mental health through social engagement, as well as policy changes that enhance paid family leave and workplace flexibility (for discussion, see Infurna et al., 2020 ). There is great need in nurturing and cultivating the health and well-being of middle-aged adults for the benefit of larger society because they constitute large segments of the workforce, are caregiving for adult and younger children and aging parents/family relatives, on top of balancing work and their own health and well-being.

The Experience of Midlife Will Evolve in the Context of an Increasingly Diverse Society

Within the context of research on midlife, most of what is known comes from research on U.S. samples that mirror traditional family structures of middle-class people who are White, married, and have children. Population estimates reveal that in addition to the U.S. population graying, it is becoming more racially and ethnically diverse ( Vespa et al., 2020 ). This trend coincides with changes in the structure and function of families through greater rates of remarriages, blended families, and cohabiting families ( Antonucci et al., 2011 ). Therefore, concerted efforts are needed to better understand diversity in how midlife is experienced across race/ethnicity, socioeconomic status (SES), gender, and sexual orientation. A large buzz has surrounded the research by Case and Deaton (2015) , who observed that deaths of despair have been rising in middle-aged non-Hispanic White males who solely attained a high school education. What has received much less attention is how these findings pale in comparison to the health inequities that have long existed across population subgroups ( Muennig et al., 2018 ; Roux, 2017 ). Research has documented how Hispanic and Black Americans are more likely to report poorer mental and physical health ( Weden et al., 2017 ), and report more disability, depressive, metabolic, and inflammatory risk relative to Whites ( Boen & Hummer, 2019 ). Across indicators of SES, low-SES individuals typically exhibit poorer mental and physical health ( Adler & Rehkopf, 2008 ). Women are more likely to report psychological distress and low well-being in midlife, compared to men ( Blanchflower & Oswald, 2020 ). Lesbian, gay, bisexual, and transgender adults show higher risk for poorer mental and physical health ( Fredriksen-Goldsen et al., 2013 , 2018 ).

The coronavirus disease 2019 (COVID-19) pandemic has exacerbated inequalities in the United States. For example, women have left the workforce at rates far higher than that of men, in addition to racial disparities in COVID-19 infection and mortality rates ( van Dorn et al., 2020 ). These impacts may exacerbate concerns about risk and magnify disparities across population subgroups in midlife.

Population-level changes, existing disparities, and the COVID-19 pandemic have made clear the importance of explicitly studying race/ethnicity, SES, gender, and sexual orientation because they convey meaning in the experience of midlife. Future research is warranted that better understands how the challenges confronting middle-aged adults and the opportunities made available to them will differ across population subgroups.

Now that I have outlined the various reasons why it is important to explicitly study middle-aged adults, the next step is to discuss methodological approaches for doing so. Longitudinal panel surveys have the advantages of large samples, the ability to detect longitudinal trajectories of change following adversity, and simultaneously examining multiple domains. However, there are disadvantages, which include the inability to examine the processes underlying development and resilience. More frequent and closely spaced assessments are needed that have the advantages of examining more immediate responses to adversity and how the accumulation of adversities impacts developmental processes ( Infurna & Luthar, 2018 ). Intensive longitudinal research designs have been around for a long time. Nesselroade (1991) discussed how they permit studying two core features of human development: intraindividual change and intraindividual variability. Intraindividual change refers to enduring changes that are construed as developmental by virtue of the nature of their antecedents, consequences, and correlates ( Baltes, 1987 ), whereas intraindividual variability refers to relatively short-term changes that are construed as more or less reversible and that occur more rapidly than intraindividual changes. Intraindividual change focuses on developmental trajectories of self/identity, well-being, cognition, social networks, and health in midlife ( Galambos et al., 2020 ; Lachman et al., 2015 ). Focusing on intraindividual variability allows for studying processes that transpire at a more dynamic time scale of days, weeks, or months and can thereby be linked to intraindividual change over years and decades ( Ram & Gerstorf, 2009 ). An advantage of intensive longitudinal research designs is the ability to study ways episodes of continual stress contribute to pertinent outcomes. For example, Schilling and Diehl (2014) have applied such an approach to daily survey data, revealing that the accumulation of stressors over a 6-day period was associated with reporting higher levels of negative affect, above and beyond concurrent levels of stressors.

Intensive longitudinal research designs can be implemented to study life transitions and the impact of intergenerational dynamics and financial challenges in midlife. Intergenerational dynamics is a rich area of study. For example, Huo and colleagues (2019) have shown how daily support exchanges between younger and older generations are associated with daily well-being and health for middle-aged adults. A recent review by Fingerman and colleagues (2020) discussed how the Great Recession and accompanying financial strains altered the nature of many parent/child ties, and events such as divorce, addiction, and physical health problems greatly impacted intergenerational support. Middle-aged adults constitute large segments of the workforce. DePasquale and colleagues (2016) found that double- and triple-duty caregiving disrupts work performance, well-being, and sleep. The COVID-19 pandemic has led to middle-aged adults finding themselves in challenging life circumstances, such as job loss, financial strain, loss of or disruptions in health care, and having to balance work with overseeing school for their children ( Settersten et al., 2020 ). Ultimately, the use of intensive longitudinal designs offers the opportunity to study the nature and processes of how these challenges play out over the course of days, weeks, and months and monitoring their long-term impact on development over years and decades.

Qualitative approaches have the potential to reveal important insights into the opportunities and challenges confronting middle-aged adults. Adler and colleagues (2017) elaborate on the advantages of such techniques in the context of research on narrative identity, such as detailing motivational and affective themes, themes pertaining to meaning and structural elements to the broader questions at hand. Heid and colleagues (2021) embedded open-ended questions into an existing longitudinal panel survey to explore the consequences of COVID-19 on older adults. In the context of midlife, qualitative approaches can help get in-depth insights into life transitions and challenges they are confronting and effective strategies and resources individuals are relying on to overcome them. By embedding these questions into a longitudinal research design, quantitative measures can be used to examine overlap with health and well-being indicators.

Examining historical trends of (declining) mental and physical health in U.S. middle-aged adults is another promising area of research that is in line with life-span developmental principles of exploring how historical embeddedness and cultural contextualism influence developmental processes ( Baltes, 1987 ). Research on cohort effects has primarily focused on older adults. Empirical evidence suggests that recent cohorts of older adults are performing better than early-born cohorts across multiple indices of mental and physical health and psychosocial functioning (for overview, see Gerstorf et al., 2020 ). The importance of studying cohort effects in middle-aged adults is how they foreshadow health in old age; if today’s middle-aged adults are doing more poorly than previous cohorts/generations, this can potentially transfer into old age. As mentioned above, research from MIDUS revealed that U.S. middle-aged adults nowadays are reporting poorer mental and physical health than earlier-born cohorts of middle-aged adults ( Almeida et al., 2020 ; Kirsch et al., 2019 ). The important question is to expand these findings by identifying whether historical declines in midlife mental and physical health are similarly transpiring across other nations beyond the United States.

We studied historical changes in midlife mental and physical health across the United States, Australia, Germany, South Korea, and Mexico and observed differences across the nations studied (see Infurna et al., In press ). Later-born cohorts of middle-aged adults in the United States and Australia showed historical declines in mental health and slight improvements in physical health. Conversely, later-born cohorts of middle-aged adults in Germany, South Korea, and Mexico exhibited historical improvements across mental and physical health. A hallmark of previous research identifying these historical trends is that low-to-middle SES individuals are showing stronger historical declines ( Almeida et al., 2020 ; Case & Deaton, 2020 ; Kirsch et al., 2019 ). We found that the effect of educational attainment differed across nations. For U.S. middle-aged adults, the protective effect of education diminished in later-born cohorts and consistent across the other nations, individuals with fewer years of education benefitted the least from historical improvements. This descriptive research lends itself to future endeavors for uncovering why cross-national differences exist, which could be attributable to variations in policy programs between nations, as well as individual- and community-level factors ( Gerstorf et al., 2020 ; Infurna et al., In press ).

The goal of this paper was to detail how various principles of life-span developmental psychology have guided my past, current, and future research. The principles of life-span development, multiple processes influencing development, and multidirectionality and multidimensionality have guided my research on resilience to adversity and current and future research on resilience in midlife. Resilience is a complex process that contains many elements (see Table 1 ). Studying resilience in midlife is a burgeoning/promising area of research because the defining features of midlife lend themselves to examining resilience, midlife continues to not be well understood, midlife health foreshadows health in old age, and the experience of midlife will evolve in the context of an increasingly more diverse society. Future research directions include examining the diverse types of adversities that impact middle-aged adults, exploring historical trends in middle-aged adults mental and physical health across nations, and using both intensive longitudinal designs and qualitative approaches to shed light on midlife development. By elucidating the key features of midlife and the mechanisms and ways middle-aged adults can overcome diverse types of adversities, this can provide meaningful insights for interventions and benefit the greater good of society due to middle-aged adult’s involvement in numerous roles, tasks, and responsibilities across work and family.

An earlier version of this article, “Utilizing Principles of Lifespan Developmental Psychology to Examine Resilience to Adversity,” was presented as the 2019 Baltes Award Lecture on November 14, 2019 at The Gerontological Society of America 2019 Annual Scientific Meeting held in Austin, Texas.

None declared.

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International Handbook of Educational Research in the Asia-Pacific Region pp 379–393 Cite as

Lifespan Human Development

  • Candida C. Peterson 10  

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Part of the Springer International Handbooks of Education book series (SIHE,volume 11)

This article explores psychological development from a lifespan perspective, with a special focus on the periods of youth, adulthood and old age. These phases, like infancy and childhood before them, are exciting periods of developmental change. As adolescents embark upon mature lives independently, and as adults progress through the successive milestones and turning points of mature life (like marriage, a new baby, a new career, the launching of adult children into independence, retirement from a lifelong career, the birth of a grandchild, or widowhood), new opportunities for psychological growth are continually presented. At the same time, the range of available choices may narrow, losses will arise, and problems and disappointments will almost certainly occur. These adversities, too, will provide the impetus and opportunity for psychological adjustment, and gains in maturity can arise out of successful coping late in life, just as they did during childhood. The lifespan approach to the study of human development seeks to understand these continuities and discontinuities in psychological growth and change over the whole of life.

  • Psychological Functioning
  • Psychological Development
  • Filial Piety
  • Psychological Capacity
  • Psychological Growth

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Peterson, C.C. (2003). Lifespan Human Development. In: Keeves, J.P., et al. International Handbook of Educational Research in the Asia-Pacific Region. Springer International Handbooks of Education, vol 11. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-3368-7_27

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