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Developmental Psychology Research Methods

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

research methods in studying human development

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

Jose Luis Pelaez Inc/Getty Images

Cross-Sectional Research Methods

Longitudinal research methods, correlational research methods, experimental research methods.

There are many different developmental psychology research methods, including cross-sectional, longitudinal, correlational, and experimental. Each has its own specific advantages and disadvantages. The one that a scientist chooses depends largely on the aim of the study and the nature of the phenomenon being studied.

Research design provides a standardized framework to test a hypothesis and evaluate whether the hypothesis is correct, incorrect, or inconclusive. Even if the hypothesis is untrue, the research can often provide insights that may prove valuable or move research in an entirely new direction.

At a Glance

In order to study developmental psychology, researchers utilize a number of different research methods. Some involve looking at different cross-sections of a population, while others look at how participants change over time. In other cases, researchers look at how whether certain variables appear to have a relationship with one another. In order to determine if there is a cause-and-effect relationship, however, psychologists much conduct experimental research.

Learn more about each of these different types of developmental psychology research methods, including when they are used and what they can reveal about human development.

Cross-sectional research involves looking at different groups of people with specific characteristics.

For example, a researcher might evaluate a group of young adults and compare the corresponding data from a group of older adults.

The benefit of this type of research is that it can be done relatively quickly; the research data is gathered at the same point in time. The disadvantage is that the research aims to make a direct association between a cause and an effect. This is not always so easy. In some cases, there may be confounding factors that contribute to the effect.

To this end, a cross-sectional study can suggest the odds of an effect occurring both in terms of the absolute risk (the odds of something happening over a period of time) and the relative risk (the odds of something happening in one group compared to another).

Longitudinal research involves studying the same group of individuals over an extended period of time.

Data is collected at the outset of the study and gathered repeatedly through the course of study. In some cases, longitudinal studies can last for several decades or be open-ended. One such example is the Terman Study of the Gifted , which began in the 1920s and followed 1528 children for over 80 years.

The benefit of this longitudinal research is that it allows researchers to look at changes over time. By contrast, one of the obvious disadvantages is cost. Because of the expense of a long-term study, they tend to be confined to a smaller group of subjects or a narrower field of observation.

Challenges of Longitudinal Research

While revealing, longitudinal studies present a few challenges that make them more difficult to use when studying developmental psychology and other topics.

Longitudinal studies are difficult to apply to a larger population.
Another problem is that the participants can often drop out mid-study, shrinking the sample size and relative conclusions.
Moreover, if certain outside forces change during the course of the study (including economics, politics, and science), they can influence the outcomes in a way that significantly skews the results.

For example, in Lewis Terman's longitudinal study, the correlation between IQ and achievement was blunted by such confounding forces as the Great Depression and World War II (which limited educational attainment) and gender politics of the 1940s and 1950s (which limited a woman's professional prospects).

Correlational research aims to determine if one variable has a measurable association with another.

In this type of non-experimental study, researchers look at relationships between the two variables but do not introduce the variables themselves. Instead, they gather and evaluate the available data and offer a statistical conclusion.

For example, the researchers may look at whether academic success in elementary school leads to better-paying jobs in the future. While the researchers can collect and evaluate the data, they do not manipulate any of the variables in question.

A correlational study can be appropriate and helpful if you cannot manipulate a variable because it is impossible, impractical, or unethical.

For example, imagine that a researcher wants to determine if living in a noisy environment makes people less efficient in the workplace. It would be impractical and unreasonable to artificially inflate the noise level in a working environment. Instead, researchers might collect data and then look for correlations between the variables of interest.

Limitations of Correlational Research

Correlational research has its limitations. While it can identify an association, it does not necessarily suggest a cause for the effect. Just because two variables have a relationship does not mean that changes in one will affect a change in the other.

Unlike correlational research, experimentation involves both the manipulation and measurement of variables . This model of research is the most scientifically conclusive and commonly used in medicine, chemistry, psychology, biology, and sociology.

Experimental research uses manipulation to understand cause and effect in a sampling of subjects. The sample is comprised of two groups: an experimental group in whom the variable (such as a drug or treatment) is introduced and a control group in whom the variable is not introduced.

Deciding the sample groups can be done in a number of ways:

Population sampling, in which the subjects represent a specific population
Random selection , in which subjects are chosen randomly to see if the effects of the variable are consistently achieved

Challenges in Experimental Resarch

While the statistical value of an experimental study is robust, it may be affected by confirmation bias . This is when the investigator's desire to publish or achieve an unambiguous result can skew the interpretations, leading to a false-positive conclusion.

One way to avoid this is to conduct a double-blind study in which neither the participants nor researchers are aware of which group is the control. A double-blind randomized controlled trial (RCT) is considered the gold standard of research.

What This Means For You

There are many different types of research methods that scientists use to study developmental psychology and other areas. Knowing more about how each of these methods works can give you a better understanding of what the findings of psychological research might mean for you.

Capili B. Cross-sectional studies . Am J Nurs . 2021;121(10):59-62. doi:10.1097/01.NAJ.0000794280.73744.fe

Kesmodel US. Cross-sectional studies - what are they good for? . Acta Obstet Gynecol Scand . 2018;97(4):388–393. doi:10.1111/aogs.13331

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Kell HJ, Wai J. Terman Study of the Gifted . In: Frey B, ed. The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation . Vol. 4. Thousand Oaks, CA: SAGE Publications, Inc.; 2018. doi:10.4135/9781506326139.n691

Curtis EA, Comiskey C, Dempsey O. Importance and use of correlational research . Nurse Res . 2016;23(6):20–25. doi:10.7748/nr.2016.e1382

Misra S. Randomized double blind placebo control studies, the "Gold Standard" in intervention based studies . Indian J Sex Transm Dis AIDS . 2012;33(2):131-4. doi:10.4103/2589-0557.102130

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

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Lifespan Developmental Research Methodologies

Ellen Skinner; Julia Dancis; and The Human Development Teaching & Learning Group

Learning Objectives: Lifespan Developmental Methodologies

Explain the importance of complementary multidisciplinary methodologies and converging operations.
Recognize the steps in deductive , inductive , and collaborative methodologies.
Be familiar with the many methods developmentalists use to gather information, including observations and self-reports, psychological tests and assessments, laboratory tasks, psychophysiological assessments, archival data or artifacts, case studies, and enthnographies.
Identify the general strengths and limitations of different methods (e.g., reactivity, social desirability, accessibility, generalizability).

Because interventionists and practitioners use bodies of scientific evidence to transform systems and change practices in the world, it is crucial that researchers produce the highest quality evidence possible, and evaluate and critique it thoughtfully. The tools that scientists use to generate such knowledge are called research methods or methodologies. Many textbooks describe “the” scientific method, as if there were only one way of knowing scientifically. Just as lifespan development spans multiple disciplines, each with their own preferred epistemologies and methodologies, we believe that there are multiple scientific methods, or multiple perspectives, each one providing a complementary line of sight on a given target phenomenon. Social and developmental sciences have been critiqued for our reliance on a narrow range of methodologies, favoring methods that quantify observations (e.g., via surveys, ratings, or numerical codings) and control extraneous variables or confounds, either statistically or, for example, by bringing people into the lab. Social scientists often seem to favor these more quantitative methods, and to discount methodologies that are more situated, contextualized, and wholistic, sometimes called qualitative methods.

An illustration of four men touching an elephant, demonstrating the parable of the blind men and the elephant

However, it has become clear that these methodologies are not antagonistic. Instead, they are complementary ways of knowing or lines of sight on target phenomena, each whole and important in its own right, but incomplete. We think about these multiple perspectives the same way that they are described in the parable of the six blind men and the elephant. In this story, each person makes contact with a different part of the elephant and comes to his own conclusions– the one who encounters its legs explains that elephants are tree trunks, the ears reveal it to be a fan, the flank a wall, the tail a rope, the trunk a snake, and the tusk a spear.

Each one’s understanding is correct, but unknown to all of them, each is also incomplete. They need the views from all of these perspectives, what we sometimes call 360 o lines of sight, to fully appreciate the elephant in its wholeness and complexity. In the same way, multiple cross-disciplinary, inter-disciplinary, and multi-disciplinary methodologies are needed to understand our developmental phenomena in their wholeness and complexity. We find a lifespan developmental systems perspective especially useful in articulating this view (Baltes, Reese, & Nesselroade, 1977; Cairns, Elder, & Costello, 2001; Lerner, 2006; Overton, 2010; Overton & Molenaar, 2015; Skinner, Kindermann, & Mashburn, 2019). The best research and graduate training programs in human development teach their doctoral students about a wide range of epistemologies and methodologies and see them all as parts of “ converging operations .”

What is meant by converging operations?

This was an idea, brought to the attention of developmentalists almost 50 years ago (Baer, 1973), to help deal with the unsettling realization that every method ever devised to conduct scientific studies has serious shortcomings. The main idea is that good science needs a wide variety of differing methodologies, so that the strengths of one can compensate for the limitations of others. From this perspective, a body of evidence is much stronger when findings from multiple complementary methodologies converge on the same conclusions. That is why we favor developmental science that incorporates methodologies from many disciplines, and continues to question and critique those methodologies as part of its reflective practice.

Deductive Methodologies

In discussions of scientific methods, the procedure that is often highlighted is the deductive method — in which a scientist starts with a falsifiable hypothesis and then conducts a series of observations to test whether the specifics on the ground are consistent with this hypothesis. In this process, the scientist foregrounds “thinking” (the theory) and follows this up with figuring out how to “look” (i.e., conduct the study or observation) in ways that test the validity of this theory. This process unfolds in multiple recursive or circular steps, including:

Review previous studies (known as a literature review) to determine what has been found to date
Identify the deficiencies or gaps in previous research
Formulate a working theory of the target phenomenon and propose a hypothesis
Who? Sampling . Determine the people to be included
What? Measurement . Determine the measures to be used to capture the phenomena of interest
Where? Setting . Determine the setting where the study will take place
How? and When? Design . Determine the study design
Consider the limitations of the study
Draw conclusions, including rejecting the hypothesis and revising the original theory
Suggest future studies
Share information with the scientific community
Invite scrutiny of work by other experts

Inductive Methodologies

A second set of procedures is more inductive . This process, often called grounded theory , starts with a general question and then constructs a theory of the phenomenon based, not on the scientific community’s or researcher’s preconceived notions, but on the researcher’s actual observations of many specific experiences on the ground. As you can see, in the process, the scientist foregrounds “looking” (the observations and experiences in the target setting) and uses this process to scaffold “thinking” (i.e., theorizing or building a mental model of what has been observed). This process also unfolds in multiple recursive or circular steps, including:

Review the literature to justify the importance of the problem
See how the problem fits into a larger set of issues
Identify the deficiencies or gaps in other work on the topic
Who? and Where? Gain entrance into a group and natural setting relevant to the problem of study
What? Ask open-ended, broad “grand tour” types of questions when interviewing and observing participants; focus on participant perspectives
How? Gather field notes about the setting, the people, the structure, the activities or other areas of interest; collect artifacts, pictures
Reflect . Modify research questions as the study evolves and follow the emergent questions
Note own participation and biases
Note patterns or consistencies, uncover themes, categories, interrelationships
Focus on centrality of meaning of the participants
Explore new areas deemed important by participants
Check back in with participants to get their perspectives on your interpretations

Collaborative Methodologies

A third set of methodologies is based on the assumption that knowledge, research, and effective social action can best be co-constructed among researchers and community participants, incorporating the strengths and perspectives of all the stakeholders involved in a particular set of issues. This approach, often called community-based participatory action research , holds that complex social issues cannot be well understood or resolved by “expert” research, pointing to interventions from outside of the community which often have disappointing results or unintended side effects. In collaborative approaches, researchers and community partners build a genuine trusting relationship, and this cooperative partnership is the basis on which all decisions about the project are made: from articulating a set of research questions, to identifying data collection strategies, analysis and interpretation of information, and dissemination and application of findings.

The process is inherently:

Community-based. Researchers build a collaborative partnership with community members who are already living with, involved in, or working on the problem of interest. Hence, this work is situated within neighborhoods and community organizations or groups, and builds on their strengths and priorities. Instead of taking individuals out of communities and into lab settings for study or providing individualized therapy to “fix” broken individuals, the goal of this work is to help facilitate change within the community itself, making it a more supportive context for all its inhabitants.
Participatory . As the collaboration develops, members discuss and learn more about each other so that together they can co-create and frame a common agenda for research and action. These projects incorporate researchers’ expertise and goals, but they foreground the knowledge, concerns, and needs of community partners. For example, researchers interested in homeless youth could reach out to youth-serving organizations and begin conversations exploring whether they would like to work together. These conversations would also soon involve the homeless youth themselves, consistent with the slogan popularized by the disability rights movement, “Nothing about us without us!” Community knowledge is considered irreplaceable as it provides key insights about target issues.
Action. All research activities are anchored and oriented by the larger goal of enhancing strategic action that leads to social change and community transformation as part of the research program. Community action make take the form of public education surrounding community issues (e.g., information campaigns, teach-ins), changing existing policies that harm groups of people (e.g., harsh discipline policies at school), creating new public spaces (e.g., community gardens and farmers’ markets), and so on.
Research. The community action plan is informed by organizing existing information and collecting new information from key stakeholders relevant to the community issues under scrutiny. Methods to conduct these studies are planned together in ways that researchers believe will produce high quality information and that collaborators believe will be useful to them in making progress on their agenda. All partners are also involved in the scrutiny, visualization, discussion, and interpretation of data, and make joint decisions about how it should be disseminated and used going forward. These efforts feed into next steps in both research and action.
Ongoing collaboration. Such university-community partnerships typically last for many years. Researchers are thoughtful about how to bring them successfully to a close, making sure that an ongoing goal of the collaboration is to build capacity within the community partnership so members can sustain collective action after the research team leaves.

A good way to become more familiar with these collaborative, inductive, and deductive research methods is to look at journal articles. You will see that they are written in sections that follow the steps in the scientific process. In general, the structure includes: (1) abstract (summary of the article), (2) introduction or literature review, (3) methods explaining how the study was conducted, (4) results of the study, (5) discussion and interpretation of findings, and (6) references (a list of studies cited in the article).

Methods of Gathering Information

“Methods” is also a name given to many different procedures scientists use to make their observations or collect information. Since developmentalists are interested in a wide range of human capacities, they want to know not only about people’s actions and thoughts, as expressed in words and deeds, but also about underlying processes, like abilities, emotions, desires, intentions, and motivations. Moreover, they want to go deeper, looking into biological and neurophysiological processes, and they want to consider many factors outside the person of study, looking at social relationships and interactions, as well as environmental materials, tasks, and affordances, and societal contexts. And, as lifespan researchers, they want to study these capacities at all ages, from the tiniest babies to the oldest grandmothers. No wonder developmental scientists need so many tools, and are inventing more all the time.

Every time you come across a conclusion in a textbook or research article (for example, when you read that “18-month-olds do not yet have a sense of self”), you should stop and ask, “How do you know that?” That is a great question. And a great scientific attitude. Over and over, we will want to scrutinize the evidence scientists are using to make their conclusions, considering carefully the extent to which the methods scientists use justify the conclusions they make. If a baby can’t yet talk, how would we know whether they have a sense of self? And even when a child can talk, what is the connection between what they are telling us and what they are truly thinking? You can be sure that these kinds of questions stoke lively debates in scientific circles.

As with methodologies more generally, science is strengthened by the use of a variety of approaches to collecting information. The shortcomings of one can be compensated for by the strengths of others. If we find that a new mother says that she is feeling stressed, and her best friend agrees, and we see elevated cortisol levels, and her survey results are higher than usual, and she becomes irritated when her two-year-old makes a mess– well, we think we have captured something meaningful here. We are always in favor of multiple sources of data, and we especially appreciate methods that get us thick, rich information, as close to lived experience in context as possible.

Here are some examples of methods commonly used in developmental research today:

Observations: Looking at People and their Actions

Often considered the basic building blocks of developmental science, observational methods are those in which the researcher carefully watches participants, noting what they are doing, saying, and expressing, both verbally and nonverbally. Researchers can observe participants doing just about anything, including working on tasks, playing with toys, reading the newspaper, or interacting with others. Observations are ideal for gathering information about people’s verbal and physical behavior, but it is less clear whether internal states, like emotions and intentions, can be unambiguously discerned through observation.

Naturalistic observations take place when researchers conduct observations in the regular settings of everyday life. This method allows researchers to get very close to the phenomenon as it actually unfolds, but researchers worry that their participation may impact participants’ behaviors (a problem called reactivity ). And, since researchers have little control over the environment, they realize that the different behaviors they observe may be due to differences in situational factors.
Laboratory observations , in contrast, take place in a specialized setting created by the researcher, that is, the lab. For example, researchers bring babies and their caregivers to the lab in a systematic procedure known as the strange situation, which you will learn about in the section on attachment. Observing in the lab allows researchers to set up a specific space and to have control over situational factors. However, researchers worry that the artificial nature of the situation may have an impact on people’s behavior, and that the behaviors people show in the lab are not typical of the ones they show in regular contexts of daily life (a problem called generalizability ).
Video or audio observations can be gathered using automatic recording devices that collect information even when a researcher is not present. For example, researchers ask caregivers to record family dinners or teachers to tape class sessions; or place a small recording device on a young child’s chest that records every word the child says or hears. These records can then be watched or listened to by researchers. Such procedures reduce reactivity, but the resultant recordings are narrower in scope than what researchers could hear or see if they were present observing in the actual context.
Local expert observers can provide researchers with information about the verbal and non-verbal behavior of participants they have observed or interacted with many times. For example, caregivers and teachers can report on their children and students, and even children can provide their perspectives. Reports from others typically incorporate many more observations than a researcher could collect (e.g., a teacher sees a child in class every week day), so the information is more representative of the target’s typical behavior. However, researchers worry that information could be distorted, for example, because reporters are biased or are not trained to observe or categorize the behaviors they have witnessed.
Participant observations, which are especially common in anthropology and sociology, take place when researchers gain entrance into a setting, not as an observer, but as a participant, with the aim of gaining a close and intimate familiarity with a given group of individuals or a particular community, and their behaviors, relationships, and practices. These observations are usually conducted over an extended period of time, sometimes months or years, which means that the observer can directly observe variations and changes in actions and interactions. Such observations provide rich and detailed information, but are limited to the specific setting.

Self-reports: Listening to People and their Thoughts

When researchers are studying people, one of the most common ways of gathering information about them is by asking them, via self-report methods. These can range from informal open-ended interviews or requests for participants to write responses to prompts, all the way to surveys, when participants can only choose among researcher-generated options. Self-report data are ideal for learning about people’s inner thoughts or opinions, but researchers worry that participants may distort the truth to present themselves in a favorable light (a problem called social desirability ). There is also debate about whether participants have access to some of their internal processes, like their genuine motivations.

Surveys gather information using standardized questionnaires, which can be administered either verbally or in writing. Surveys capture an enormous range of psychological and social processes, and their items can be tested for their reliability and validity (called psychometric properties ), but they typically yield only surface information. Researchers worry that participants may misinterpret questions and realize that the information so collected is restricted to exactly those pre-packaged questions and responses.
Standardized, structured, or semi-structured interviews involve researchers directly asking a series of predetermined questions. Because researchers are present, they can ask follow up questions and participants can ask for clarification. This allows researchers to learn more from participants than they could from standardized questionnaires, but researchers worry that their presence could cause reactivity , such as when participants want to provide more socially desirable responses in a face-to-face setting than on an anonymous survey.
Open-ended interviews typically use targeted questions or prompts to get the conversation flowing, and then follow the interview where ever it leads. This allows for more customized questioning and in-depth answers, as researchers probe responses for greater clarity and understanding. However, since each respondent participates in a different interview conversation, it can be difficult to compare responses from person to person.
Focus groups involve group open-ended interviews, in which a small number of people (6-10) discuss a series of questions or prompts in guided or open discussion with a trained facilitator. In this format, focus group members listen and can react to each other’s comments and build discussion at the group level.
Responses to prompts are used when researchers ask participants to write down their thoughts. These can range from relatively unstructured free writes to short answers to a series of well-structured questions. Daily diaries , often organized electronically, allow participants to respond to online questions or prompts many days in a row.

Psychological Tests and Assessments: Mental Capacities and Conditions

Most of us are familiar with tests that measure, for example, IQ or other mental abilities, and with diagnostic assessments that classify people according to psychological conditions. When you read about the aging of intelligence, for example, some of those studies utilize measures of crystalized and fluid intelligence. Tests to measure mental abilities have been created for people of all ages, although it is not always clear how the measures used at different ages are connected to each other.

Laboratory Tasks: Interactions that Elicit or Capture Psychological Processes

Researchers create and invent all manner of tasks for participants to work on, either in the lab or in real life settings (e.g., at home or school). These tasks allow researchers to set up activities that can assess a range of psychological attributes for people of all ages, ranging from problem-solving abilities to regulatory capacities (e.g., using the “ Heads, Shoulders, Knees, and Toes ” task), prosocial behaviors, learned helplessness, theories of mind, social information processing, rejection sensitivity, and so on. Many YouTube videos show children and adolescents participating in these tasks, and it is instructive to try to figure out exactly what is captured in each one. If you would like to see an example, you can watch a video of The Shopping Cart Study (not required, bonus information).

Psychophysiological Assessment: Underlying Neurophysiological Functioning

Researchers also use a range of methods to capture information about neurophysiological functioning across the lifespan, including technology that can measure heart rate, blood pressure, hormone levels, and many kinds of brain activity to help explain development. These assessments provide information about what is happening “under the skin,” and researchers can see how these biological processes are connected to behavioral development. Usually connections are bidirectional– neurophysiology contributes to the development of behavior, and behaviors shape physiological functioning and development.

Archival Data or Artifacts: Information from Business as Usual

Researchers sometimes utilize information that has already been collected as a regular part of daily life. Such data include, for example, students’ grades and achievement tests scores, documents or other media, drawings, work products, or other materials that might provide information about participants’ developmental progress or causal factors contributing to their development. These kinds of data have the advantage of low reactivity and high authenticity, in that they were created or gathered in the normal course of events, but it is sometimes unclear exactly what they mean or what constructs they measure.

Case Study: All of the Above with Carefully Selected Participants or Settings

One of the best ways to gather in depth information about a person or group of people (e.g., a classroom, school, or neighborhood) is through a research methodology called the case study . Researchers focus on only one or a small number of target units, usually carefully selected for specific characteristics (e.g., an individual identified as wise, a homeless teenager, a very effective school, or a workplace with high turnover rates), and amass everything they can about that person or place. Researchers typically conduct in-depth open-ended interviews with people, including friends or family of the target person, and collect archival data and artifacts, which they might discuss in depth with participants. For example, they might go through the person’s photo albums and discuss memories of their early life. Classical examples of case studies are the so-called baby diaries , in which researchers like Jean Piaget and William Stern conducted extensive observations on their individual children and took detailed notes about every aspect of their behavior and development. They also tested some of their hypotheses about development, by giving their babies toys to play with or engaging them in interesting tasks. These case studies were conducted over years. When case studies also extend into the past of the individual (for example, when researchers are interested in life review processes), they can be called biographical methods .

Sometimes researchers who focus on a group of individuals or a setting are particularly interested in the cultural context and its functioning. These studies can be called ethnographies . Drawn originally from anthropology, ethnographic methods describe an approach in which researchers carefully study and document people and their cultural settings, usually through extensive participant-observation, interviews, and engagement in the setting. In these studies, as in all scientific investigations, researchers are the students and the people in the setting are the teachers. Researchers strive to create a wholistic, higher-order narrative account that privileges the perspectives of the people studied.

Take Home Messages about Lifespan Developmental Methodologies

We would highlight four main themes from this section:

Because interventionists and practitioners use bodies of scientific evidence to transform systems and change practices in the world, it is crucial that researchers produce the highest quality evidence possible , and evaluate and critique it thoughtfully.
Developmental science incorporates multiple methodologies from many disciplines, and these deductive, inductive, and collaborative methodologies make our conclusions stronger because they provide complementary lines of sight on our target phenomena.
Science is also strengthened by the use of a variety of approaches (or methods) for collecting information , including observations, self-reports, and other strategies, because together they provide a richer picture of our target developing phenomena.
The advantages of using multiple methodologies and sources of information are highlighted by the idea of “ converging operations, ” which points out that this practice allows the shortcomings of one method to be compensated for by the strengths of others, and reminds us that bodies of evidence are stronger when findings from multiple complementary methodologies and sources of information converge on the same conclusions.

Baer, D. M. (1973). The control of developmental process: Why wait? In J. R. Nesselroade & H. W. Reese (Eds.), Lifespan developmental psychology: Methodological issues (pp. 187-193). New York: Academic Press.

Baltes, P. B., Reese, H. W., & Nesselroade, J. R. (1977). Life-span developmental psychology: Introduction to research methods . Oxford, England: Brooks/Cole.

Cairns, R. B., Elder, G. H., & Costello, E. J. (Eds.). (2001). Developmental science . New York: Cambridge University Press.

Lerner, R. M. (2006). Developmental science, developmental systems, and contemporary theories of human development. In R. M. Lerner (Vol. Ed.) and R. M. Lerner & W. E. Damon (Eds-in-Chief.). Handbook of child psychology: Vol 1, Theoretical models of human development (pp. 1-17). John Wiley & Sons Inc.

Overton, W. F. (2010). Life‐span development: Concepts and issues. In W. F. Overton (Vol. Ed.) R.M. Lerner (Ed.-in-Chief), The handbook of life-span development: Vol. 1. Cognition, biology, and methods (pp. 1-29). Hoboken, NJ: Wiley.

Overton, W. F., & Molenaar, P. (2015). Handbook of child psychology and developmental science (R. M. Lerner, Ed.-in-Chief) : Vol 1, Theory and method . John Wiley & Sons Inc.

Skinner, E. A., Kindermann, & Mashburn, A. J. (2019). Lifespan developmental systems: Meta-theory, methodology, and the study of applied problems. An Advanced Textbook . New York, NY: Routledge.

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3.2 Research Methods

Learning objectives.

Describe methods for collecting research data (including observation, survey, case study, content analysis, and secondary content analysis)

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 on how or what kind of data was collected.

Types of Descriptive Research

Observation.

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

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

Case Studies

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

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.

Of course, surveys can be designed in a number of ways. They may include forced-choice questions and semi-structured questions in which the researcher allows the respondent to describe or give details about certain events. One of the most difficult aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather than choosing “undecided” each time. Knowing that 30% of respondents are undecided is of little use! So a lot of time and effort should be placed on the construction of survey items. One of the benefits of having forced-choice items is that each response is coded so that the results can be quickly entered and analyzed using statistical software. The analysis takes much longer when respondents give lengthy responses that must be analyzed in a different way. 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.

In this video, Harvard psychologist Dan Gilbert explains survey research that was conducted to explore the way our preferences change over time.

You can view the transcript for “The psychology of your future self | Dan Gilbert” here (opens in new window) .

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.

Link to Learning: Data on Human Development

U.S. Census Data is available and widely used to look at trends and changes taking place in the United States (visit the United States Census website and check it out). There are also a number of other agencies that collect data on family life, sexuality, and on many other areas of interest in human development (go to the NORC at the University of Chicago website or the Henry J Kaiser Family Foundation website and see what you find.).

Psyc 200 Lifespan Psychology. Authored by : Laura Overstreet. Located at : http://opencourselibrary.org/econ-201/ . License : CC BY: Attribution
magnifying glass. Authored by : nachar. Located at : https://pixabay.com/en/magnifying-glass-magnifier-glass-189254/ . License : CC0: No Rights Reserved
Survey. Authored by : Andreas Breitling. Located at : https://pixabay.com/images/id-1594962/ . License : CC0: No Rights Reserved
The psychology of your future self | Dan Gilbert. Provided by : TED. Located at : https://www.youtube.com/watch?v=XNbaR54Gpj4 . License : Other . License Terms : Standard YouTube License

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Human Development Research Resources: Introduction

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Human Development studies how humans learn and develop, from birth through old age and in many specific contexts. Researchers might look at how children are affected when their parents are incarcerated or how close friendships change as we grow older. The field mixes principles of psychology, sociology, and health to study and improve people's daily life experiences.

Writing in Human Development

Scholars and professionals in human development write in a variety of genres. Scholars may write literature reviews, journal articles, book reviews, and books. All of this writing will be based on and incorporate scholarly literature and human development theory. Professionals working in human services will often need to write content related to their jobs, such as client reports, reports for an organization, client histories, and grant applications.

As a student in human development, you'll be asked to read and to write in a range of these genres.

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Last Updated: Apr 20, 2020 2:10 PM

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.

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

Types of Descriptive Research

Observation.

Case Studies

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.

Sequential research designs

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

Challenges Conducting Developmental Research

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

Ethical Concerns

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

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

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

Recruitment

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

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

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

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.

Conclusions

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

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

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1.8: Research in Lifespan Development

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Learning Outcomes

Explain how the scientific method is used in researching development
Compare various types and objectives of developmental research

How do we know what we know?

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. Read the following sentence aloud:

Paris in the the spring

Are you sure that is what it said? Read it again:

If you read it differently the second time (adding the second “the”) you just experienced one of the problems with relying on personal inquiry; that is, the tendency to see what we believe. 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.

Scientific Methods

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)

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.

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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 children?”
“How many times per week do couples have intercourse?”
“When is marital satisfaction greatest?”

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

This Crash Course video provides a brief overview of psychological research, which we’ll cover in more detail on the coming pages.

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You can view the transcript for “Psychological Research: Crash Course Psychology #2” here (opens in new window) .

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[glossary-page] [glossary-term]correlational research:[/glossary-term] [glossary-definition]research that formally tests whether a relationship exists between two or more variables, however, correlation does not imply causation[/glossary-definition]

[glossary-term]descriptive studies:[/glossary-term] [glossary-definition]research focused on describing an occurrence[/glossary-definition]

[glossary-term]evaluation research:[/glossary-term] [glossary-definition]research designed to assess the effectiveness of policies or programs[/glossary-definition]

[glossary-term]experimental research:[/glossary-term] [glossary-definition]research that involves randomly assigning people to different conditions and using hypothesis testing to make inferences about how these conditions affect behavior; the only method that measures cause and effect between variables[/glossary-definition]

[glossary-term]explanatory studies:[/glossary-term] [glossary-definition]research that tries to answer the question “why”[/glossary-definition]

[glossary-term]qualitative research:[/glossary-term] [glossary-definition]theoretical ideas are “grounded” in the experiences of the participants, who answer open-ended questions[/glossary-definition]

[glossary-term]quantitative research:[/glossary-term] [glossary-definition]involves numerical data that are quantified using statistics to understand and report what has been studied[/glossary-definition] [/glossary-page]

Contributors and Attributions

Psyc 200 Lifespan Psychology. Authored by : Laura Overstreet. Located at : http://opencourselibrary.org/econ-201/ . License : CC BY: Attribution
question mark. Authored by : Alexas_Fotos. Located at : https://pixabay.com/en/question-mark-tissue-structure-1098294/ . License : CC0: No Rights Reserved
Descriptive Research. Provided by : Lumen Learning. Located at : https://courses.lumenlearning.com/waymaker-psychology/chapter/reading-clinical-or-case-studies/ . License : CC BY: Attribution
Psychological Research: Crash Course Psychology #2. Provided by : CrashCourse. Located at : https://www.youtube.com/watch?v=hFV71QPvX2I . License : Other . License Terms : Standard YouTube License

1.8: Research Methods

An important part of learning any science, including psychology, 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. Science involves continuously renewing our understanding of the subjects in question and an ongoing investigation of how and why events occur. The scientific method is the set of assumptions, rules, and procedures scientists use to conduct research .

Descriptive Research

Case Study: Sometimes the data in a descriptive research project are based on only a small set of individuals, often only one person or a single small group. These research designs are known as case studies which are descriptive records of one or a small group of individuals ’ experiences and behavior . Sometimes case studies involve ordinary individuals. Developmental psychologist Jean Piaget observed his own children. More frequently, case studies are conducted on individuals who have unusual or abnormal experiences. The assumption is that by carefully studying these individuals, we can learn something about human nature. Case studies have a distinct disadvantage in that, although it allows us to get an idea of what is currently happening, it is usually limited to static pictures. Although descriptions of particular experiences may be interesting, they are not always transferable to other individuals in similar situations. They are also time consuming and expensive as many professionals are involved in gathering the information.

Observations: Another type of descriptive research is known as observation. When using naturalistic observation , psychologists observe and record behavior that occurs in everyday settings . For instance, a developmental psychologist might watch children on a playground and describe what they say to each other. However, naturalistic observations do not allow the researcher to have any control over the environment.

Laboratory observation, unlike the naturalistic observation, is conducted in a setting created by the researcher . This permits the researcher to control more aspects of the situation. One example of laboratory observation involves a systematic procedure known as the strange situation test, which you will learn about in chapter three. Concerns regarding laboratory observations are that the participants are aware that they are being watched, and there is no guarantee that the behavior demonstrated in the laboratory will generalize to the real world.

Survey: In other cases the data from descriptive research projects come in the form of a survey , which is a measure administered through either a verbal or written questionnaire to get a picture of the beliefs or behaviors of a sample of people of interest . The people chosen to participate in the research, known as the sample , are selected to be representative of all the people that the researcher wishes to know about called the population . A representative sample would include the same percentages of males, females, age groups, ethnic groups, and socio-economic groups as the larger population.

Surveys gather information from many individuals in a short period of time, which is the greatest benefit for surveys. Additionally, surveys are inexpensive to administer. However, surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior. Another problem is that respondents may lie because they want to present themselves in the most favorable light, known as social desirability . They also may be embarrassed to answer truthfully or are worried that their results will not be kept confidential. Additionally, questions can be perceived differently than intended.

Interviews: Rather than surveying participants, they can be interviewed which means they are directly questioned by a researcher. Interviewing participants on their behaviors or beliefs can solve the problem of misinterpreting the questions posed on surveys. The examiner can explain the questions and further probe responses for greater clarity and understanding. Although this can yield more accurate results, interviews take longer and are more expensive to administer than surveys. Participants can also demonstrate social desirability, which will affect the accuracy of the responses.

Psychophysiological Assessment: Researchers may also record psychophysiological data, such as measures of heart rate, hormone levels, or brain activity to help explain development. These measures may be recorded by themselves or in combination with behavioral data to better understand the bidirectional relations between biology and behavior. Special equipment has been developed to allow researchers to record the brain activity of very young and very small research subjects. One manner of understanding associations between brain development and behavioral advances is through the recording of event-related potentials (ERPs). ERPs are recorded by fitting a research participant with a stretchy cap that contains many small sensors or electrodes. These electrodes record tiny electrical currents on the scalp of the participant in response to the presentation of stimuli, such as a picture or a sound.

The use of ERPs has provided important insight as to how infants and children understand the world around them. Webb, Dawson, Bernier, and Panagiotides (2006) examined face and object processing in children with autism spectrum disorders, those with developmental delays, and those who were typically developing. The children wore electrode caps and had their brain activity recorded as they watched still photographs of faces of their mother or of a stranger, and objects, including those that were familiar or unfamiliar to them. The researchers examined differences in face and object processing by group by observing a component of the brainwaves. Findings suggest that children with autism are in some way processing faces differently than typically developing children and those with more general developmental delays.

Secondary/Content Analysis 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. For example, the U. S. Census Data is available and widely used to look at trends and changes taking place in the United States. 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.

Conditional Research

In contrast to descriptive research, which is designed primarily to provide static pictures, correlational research involves the measurement of two or more relevant variables and an assessment of the relationship between or among those variables. For instance, the variables of height and weight are systematically related (correlated) because taller people generally weigh more than shorter people.

The Pearson Correlation Coefficient , symbolized by the letter r, is the most common statistical measure of the strength of linear relationships among variables . The value of the correlation coefficient ranges from r = –1.00 to r = +1.00. The strength of the linear relationship is indexed by the distance of the correlation coefficient from zero (its absolute value). For instance, r = –.54 is a stronger relationship than r = .30, and r = .72 is a stronger relationship than r = –.57. The direction of the linear relationship is indicated by the sign of the correlation coefficient. Positive values of r (such as r = .54 or r = .67) indicate that the relationship is positive (i.e., the pattern of the dots on the scatter plot runs from the lower left to the upper right), whereas negative values of r (such as r = –.30 or r = –.72) indicate negative relationships (i.e., the dots run from the upper left to the lower right).

When the straight line indicates that individuals who have high values for one variable also tend to have high values for the other variable , as in part (a), the relationship is said to be positive correlation . Examples of positive correlations include those between education and income, and between age and mathematical abilities in children. In each case people who score higher on one of the variables also tend to score higher on the other variable. Negative correlations , in contrast, as shown in part (b), occur when high values for one variable tend to be associated with low values for the other varia ble. Examples of negative correlations include those between the age of a child and the number of diapers the child uses, and between practice and errors made on a learning task. In these cases people who score higher on one of the variables tend to score lower on the other variable.

An important limitation of correlational research designs is that they cannot be used to draw conclusions about the causal relationships among the measured variables. Consider, for instance, a researcher who has hypothesized that viewing violent behavior will cause increased aggressive play in children. He has collected, from a sample of fourth-grade children, a measure of how much violent television each child views during the week, as well as a measure of how aggressively each child plays. The researcher discovers a positive correlation between the two measured variables. Although this positive correlation appears to support the hypothesis, it cannot be taken to indicate that viewing violent television causes aggressive behavior as there are other possible explanations. One alternative is that children who behaved aggressively at school want to watch violent television shows. Still another possible explanation for the observed correlation is that it has been produced by the presence of a third variable .

A third variable is a variable that is not part of the research hypothesis but produces the observed correlation between them . In our example a potential third variable is the discipline style of the children’s parents. Parents who use a harsh and punitive discipline style may produce children who both like to watch violent television and who behave aggressively in comparison to children whose parents use less harsh discipline.

For this reason, we are left with the basic limitation of correlational research: Correlation does not demonstrate causation ! It is important that when you read about correlational research projects, you keep in mind the possibility of third variables.

Strengths and limitations: Correlational research can be used when experimental research is not possible because the variables cannot be manipulated or it would be unethical to use an experiment. Correlational designs also have the advantage of allowing the researcher to study behavior as it occurs in everyday life. We can also use correlational designs to make predictions. For instance, we can predict from the scores on a battery of tests the success of job trainees during a training session. However, we cannot use such correlational information to determine whether one variable caused another variable. For that, researchers rely on an experiment.

Experimental Research

The goal of the experimental method is to provide more definitive conclusions about the causal relationships among the variables in a research hypothesis than what is available from correlational research. Experiments are designed to test hypotheses , or specific statements about the relationship between variables . Experiments are conducted in a controlled setting in an effort to explain how certain factors or events produce outcomes. A variable is anything that changes in value . In the experimental research design, the variables of interest are called the independent variable and the dependent variable. The independent variable in an experiment is the causing variable that is created or manipulated by the experimenter . The dependent variable in an experiment is a measured variable that is expected to be influenced by the experimental manipulation.

A good experiment randomly assigns participants to at least two groups that are compared. The experimental group receives the treatment under investigation, while the control group does not receive the treatment the experimenter is studying as a comparison. For instance, to assess whether violent TV affects aggressive behavior the experimental group might view a violent television show, while the control group watches a non-violent show. Additionally, experimental designs control for extraneous variables , or variables that are not part of the experiment that could inadvertently effect either the experimental or control group, thus distorting the results.

Despite the advantage of determining causation, experiments do have limitations. One is that they are often conducted in laboratory situations rather than in the everyday lives of people. Therefore, we do not know whether results that we find in a laboratory setting will necessarily hold up in everyday life. Second, and more important, is that some of the most interesting and key social variables cannot be experimentally manipulated because of ethical concerns. If we want to study the influence of abuse on children’s development of depression, these relationships must be assessed using correlational designs because it is simply not ethical to experimentally manipulate these variables. Characteristics of descriptive, correlational, and experimental research designs can be found in Table 1.5.

Lifespan Development - A Psychological Perspective by Martha Lally and Suzanne Valentine-French is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Methods of Research on Human Development and Families

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Shannon N. Davis - George Mason University Korea, George Mason University
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Research Methods in Developmental Psychology

University of Calfornia, Irvine

What do infants know about the world in which they live – and how do they grow and change with age? These are the kinds of questions answered by developmental scientists. This module describes different research techniques that are used to study psychological phenomena in infants and children, research designs that are used to examine age-related changes in development, and unique challenges and special issues associated with conducting research with infants and children. Child development is a fascinating field of study, and many interesting questions remain to be examined by future generations of developmental scientists – maybe you will be among them!

Child development
Developmental psychology
Infant development
Research designs
Research methods
Learning Objectives
Describe different research methods used to study infant and child development
Discuss different research designs, as well as their strengths and limitations
Report on the unique challenges associated with conducting developmental research

Introduction

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

A young girl smiles as she peeks out from a hiding place.

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

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

Research Methods

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

Involuntary or obligatory responses

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

An infant lies on its back with its eyes fixed on a nearby object.

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

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

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

Voluntary responses

A woman inspects tomatoes as she puts them into a shopping bag.

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

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

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

The two-step event sequence Find the Surprise. The picture on the left shows all of the toys needed to complete the event. The picture in the middle shows a hand flipping the latch out of the way so the door can be opened (step 1). The picture on the right shows a hand opening the door, ultimately revealing a plastic figurine hidden inside (step 2).

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

Psychophysiology

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

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

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

Parent-report questionnaires

A mother and infant lie together on the grass.

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

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

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

Interview techniques

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

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

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

Research Design

Now you know about some tools used to conduct research with infants and young children. Remember, research methods are the tools that are used to collect information. But it is easy to confuse research methods and research design . Research design is the strategy or blueprint for deciding how to collect and analyze information. Research design dictates which methods are used and how.

Researchers typically focus on two distinct types of comparisons when conducting research with infants and children. The first kind of comparison examines change within individuals . As the name suggests, this type of analysis measures the ways in which a specific person changes (or remains the same) over time. For example, a developmental scientist might be interested in studying the same group of infants at 12 months, 18 months, and 24 months to examine how vocabulary and grammar change over time. This kind of question would be best answered using a longitudinal research design. Another sort of comparison focuses on changes between groups . In this type of analysis, researchers study average changes in behavior between groups of different ages. Returning to the language example, a scientist might study the vocabulary and grammar used by 12-month-olds, 18-month-olds, and 24-month-olds to examine how language abilities change with age. This kind of question would be best answered using a cross-sectional research design.

Longitudinal research designs

Longitudinal research designs are used to examine behavior in the same infants and children over time. For example, when considering our example of hide-and-seek behaviors in preschoolers, a researcher might conduct a longitudinal study to examine whether 2-year-olds develop into better hiders over time. To this end, a researcher might observe a group of 2-year-old children playing hide-and-seek with plans to observe them again when they are 4 years old – and again when they are 6 years old. This study is longitudinal in nature because the researcher plans to study the same children as they age. Based on her data, the researcher might conclude that 2-year-olds develop more mature hiding abilities with age. Remember, researchers examine games such as hide-and-seek not because they are interested in the games themselves, but because they offer clues to how children think, feel and behave at various ages.

Chart of a longitudinal research design. Child "A" is first observed in 2004 at the age of two. Child "A' is next observed in 2006 at age four. The next observation is in 2008 when Child "A" is six. Finally, in 2010 at the age of eight Child "A" is observed again.

Longitudinal studies may be conducted over the short term (over a span of months, as in Wiebe, Lukowski, & Bauer, 2010 ) or over much longer durations (years or decades, as in Lukowski et al., 2010) . For these reasons, longitudinal research designs are optimal for studying stability and change over time. Longitudinal research also has limitations, however. For one, longitudinal studies are expensive: they require that researchers maintain continued contact with participants over time, and they necessitate that scientists have funding to conduct their work over extended durations (from infancy to when participants were 19 years old in Lukowski et al., 2010 ). An additional risk is attrition . Attrition occurs when participants fail to complete all portions of a study. Participants may move, change their phone numbers, or simply become disinterested in participating over time. Researchers should account for the possibility of attrition by enrolling a larger sample into their study initially, as some participants will likely drop out over time.

The results from longitudinal studies may also be impacted by repeated assessments. Consider how well you would do on a math test if you were given the exact same exam every day for a week. Your performance would likely improve over time not necessarily because you developed better math abilities, but because you were continuously practicing the same math problems. This phenomenon is known as a practice effect . Practice effects occur when participants become better at a task over time because they have done it again and again; not due to natural psychological development. A final limitation of longitudinal research is that the results may be impacted by cohort effects . Cohort effects occur when the results of the study are affected by the particular point in historical time during which participants are tested. As an example, think about how peer relationships in childhood have likely changed since February 2004 – the month and year Facebook was founded. Cohort effects can be problematic in longitudinal research because only one group of participants are tested at one point in time – different findings might be expected if participants of the same ages were tested at different points in historical time.

Cross-sectional designs

Cross-sectional research designs are used to examine behavior in participants of different ages who are tested at the same point in time. When considering our example of hide-and-seek behaviors in children, for example, a researcher might want to examine whether older children more often hide in novel locations (those in which another child in the same game has never hidden before) when compared to younger children. In this case, the researcher might observe 2-, 4-, and 6-year-old children as they play the game (the various age groups represent the “cross sections”). This research is cross-sectional in nature because the researcher plans to examine the behavior of children of different ages within the same study at the same time. Based on her data, the researcher might conclude that 2-year-olds more commonly hide in previously-searched locations relative to 6-year-olds.

A chart shows an example of a cross-sectional design. The year is 2004 and three separate cohorts are included in a study. Participants in Cohort

Cross-sectional designs are useful for many reasons. Because participants of different ages are tested at the same point in time, data collection can proceed at a rapid pace. In addition, because participants are only tested at one point in time, practice effects are not an issue – children do not have the opportunity to become better at the task over time. Cross-sectional designs are also more cost-effective than longitudinal research designs because there is no need to maintain contact with and follow-up on participants over time.

One of the primary limitations of cross-sectional research, however, is that the results yield information on age-related change, not development per se . That is, although the study described above can show that 6-year-olds are more advanced in their hiding behavior than 2-year-olds, the data used to come up with this conclusion were collected from different children. It could be, for instance, that this specific sample of 6-year-olds just happened to be particularly clever at hide-and-seek. As such, the researcher cannot conclude that 2-year-olds develop into better hiders with age; she can only state that 6-year-olds, on average, are more sophisticated hiders relative to children 4 years younger.

Sequential research designs

Consider, once again, our example of hide-and-seek behaviors. In a study with a sequential design, a researcher might enroll three separate groups of children (Groups A, B, and C). Children in Group A would be enrolled when they are 2 years old and would be tested again when they are 4 and 6 years old (similar in design to the longitudinal study described previously). Children in Group B would be enrolled when they are 4 years old and would be tested again when they are 6 and 8 years old. Finally, children in Group C would be enrolled when they are 6 years old and would be tested again when they are 8 and 10 years old.

A chart of a sequential design: The study begins in 2002 with Cohort

Studies with sequential designs are powerful because they allow for both longitudinal and cross-sectional comparisons. This research design also allows for the examination of cohort effects. For example, the researcher could examine the hide-and-seek behavior of 6-year-olds in Groups A, B, and C to determine whether performance differed by group when participants were the same age. If performance differences were found, there would be evidence for a cohort effect. In the hide-and-seek example, this might mean that children from different time periods varied in the amount they giggled or how patient they are when waiting to be found. Sequential designs are also appealing because they allow researchers to learn a lot about development in a relatively short amount of time. In the previous example, a four-year research study would provide information about 8 years of developmental time by enrolling children ranging in age from two to ten years old.

Because they include elements of longitudinal and cross-sectional designs, sequential research has many of the same strengths and limitations as these other approaches. For example, sequential work may require less time and effort than longitudinal research, but more time and effort than cross-sectional research. Although practice effects may be an issue if participants are asked to complete the same tasks or assessments over time, attrition may be less problematic than what is commonly experienced in longitudinal research since participants may not have to remain involved in the study for such a long period of time.

When considering the best research design to use in their research, scientists think about their main research question and the best way to come up with an answer. A table of advantages and disadvantages for each of the described research designs is provided here to help you as you consider what sorts of studies would be best conducted using each of these different approaches.

Advantages and disadvantages of different research designs are summarized from the text

Challenges Associated with Conducting Developmental Research

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

Ethical concerns

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

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

Recruitment

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

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

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

Conclusions

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

Outside Resources

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

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Published: 14 May 2024

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Qingxi Long ORCID: orcid.org/0000-0002-0795-403X 1 ,
Pingshu Zhang 1 , 2 ,
Ya Ou 1 , 2 ,
Qi Yan 1 &
Xiaodong Yuan ORCID: orcid.org/0000-0002-2612-2781 1 , 2

Mesenchymal stem/stromal cells (MSCs), originating from the mesoderm, represent a multifunctional stem cell population capable of differentiating into diverse cell types and exhibiting a wide range of biological functions. Despite more than half a century of research, MSCs continue to be among the most extensively studied cell types in clinical research projects globally. However, their significant heterogeneity and phenotypic instability have significantly hindered their exploration and application. Single-cell sequencing technology emerges as a powerful tool to address these challenges, offering precise dissection of complex cellular samples. It uncovers the genetic structure and gene expression status of individual contained cells on a massive scale and reveals the heterogeneity among these cells. It links the molecular characteristics of MSCs with their clinical applications, contributing to the advancement of regenerative medicine. With the development and cost reduction of single-cell analysis techniques, sequencing technology is now widely applied in fundamental research and clinical trials. This study aimed to review the application of single-cell sequencing in MSC research and assess its prospects.

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This study was supported by grants from Performance-Based Subsidy for the Key Laboratory of Neurobiological Functioning in Hebei Province (20567622H), Medical Science Research Program of Hebei Province (20210526), and Hebei Province Medical Technology Monitoring Program (GZ2023049).

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Last year, Richard Welsh reported findings on the persistence of racial disparities in exclusionary school discipline practices. Despite suspensions declining over the past decade as schools reformed their policies, exclusionary disciplinary rates remained higher for African American students. Across the South, in-school suspensions (ISS) are particularly prevalent and disruptive to the education of racially minoritized students. Given these facts, Welsh has embarked on a new co-design process of ISS that leverages an existing research-practice partnership with a school district in Georgia to crack the code on truly resolving racial inequities in school discipline policies and practices.

Supported by a $474,178 grant from the William T. Grant Foundation and a $125,000 grant from the American Institutes of Research Equity Initiative, Welsh is leading a three-year project with the school district to understand the role of race and power in equity-centered research-practice partnerships, how the dynamics of the partnership affect partnership activities, and how these activities influence research use by school administrators, district leaders, and school board members.

“These are the three key decisionmakers who can advance racial equity in school districts through policies, programs, and personnel. They make decisions about codes of conduct, which disciplinary programs to implement, and who to hire, including behavioral specialists to support students’ social-emotional development,” said Welsh, associate professor of education and public policy at Vanderbilt Peabody College of education and human development.

“Improving the use of research evidence among education leaders via equity-centered research-practice partnerships can possibly lead to disruptive decisions necessary to addressing persistent racial inequities in school discipline. Also, turning the analytical lens on ourselves to examine how inequities might manifest in the partnership has implications for partnership and student outcomes,” Welsh added.

The research team will analyze their interviews with key decision makers, research-practice partnership primary investigators, and co-design team members. They will also observe school board meetings, school discipline committee meetings, and partnership meetings, as well as co-design workshops, district- and school-level documents, and materials to record the partnering process as well as the use of research evidence and disruptive decision-making. By engaging in cycles of disciplined inquiry to improve ISS processes, the partnership aims to reach its goal of improving youth outcomes.

The co-design process includes working with a team of school leaders and school personnel at three middle schools to analyze and reimagine their ISS process and infrastructure.

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Monographs of the Society for Research in Child Development
I. Place-Based Developmental Research: Conceptual, Methodological, and Empirical Advances in the Study of Development in Context. Developmental scientists have, for some time, recognized that development unfolds in numerous settings, such as schools, extracurricular activities, hang-outs (i.e., places individuals may engage for recreation and pleasure, often unstructured environments), and ...
Handbook of Research Methods in Developmental Science
Reviews. "As the title suggests, this is a wide-ranging handbook for students and researchers covering five key areas: developmental research designs, issues around development measurement, data analysis, methods in developmental psychology and new directions in devlopmental research. A state of the art treatment."
3.2 Research Methods
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 ...
Human Development Research Resources: Introduction
Human Development studies how humans learn and develop, from birth through old age and in many specific contexts. Researchers might look at how children are affected when their parents are incarcerated or how close friendships change as we grow older. The field mixes principles of psychology, sociology, and health to study and improve people's ...
PDF INTRODUCTION: WHY DEVELOPMENT RESEARCH MATTERS
We take a definition of human development compatible with the following, that 'human development aims to expand people's ... Research methods are also used in programme monitoring, evaluation and review. What we call research can range ... x In a multi-country World Health Organization study, between 20 and 65 per cent of school- ...
Research in Developmental Psychology
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.
1.8: Research in Lifespan Development
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.
Handbook of Research Methods in Developmental Science
The Handbook of Research Methods in Developmental Science is a collection of newly written articles that provide an overview of methods and approaches associated with the study of human development. Contains accessible contributions from some of the most renowned developmental scientists in the field. Provides basic information on the strengths and challenges inherent in traditional and ...
1.8: Research Methods
The scientific method is the set of assumptions, rules, and procedures scientists use to conduct research. A research design is the specific method a researcher uses to collect, analyze, and interpret data. Psychologists use three major types of research designs in their research, and each provides an essential avenue for scientific ...
Research methods in human development, 2nd ed.
Abstract. Our goal in revising this book was to produce an undergraduate level textbook that introduces students to basic research techniques in methodology. The book is intended to teach students to evaluate research critically, assessing strengths and weaknesses of various research paradigms. In addition, the textbook provides a framework for ...
Research Methods in Human Development
• Optional: A Concise Introduction to Mixed Methods Research, by John W. Creswell (ISBN: 978-1-4833-5904-5) Course Description. This course addresses the scientific concepts and principles central to the study of human development and learning. Students will learn about basic research methods for studying human
Studying social change, culture, and human development: A theoretical
Introduction. In a time of massive social change around the world, a major goal of the present article is to provide methods for studying social change, culture, and human development and an interdisciplinary theory that can serve as a framework for this research (Greenfield, 2009, Greenfield, 2016).Cultural change has drawn considerable attention from important researchers in social ...
Research in Human Development Aims & Scope
Editorial Scope. Research in Human Development ( RHD) promotes conceptual, empirical, and methodological integrative and interdisciplinary approaches to the study of human development across the entire life span. The journal emphasizes theory and research concerning person-context relationships across the life course, and the employment of a variety of quantitative and qualitative methods (e.g ...
Methods of Research on Human Development and Families
Preview. Methods of Research on Human Development and Families is an introduction to quantitative and qualitative research methods that teaches students how to be intelligent and critical consumers of research on families. This new book has been adapted from the author team's previous SAGE text, Methods of Family Research, and includes ...
Research Methods in Developmental Psychology
Child development is a fascinating field of study - but care must be taken to ensure that researchers use appropriate methods to examine infant and child behavior, use the correct experimental design to answer their questions, and be aware of the special challenges that are part-and-parcel of developmental research.
Single-cell sequencing advances in research on mesenchymal ...
Mesenchymal stem/stromal cells (MSCs), originating from the mesoderm, represent a multifunctional stem cell population capable of differentiating into diverse cell types and exhibiting a wide range of biological functions. Despite more than half a century of research, MSCs continue to be among the most extensively studied cell types in clinical research projects globally. However, their ...
Impacts of Anthropogenic Land Cover Changes on Wildlife Bioenergetics
The spatial expansion of human development can block or slow the movement of wildlife. ... In our study of mule deer, we show that oil and gas development can increase the energy requirements of a deer by 7%, regardless of terrain, and that the arrangement of gas pads and access roads has a significant impact on how costly a landscape is to ...
Research Snapshot: Brand Extensions and Esports
The study's results, ... Glynn McGehee (Ph.D. '19) CEHD alum Glynn McGehee earned his Ph.D. from the College of Education & Human Development in 2019. His research expertise includes brand communication, sport and public policy, and esports. He currently works in operations for Play On! Sports, a high school sports media and technology company.
1.3 Science of Development
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.
Research and Application of the Simulation Method for Product ...
Product development is a complex process involving intricate components, dynamics and constantly evolving internal and external environments, as well as numerous influencing factors. In order to accurately simulate and predict the effectiveness of the development process, this paper proposes a system dynamics simulation method based on information maturity. Different types of development ...
Welsh leads equity-centered research practice partnership to reduce
Supported by a $474,178 grant from the William T. Grant Foundation and a $125,000 grant from the American Institutes of Research Equity Initiative, Welsh is leading a three-year project with the ...

Developmental Psychology Research Methods

Cross-Sectional Research Methods

At a Glance

Challenges of Longitudinal Research

Limitations of Correlational Research

Challenges in Experimental Resarch

What This Means For You

Lifespan Developmental Research Methodologies

Methods of Gathering Information

Media Attributions

3.2 Research Methods

Types of Descriptive Research

Case Studies

Content Analysis

Link to Learning: Data on Human Development

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Human Development Research Resources: Introduction

Writing in Human Development

Research in Developmental Psychology

Learning outcomes

Research in Lifespan Development

Personal Knowledge

Scientific Methods

Link to Learning

Research Methods and Objectives

Research Methods

Types of Descriptive Research

Case Studies

Content Analysis

Correlational and Experimental Research

Understanding Correlation

Experimental Research

Developmental Research Designs

Cross-sectional designs

Longitudinal research designs

Sequential research designs

Ethical Concerns

Recruitment

Conclusions

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Margin Size

1.8: Research in Lifespan Development

How do we know what we know?

Personal Knowledge

Scientific Methods

Research Methods and Objectives

Contributors and Attributions

1.8: Research Methods

Descriptive Research

Conditional Research

Experimental Research

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Methods of Research on Human Development and Families

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Research Methods in Developmental Psychology

Introduction

Research Methods

Involuntary or obligatory responses

Voluntary responses

Psychophysiology

Parent-report questionnaires

Interview techniques

Research Design

Longitudinal research designs

Cross-sectional designs

Sequential research designs

Challenges Associated with Conducting Developmental Research

Ethical concerns

Recruitment

Conclusions

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Single-cell sequencing advances in research on mesenchymal stem/stromal cells

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