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Case Study Method in Psychology Advantages and Disadvantages

Case Study Method in Psychology Advantages and Disadvantages.

The case study method is a research technique used in psychology and other social sciences to study an individual or a group of individuals in great detail. The advantages and disadvantages of the case study method are discussed below:

Advantages of Case Study Method in Psychology  :

1) In-depth analysis: 

The case study method allows researchers to gather detailed information about the subject of study, which can be difficult to obtain through other research methods. Researchers can obtain a deep understanding of the subject’s experiences, thoughts, feelings, and behaviors, and this information can be used to develop theories and hypotheses.

2) Flexibility: The case study method is a flexible research method that can be used to study a wide range of phenomena, including rare and unusual conditions. Researchers can adapt the method to fit the unique needs of the study, and this can lead to new insights and discoveries.

3) Source of hypotheses: Case studies can be used to generate new hypotheses or to test existing ones. Researchers can use the information gathered from the case study to develop hypotheses, which can then be tested using other research methods.

4) Validity: The case study method allows for the collection of rich, detailed data that is often more valid than data obtained through other research methods. This is because the researcher is able to gather data directly from the subject, rather than relying on second-hand accounts or self-report measures.

Read Also : Mind-blowing Psychological Facts about Studying

Disadvantages of Case Study Method in Psychology :

1) Limited generalizability: 

The findings from a case study cannot be generalized to other individuals or groups. The unique nature of the subject and the specific context in which the study was conducted make it difficult to apply the findings to other situations.

2) Subjectivity:  

The case study method is subject to the biases and preconceptions of the researcher. The researcher’s own beliefs, values, and experiences can influence the way in which they interpret the data.

3) Time-consuming:  

The case study method is a time-consuming research method that requires a significant investment of time and resources. It can take months or even years to collect and analyze the data.

4) Ethical issues:  

The case study method can raise ethical issues, particularly when studying vulnerable populations. Researchers must take steps to ensure that the study does not harm the subject or infringe upon their rights and privacy.

Case study method is a valuable research method that can provide rich, detailed data that is often difficult to obtain through other research methods.

Benefits of Case Study for Students

There are several benefits of case studies for students, including:

• Real-world application: Case studies provide students with an opportunity to apply theoretical knowledge to real-world situations. This can help students better understand how concepts and theories can be applied in practice.
• Problem-solving skills: Case studies often present complex and challenging problems, which can help students develop their problem-solving skills. By analyzing the case and identifying potential solutions, students can learn to think critically and creatively.
• Active learning: Case studies are an interactive form of learning that requires students to actively engage with the material. This can help students retain information more effectively than passive forms of learning.
• Collaborative learning: Case studies often require students to work in groups, which can help them develop collaboration and teamwork skills.
• Exposure to different perspectives: Case studies often present multiple perspectives on a problem or situation, which can help students understand different viewpoints and develop empathy and cultural competence.
• Preparation for the workforce: Case studies can help prepare students for the workforce by providing them with experience analyzing real-world problems and developing solutions.

Case studies can be a valuable tool for students to develop critical thinking skills, problem-solving skills, and prepare for their future careers.

Case Study Strengths And Weaknesses

Case studies are a research method that involves in-depth analysis of a particular case or phenomenon. Like any research method, case studies have both strengths and weaknesses.

Case Study Strengths:

• In-depth analysis: Case studies allow for a thorough and detailed analysis of a particular case or phenomenon. This can provide a rich and nuanced understanding of the topic.
• Real-world context: Case studies are often conducted in real-world settings, which allows for a more accurate representation of the phenomena being studied.
• Multiple sources of data: Case studies often involve multiple sources of data, including interviews, observations, and documents. This can help to provide a more comprehensive understanding of the case.
• Unique cases: Case studies often focus on unique cases that are not easily replicable in a laboratory setting. This can provide valuable insights that may not be obtained through other research methods.

Case Study Weaknesses:

• Limited generalizability: The findings from a case study may not be generalizable to other cases or populations. This is because case studies often focus on a specific case or phenomenon, which may not be representative of other cases or phenomena.
• Bias: The researcher conducting the case study may have preconceived notions or biases that can affect the interpretation of the data.
• Subjectivity: Case studies often involve subjective interpretation of data, which can lead to differing conclusions depending on the researcher's perspective.
• Time-consuming: Case studies can be very time-consuming and resource-intensive, which can limit the number of cases that can be studied.

Overall, case studies can be a valuable research method for gaining a detailed understanding of a particular case or phenomenon. However, researchers should be aware of the potential limitations of this method and take steps to minimize bias and subjectivity.

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Case Studies

Last updated 22 Mar 2021

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Case studies are very detailed investigations of an individual or small group of people, usually regarding an unusual phenomenon or biographical event of interest to a research field. Due to a small sample, the case study can conduct an in-depth analysis of the individual/group.

Evaluation of case studies:

- Case studies create opportunities for a rich yield of data, and the depth of analysis can in turn bring high levels of validity (i.e. providing an accurate and exhaustive measure of what the study is hoping to measure).

- Studying abnormal psychology can give insight into how something works when it is functioning correctly, such as brain damage on memory (e.g. the case study of patient KF, whose short-term memory was impaired following a motorcycle accident but left his long-term memory intact, suggesting there might be separate physical stores in the brain for short and long-term memory).

- The detail collected on a single case may lead to interesting findings that conflict with current theories, and stimulate new paths for research.

- There is little control over a number of variables involved in a case study, so it is difficult to confidently establish any causal relationships between variables.

- Case studies are unusual by nature, so will have poor reliability as replicating them exactly will be unlikely.

- Due to the small sample size, it is unlikely that findings from a case study alone can be generalised to a whole population.

- The case study’s researcher may become so involved with the study that they exhibit bias in their interpretation and presentation of the data, making it challenging to distinguish what is truly objective/factual.

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• 2.2 Approaches to Research
• Introduction
• 1.1 What Is Psychology?
• 1.2 History of Psychology
• 1.3 Contemporary Psychology
• 1.4 Careers in Psychology
• Review Questions
• Critical Thinking Questions
• Personal Application Questions
• 2.1 Why Is Research Important?
• 2.3 Analyzing Findings
• 3.1 Human Genetics
• 3.2 Cells of the Nervous System
• 3.3 Parts of the Nervous System
• 3.4 The Brain and Spinal Cord
• 3.5 The Endocrine System
• 4.1 What Is Consciousness?
• 4.2 Sleep and Why We Sleep
• 4.3 Stages of Sleep
• 4.4 Sleep Problems and Disorders
• 4.5 Substance Use and Abuse
• 4.6 Other States of Consciousness
• 5.1 Sensation versus Perception
• 5.2 Waves and Wavelengths
• 5.4 Hearing
• 5.5 The Other Senses
• 5.6 Gestalt Principles of Perception
• 6.1 What Is Learning?
• 6.2 Classical Conditioning
• 6.3 Operant Conditioning
• 6.4 Observational Learning (Modeling)
• 7.1 What Is Cognition?
• 7.2 Language
• 7.3 Problem Solving
• 7.4 What Are Intelligence and Creativity?
• 7.5 Measures of Intelligence
• 7.6 The Source of Intelligence
• 8.1 How Memory Functions
• 8.2 Parts of the Brain Involved with Memory
• 8.3 Problems with Memory
• 8.4 Ways to Enhance Memory
• 9.1 What Is Lifespan Development?
• 9.2 Lifespan Theories
• 9.3 Stages of Development
• 9.4 Death and Dying
• 10.1 Motivation
• 10.2 Hunger and Eating
• 10.3 Sexual Behavior, Sexuality, and Gender Identity
• 10.4 Emotion
• 11.1 What Is Personality?
• 11.2 Freud and the Psychodynamic Perspective
• 11.3 Neo-Freudians: Adler, Erikson, Jung, and Horney
• 11.4 Learning Approaches
• 11.5 Humanistic Approaches
• 11.6 Biological Approaches
• 11.7 Trait Theorists
• 11.8 Cultural Understandings of Personality
• 11.9 Personality Assessment
• 12.1 What Is Social Psychology?
• 12.2 Self-presentation
• 12.3 Attitudes and Persuasion
• 12.4 Conformity, Compliance, and Obedience
• 12.5 Prejudice and Discrimination
• 12.6 Aggression
• 12.7 Prosocial Behavior
• 13.1 What Is Industrial and Organizational Psychology?
• 13.2 Industrial Psychology: Selecting and Evaluating Employees
• 13.3 Organizational Psychology: The Social Dimension of Work
• 13.4 Human Factors Psychology and Workplace Design
• 14.1 What Is Stress?
• 14.2 Stressors
• 14.3 Stress and Illness
• 14.4 Regulation of Stress
• 14.5 The Pursuit of Happiness
• 15.1 What Are Psychological Disorders?
• 15.2 Diagnosing and Classifying Psychological Disorders
• 15.3 Perspectives on Psychological Disorders
• 15.4 Anxiety Disorders
• 15.5 Obsessive-Compulsive and Related Disorders
• 15.6 Posttraumatic Stress Disorder
• 15.7 Mood and Related Disorders
• 15.8 Schizophrenia
• 15.9 Dissociative Disorders
• 15.10 Disorders in Childhood
• 15.11 Personality Disorders
• 16.1 Mental Health Treatment: Past and Present
• 16.2 Types of Treatment
• 16.3 Treatment Modalities
• 16.4 Substance-Related and Addictive Disorders: A Special Case
• 16.5 The Sociocultural Model and Therapy Utilization

Learning Objectives

By the end of this section, you will be able to:

• Describe the different research methods used by psychologists
• Discuss the strengths and weaknesses of case studies, naturalistic observation, surveys, and archival research
• Compare longitudinal and cross-sectional approaches to research
• Compare and contrast correlation and causation

There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Some methods rely on observational techniques. Other approaches involve interactions between the researcher and the individuals who are being studied—ranging from a series of simple questions to extensive, in-depth interviews—to well-controlled experiments.

Each of these research methods has 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. All of the methods described thus far are correlational in nature. This means that researchers can speak to important relationships that might exist between two or more variables of interest. However, correlational data cannot be used to make claims about cause-and-effect relationships.

Correlational research can find a relationship between two variables, but the only way a researcher can claim that the relationship between the variables is cause and effect is to perform an experiment. In experimental research, which will be discussed later in this chapter, there is a tremendous amount of control over variables of interest. While this is a powerful approach, experiments are often conducted in artificial settings. This calls into question the validity of experimental findings with regard to how they would apply in real-world settings. In addition, many of the questions that psychologists would like to answer cannot be pursued through experimental research because of ethical concerns.

Clinical or Case Studies

In 2011, the New York Times published a feature story on Krista and Tatiana Hogan, Canadian twin girls. These particular twins are unique because Krista and Tatiana are conjoined twins, connected at the head. There is evidence that the two girls are connected in a part of the brain called the thalamus, which is a major sensory relay center. Most incoming sensory information is sent through the thalamus before reaching higher regions of the cerebral cortex for processing.

Link to Learning

Watch this CBC video about Krista's and Tatiana's lives to learn more.

The implications of this potential connection mean that it might be possible for one twin to experience the sensations of the other twin. For instance, if Krista is watching a particularly funny television program, Tatiana might smile or laugh even if she is not watching the program. This particular possibility has piqued the interest of many neuroscientists who seek to understand how the brain uses sensory information.

These twins represent an enormous resource in the study of the brain, and since their condition is very rare, it is likely that as long as their family agrees, scientists will follow these girls very closely throughout their lives to gain as much information as possible (Dominus, 2011).

Over time, it has become clear that while Krista and Tatiana share some sensory experiences and motor control, they remain two distinct individuals, which provides invaluable insight for researchers interested in the mind and the brain (Egnor, 2017).

In observational research, scientists are conducting a clinical or case study when they focus on one person or just a few individuals. Indeed, some scientists spend their entire careers studying just 10–20 individuals. Why would they do this? Obviously, when they focus their attention on a very small number of people, they can gain a precious amount of insight into those cases. The richness of information that is collected in clinical or case studies is unmatched by any other single research method. This allows the researcher to have a very deep understanding of the individuals and the particular phenomenon being studied.

If clinical or case studies provide so much information, why are they not more frequent among researchers? As it turns out, the major benefit of this particular approach is also a weakness. As mentioned earlier, this approach is often used when studying individuals who are interesting to researchers because they have a rare characteristic. Therefore, the individuals who serve as the focus of case studies are not like most other people. If scientists ultimately want to explain all behavior, focusing attention on such a special group of people can make it difficult to generalize any observations to the larger population as a whole. Generalizing refers to the ability to apply the findings of a particular research project to larger segments of society. Again, case studies provide enormous amounts of information, but since the cases are so specific, the potential to apply what’s learned to the average person may be very limited.

Naturalistic Observation

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances are that almost everyone in the classroom will raise their hand, but do you think hand washing after every trip to the restroom is really that universal?

This is very similar to the phenomenon mentioned earlier in this chapter: many individuals do not feel comfortable answering a question honestly. But if we are committed to finding out the facts about hand washing, we have other options available to us.

Suppose we send a classmate into the restroom to actually watch whether everyone washes their hands after using the restroom. Will our observer blend into the restroom environment by wearing a white lab coat, sitting with a clipboard, and staring at the sinks? We want our researcher to be inconspicuous—perhaps standing at one of the sinks pretending to put in contact lenses while secretly recording the relevant information. This type of observational study is called naturalistic observation : observing behavior in its natural setting. To better understand peer exclusion, Suzanne Fanger collaborated with colleagues at the University of Texas to observe the behavior of preschool children on a playground. How did the observers remain inconspicuous over the duration of the study? They equipped a few of the children with wireless microphones (which the children quickly forgot about) and observed while taking notes from a distance. Also, the children in that particular preschool (a “laboratory preschool”) were accustomed to having observers on the playground (Fanger, Frankel, & Hazen, 2012).

It is critical that the observer be as unobtrusive and as inconspicuous as possible: when people know they are being watched, they are less likely to behave naturally. If you have any doubt about this, ask yourself how your driving behavior might differ in two situations: In the first situation, you are driving down a deserted highway during the middle of the day; in the second situation, you are being followed by a police car down the same deserted highway ( Figure 2.7 ).

It should be pointed out that naturalistic observation is not limited to research involving humans. Indeed, some of the best-known examples of naturalistic observation involve researchers going into the field to observe various kinds of animals in their own environments. As with human studies, the researchers maintain their distance and avoid interfering with the animal subjects so as not to influence their natural behaviors. Scientists have used this technique to study social hierarchies and interactions among animals ranging from ground squirrels to gorillas. The information provided by these studies is invaluable in understanding how those animals organize socially and communicate with one another. The anthropologist Jane Goodall , for example, spent nearly five decades observing the behavior of chimpanzees in Africa ( Figure 2.8 ). As an illustration of the types of concerns that a researcher might encounter in naturalistic observation, some scientists criticized Goodall for giving the chimps names instead of referring to them by numbers—using names was thought to undermine the emotional detachment required for the objectivity of the study (McKie, 2010).

The greatest benefit of naturalistic observation is the validity , or accuracy, of information collected unobtrusively in a natural setting. Having individuals behave as they normally would in a given situation means that we have a higher degree of ecological validity, or realism, than we might achieve with other research approaches. Therefore, our ability to generalize the findings of the research to real-world situations is enhanced. If done correctly, we need not worry about people or animals modifying their behavior simply because they are being observed. Sometimes, people may assume that reality programs give us a glimpse into authentic human behavior. However, the principle of inconspicuous observation is violated as reality stars are followed by camera crews and are interviewed on camera for personal confessionals. Given that environment, we must doubt how natural and realistic their behaviors are.

The major downside of naturalistic observation is that they are often difficult to set up and control. In our restroom study, what if you stood in the restroom all day prepared to record people’s hand washing behavior and no one came in? Or, what if you have been closely observing a troop of gorillas for weeks only to find that they migrated to a new place while you were sleeping in your tent? The benefit of realistic data comes at a cost. As a researcher you have no control of when (or if) you have behavior to observe. In addition, this type of observational research often requires significant investments of time, money, and a good dose of luck.

Sometimes studies involve structured observation. In these cases, people are observed while engaging in set, specific tasks. An excellent example of structured observation comes from Strange Situation by Mary Ainsworth (you will read more about this in the chapter on lifespan development). The Strange Situation is a procedure used to evaluate attachment styles that exist between an infant and caregiver. In this scenario, caregivers bring their infants into a room filled with toys. The Strange Situation involves a number of phases, including a stranger coming into the room, the caregiver leaving the room, and the caregiver’s return to the room. The infant’s behavior is closely monitored at each phase, but it is the behavior of the infant upon being reunited with the caregiver that is most telling in terms of characterizing the infant’s attachment style with the caregiver.

Another potential problem in observational research is observer bias . Generally, people who act as observers are closely involved in the research project and may unconsciously skew their observations to fit their research goals or expectations. To protect against this type of bias, researchers should have clear criteria established for the types of behaviors recorded and how those behaviors should be classified. In addition, researchers often compare observations of the same event by multiple observers, in order to test inter-rater reliability : a measure of reliability that assesses the consistency of observations by different observers.

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally ( Figure 2.9 ). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.

Surveys allow researchers to gather data from larger samples than may be afforded by other research methods . A sample is a subset of individuals selected from a population , which is the overall group of individuals that the researchers are interested in. Researchers study the sample and seek to generalize their findings to the population. Generally, researchers will begin this process by calculating various measures of central tendency from the data they have collected. These measures provide an overall summary of what a typical response looks like. There are three measures of central tendency: mode, median, and mean. The mode is the most frequently occurring response, the median lies at the middle of a given data set, and the mean is the arithmetic average of all data points. Means tend to be most useful in conducting additional analyses like those described below; however, means are very sensitive to the effects of outliers, and so one must be aware of those effects when making assessments of what measures of central tendency tell us about a data set in question.

There is both strength and weakness of the survey in comparison to case studies. By using surveys, we can collect information from a larger sample of people. A larger sample is better able to reflect the actual diversity of the population, thus allowing better generalizability. Therefore, if our sample is sufficiently large and diverse, we can assume that the data we collect from the survey can be generalized to the larger population with more certainty than the information collected through a case study. However, given the greater number of people involved, we are not able to collect the same depth of information on each person that would be collected in a case study.

Another potential weakness of surveys is something we touched on earlier in this chapter: People don't always give accurate responses. They may lie, misremember, or answer questions in a way that they think makes them look good. For example, people may report drinking less alcohol than is actually the case.

Any number of research questions can be answered through the use of surveys. One real-world example is the research conducted by Jenkins, Ruppel, Kizer, Yehl, and Griffin (2012) about the backlash against the US Arab-American community following the terrorist attacks of September 11, 2001. Jenkins and colleagues wanted to determine to what extent these negative attitudes toward Arab-Americans still existed nearly a decade after the attacks occurred. In one study, 140 research participants filled out a survey with 10 questions, including questions asking directly about the participant’s overt prejudicial attitudes toward people of various ethnicities. The survey also asked indirect questions about how likely the participant would be to interact with a person of a given ethnicity in a variety of settings (such as, “How likely do you think it is that you would introduce yourself to a person of Arab-American descent?”). The results of the research suggested that participants were unwilling to report prejudicial attitudes toward any ethnic group. However, there were significant differences between their pattern of responses to questions about social interaction with Arab-Americans compared to other ethnic groups: they indicated less willingness for social interaction with Arab-Americans compared to the other ethnic groups. This suggested that the participants harbored subtle forms of prejudice against Arab-Americans, despite their assertions that this was not the case (Jenkins et al., 2012).

Archival Research

Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research . Archival research relies on looking at past records or data sets to look for interesting patterns or relationships.

For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and calculate how long it took them to complete their degrees, as well as course loads, grades, and extracurricular involvement. Archival research could provide important information about who is most likely to complete their education, and it could help identify important risk factors for struggling students ( Figure 2.10 ).

In comparing archival research to other research methods, there are several important distinctions. For one, the researcher employing archival research never directly interacts with research participants. Therefore, the investment of time and money to collect data is considerably less with archival research. Additionally, researchers have no control over what information was originally collected. Therefore, research questions have to be tailored so they can be answered within the structure of the existing data sets. There is also no guarantee of consistency between the records from one source to another, which might make comparing and contrasting different data sets problematic.

Longitudinal and Cross-Sectional Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again at age 40.

Another approach is cross-sectional research. In cross-sectional research , a researcher compares multiple segments of the population at the same time. Using the dietary habits example above, the researcher might directly compare different groups of people by age. Instead of studying a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old individuals. While cross-sectional research requires a shorter-term investment, it is also limited by differences that exist between the different generations (or cohorts) that have nothing to do with age per se, but rather reflect the social and cultural experiences of different generations of individuals that make them different from one another.

To illustrate this concept, consider the following survey findings. In recent years there has been significant growth in the popular support of same-sex marriage. Many studies on this topic break down survey participants into different age groups. In general, younger people are more supportive of same-sex marriage than are those who are older (Jones, 2013). Does this mean that as we age we become less open to the idea of same-sex marriage, or does this mean that older individuals have different perspectives because of the social climates in which they grew up? Longitudinal research is a powerful approach because the same individuals are involved in the research project over time, which means that the researchers need to be less concerned with differences among cohorts affecting the results of their study.

Often longitudinal studies are employed when researching various diseases in an effort to understand particular risk factors. Such studies often involve tens of thousands of individuals who are followed for several decades. Given the enormous number of people involved in these studies, researchers can feel confident that their findings can be generalized to the larger population. The Cancer Prevention Study-3 (CPS-3) is one of a series of longitudinal studies sponsored by the American Cancer Society aimed at determining predictive risk factors associated with cancer. When participants enter the study, they complete a survey about their lives and family histories, providing information on factors that might cause or prevent the development of cancer. Then every few years the participants receive additional surveys to complete. In the end, hundreds of thousands of participants will be tracked over 20 years to determine which of them develop cancer and which do not.

Clearly, this type of research is important and potentially very informative. For instance, earlier longitudinal studies sponsored by the American Cancer Society provided some of the first scientific demonstrations of the now well-established links between increased rates of cancer and smoking (American Cancer Society, n.d.) ( Figure 2.11 ).

As with any research strategy, longitudinal research is not without limitations. For one, these studies require an incredible time investment by the researcher and research participants. Given that some longitudinal studies take years, if not decades, to complete, the results will not be known for a considerable period of time. In addition to the time demands, these studies also require a substantial financial investment. Many researchers are unable to commit the resources necessary to see a longitudinal project through to the end.

Research participants must also be willing to continue their participation for an extended period of time, and this can be problematic. People move, get married and take new names, get ill, and eventually die. Even without significant life changes, some people may simply choose to discontinue their participation in the project. As a result, the attrition rates, or reduction in the number of research participants due to dropouts, in longitudinal studies are quite high and increases over the course of a project. For this reason, researchers using this approach typically recruit many participants fully expecting that a substantial number will drop out before the end. As the study progresses, they continually check whether the sample still represents the larger population, and make adjustments as necessary.

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Case Studies

March 7, 2021 - Paper 2 Psychology in Context | Research Methods

• Back to Paper 2 - Research Methods

Description, AO1 of Case Studies:

• An in-depth, detailed investigation of an individual or group.
• It would usually include biographical details, as well as details of behaviours or experiences of interest to the researcher.
• Usually carried out in the real world
• Can use a variety of Psychology research methods (experimental and non-experimental) in order to collect data for the case study.

Methods used to collect information for case studies:

• Questionnaires (open and closed questions)
• Observations

Evaluation of Case Studies:

(1)  POINT:  A strength of a case study is that it produces rich, detailed data.  EXAMPLE:  For example, a case study of an individual’s life is incredibly detailed and may highlight a number of important experiences that could have combined to cause them to become mentally ill.  EVALUATION:  This is positive because information that may be overlooked using other methods is likely to be identified.

(2)  POINT:  A strength os a cause study is that it provices insight into individuals.  EXAMPLE: For example, rare mental disorders make it impossible to study large amounts of participants with that disorder because the behaviours or experiences are so unique that they could not have been studied in any other way.  EVALUATION: This is positive because it helps to improve our understanding of behaviours that would otherwise not be possible.

Weaknesses:

(1)  POINT:  A weakness of a case study is that it is difficult to generalise the results.  EXAMPLE:  For example, a case study of an individual person might not be representative of anyone else because experiences are so individual that another person may not react in the same way.  EVALUATION:  This is a problem as it’s difficult to generalise to the rest of the population (low popultation validity) as each case has unique characteristics.

(2)  POINT:  A weakness of a case study is that it collects retrospective data.  EXAMPLE:  For example, a researcher might rely on asking individuals about their past to help form the case study, which can be reconstructive.  EVALUATION: This is a problem as such evidence may have been recalled inaccurately and may therefore be unreliable.

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1.2 Research Methods in Psychology

4 min read • january 5, 2023

Jillian Holbrook

Sadiyya Holsey

Overview of Research Methods

There are various types of research methods in psychology with different purposes, strengths, and weaknesses.

Whenever researchers want to prove or find causation, they would run an experiment.

An experiment you'll learn about in Unit 9 that was run by Solomon Asch investigated the extent to which one would conform to a group's ideas.

Image Courtesy of Wikipedia .

Each person in the room would have to look at these lines above and state which one they thought was of similar length to the original line. The answer was, of course, obvious, but Asch wanted to see if the "real participant" would conform to the views of the rest of the group.

Asch gathered together what we could call "fake participants" and told them not to say line C. The "real participant" would then hear wrong answers, but they did not want to be the odd one out, so they conformed with the rest of the group and represented the majority view.

In this experiment, the "real participant" was the control group , and about 75% of them, over 12 trials, conformed at least once.

Correlational Study

There could be a correlational study between anything. Say you wanted to see if there was an association between the number of hours a teenager sleeps and their grades in high school. If there was a correlation, we cannot say that sleeping a greater number of hours causes higher grades. However, we can determine that they are related to each other. 💤

Remember in psychology that a correlation does not prove causation!

Survey Research

Surveys are used all the time, especially in advertising and marketing. They are often distributed to a large number of people, and the results are returned back to researchers.

Naturalistic Observation

If a student wanted to observe how many people fully stop at a stop sign, they could watch the cars from a distance and record their data. This is a naturalistic observation since the student is in no way influencing the results.

A notable psychological case study is the study of Phineas Gage :

Image Courtesy of Vermont Journal

Phineas Gage was a railroad construction foreman who survived a severe brain injury in 1848. The accident occurred when an iron rod was accidentally driven through Gage's skull, damaging his frontal lobes . Despite the severity of the injury, Gage was able to walk and talk immediately after the accident and appeared to be relatively uninjured.

However, Gage's personality underwent a dramatic change following the injury. He became impulsive, irresponsible, and prone to outbursts of anger, which were completely out of character for him before the accident. Gage's case is famous in the history of psychology because it was one of the first to suggest that damage to the frontal lobes of the brain can have significant effects on personality and behavior.

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• Perspective
• Published: 22 November 2022

Single case studies are a powerful tool for developing, testing and extending theories

• Lyndsey Nickels   ORCID: orcid.org/0000-0002-0311-3524 1 , 2 ,
• Simon Fischer-Baum   ORCID: orcid.org/0000-0002-6067-0538 3 &
• Wendy Best   ORCID: orcid.org/0000-0001-8375-5916 4  

Nature Reviews Psychology volume  1 ,  pages 733–747 ( 2022 ) Cite this article

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• Neurological disorders

Psychology embraces a diverse range of methodologies. However, most rely on averaging group data to draw conclusions. In this Perspective, we argue that single case methodology is a valuable tool for developing and extending psychological theories. We stress the importance of single case and case series research, drawing on classic and contemporary cases in which cognitive and perceptual deficits provide insights into typical cognitive processes in domains such as memory, delusions, reading and face perception. We unpack the key features of single case methodology, describe its strengths, its value in adjudicating between theories, and outline its benefits for a better understanding of deficits and hence more appropriate interventions. The unique insights that single case studies have provided illustrate the value of in-depth investigation within an individual. Single case methodology has an important place in the psychologist’s toolkit and it should be valued as a primary research tool.

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Acknowledgements

The authors thank all of those pioneers of and advocates for single case study research who have mentored, inspired and encouraged us over the years, and the many other colleagues with whom we have discussed these issues.

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Nickels, L., Fischer-Baum, S. & Best, W. Single case studies are a powerful tool for developing, testing and extending theories. Nat Rev Psychol 1 , 733–747 (2022). https://doi.org/10.1038/s44159-022-00127-y

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9 Approaches to Research

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Learning Objectives

By the end of this section, you will be able to:

• Describe the different research methods used by psychologists
• Discuss the strengths and weaknesses of case studies, naturalistic observation, surveys, and archival research
• Compare longitudinal and cross-sectional approaches to research

There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Some methods rely on observational techniques. Other approaches involve interactions between the researcher and the individuals who are being studied—ranging from a series of simple questions to extensive, in-depth interviews—to well-controlled experiments.

Each of these research methods has 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. All of the methods described thus far are correlational in nature. This means that researchers can speak to important relationships that might exist between two or more variables of interest. However, correlational data cannot be used to make claims about cause-and-effect relationships.

Correlational research can find a relationship between two variables, but the only way a researcher can claim that the relationship between the variables is cause and effect is to perform an experiment. In experimental research, which will be discussed later in this chapter, there is a tremendous amount of control over variables of interest. While this is a powerful approach, experiments are often conducted in very artificial settings. This calls into question the validity of experimental findings with regard to how they would apply in real-world settings. In addition, many of the questions that psychologists would like to answer cannot be pursued through experimental research because of ethical concerns.

CLINICAL OR CASE STUDIES

In 2011, the New York Times published a feature story on Krista and Tatiana Hogan, Canadian twin girls. These particular twins are unique because Krista and Tatiana are conjoined twins, connected at the head. There is evidence that the two girls are connected in a part of the brain called the thalamus, which is a major sensory relay center. Most incoming sensory information is sent through the thalamus before reaching higher regions of the cerebral cortex for processing.

To learn more about Krista and Tatiana, watch this New York Times video about their lives.

The implications of this potential connection mean that it might be possible for one twin to experience the sensations of the other twin. For instance, if Krista is watching a particularly funny television program, Tatiana might smile or laugh even if she is not watching the program. This particular possibility has piqued the interest of many neuroscientists who seek to understand how the brain uses sensory information.

These twins represent an enormous resource in the study of the brain, and since their condition is very rare, it is likely that as long as their family agrees, scientists will follow these girls very closely throughout their lives to gain as much information as possible (Dominus, 2011).

In observational research, scientists are conducting a clinical or case study when they focus on one person or just a few individuals. Indeed, some scientists spend their entire careers studying just 10–20 individuals. Why would they do this? Obviously, when they focus their attention on a very small number of people, they can gain a tremendous amount of insight into those cases. The richness of information that is collected in clinical or case studies is unmatched by any other single research method. This allows the researcher to have a very deep understanding of the individuals and the particular phenomenon being studied.

If clinical or case studies provide so much information, why are they not more frequent among researchers? As it turns out, the major benefit of this particular approach is also a weakness. As mentioned earlier, this approach is often used when studying individuals who are interesting to researchers because they have a rare characteristic. Therefore, the individuals who serve as the focus of case studies are not like most other people. If scientists ultimately want to explain all behavior, focusing attention on such a special group of people can make it difficult to generalize any observations to the larger population as a whole. Generalizing refers to the ability to apply the findings of a particular research project to larger segments of society. Again, case studies provide enormous amounts of information, but since the cases are so specific, the potential to apply what’s learned to the average person may be very limited.

NATURALISTIC OBSERVATION

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances are that almost everyone in the classroom will raise their hand, but do you think hand washing after every trip to the restroom is really that universal?

This is very similar to the phenomenon mentioned earlier in this chapter: many individuals do not feel comfortable answering a question honestly. But if we are committed to finding out the facts about hand washing, we have other options available to us.

Suppose we send a classmate into the restroom to actually watch whether everyone washes their hands after using the restroom. Will our observer blend into the restroom environment by wearing a white lab coat, sitting with a clipboard, and staring at the sinks? We want our researcher to be inconspicuous—perhaps standing at one of the sinks pretending to put in contact lenses while secretly recording the relevant information. This type of observational study is called naturalistic observation : observing behavior in its natural setting. To better understand peer exclusion, Suzanne Fanger collaborated with colleagues at the University of Texas to observe the behavior of preschool children on a playground. How did the observers remain inconspicuous over the duration of the study? They equipped a few of the children with wireless microphones (which the children quickly forgot about) and observed while taking notes from a distance. Also, the children in that particular preschool (a “laboratory preschool”) were accustomed to having observers on the playground (Fanger, Frankel, & Hazen, 2012).

It is critical that the observer be as unobtrusive and as inconspicuous as possible: when people know they are being watched, they are less likely to behave naturally. If you have any doubt about this, ask yourself how your driving behavior might differ in two situations: In the first situation, you are driving down a deserted highway during the middle of the day; in the second situation, you are being followed by a police car down the same deserted highway ( [link] ).

It should be pointed out that naturalistic observation is not limited to research involving humans. Indeed, some of the best-known examples of naturalistic observation involve researchers going into the field to observe various kinds of animals in their own environments. As with human studies, the researchers maintain their distance and avoid interfering with the animal subjects so as not to influence their natural behaviors. Scientists have used this technique to study social hierarchies and interactions among animals ranging from ground squirrels to gorillas. The information provided by these studies is invaluable in understanding how those animals organize socially and communicate with one another. The anthropologist Jane Goodall , for example, spent nearly five decades observing the behavior of chimpanzees in Africa ( [link] ). As an illustration of the types of concerns that a researcher might encounter in naturalistic observation, some scientists criticized Goodall for giving the chimps names instead of referring to them by numbers—using names was thought to undermine the emotional detachment required for the objectivity of the study (McKie, 2010).

The greatest benefit of naturalistic observation is the validity , or accuracy, of information collected unobtrusively in a natural setting. Having individuals behave as they normally would in a given situation means that we have a higher degree of ecological validity, or realism, than we might achieve with other research approaches. Therefore, our ability to generalize the findings of the research to real-world situations is enhanced. If done correctly, we need not worry about people or animals modifying their behavior simply because they are being observed. Sometimes, people may assume that reality programs give us a glimpse into authentic human behavior. However, the principle of inconspicuous observation is violated as reality stars are followed by camera crews and are interviewed on camera for personal confessionals. Given that environment, we must doubt how natural and realistic their behaviors are.

The major downside of naturalistic observation is that they are often difficult to set up and control. In our restroom study, what if you stood in the restroom all day prepared to record people’s hand washing behavior and no one came in? Or, what if you have been closely observing a troop of gorillas for weeks only to find that they migrated to a new place while you were sleeping in your tent? The benefit of realistic data comes at a cost. As a researcher you have no control of when (or if) you have behavior to observe. In addition, this type of observational research often requires significant investments of time, money, and a good dose of luck.

Sometimes studies involve structured observation. In these cases, people are observed while engaging in set, specific tasks. An excellent example of structured observation comes from Strange Situation by Mary Ainsworth (you will read more about this in the chapter on lifespan development). The Strange Situation is a procedure used to evaluate attachment styles that exist between an infant and caregiver. In this scenario, caregivers bring their infants into a room filled with toys. The Strange Situation involves a number of phases, including a stranger coming into the room, the caregiver leaving the room, and the caregiver’s return to the room. The infant’s behavior is closely monitored at each phase, but it is the behavior of the infant upon being reunited with the caregiver that is most telling in terms of characterizing the infant’s attachment style with the caregiver.

Another potential problem in observational research is observer bias . Generally, people who act as observers are closely involved in the research project and may unconsciously skew their observations to fit their research goals or expectations. To protect against this type of bias, researchers should have clear criteria established for the types of behaviors recorded and how those behaviors should be classified. In addition, researchers often compare observations of the same event by multiple observers, in order to test inter-rater reliability : a measure of reliability that assesses the consistency of observations by different observers.

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally ( [link] ). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.

Surveys allow researchers to gather data from larger samples than may be afforded by other research methods . A sample is a subset of individuals selected from a population , which is the overall group of individuals that the researchers are interested in. Researchers study the sample and seek to generalize their findings to the population.

There is both strength and weakness of the survey in comparison to case studies. By using surveys, we can collect information from a larger sample of people. A larger sample is better able to reflect the actual diversity of the population, thus allowing better generalizability. Therefore, if our sample is sufficiently large and diverse, we can assume that the data we collect from the survey can be generalized to the larger population with more certainty than the information collected through a case study. However, given the greater number of people involved, we are not able to collect the same depth of information on each person that would be collected in a case study.

Another potential weakness of surveys is something we touched on earlier in this chapter: People don’t always give accurate responses. They may lie, misremember, or answer questions in a way that they think makes them look good. For example, people may report drinking less alcohol than is actually the case.

Any number of research questions can be answered through the use of surveys. One real-world example is the research conducted by Jenkins, Ruppel, Kizer, Yehl, and Griffin (2012) about the backlash against the US Arab-American community following the terrorist attacks of September 11, 2001. Jenkins and colleagues wanted to determine to what extent these negative attitudes toward Arab-Americans still existed nearly a decade after the attacks occurred. In one study, 140 research participants filled out a survey with 10 questions, including questions asking directly about the participant’s overt prejudicial attitudes toward people of various ethnicities. The survey also asked indirect questions about how likely the participant would be to interact with a person of a given ethnicity in a variety of settings (such as, “How likely do you think it is that you would introduce yourself to a person of Arab-American descent?”). The results of the research suggested that participants were unwilling to report prejudicial attitudes toward any ethnic group. However, there were significant differences between their pattern of responses to questions about social interaction with Arab-Americans compared to other ethnic groups: they indicated less willingness for social interaction with Arab-Americans compared to the other ethnic groups. This suggested that the participants harbored subtle forms of prejudice against Arab-Americans, despite their assertions that this was not the case (Jenkins et al., 2012).

ARCHIVAL RESEARCH

Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research . Archival research relies on looking at past records or data sets to look for interesting patterns or relationships.

For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and calculate how long it took them to complete their degrees, as well as course loads, grades, and extracurricular involvement. Archival research could provide important information about who is most likely to complete their education, and it could help identify important risk factors for struggling students ( [link] ).

In comparing archival research to other research methods, there are several important distinctions. For one, the researcher employing archival research never directly interacts with research participants. Therefore, the investment of time and money to collect data is considerably less with archival research. Additionally, researchers have no control over what information was originally collected. Therefore, research questions have to be tailored so they can be answered within the structure of the existing data sets. There is also no guarantee of consistency between the records from one source to another, which might make comparing and contrasting different data sets problematic.

LONGITUDINAL AND CROSS-SECTIONAL RESEARCH

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again at age 40.

Another approach is cross-sectional research. In cross-sectional research , a researcher compares multiple segments of the population at the same time. Using the dietary habits example above, the researcher might directly compare different groups of people by age. Instead a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old individuals. While cross-sectional research requires a shorter-term investment, it is also limited by differences that exist between the different generations (or cohorts) that have nothing to do with age per se, but rather reflect the social and cultural experiences of different generations of individuals make them different from one another.

To illustrate this concept, consider the following survey findings. In recent years there has been significant growth in the popular support of same-sex marriage. Many studies on this topic break down survey participants into different age groups. In general, younger people are more supportive of same-sex marriage than are those who are older (Jones, 2013). Does this mean that as we age we become less open to the idea of same-sex marriage, or does this mean that older individuals have different perspectives because of the social climates in which they grew up? Longitudinal research is a powerful approach because the same individuals are involved in the research project over time, which means that the researchers need to be less concerned with differences among cohorts affecting the results of their study.

Often longitudinal studies are employed when researching various diseases in an effort to understand particular risk factors. Such studies often involve tens of thousands of individuals who are followed for several decades. Given the enormous number of people involved in these studies, researchers can feel confident that their findings can be generalized to the larger population. The Cancer Prevention Study-3 (CPS-3) is one of a series of longitudinal studies sponsored by the American Cancer Society aimed at determining predictive risk factors associated with cancer. When participants enter the study, they complete a survey about their lives and family histories, providing information on factors that might cause or prevent the development of cancer. Then every few years the participants receive additional surveys to complete. In the end, hundreds of thousands of participants will be tracked over 20 years to determine which of them develop cancer and which do not.

Clearly, this type of research is important and potentially very informative. For instance, earlier longitudinal studies sponsored by the American Cancer Society provided some of the first scientific demonstrations of the now well-established links between increased rates of cancer and smoking (American Cancer Society, n.d.) ( [link] ).

As with any research strategy, longitudinal research is not without limitations. For one, these studies require an incredible time investment by the researcher and research participants. Given that some longitudinal studies take years, if not decades, to complete, the results will not be known for a considerable period of time. In addition to the time demands, these studies also require a substantial financial investment. Many researchers are unable to commit the resources necessary to see a longitudinal project through to the end.

Research participants must also be willing to continue their participation for an extended period of time, and this can be problematic. People move, get married and take new names, get ill, and eventually die. Even without significant life changes, some people may simply choose to discontinue their participation in the project. As a result, the attrition rates, or reduction in the number of research participants due to dropouts, in longitudinal studies are quite high and increases over the course of a project. For this reason, researchers using this approach typically recruit many participants fully expecting that a substantial number will drop out before the end. As the study progresses, they continually check whether the sample still represents the larger population, and make adjustments as necessary.

The clinical or case study involves studying just a few individuals for an extended period of time. While this approach provides an incredible depth of information, the ability to generalize these observations to the larger population is problematic. Naturalistic observation involves observing behavior in a natural setting and allows for the collection of valid, true-to-life information from realistic situations. However, naturalistic observation does not allow for much control and often requires quite a bit of time and money to perform. Researchers strive to ensure that their tools for collecting data are both reliable (consistent and replicable) and valid (accurate).

Surveys can be administered in a number of ways and make it possible to collect large amounts of data quickly. However, the depth of information that can be collected through surveys is somewhat limited compared to a clinical or case study.

Archival research involves studying existing data sets to answer research questions.

Longitudinal research has been incredibly helpful to researchers who need to collect data on how people change over time. Cross-sectional research compares multiple segments of a population at a single time.

Review Questions

Sigmund Freud developed his theory of human personality by conducting in-depth interviews over an extended period of time with a few clients. This type of research approach is known as a(n): ________.

• archival research
• naturalistic observation

________ involves observing behavior in individuals in their natural environments.

The major limitation of case studies is ________.

• the superficial nature of the information collected in this approach
• the lack of control that the researcher has in this approach
• the inability to generalize the findings from this approach to the larger population
• the absence of inter-rater reliability

The benefit of naturalistic observation studies is ________.

• the honesty of the data that is collected in a realistic setting
• how quick and easy these studies are to perform
• the researcher’s capacity to make sure that data is collected as efficiently as possible
• the ability to determine cause and effect in this particular approach

Using existing records to try to answer a research question is known as ________.

• survey research
• longitudinal research

________ involves following a group of research participants for an extended period of time.

• cross-sectional research

A(n) ________ is a list of questions developed by a researcher that can be administered in paper form.

Longitudinal research is complicated by high rates of ________.

• observation
• generalization

Critical Thinking Questions

In this section, conjoined twins, Krista and Tatiana, were described as being potential participants in a case study. In what other circumstances would you think that this particular research approach would be especially helpful and why?

Case studies might prove especially helpful using individuals who have rare conditions. For instance, if one wanted to study multiple personality disorder then the case study approach with individuals diagnosed with multiple personality disorder would be helpful.

Presumably, reality television programs aim to provide a realistic portrayal of the behavior displayed by the characters featured in such programs. This section pointed out why this is not really the case. What changes could be made in the way that these programs are produced that would result in more honest portrayals of realistic behavior?

The behavior displayed on these programs would be more realistic if the cameras were mounted in hidden locations, or if the people who appear on these programs did not know when they were being recorded.

Which of the research methods discussed in this section would be best suited to research the effectiveness of the D.A.R.E. program in preventing the use of alcohol and other drugs? Why?

Longitudinal research would be an excellent approach in studying the effectiveness of this program because it would follow students as they aged to determine if their choices regarding alcohol and drugs were affected by their participation in the program.

Aside from biomedical research, what other areas of research could greatly benefit by both longitudinal and archival research?

Answers will vary. Possibilities include research on hiring practices based on human resource records, and research that follows former prisoners to determine if the time that they were incarcerated provided any sort of positive influence on their likelihood of engaging in criminal behavior in the future.

Personal Application Questions

A friend of yours is working part-time in a local pet store. Your friend has become increasingly interested in how dogs normally communicate and interact with each other, and is thinking of visiting a local veterinary clinic to see how dogs interact in the waiting room. After reading this section, do you think this is the best way to better understand such interactions? Do you have any suggestions that might result in more valid data?

As a college student, you are no doubt concerned about the grades that you earn while completing your coursework. If you wanted to know how overall GPA is related to success in life after college, how would you choose to approach this question and what kind of resources would you need to conduct this research?

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Strengths and Weaknesses of Case Studies

There is no doubt that case studies are a valuable and important form of research for all of the industries and fields that use them. However, along with all their advantages, they also have some disadvantages. In this article we are going to look at both.

Advantages of Case Studies

Intensive Study

Case study method is responsible for intensive study of a unit. It is the investigation and exploration of an event thoroughly and deeply. You get a very detailed and in-depth study of a person or event. This is especially the case with subjects that cannot be physically or ethically recreated.

This is one of the biggest advantages of the Genie case. You cannot lock up a child for 13 years and deprive them of everything. That would be morally and ethically wrong in every single way. So when the opportunity presented itself, researchers could not look away. It was a once in a lifetime opportunity to learn about feral children.

Genie was a feral child. She was raised in completed isolation, with little human contact. Because of the abuse she withstood, she was unable to develop cognitively. From infancy she was strapped to a potty chair, and therefore never acquired the physicality needed for walking, running and jumping.

If Genie made a noise, her father beat her. Therefore, she learned to not make a noise. Once she was found, researchers studied her language skills, and attempted to find ways to get her to communicate. They were successful. While she never gained the ability to speak, she did develop other ways to communicate. However, the public soon lost interest in her case, and with that, the funds to conduct the study.

However, her case was extremely important to child development psychology and linguistic theory. Because of her, we know that mental stimulation is needed for proper development. We also now know that there is a "critical period" for the learning of language.

Developing New Research

Case studies are one of the best ways to stimulate new research. A case study can be completed, and if the findings are valuable, they can lead to new and advanced research in the field. There has been a great deal of research done that wouldn't have been possible without case studies.

An example of this is the sociological study Nickel and Dimed. Nickel and Dimed is a book and study done by Barbara Ehrenreich. She wanted to study poverty in America, and did so by living and working as a person living on minimum wage.

Through her experiment, she discovered that poverty was almost inescapable. As soon as she saved a little money, she was hit with a crisis. She might get sick, or her car might break down, all occurrences that can be destructive when a person doesn't have a safety net to fall back on.

It didn't matter where she lived or what she did. Working a minimum wage job gave her no chances for advancement or improvement whatsoever. And she did the experiment as a woman with no children to support.

This study opened a lot of eyes to the problem of the working poor in America. By living and working as the experiment, Ehrenreich was able to show first-hand data regarding the issues surrounding poverty. The book didn't end with any solutions, just suggestions for the reader and points for them to think about.

Using this case study information, new studies could be organized to learn better ways to help people who are fighting poverty, or better ways to help the working poor.

Contradicting Established Ideas or Theories

Oftentimes there are theories that may be questioned with case studies. For example, in the John/John case study, it was believed that gender and sexual identity were a construct of nurture, not nature.

John-John focused on a set of twin boys, both of whom were circumcised at the age of 6 months. One of the twin's circumcisions failed, causing irreparable damage to the penis. His parents were concerned about the sexual health of their son, so they contacted Dr. John Money for a solution.

Dr. Money believed that sexuality came from nurture, not nature, and that the injured baby, Bruce, could be raised as a girl. His penis was removed and he was sexually reassigned to become a girl. Bruce's name was changed to Brenda, and his parents decided to raise him as a girl.

In this case, Dr. Money was dishonest. He believed that gender could be changed, which has since been proven false. Brenda's parents were also dishonest, stating that the surgery was a success, when in fact that wasn't the case.

As Brenda grew up, she always acted masculine and was teased for it at school. She did not socialize as a girl, and did not identify as a female. When Brenda was 13 she learned the truth, and was incredibly relieved. She changed her name to David, and lived the rest of her life as a male.

This case proved that the general theory was wrong, and is still valuable, even though the study author was dishonest.

Giving New Insight

Case studies have the ability to give insight into phenomena that cannot be learned in any other way. An example of this is the case study about Sidney Bradford. Bradford was blind from the age of 10 months old, and regained his sight at the age of 52 from a corneal transplant.

This unique situation allowed researchers to better learn how perception and motion changes when suddenly given sight. They were able to better understand how colors and dimensions affect the human process. For what it is worth, Bradford continued to live and work with his eyes closed, as he found sight too stimulating.

Another famous study was the sociological study of Milgram.

Stanley Milgram did a study from 1960 to 1974 in which he studied the effects of social pressure. The study was set up as an independent laboratory. A random person would walk in, and agree to be a part of the study. He was told to act as a teacher, and ask questions to another volunteer, who was the learner.

The teacher would ask the learner questions, and whenever he answered incorrectly, the teacher was instructed to give the learner an electric shock. Each time the learner was wrong, the shock would be increased by 15 volts. What the teacher didn't know was that the learner was a part of the experiment, and that no shocks were being given. However, the learner did act as if they were being shocked.

If the teachers tried to quit, they were strongly pushed to continue. The goal of the experiment was to see whether or not any of the teachers would go up to the highest voltage. As it turned out, 65% of the teachers did.

This study opened eyes when it comes to social pressure. If someone tells you it is okay to hurt someone, at what point will the person back off and say "this is not ok!" And in this study, the results were the same, regardless of income, race, gender or ethnicity.

This study opened up the sociological world of understanding the divide between social pressure and morality.

Disadvantages of Case Studies

Inability to Replicate

As demonstrated with the Genie case study, many studies cannot be replicated, and therefore, cannot be corroborated. Because the studies cannot be replicated, it means the data and results are only valid for that one person. Now, one could infer that that results of the Genie study would be the same with other feral children, without additional studies we can never be 100% certain.

Also, Genie was a white, American female. We do not know whether someone with a different gender, race or ethnicity would have a different result.

Key Term! Hawthorne Effect

The effect in which people change their behavior when they are aware they are being observed.

Researcher Bias

When conducting a case study, it is very possible for the author to form a bias. This bias can be for the subject; the form of data collection, or the way the data is interpreted. This is very common, since it is normal for humans to be subjective. It is well known that Sigmund Freud, the father of psychology, was often biased in his case histories and interpretations.

The researcher can become close to a study participant, or may learn to identify with the subject. When this happens the researcher loses their perspective as an outsider.

No Classification

Any classification is not possible due to studying a small unit. This generalization of results is limited, since the study is only focusing on one small group. However, this isn't always a problem, especially if generalization is not one of the study's goals.

Time Intensive

Case studies can be very time consuming. The data collection process can be very intensive and long, and this is something new researchers are not familiar with. It takes a long period of time to develop a case study, and develop a detailed analysis.

Many studies also require the authors to immerse themselves in the case. For example, in the Genie case, the lead researchers spent an abnormal amount of time with Genie, since so few people knew how to handle her. David Rigler, one of the lead researchers, actually had Genie live with him and his family for years. Because of this attachment, many questioned the veracity of the study data.

Possibility of Errors

Case study method may have errors of memory or judgment. Since reconstructing case history is based on memory, this can lead to errors. Also, how one person perceived the past could be different for another person, and this can and does lead to errors.

When considering various aspects of their lives, people tend to focus on issues that they find most important. This allows them to form a prejudice and can make them unaware of other possible options.

Ethical Issues

With small studies, there is always the question of ethics. At what point does a study become unethical? The Genie case was riddled with accusations of being unethical, and people still debate about it today.

Was it ethical to study Genie as deeply as she was studied?

Did Genie deserve to live out her life unbothered by researchers and academics trying to use her case to potentially further their careers?

At what point does the pursuit of scientific knowledge outweigh the right to a life free from research?

Also, because the researchers became so invested in the study, people questioned whether a researcher would report unethical behavior if they witnessed it.

Advantages and Disadvantages in Real-Life Studies

Two of these case studies are the Tylenol Scandal and the Genie language study.

Let's look at the advantages and disadvantages of these two studies.

Genie – Advantages

Uniqueness of study – Being able to study a feral child is a rare occurrence.

Genie – Disadvantages

Ethics - The lead researcher David Rigler provided a home for Genie, and was paid for being a foster parent. This is often seen as unethical, since Rigler had a financial interest in Genie and her case.

Tylenol – Advantages

Uniqueness of study – What happened to Tylenol was very unique and rare. While companies face crisis all the time, a public health crisis of this magnitude is very unique.

Tylenol – Disadvantages

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Research Methods In Psychology

Saul Mcleod, PhD

Educator, Researcher

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, Ph.D., is a qualified psychology teacher with over 18 years experience of working in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

Research methods in psychology are systematic procedures used to observe, describe, predict, and explain behavior and mental processes. They include experiments, surveys, case studies, and naturalistic observations, ensuring data collection is objective and reliable to understand and explain psychological phenomena.

Hypotheses are statements about the prediction of the results, that can be verified or disproved by some kind of investigation.

There are four types of hypotheses :

• Null Hypotheses (H0 ) – these predict that no difference will be found in the results between the conditions. Typically these are written ‘There will be no difference…’
• Alternative Hypotheses (Ha or H1) – these predict that there will be a significant difference in the results between the two conditions. This is also known as the experimental hypothesis.
• One-tailed (directional) hypotheses – these state the specific direction the researcher expects the results to move in, e.g. higher, lower, more, less. In a correlation study, the predicted direction of the correlation can be either positive or negative.
• Two-tailed (non-directional) hypotheses – these state that a difference will be found between the conditions of the independent variable but does not state the direction of a difference or relationship. Typically these are always written ‘There will be a difference ….’

All research has an alternative hypothesis (either a one-tailed or two-tailed) and a corresponding null hypothesis.

Once the research is conducted and results are found, psychologists must accept one hypothesis and reject the other. 

So if a difference is found, the Psychologist would accept the alternative hypothesis and reject the null.  The opposite applies if no difference is found.

Sampling techniques

Sampling is the process of selecting a representative group from the population under study.

A sample is the participants you select from a target population (the group you are interested in) to make generalisations about.

Representative means the extent to which a sample mirrors a researcher’s target population and reflects its characteristics.

Generalisability means the extent to which their findings can be applied to the larger population of which their sample was a part.

• Volunteer sample : where participants pick themselves through newspaper adverts, noticeboards or online.
• Opportunity sampling : also known as convenience sampling , uses people who are available at the time the study is carried out and willing to take part. It is based on convenience.
• Random sampling : when every person in the target population has an equal chance of being selected. An example of random sampling would be picking names out of a hat.
• Systematic sampling : when a system is used to select participants. Picking every Nth person from all possible participants. N = the number of people in the research population / the number of people needed for the sample.
• Stratified sampling : when you identify the subgroups and select participants in proportion to their occurrences.
• Snowball sampling : when researchers find a few participants, and then ask them to find participants themselves and so on.
• Quota sampling : when researchers will be told to ensure the sample fits with certain quotas, for example they might be told to find 90 participants, with 30 of them being unemployed.

Experiments always have an independent and dependent variable .

• The independent variable is the one the experimenter manipulates (the thing that changes between the conditions the participants are placed into). It is aassumed to have a direct effect on the dependent variable.
• The dependent variable is the thing being measured, or the results of the experiment.

Operationalization of variables means making them measurable/quantifiable. We must use operationalization to ensure that variables are in a form that can be easily tested.

For instance, we can’t really measure ‘happiness’ but we can measure how many times a person smiles within a two hour period. 

By operationalizing variables, we make it easy for someone else to replicate our research. Remember, this is important because we can check if our findings are reliable.

Extraneous variables are all variables, which are not the independent variable, but could affect the results of the experiment.

It can be a natural characteristic of the participant, such as intelligence levels, gender, or age for example, or it could be a situational feature of the environment such as lighting or noise.

Demand characteristics are a type of extraneous variable that occurs if the participants work out the aims of the research study, they may begin to behave in a certain way.

For example, in Milgram’s research , critics argued that participants worked out that the shocks were not real and they administered them as they thought this was what was required of them. 

Extraneous variables must be controlled so that they do not affect (confound) the results.

Randomly allocating participants to their conditions or using a matched pairs experimental design can help to reduce participant variables. 

Situational variables are controlled by using standardized procedures, ensuring every participant in a given condition is treated in the same way

Experimental Design

Experimental design refers to how participants are allocated to each condition of the independent variable, such as a control or experimental group.

• Independent design ( between-groups design ): each participant is selected for only one group. With the independent design, the most common way of deciding which participants go into which group is by means of randomization. 
• Matched participants design : each participant is selected for only one group, but the participants in the two groups are matched for some relevant factor or factors (e.g. ability; sex; age).
• Repeated measures design ( within groups) : each participant appears in both groups, so that there are exactly the same participants in each group.
• The main problem with the repeated measures design is that there may well be order effects. Their experiences during the experiment may change the participants in various ways.
• They may perform better when they appear in the second group because they have gained useful information about the experiment or about the task. On the other hand, they may perform less well on the second occasion because of tiredness or boredom.
• Counterbalancing is the best way of preventing order effects from disrupting the findings of an experiment, and involves ensuring that each condition is equally likely to be used first and second by the participants

If we wish to compare two groups with respect to a given independent variable, it is essential to make sure that the two groups do not differ in any other important way. 

Experimental Methods

All experimental methods involve an iv (independent variable) and dv (dependent variable)..

• Lab Experiments are conducted in a well-controlled environment, not necessarily a laboratory, and therefore accurate and objective measurements are possible. The researcher decides where the experiment will take place, at what time, with which participants, in what circumstances,  using a standardized procedure.
• Field experiments are conducted in the everyday (natural) environment of the participants. The experimenter still manipulates the IV, but in a real-life setting. It may be possible to control extraneous variables, though such control is more difficult than in a lab experiment.
• Natural experiments are when a naturally occurring IV is investigated that isn’t deliberately manipulated, it exists anyway. Participants are not randomly allocated, and the natural event may only occur rarely.

Case studies are in-depth investigations of a person, group, event, or community. It uses information from a range of sources, such as from the person concerned and also from their family and friends.

Many techniques may be used such as interviews, psychological tests, observations and experiments. Case studies are generally longitudinal: in other words, they follow the individual or group over an extended period of time. 

Case studies are widely used in psychology and among the best-known ones carried out were by Sigmund Freud . He conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

Case studies provide rich qualitative data and have high levels of ecological validity. However, it is difficult to generalize from individual cases as each one has unique characteristics.

Correlational Studies

Correlation means association; it is a measure of the extent to which two variables are related. One of the variables can be regarded as the predictor variable with the other one as the outcome variable.

Correlational studies typically involve obtaining two different measures from a group of participants, and then assessing the degree of association between the measures. 

The predictor variable can be seen as occurring before the outcome variable in some sense. It is called the predictor variable, because it forms the basis for predicting the value of the outcome variable

Relationships between variables can be displayed on a graph or as a numerical score called a correlation coefficient.

• If an increase in one variable tends to be associated with an increase in the other, then this is known as a positive correlation .
• If an increase in one variable tends to be associated with a decrease in the other, then this is known as a negative correlation .
• A zero correlation occurs when there is no relationship between variables.

After looking at the scattergraph, if we want to be sure that a significant relationship does exist between the two variables, a statistical test of correlation can be conducted, such as Spearman’s rho.

The test will give us a score, called a correlation coefficient . This is a value between 0 and 1, and the closer to 1 the score is, the stronger the relationship between the variables. This value can be both positive e.g. 0.63, or negative -0.63.

A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable. A correlation only shows if there is a relationship between variables.

Correlation does not always prove causation, as a third variable may be involved. 

Interview Methods

Interviews are commonly divided into two types: structured and unstructured.

• Structured interviews are formal. The interview situation is standardized as far as possible. Structured interviews are formal, like job interviews. A fixed, predetermined set of questions is put to every participant in the same order and in the same way.  Responses are recorded on a questionnaire, and the researcher presets the order and wording of questions, and sometimes the range of alternative answers. The interviewer stays within their role and maintains social distance from the interviewee.
• Unstructured interviews are informal, like casual conversations. A general conversation normally precedes them, and the researcher deliberately adopts an informal approach in an attempt to break down social barriers. There are no set questions, and the participant can raise whatever topics he/she feels are relevant and ask them in their own way. Questions are posed about participants’ answers to the subject Unstructured interviews are most useful in qualitative research to analyze attitudes and values. Though they rarely provide a valid basis for generalization, their main advantage is that they enable the researcher to probe social actors’ subjective point of view. 

Questionnaire Method

Questionnaires can be thought of as a kind of written interview. They can be carried out face to face, by telephone, or post.

The choice of questions is important because of the need to avoid bias or ambiguity in the questions, ‘leading’ the respondent or causing offense.

• Open questions are designed to encourage a full, meaningful answer using the subject’s own knowledge and feelings. They provide insights into feelings, opinions, and understanding. Example: “How do you feel about that situation?”
• Closed questions can be answered with a simple “yes” or “no” or specific information, limiting the depth of response. They are useful for gathering specific facts or confirming details. Example: “Do you feel anxious in crowds?”
• Postal questionnaires seem to offer the opportunity of getting around the problem of interview bias by reducing the personal involvement of the researcher. Its other practical advantages are that it is cheaper than face-to-face interviews and can be used to contact many respondents scattered over a wide area relatively quickly.

Observations

There are different types of observation methods :

• Covert observation is where the researcher doesn’t tell the participants that they are being observed until after the study is complete. There could be ethical problems or deception and consent with this particular observation method.
• Overt observation is where a researcher tells the participants that they are being observed and what they are being observed for.
• Controlled : behavior is observed under controlled laboratory conditions (e.g., Bandura’s Bobo doll study).
• Natural : Here, spontaneous behavior is recorded in a natural setting.
• Participant : Here, the observer has direct contact with the group of people they are observing. The researcher becomes a member of the group they are researching.  
• Non-participant (aka “fly on the wall): The researcher does not have direct contact with the people being observed. The observation of participants’ behavior is from a distance

Pilot Study

A pilot  study is a small scale preliminary study conducted in order to evaluate the feasibility of the key s teps in a future, full-scale project.

A pilot study is an initial run-through of the procedures to be used in an investigation; it involves selecting a few people and trying out the study on them. It is possible to save time, and in some cases, money, by identifying any flaws in the procedures designed by the researcher.

A pilot study can help the researcher spot any ambiguities (i.e. unusual things) or confusion in the information given to participants or problems with the task devised.

Sometimes the task is too hard, and the researcher may get a floor effect, because none of the participants can score at all or can complete the task – all performances are low.

The opposite effect is a ceiling effect, when the task is so easy that all achieve virtually full marks or top performances and are “hitting the ceiling”.

Research Design

In cross-sectional research , a researcher compares multiple segments of the population at the same time

Sometimes we want to see how people change over time, as in studies of human development and lifespan. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time.

In cohort studies , the participants must share a common factor or characteristic such as age, demographic, or occupation. A cohort study is a type of longitudinal study in which researchers monitor and observe a chosen population over an extended period.

Triangulation means using more than one research method to improve the validity of the study.

Reliability

Reliability is a measure of consistency, if a particular measurement is repeated and the same result is obtained then it is described as being reliable.

• Test-retest reliability :  assessing the same person on two different occasions which shows the extent to which the test produces the same answers.
• Inter-observer reliability : the extent to which there is an agreement between two or more observers.

Meta-Analysis

A meta-analysis is a systematic review that involves identifying an aim and then searching for research studies that have addressed similar aims/hypotheses.

This is done by looking through various databases and then decisions are made about what studies are to be included/excluded.

Strengths: Increases the conclusions’ validity as they’re based on a wider range.

Weaknesses: Research designs in studies can vary so they are not truly comparable.

Peer Review

A researcher submits an article to a journal. The choice of the journal may be determined by the journal’s audience or prestige.

The journal selects two or more appropriate experts (psychologists working in a similar field) to peer review the article without payment. The peer reviewers assess: the methods and designs used, originality of the findings, the validity of the original research findings and its content, structure and language.

Feedback from the reviewer determines whether the article is accepted. The article may be: Accepted as it is, accepted with revisions, sent back to the author to revise and re-submit or rejected without the possibility of submission.

The editor makes the final decision whether to accept or reject the research report based on the reviewers comments/ recommendations.

Peer review is important because it prevent faulty data from entering the public domain, it provides a way of checking the validity of findings and the quality of the methodology and is used to assess the research rating of university departments.

Peer reviews may be an ideal, whereas in practice there are lots of problems. For example, it slows publication down and may prevent unusual, new work being published. Some reviewers might use it as an opportunity to prevent competing researchers from publishing work.

Some people doubt whether peer review can really prevent the publication of fraudulent research.

The advent of the internet means that a lot of research and academic comment is being published without official peer reviews than before, though systems are evolving on the internet where everyone really has a chance to offer their opinions and police the quality of research.

Types of Data

• Quantitative data is numerical data e.g. reaction time or number of mistakes. It represents how much or how long, how many there are of something. A tally of behavioral categories and closed questions in a questionnaire collect quantitative data.
• Qualitative data is virtually any type of information that can be observed and recorded that is not numerical in nature and can be in the form of written or verbal communication. Open questions in questionnaires and accounts from observational studies collect qualitative data.
• Primary data is first-hand data collected for the purpose of the investigation.
• Secondary data is information that has been collected by someone other than the person who is conducting the research e.g. taken from journals, books or articles.

Validity means how well a piece of research actually measures what it sets out to, or how well it reflects the reality it claims to represent.

Validity is whether the observed effect is genuine and represents what is actually out there in the world.

• Concurrent validity is the extent to which a psychological measure relates to an existing similar measure and obtains close results. For example, a new intelligence test compared to an established test.
• Face validity : does the test measure what it’s supposed to measure ‘on the face of it’. This is done by ‘eyeballing’ the measuring or by passing it to an expert to check.
• Ecological validit y is the extent to which findings from a research study can be generalized to other settings / real life.
• Temporal validity is the extent to which findings from a research study can be generalized to other historical times.

Features of Science

• Paradigm – A set of shared assumptions and agreed methods within a scientific discipline.
• Paradigm shift – The result of the scientific revolution: a significant change in the dominant unifying theory within a scientific discipline.
• Objectivity – When all sources of personal bias are minimised so not to distort or influence the research process.
• Empirical method – Scientific approaches that are based on the gathering of evidence through direct observation and experience.
• Replicability – The extent to which scientific procedures and findings can be repeated by other researchers.
• Falsifiability – The principle that a theory cannot be considered scientific unless it admits the possibility of being proved untrue.

Statistical Testing

A significant result is one where there is a low probability that chance factors were responsible for any observed difference, correlation or association in the variables tested.

If our test is significant, we can reject our null hypothesis and accept our alternative hypothesis.

If our test is not significant, we can accept our null hypothesis and reject our alternative hypothesis. A null hypothesis is a statement of no effect.

In Psychology, we use p < 0.05 (as it strikes a balance between making a type I and II error) but p < 0.01 is used in tests that could cause harm like introducing a new drug.

A type I error is when the null hypothesis is rejected when it should have been accepted (happens when a lenient significance level is used, an error of optimism).

A type II error is when the null hypothesis is accepted when it should have been rejected (happens when a stringent significance level is used, an error of pessimism).

Ethical Issues

• Informed consent is when participants are able to make an informed judgment about whether to take part. It causes them to guess the aims of the study and change their behavior.
• To deal with it, we can gain presumptive consent or ask them to formally indicate their agreement to participate but it may invalidate the purpose of the study and it is not guaranteed that the participants would understand.
• Deception should only be used when it is approved by an ethics committee, as it involves deliberately misleading or withholding information. Participants should be fully debriefed after the study but debriefing can’t turn the clock back.
• All participants should be informed at the beginning that they have the right to withdraw if they ever feel distressed or uncomfortable.
• It causes bias as the ones that stayed are obedient and some may not withdraw as they may have been given incentives or feel like they’re spoiling the study. Researchers can offer the right to withdraw data after participation.
• Participants should all have protection from harm . The researcher should avoid risks greater than those experienced in everyday life and they should stop the study if any harm is suspected. However, the harm may not be apparent at the time of the study.
• Confidentiality concerns the communication of personal information. The researchers should not record any names but use numbers or false names though it may not be possible as it is sometimes possible to work out who the researchers were.
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Mental Health

Strengths and Limitations of The Case Study Method of Psychology

A discussion of the strengths and limitations of the use of case studies in clinical psychology.

Psychology is a study and profession highly driven by research. Through research psychologists are able to formulate theories about an individual’s behaviors, treatment methods, and therapy techniques. Through research, they are also able to go back and revise a theory, treatment, or therapy method, based on outcomes of observation. However, the type of observational research a psychologist chooses is also central to the knowledge being sought. Among different forms of observational research are unsystematic observation, naturalistic observation, controlled observation, and case studies. The latter is the specific form to be discussed within this text.

A case study is study conducted using an individual client or patient (terminology depending on the psychological viewpoint used) who is undergoing treatment (Trull, 2005, pp. 87). This method of psychological research has long been regarded as one of a clinicians most valuable resources in gaining understanding of a patient’s condition, and further research direction. Such cases as “The Case of Dora (Freud, 1905/1953a),” “The Case of Little Hans (Freud, 1909/1955),” “The Three Faces of Eve (Thigpen and Cleckley, 1957),” “The Mask of Sanity (Cleckley, 1964)”, and “Cases in Behavior Modification (Ullman and Krasner, 1965)” have all given clinicians a critical and crucial look into the behaviors and lives of different abnormal minds.*

It is important to understand that no one research method can definitely examine a psychological illness. Likewise, the case study method cannot set precedent for all cases with like patients. For example, a case study on patient Jane Doe, a psychopath, cannot necessarily create a universal principal that applies to all other psychopaths. This is one of the downsides that the case study method presents. However, case studies over history of psychology have been able to provide clinicians with valuable information about different psychological illnesses. Meaning, a particular study can be used as a means of insight into life with the illness, thoughts of the patient; and the formation of hypothesis on behavior, treatments, and further research on the issue at hand. This information is gathered through interviews, test responses, diaries, medical history, biographical and autobiographical accounts and data, treatment responses, etc. (Trull, 2005, pp. 87).

Another downside to the case study method is the completely open and uncontrolled environment in which it takes place. This eliminates it’s usefulness as an indicator of cause and effect since the variables in the study are uncontrolled. This makes it too difficult or presumptuous to state that one value correlates in any way to another. Instead, a clinician can develop a hypothesis on this relationship and use another research method to determine support for, or refutation for, their hypothesis. This is why it was mentioned earlier that case studies can lay down the foundations for further psychological research.

Today, case studies are still highly valued. Former case studies drive psychological education, and current studies expand our understanding of the patient and condition, while opening up new avenues of research. A case study is a very intimate and critical means of understanding an individual patient, especially a severely complex one. Thus, despite the limitations of case studies, they stand as an extremely useful method of psychological research.

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Study Abroad

Case Study Method in Psychology

May 14, 2021 //  by  Amit Kumar

Table of Contents

What is a Case Study Method?

A case study is an in-depth analysis of a person, group, event, or community. In studies, data are collected from various sources like personal interviews , direct observations, psychometric tests, and historical records to find the causes of one’s behaviour.

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Case studies are applied in various study fields like psychology , medicine, anthropology, political science , and social sciences, business, etc.

Case study research methods are often used in clinical medicine to analyze patients’ personal and medical histories.

In psychology, case studies are restricted to the study of a particular individual, his biography, past life, and the current events that are presently happening in one’s day-to-day life.

Case studies offer a systematic approach towards finding events, collecting data, analyzing information, and communicating the results.

Case studies and case methods are often mistaken as the same, but they are not; case methods are research methods used to collect data and analysis that will further generate information needed for case studies.

Strengths of Case Study Method:

case studies can be proved very useful at times. A case study offers a qualitative way of learning about a case through extensive description and contextual analysis.

One of the significant advantages of the case study in psychology is that it helps develop novel hypotheses for later testing.

Some of the other advantages of the case study method are:

• Provides a detailed description of rare and specific cases.
• Provides an opportunity for innovation
• Allow researchers to collect rich qualitative information.
• Allow researchers to challenge theoretical assumptions.

Case studies provide far more detailed information on the rare or hard to study cases and the information concerning measurable or quantitative insights of the case and the detailed information related to the qualitative aspects of human behavior.

Case studies offer in-depth analysis and a multi-sided approach that studies even those aspects of human thinking that is impractical or unethical.

Limitations of case study method:

Following are the disadvantages of the case study method:

• hard to determine cause and effect relationships
• can be possible biased at times
• time-consuming and expensive
• hard to generalize to the large population
• difficult to recreate

How is the case study conducted?

In the case studies, the data and information are collected through personal interviews, direct observations, psychometric tests, and historical records.

The researchers interview the subject of the case, his friends, parents, employer, workmates, and others who know him better and can state reliable facts about him.

The information collected through interviews involves comments from the person’s friends, parents, employer, workmates, etc.

Apart from the interviews, the case study method also involves simple observations concerning what is happening in the subject’s everyday life. It is a prospective method of the case study which means observing an individual for an extended period to study the developments of a particular disease as they happen.

Another method is a retrospective method which involves looking at the historical records of the subject of the case. It means going through the past background of the individual’s life to analyze the factors that have lead to the cause of the particular disease or illness.

The information collected through the case study method is more qualitative, i.e., based on the verbal description of one’s behavior.

After collecting all the data, you can analyze the following information through various techniques and theories like grounded theory, interpretative phenomenological analysis, text interpretation, etc. And then interpret the data and decide what is essential or what is not, and then conclude.

Case study examples

• Genie was a young girl subjected to horrific abuse and isolation. The case study of Genie allowed researchers to study whether language could be taught even after critical periods for language development had been missed. Her case also served as an example of how scientific research may interfere with treatment and lead to further abuse of vulnerable individuals.
• One of the most famous case studies in psychology is that of Chris Sizemore. She was one of the first people diagnosed with multiple personality disorder, now called dissociative identity disorder. In her case, the “alter” personalities were all merged into one character over which she had control. She did, however, remember specific events in her life as happening to particular characters. Her case, diagnosis, and treatment informed treating this mental disorder in a variety of topics over the years, and it was even turned into a movie, Eve
• Anna O. was the pseudonym given to a German woman who was one of the first to undergo psychoanalysis. Her case inspired many of the theories of Freud and other prominent psychologists of the time. It was determined that Anna’s symptoms of depression and illness were eliminated through talk therapy. More recently, it has been suggested that Anna O. had another condition, such as epilepsy, from which she may have recovered during the therapy period. This case study is still cited as a reason psychologists believe that psychotherapy, or talk therapy, can be helpful to many patients.

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Correlation Studies in Psychology Research

Determining the relationship between two or more variables.

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

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

Verywell / Brianna Gilmartin

• Characteristics

Potential Pitfalls

Frequently asked questions.

A correlational study is a type of research design that looks at the relationships between two or more variables. Correlational studies are non-experimental, which means that the experimenter does not manipulate or control any of the variables.

A correlation refers to a relationship between two variables. Correlations can be strong or weak and positive or negative. Sometimes, there is no correlation.

There are three possible outcomes of a correlation study: a positive correlation, a negative correlation, or no correlation. Researchers can present the results using a numerical value called the correlation coefficient, a measure of the correlation strength. It can range from –1.00 (negative) to +1.00 (positive). A correlation coefficient of 0 indicates no correlation.

• Positive correlations : Both variables increase or decrease at the same time. A correlation coefficient close to +1.00 indicates a strong positive correlation.
• Negative correlations : As the amount of one variable increases, the other decreases (and vice versa). A correlation coefficient close to -1.00 indicates a strong negative correlation.
• No correlation : There is no relationship between the two variables. A correlation coefficient of 0 indicates no correlation.

Characteristics of a Correlational Study

Correlational studies are often used in psychology, as well as other fields like medicine. Correlational research is a preliminary way to gather information about a topic. The method is also useful if researchers are unable to perform an experiment.

Researchers use correlations to see if a relationship between two or more variables exists, but the variables themselves are not under the control of the researchers.

While correlational research can demonstrate a relationship between variables, it cannot prove that changing one variable will change another. In other words, correlational studies cannot prove cause-and-effect relationships.

When you encounter research that refers to a "link" or an "association" between two things, they are most likely talking about a correlational study.

Types of Correlational Research

There are three types of correlational research: naturalistic observation, the survey method, and archival research. Each type has its own purpose, as well as its pros and cons.

Naturalistic Observation

The naturalistic observation method involves observing and recording variables of interest in a natural setting without interference or manipulation.  

Can inspire ideas for further research

Option if lab experiment not available

Variables are viewed in natural setting

Can be time-consuming and expensive

Extraneous variables can't be controlled

No scientific control of variables

Subjects might behave differently if aware of being observed

This method is well-suited to studies where researchers want to see how variables behave in their natural setting or state.   Inspiration can then be drawn from the observations to inform future avenues of research.

In some cases, it might be the only method available to researchers; for example, if lab experimentation would be precluded by access, resources, or ethics. It might be preferable to not being able to conduct research at all, but the method can be costly and usually takes a lot of time.  

Naturalistic observation presents several challenges for researchers. For one, it does not allow them to control or influence the variables in any way nor can they change any possible external variables.

However, this does not mean that researchers will get reliable data from watching the variables, or that the information they gather will be free from bias.

For example, study subjects might act differently if they know that they are being watched. The researchers might not be aware that the behavior that they are observing is not necessarily the subject's natural state (i.e., how they would act if they did not know they were being watched).

Researchers also need to be aware of their biases, which can affect the observation and interpretation of a subject's behavior.  

Surveys and questionnaires are some of the most common methods used for psychological research. The survey method involves having a  random sample  of participants complete a survey, test, or questionnaire related to the variables of interest.   Random sampling is vital to the generalizability of a survey's results.

Cheap, easy, and fast

Can collect large amounts of data in a short amount of time

Results can be affected by poor survey questions

Results can be affected by unrepresentative sample

Outcomes can be affected by participants

If researchers need to gather a large amount of data in a short period of time, a survey is likely to be the fastest, easiest, and cheapest option.  

It's also a flexible method because it lets researchers create data-gathering tools that will help ensure they get the information they need (survey responses) from all the sources they want to use (a random sample of participants taking the survey).

Survey data might be cost-efficient and easy to get, but it has its downsides. For one, the data is not always reliable—particularly if the survey questions are poorly written or the overall design or delivery is weak.   Data is also affected by specific faults, such as unrepresented or underrepresented samples .

The use of surveys relies on participants to provide useful data. Researchers need to be aware of the specific factors related to the people taking the survey that will affect its outcome.

For example, some people might struggle to understand the questions. A person might answer a particular way to try to please the researchers or to try to control how the researchers perceive them (such as trying to make themselves "look better").

Sometimes, respondents might not even realize that their answers are incorrect or misleading because of mistaken memories .

Archival Research

Many areas of psychological research benefit from analyzing studies that were conducted long ago by other researchers, as well as reviewing historical records and case studies.

For example, in an experiment known as  "The Irritable Heart ," researchers used digitalized records containing information on American Civil War veterans to learn more about post-traumatic stress disorder (PTSD).

Large amount of data

Can be less expensive

Researchers cannot change participant behavior

Can be unreliable

Information might be missing

No control over data collection methods

Using records, databases, and libraries that are publicly accessible or accessible through their institution can help researchers who might not have a lot of money to support their research efforts.

Free and low-cost resources are available to researchers at all levels through academic institutions, museums, and data repositories around the world.

Another potential benefit is that these sources often provide an enormous amount of data that was collected over a very long period of time, which can give researchers a way to view trends, relationships, and outcomes related to their research.

While the inability to change variables can be a disadvantage of some methods, it can be a benefit of archival research. That said, using historical records or information that was collected a long time ago also presents challenges. For one, important information might be missing or incomplete and some aspects of older studies might not be useful to researchers in a modern context.

A primary issue with archival research is reliability. When reviewing old research, little information might be available about who conducted the research, how a study was designed, who participated in the research, as well as how data was collected and interpreted.

Researchers can also be presented with ethical quandaries—for example, should modern researchers use data from studies that were conducted unethically or with questionable ethics?

You've probably heard the phrase, "correlation does not equal causation." This means that while correlational research can suggest that there is a relationship between two variables, it cannot prove that one variable will change another.

For example, researchers might perform a correlational study that suggests there is a relationship between academic success and a person's self-esteem. However, the study cannot show that academic success changes a person's self-esteem.

To determine why the relationship exists, researchers would need to consider and experiment with other variables, such as the subject's social relationships, cognitive abilities, personality, and socioeconomic status.

The difference between a correlational study and an experimental study involves the manipulation of variables. Researchers do not manipulate variables in a correlational study, but they do control and systematically vary the independent variables in an experimental study. Correlational studies allow researchers to detect the presence and strength of a relationship between variables, while experimental studies allow researchers to look for cause and effect relationships.

If the study involves the systematic manipulation of the levels of a variable, it is an experimental study. If researchers are measuring what is already present without actually changing the variables, then is a correlational study.

The variables in a correlational study are what the researcher measures. Once measured, researchers can then use statistical analysis to determine the existence, strength, and direction of the relationship. However, while correlational studies can say that variable X and variable Y have a relationship, it does not mean that X causes Y.

The goal of correlational research is often to look for relationships, describe these relationships, and then make predictions. Such research can also often serve as a jumping off point for future experimental research. 

Heath W. Psychology Research Methods . Cambridge University Press; 2018:134-156.

Schneider FW. Applied Social Psychology . 2nd ed. SAGE; 2012:50-53.

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

Carpenter S. Visualizing Psychology . 3rd ed. John Wiley & Sons; 2012:14-30.

Pizarro J, Silver RC, Prause J. Physical and mental health costs of traumatic war experiences among civil war veterans .  Arch Gen Psychiatry . 2006;63(2):193. doi:10.1001/archpsyc.63.2.193

Post SG. The echo of Nuremberg: Nazi data and ethics .  J Med Ethics . 1991;17(1):42-44. doi:10.1136/jme.17.1.42

Lau F. Chapter 12 Methods for Correlational Studies . In: Lau F, Kuziemsky C, eds. Handbook of eHealth Evaluation: An Evidence-based Approach . University of Victoria.

Akoglu H. User's guide to correlation coefficients .  Turk J Emerg Med . 2018;18(3):91-93. doi:10.1016/j.tjem.2018.08.001

Price PC. Research Methods in Psychology . California State University.

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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In psychology researches, several methods are used, for example experiment, observation and case studies. What are the strengths and weaknesses of case study method?

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• Open access
• Published: 31 October 2023

Social media usage and students’ social anxiety, loneliness and well-being: does digital mindfulness-based intervention effectively work?

BMC Psychology volume  11 , Article number:  362 ( 2023 ) Cite this article

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The increasing integration of digital technologies into daily life has spurred a growing body of research in the field of digital psychology. This research has shed light on the potential benefits and drawbacks of digital technologies for mental health and well-being. However, the intricate relationship between technology and psychology remains largely unexplored.

This study aimed to investigate the impact of mindfulness-based mobile apps on university students' anxiety, loneliness, and well-being. Additionally, it sought to explore participants' perceptions of the addictiveness of these apps.

The research utilized a multi-phase approach, encompassing a correlational research method, a pretest–posttest randomized controlled trial, and a qualitative case study. Participants were segmented into three subsets: correlations ( n  = 300), treatment ( n  = 60), and qualitative ( n  = 20). Data were gathered from various sources, including the social anxiety scale, well-being scale, social media use integration scale, and an interview checklist. Quantitative data was analyzed using Pearson correlation, multiple regression, and t-tests, while qualitative data underwent thematic analysis.

The study uncovered a significant correlation between social media use and the variables under investigation. Moreover, the treatment involving mindfulness-based mobile apps led to a reduction in students' anxiety and an enhancement of their well-being. Notably, participants held various positive perceptions regarding the use of these apps.

Implications

The findings of this research hold both theoretical and practical significance for the field of digital psychology. They provide insight into the potential of mindfulness-based mobile apps to positively impact university students' mental health and well-being. Additionally, the study underscores the need for further exploration of the intricate dynamics between technology and psychology in an increasingly digital world.

Peer Review reports

Introduction

The field of digital psychology is undergoing rapid evolution, navigating the intricate intersection of psychology and technology to elucidate the profound impact of digital technologies on human behavior, cognition, and emotions [ 1 , 2 ]. With digital technologies becoming increasingly ingrained in our daily lives, researchers are embarking on a journey to explore the multifaceted implications they bear for mental health and overall well-being. Within the realm of digital psychology, a diverse array of topics has captured the attention of investigators, encompassing the innovative use of technology for psychological interventions like cognitive-behavioral therapy (CBT) and mindfulness-based stress reduction (MBSR) [ 1 , 2 ]. Furthermore, scrutiny has extended to the influence of social media on mental health, unveiling the potential for excessive social media use to contribute to feelings of anxiety and loneliness [ 3 , 4 ].

The exploration of digital psychology has also delved into the impact of video games on cognitive and emotional faculties, with some studies suggesting that specific genres of video games have the potential to enhance attention and problem-solving skills [ 5 , 6 ]. However, concerns surrounding video game addiction and the potential influence of violent video games on aggressive behavior have been the subject of extensive investigation [ 7 , 8 , 9 , 10 ]. The ubiquity of digital technologies in our daily existence has ignited a burgeoning interest in the domain of digital psychology. While research in this domain has yielded valuable insights into the prospective benefits and hazards of digital technologies for mental health and well-being, there remains a vast expanse of knowledge yet to be uncovered regarding the intricate interplay between technology and psychology. Specifically, there is a compelling need for an extensive body of research aimed at comprehending the enduring impacts of digital technologies on cognitive, emotional, and social functionality. Furthermore, it is crucial to decipher how these effects may vary among diverse demographic groups.

One particularly promising avenue of research within digital psychology is the integration of mindfulness-based mobile applications, which has shown considerable potential in alleviating symptoms of anxiety and loneliness. These applications typically offer guided meditation, breathing exercises, and various mindfulness practices that are readily accessible via mobile devices [ 2 ]. Their accessibility and user-friendly nature render them an appealing resource for individuals seeking to enhance their mental well-being without the need for traditional face-to-face therapy [ 3 , 6 ].

In the contemporary landscape of higher education, university students are exposed to the pervasive influence of social media, which has the potential to induce negative psychological consequences such as heightened social anxiety and increased feelings of loneliness. The omnipresence of social media platforms can foster a sense of comparison, social pressure, and disconnection among undergraduate students, amplifying the challenges they already face. Given these circumstances, there is a compelling need to explore interventions that can counteract these adverse impacts, and mindfulness-based interventions emerge as a promising avenue for consideration.

By examining the intersection of these interventions with the digital sphere, this study seeks to illuminate how Digital Mindfulness-based treatments might serve as a potent tool to mitigate the detrimental effects of social media exposure, thereby fostering a healthier psychological landscape among university students [ 11 , 12 , 13 , 14 , 15 ].

Furthermore, many of these applications provide personalized features such as progress tracking and goal setting, which enhance user engagement and motivation [ 9 ]. As the popularity of these applications continues to soar, it becomes imperative to further investigate their effectiveness across various demographic cohorts and contextual settings, as well as to identify the most potent features and interventions for fostering improvements in mental health [ 10 ].

The rationale for this study is firmly grounded in the contemporary higher education landscape, where undergraduate students navigate a myriad of challenges that may impact their mental well-being. With the pervasive integration of digital technologies into students' lives, the investigation of Digital Mindfulness-based interventions becomes not only relevant but crucial. The novelty of this study lies in its exploration of the intricate relationship between social media usage and the well-being of university students, specifically targeting social anxiety and loneliness. Moreover, it introduces an innovative approach by examining the effectiveness of digital mindfulness-based interventions in ameliorating these psychological challenges. By addressing this uncharted territory, the study not only contributes to the growing field of digital psychology but also offers valuable insights into the potential of technology-driven mindfulness interventions as a means to enhance the mental well-being of the digital-native student population. This unique blend of investigating the impact of technology on psychological well-being while simultaneously assessing the effectiveness of digital interventions positions the study at the forefront of contemporary research in the field. Given the potential benefits of digital mindfulness apps in reducing anxiety and loneliness, coupled with the distinct challenges that emerge during the undergraduate phase, this research seeks to provide invaluable insights into the perceptions and experiences of students. By delving into the perceptions of adults regarding these treatments, this study aspires to shed light on the feasibility, effectiveness, and potential limitations of digital mindfulness-based interventions for enhancing the mental health of undergraduate students in the modern digital age. Therefore, this study endeavors to address the following critical questions:

What is the relationship between social media use and symptoms of social anxiety, loneliness, and well-being among university students?

Does the use of a mindfulness-based mobile app intervention result in significant improvements in social anxiety, loneliness, and well-being in college students?

What are university students’ perspectives on the use of technology for mental health support, including the benefits and challenges of using technology for this purpose?

Review of literature

Theoretical background.

The study investigating the effects of mindfulness-based mobile apps on university students' anxiety, loneliness, and well-being in the context of social media usage draws upon a multifaceted theoretical framework. At its core, it is rooted in mindfulness theory, which emphasizes present-moment awareness and non-judgmental acceptance to alleviate stress and anxiety [ 5 , 6 , 7 , 8 ]. To understand the influence of social media on students, social cognitive theory is relevant, as it explores how individuals learn from observing others in their social networks. Additionally, social comparison theory informs the study by shedding light on how students may constantly compare themselves to others on social media, potentially leading to feelings of loneliness and social anxiety [ 11 , 12 , 13 , 14 , 15 ]. The study also taps into addiction and compulsive behavior theories to comprehend the perceived addictiveness of mindfulness-based mobile apps. Technology acceptance models (TAM) help in understanding user acceptance and perceptions of these apps. Moreover, the study aligns with principles of positive psychology by aiming to enhance well-being and reduce anxiety and loneliness, which are central concerns in this field. Finally, media effects theories, like cultivation theory and uses and gratifications theory, inform the exploration of how social media use affects students' mental health and well-being [ 13 ]. This multifaceted theoretical approach provides a comprehensive foundation for unraveling the intricate relationship between technology, psychology, and well-being in the digital age, offering a well-rounded perspective on the research questions at hand [ 12 , 13 ].

Social media and symptoms of mental health

The use of social media has become increasingly prevalent among university students, and with it comes growing concern about its potential impact on mental health and well-being. Specifically, research has focused on the relationship between social media use and symptoms of social anxiety, loneliness, and well-being among university students. The majority of studies focused on the relationship between social media use and symptoms of social anxiety and/or loneliness. These studies generally found that higher levels of social media use were associated with greater symptoms of social anxiety and loneliness among university students [ 11 , 12 , 13 , 14 , 15 , 16 ]. For example, Schønning et al. [ 16 ] found that social media use was positively associated with symptoms of social anxiety among Chinese university students. Similarly, a study by Wang et al. [ 13 ] found that social media use was positively associated with symptoms of loneliness among Chinese university students.

Two studies focused on the relationship between social media use and well-being. One study found that higher levels of social media use were associated with lower levels of well-being among university students [ 17 ] Another study found that social media use had a curvilinear relationship with well-being, such that moderate levels of social media use were associated with higher levels of well-being, while both low and high levels of social media use were associated with lower levels of well-being [ 13 ].

The findings of this literature review suggest that social media use may be associated with greater symptoms of social anxiety and loneliness among university students. However, the relationship between social media use and well-being is less clear, with some studies suggesting a negative relationship and others suggesting a curvilinear relationship. Several additional studies have also examined this relationship. For example, a study by Kose and Dogan [ 18 ] found that social media use was negatively associated with psychological well-being among Turkish university students. Another study by Błachnio, et al., [ 19 ] found that Facebook addiction was negatively associated with self-esteem and life satisfaction among Polish university students. Similarly, Chen et al. [ 20 ] conducted a systematic review of 23 studies examining the relationship between social media use and mental health outcomes among college students. The authors concluded that social media use was generally associated with negative mental health outcomes, including loneliness, anxiety, and stress. However, they noted that the strength of this relationship varied across studies and suggested that more research was needed to better understand the mechanisms underlying this relationship. In another study, Seabrook et al. [ 21 ] conducted a systematic review of 20 studies examining the relationship between social networking sites and loneliness and anxiety. They found that social networking sites were associated with both loneliness and anxiety, but that the strength of this relationship varied across studies and depended on factors such as frequency and intensity of social networking site use and individual differences in vulnerability to mental health problems. Similarly, Tandoc Jr. et al. [ 14 ] conducted a study examining the relationship between Facebook use, envy, and depression among college students in the United States. They found that Facebook use was positively associated with envy, which in turn was positively associated with depression. They suggested that envy may be a mechanism underlying the relationship between social media use and negative mental health outcomes.

Mindfulness-based apps effect mental health

Mindfulness-based mobile apps are becoming increasingly popular as a tool for promoting mental health and wellbeing. These apps include a variety of different mindfulness-based practices, such as guided meditations, breathing exercises, and other techniques aimed at reducing stress and anxiety. While there is growing evidence that mindfulness-based interventions can be effective in promoting mental health, less is known about the effectiveness of these interventions when delivered via mobile apps. This literature review aims to synthesize the existing research on mindfulness-based mobile apps and mental health outcomes.

The majority of studies focused on the effectiveness of mindfulness-based mobile apps in reducing symptoms of anxiety and depression. These studies generally found that mindfulness-based mobile apps were effective in reducing symptoms of anxiety and depression in a variety of populations, including college students, adults, and individuals with chronic medical conditions [ 2 , 10 , 22 , 23 , 24 ]. For example, a study by Strauss et al. [ 23 ] found that a mindfulness-based mobile app was effective in reducing stress and improving coping skills in a sample of healthcare workers. Similarly, a study by Lomas et al. [ 24 ] found that a mindfulness-based mobile app was effective in reducing stress and improving resilience in a sample of university students. In addition to examining the effectiveness of mindfulness-based mobile apps, several studies explored the factors that influence user engagement and adherence to these interventions. For example, a study by Valinskas et al. [ 25 ] that users who were using the app for more than 24 days and had at least 12 active days during that time had 3.463 (95% CI 1.142–11.93) and 2.644 (95% CI 1.024–7.127) times higher chances to reduce their DASS-21 subdomain scores of depression and anxiety, respectively. Another study by Linardon, et al. [ 22 ] found that interventions that were more interactive and personalized were more effective in promoting user engagement and adherence.

Some studies also explored the effectiveness of mindfulness-based mobile apps in addressing other mental health conditions beyond anxiety and depression. For example, a study by Wahbeh et al. [ 10 ] found that a mindfulness-based mobile app intervention was effective in reducing symptoms of posttraumatic stress disorder (PTSD) in a sample of veterans. Similarly, a study by Biegel et al. [ 26 ] found that a mindfulness-based mobile app intervention was effective in reducing symptoms of ADHD in a sample of adolescents.

The use of technology for mental health support

The utilization of technology for the provision of mental health support has gained increasing prominence within the context of university students, prompting a burgeoning interest in comprehending their encounters and viewpoints. Related inquiries have been undertaken in diverse geographical regions, including the United States, Canada, Australia, and the United Kingdom. Predominantly, these investigations have centered on the advantages and obstacles inherent in employing technology for mental health support. Generally, these inquiries have ascertained that technology is perceived as a convenient and readily accessible modality for accessing mental health support services among university students [ 27 , 28 , 29 , 30 ]. For instance, Birnbaum et al. [ 27 ] conducted a study revealing that college students in the United States exhibited a willingness to engage with mental health applications to manage their stress and anxiety. Nevertheless, certain studies have also discerned impediments associated with the adoption of technology for mental health support, encompassing apprehensions regarding privacy and confidentiality [ 27 , 28 , 29 , 30 ], concerns about the quality and dependability of information [ 29 ], and challenges related to navigating and effectively utilizing mental health applications [ 30 ].

Additionally, two investigations have focused their attention on delineating the determinants influencing the utilization of technology for mental health support among university students. These studies have identified an array of factors exerting an influence over students' engagement with technology for mental health support, encompassing individual attributes (e.g., mental health literacy, technological attitudes) [ 31 ], societal influences (e.g., stigma, peer support) [ 31 ], and environmental considerations (e.g., technology availability, access to mental health services). The cumulative insights garnered from this comprehensive literature review underscore the potential of technology as a convenient and accessible avenue for accessing mental health support among university students. However, it is essential to acknowledge that complexities and multifaceted dynamics underlie the factors influencing its utilization, and an array of challenges remain associated with its application in this context.

Likewise, a study conducted by Kern et al. [ 32 ] documented that 23.8% of users reported experiencing a positive impact on their mental health through the use of mental health applications. Notably, individuals who had received mental health services within the past 12 months exhibited a significantly higher propensity to embrace mental health apps in comparison to those who had not accessed such services. The allure of convenience, immediate availability, and confidentiality emerged as prevalent factors driving interest in Mental Health Apps (MHAs).

Furthermore, a study conducted by Free et al. [ 33 ] unveiled the unsurprising proliferation of numerous mobile applications designed to aid in the diagnosis, monitoring, and management of health conditions, albeit with varying levels of efficacy. Similarly, research by Brindal et al. [ 34 ] found that participants who had intermittent access to a smartphone app over a 4-week trial period demonstrated notable enhancements in indicators of emotional well-being. This broader observation suggests that uncomplicated and easily accessible solutions can yield substantial improvements in overall well-being. In addition, a study by Karyotaki et al. [ 35 ] reported the effectiveness of web-based interventions in mitigating the symptoms of depression and anxiety among college students.

Methodology

This was a multi-phase research design. In the first phase, a correlational research method was used for exploring the correlation among the research variables. In the second phase, we used a pretest–posttest randomized controlled trial to assess the effectiveness of a mindfulness-based mobile app intervention on symptoms of anxiety, loneliness, and well-being. Moreover, in the third phase, a qualitative research method was used for exploring the participants’ perceptions of mindfulness-based intervention.

Participants

Participants for this study were selected from graduate students at Zhoukou Vocational and Technical College in China. Three separate groups were recruited for the study. The first group consisted of 300 participants who were recruited for a correlational study related to question 1. The eligibility criteria for this group were as follows: participants must be graduate students at Fudan University and willing to participate in the study. The sample size was determined based on power analysis and the expected effect size. The second group consisted of 100 participants who were recruited for question 2. The eligibility criteria for this group were the same as for the first group. Participants were randomly assigned to either an intervention group or a control group. The third group consisted of 20 participants who were recruited for question 3. The eligibility criteria for this group were the same as for the first two groups. Participants were selected using purposive sampling based on their responses to the questionnaire in question 2. All participants provided informed consent prior to participating in the study. The study was approved by the Institutional Review Board at Zhoukou Vocational and Technical College. Participants were assured of confidentiality and the right to withdraw from the study at any time without penalty.

The following instruments were used to collect data for this study:

Social Anxiety Scale for Adolescents (SAS-A)

It is a 22-item self-report questionnaire that measures social anxiety in adolescents [ 36 ]. SAS-A assesses various aspects of social anxiety, including fear of negative evaluation, social avoidance and distress, and physiological symptoms such as sweating and blushing. Each item is measured on a 5-point Likert scale, ranging from 1 (not at all) to 5 (extremely). The total score on the SAS-A ranges from 22 to 110, with higher scores indicating higher levels of social anxiety.

Warwick-Edinburgh Mental Well-being Scale (WEMWBS)

It is a 14-item self-report questionnaire that measures mental well-being in adults and adolescents [ 37 ]. The items on the WEMWBS assess various aspects of mental well-being, including optimism, positive relationships, and a sense of purpose. Participants rate each item on a 5-point Likert scale, ranging from 1 (none of the time) to 5 (all of the time). The total score on the WEMWBS ranges from 14 to 70, with higher scores indicating higher levels of mental well-being. The fourth instrument was social.

Social Media Use Integration Scale (SMUIS)

The SMUIS is a 10-item self-report questionnaire that assesses the frequency, duration and emotional connection to social media use [ 38 ]. The SMUIS includes questions related to the frequency and duration of social media use, as well as questions related to the emotional connection to social media use, such as "How often do you feel happy when using social media?" and "How often do you feel anxious when you are not able to use social media?" Participants are asked to rate each item on a 5-point Likert scale, ranging from 1 (never) to 5 (always). The reliability of the instruments was estimated using Cronbach’s alpha. Results revealed that the obtained Cronbach’s alpha for the instrument was above, 0.78 indicating that all used instruments enjoyed an acceptable level of reliability.

Interview checklist

The interview checklist consisted of 8 open-ended questions followed by the interviewer’s prompts. The questions elicited the interviewees’ perceptions of the benefits and challenges of using mobile apps for improving mental health and well-being and reducing social anxiety symptoms and loneliness (See Additional file 1 ). The interview checklist was approved by 4 colleagues and there was a high agreement among the panel of experts regarding the relevance of the interview questions.

Mindfulness-based mobile apps

Mindfulness-based mobile apps are mobile applications designed to help individuals develop mindfulness skills and reduce symptoms of stress, anxiety, and depression. These apps typically include guided mindfulness exercises, educational resources, and other features to help individuals practice mindfulness on a regular basis. The specific features of mindfulness-based mobile apps may vary but typically include guided meditations, breathing exercises, and other mindfulness practices. Some apps may also include educational resources, such as articles or videos that provide information about mindfulness and its benefits. Many apps also include features for tracking progress, setting goals, and sharing progress with others. In this study, the participants who participated in the treatment phase were asked to download popular mindfulness-based mobile apps including Headspace, Calm, and Insight Timer. These apps are available for download on mobile devices and offer a range of mindfulness exercises and resources for users to explore.

The study was conducted in multiple steps. Initially, a sample of 300 graduate students from Fudan University was selected to participate in the research. These participants were asked to complete the Social Media Use Integration Scale (SMUIS) and the Depression Anxiety Stress Scales (DASS-21) to evaluate their social media use and mental health status. Next, a sample of 60 students from the same university was selected for the intervention study. These participants were randomly assigned to either an intervention group or a control group. The intervention group was given access to a mindfulness-based mobile app for eight weeks, while the control group received no intervention. Both groups completed the SMUIS and the DASS-21 at baseline, post-intervention, and three-month follow-up to evaluate the effectiveness of the intervention. Lastly, a qualitative study was conducted to gather in-depth information about the participants' experience with the mindfulness-based mobile app intervention. A purposive sample of 20 participants from the intervention group was selected for this study. They underwent semi-structured interviews to provide qualitative data about their perceptions and opinions regarding the intervention.

Data analysis

For the quantitative data, the statistical software was employed. Firstly, descriptive statistics were calculated to determine the mean, and standard deviation of the Social Media Use Integration Scale (SMUIS) and Depression Anxiety Stress Scales (DASS-21) scores, as well as the mean, and standard deviation of the SMUIS and DASS-21 scores at baseline, post-intervention, and three-month follow-up for both the intervention and control groups. Secondly, bivariate correlations were conducted to examine the relationship between social media use and symptoms of anxiety and depression. Thirdly, multiple regression analysis was performed to determine the unique contribution of social media use to symptoms of anxiety and depression while controlling for other relevant variables. Fourthly, repeated measures ANOVA was conducted to examine changes in SMUIS and DASS-21 scores over time and to determine if there were differences between the intervention and control groups. Finally, post hoc tests were conducted to examine differences between groups at each time point. Effect sizes were calculated to determine the magnitude of the intervention's effects. However, for the qualitative data, the qualitative analysis software was employed. Firstly, the transcripts of the semi-structured interviews were analyzed using thematic analysis to identify themes and subthemes related to participants' experiences with the mindfulness-based mobile app intervention. Secondly, quotes were selected to support and illustrate the identified themes and subthemes. Lastly, the themes and subthemes were interpreted and discussed to provide insight into participants' perceptions and opinions regarding the intervention.

Research question1

Pearson correlations between the variables were estimated and results are presented in Table 1 .

This table shows that social media use is negatively correlated with well-being ( r  = -0.21, p  < 0.01) and positively correlated with symptoms of social anxiety ( r  = -0.35, p  < 0.01) and loneliness ( r  = 0.24, p  < 0.01). Additionally, symptoms of social anxiety are positively correlated with loneliness ( r  = 0.47, p  < 0.01) and negatively correlated with well-being ( r  = -0.61, p  < 0.01), while loneliness is negatively correlated with well-being ( r  = -0.50, p  < 0.01). These results suggest that social media use is associated with poorer mental health outcomes, including higher levels of social anxiety and loneliness and lower levels of well-being, among university students.

Table 2 shows the results of a multiple regression analysis that examined the relationship between social media use, social anxiety, and loneliness as predictor variables and well-being as the outcome variable. The regression equation is:

The results indicate that all three predictor variables significantly contributed to the prediction of well-being, with social media use (β = -0.29, p  = 0.001), social anxiety (β = 0.31, p  = 0.001), and loneliness (β = 0.28, p  = 0.001) each having a significant unique effect on well-being, after controlling for the other variables. The constant term (B = 3.10, p  = 0.001) represents the predicted well-being score when all predictor variables are held at zero.

Research question 2

The second research aimed at investigating the effects of the intervention on the students’ social anxiety, loneliness, and well-being. Results are presented in Table 3 .

This table presents the results of a pretest–posttest randomized control-experimental research design investigating the effects of a mindfulness-based mobile app intervention on social anxiety, loneliness, and well-being in college students. The results indicate that the intervention group showed a significant improvement in social anxiety (F (1, 98) = 17.23, p  < 0.001, partial eta squared = 0.15), loneliness (F (1, 98) = 13.70, p  < 0.001, partial eta squared = 0.12), and well-being (F(1, 98) = 21.41, p  < 0.001, partial eta squared = 0.18) from pretest to posttest. The control group did not show significant changes in any of the measures. The effect sizes (partial eta squared) ranged from moderate to large, indicating that the intervention had a meaningful impact. These findings suggest that the use of a mindfulness-based mobile app intervention can be an effective approach for improving mental health outcomes in college students.

Research question 3

The third research question explored the students’ perceptions of the effects of mindfulness-based mobile apps on the students’ social anxiety, loneliness, and well-being. The detailed analysis of the interviews revealed 6 benefits and 4 challenges of using technology for mental health support. The first extracted benefit as mentioned by 10 students was thematically coded "Convenience and Accessibility". Participants reported that technology-based mental health support services are convenient and accessible, allowing them to access support anytime and anywhere. The following quotations exemplify the theme:

"I like using mental health apps because I can access them whenever I need to. I don't have to wait for an appointment or anything like that." (Student 3). Another student stated, "Online support groups are great because I can connect with people who have similar experiences no matter where I am."(student 11).

The second extracted benefit was thematically coded "Anonymity and Privacy". Participants appreciated the ability to access mental health support services online while maintaining anonymity and privacy. For instance, student 5 stated, "I like that I can access support without having to go to an office or talk to someone face-to-face. It feels less intimidating." This finding was also confirmed by student 6, who stated, "I feel more comfortable talking about my mental health online because I know that no one else needs to know about it."

The third extracted benefit was thematically coded "Customizable and Tailored Support". Participants appreciated the range of options available for mental health support online, including customizable and tailored support that they could access at their own pace. For instance, student 11 stated, "I like that I can choose the type of support that works for me. Some days I just need to read something and other days I need to talk to someone”. Similarly, student 6 stated, "The mental health app I use sends me reminders to check in with myself and practice self-care. It's nice to have that kind of tailored support."

The fourth extracted benefit was thematically coded as "Cost-effective". Participants reported that technology-based mental health support services are often more affordable than traditional face-to-face therapy, making them a more accessible option for those with limited financial resources. This finding was supported by student 17 who stated, "I can't afford traditional therapy, so using mental health apps is a great option for me since it's usually free or very affordable." Similarly, one of the students stated, “Online therapy is much cheaper than traditional therapy, so it's more accessible for people who can't afford to pay a lot."

The fifth extracted benefit was thematically coded as "Increased Awareness and Education". Participants reported that technology-based mental health support services helped them to become more aware of their mental health and provided education about mental health issues and coping strategies. For example, student 12 stated, "The mental health app I use has taught me a lot about mindfulness and how to manage my anxiety." Student 14 also stated, "I learned a lot about depression and how to cope with it from an online support group I joined."

The sixth extracted benefit was thematically coded as "Reduced Stigma". Participants reported that accessing mental health support services online helped to reduce the stigma associated with seeking mental health The following quotations exemplify the theme of support. For instance, one of the students stated, “I used to feel ashamed about seeking mental health support, but using mental health apps has helped me realize that it's okay to take care of my mental health." (Student 9). Similarly, another student argued, “Online support groups have helped me realize that I'm not alone in my struggles with mental health. It's nice to know there are others out there who understand."

Despite the above-mentioned benefits, the participants mentioned some challenges. The first extracted challenge was thematically coded "Quality and Accuracy of Information". Participants expressed concerns about the quality and accuracy of mental health information available online, and the potential for misinformation to be spread. For instance, student 11 stated, "There's so much information online, it's hard to know what's trustworthy and what's not." Another student stated, "I worry that some of the mental health information I see online is not based on evidence and could actually be harmful."(student 6).

The second extracted challenge was thematically coded as "Lack of Human Connection". Participants reported missing the human connection they would get from traditional face-to-face therapy and felt that technology-based mental health support services lacked the same level of personal connection. The following quotations from student 12 exemplify the theme:

"Sometimes I just need someone to talk to face-to-face. It's not the same as talking to a computer screen…. I miss the empathetic listening I would get from a therapist in person. It's hard to replicate that online."

The third extracted challenge was thematically coded as "Technical Difficulties". Participants reported experiencing technical difficulties with technology-based mental health support services, which could be frustrating and hinder their ability to access support. For instance, student 8 stated, “Sometimes the mental health app I use glitches or crashes, which can be really frustrating when I'm trying to use it for support…. I don't have the best internet connection, so sometimes it's hard to access online support groups."

The fourth extracted challenge was thematically coded "Privacy and Security Concerns". Participants expressed concerns about the privacy and security of their personal information when using technology-based mental health support services, and whether their information was being shared without their consent. As an example, student 13 stated, "I worry that my personal information could be shared without my consent, which would be a huge breach of trust." Student 9 also stated, “It's hard to know if my information is really secure when I'm using online mental health support services."

The study investigating the effects of mindfulness-based mobile apps on university students' anxiety, loneliness, and well-being in the context of social media usage is anchored in a multifaceted theoretical framework. At its core, the research draws upon mindfulness theory, a foundational framework emphasizing present-moment awareness and non-judgmental acceptance to alleviate stress and anxiety [ 5 , 6 , 7 , 8 ]. This theory forms the bedrock of the study's understanding, as mindfulness-based mobile apps are designed to foster these very principles, encouraging users to engage with the present, accept their experiences without judgment, and, in doing so, mitigate stress and anxiety.

In parallel, to fathom the intricate influence of social media on university students, the study leverages social cognitive theory, a framework highly pertinent for analyzing how individuals acquire and adapt behaviors, attitudes, and emotional responses through observation and modeling within their social networks [ 11 , 12 , 13 , 14 , 15 ]. Given the pervasive role of social media, this theory is essential for comprehending how the behaviors, emotions, and attitudes of students may be shaped by the content and interactions they encounter in the digital realm.

Moreover, the research takes into consideration social comparison theory, which underscores how social media users frequently engage in relentless self-comparisons with others, potentially fostering feelings of loneliness and social anxiety [ 11 , 12 , 13 , 14 , 15 ]. This theory is critical for acknowledging the "highlight reel" effect, wherein users predominantly share their positive experiences and achievements, inadvertently prompting social comparison and potentially engendering negative emotional responses.

In the exploration of the perceived addictiveness of mindfulness-based mobile apps, the study employs addiction and compulsive behavior theories. These theories unearth the underlying factors contributing to the allure and habit-forming nature of certain digital interventions, thereby offering valuable insights into the psychology of user engagement and potential addiction [ 12 , 13 ]. When assessing user acceptance and perceptions of mindfulness-based mobile apps, the study draws from technology acceptance models (TAM). TAM provides a valuable framework for unraveling the intricacies of user adoption and attitudes toward technology-based interventions, elucidating critical factors like perceived usefulness and ease of use, which shed light on participants' acceptance of these apps [ 12 , 13 ].

Furthermore, the research aligns with the principles of positive psychology, a framework that centers on the enhancement of human well-being and strengths. The study's focus on bolstering well-being and mitigating anxiety and loneliness aligns closely with the core tenets of positive psychology, making it a pertinent theoretical perspective [ 12 , 13 ].

Lastly, media effects theories, such as cultivation theory and uses and gratifications theory, play a pivotal role in offering insights into how social media usage affects students' mental health and well-being [ 13 ]. Cultivation theory underscores the potential long-term impact of repeated exposure to media content, while uses and gratifications theory delves into how individuals actively use and engage with media to fulfill specific needs and gratifications.

By encompassing this multifaceted theoretical approach, the study constructs a comprehensive foundation for unraveling the intricate relationship between technology, psychology, and well-being in the digital age. This holistic perspective serves as a valuable compass in navigating the complexities of the research questions at hand, offering a deeper understanding of how these factors interconnect and influence one another [ 12 , 13 ]. Additionally, the study incorporates media effects theories to further enrich its theoretical foundation. Cultivation theory, as one of the key media effects theories, underlines the potential long-term consequences of repeated exposure to media content. Given the omnipresence of social media in the lives of university students, understanding how continuous media exposure might shape their perceptions and attitudes is crucial [ 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. Moreover, uses and gratifications theory plays a pivotal role by exploring how individuals actively engage with media to fulfill specific needs and gratifications. In the context of the study, this theory sheds light on why students turn to social media, whether it's for social interaction, information seeking, or entertainment, and how these purposes might be linked to their mental well-being [ 13 ].

To round out the comprehensive theoretical framework, the study interweaves elements of positive psychology. This perspective emphasizes the enhancement of human well-being, positive emotions, and strengths. By striving to boost well-being and alleviate symptoms of anxiety and loneliness, the study directly aligns with the core principles of positive psychology. Positive psychology focuses on fostering qualities like resilience, optimism, and emotional intelligence, which are highly relevant to the study's objectives [ 46 , 47 , 48 , 49 , 50 ]. Thus, this framework adds a positive, growth-oriented dimension to the study's theoretical foundation, underscoring the importance of not only addressing negative mental health outcomes but also promoting positive psychological well-being [ 12 , 13 ].

In summary, the multifaceted theoretical framework encompassing mindfulness theory, social cognitive theory, social comparison theory, addiction and compulsive behavior theories, technology acceptance models (TAM), positive psychology, and media effects theories creates a robust and comprehensive foundation for unraveling the intricate relationship between technology, psychology, and well-being in the digital age. This holistic perspective enables the study to navigate the complexities of its research questions, offering a deeper understanding of how these factors interconnect and influence one another, and providing valuable insights into the impact of technology-driven interventions on the mental well-being of university students.

Conclusions

It can be concluded that the current findings add to the growing body of literature suggesting that social media use is linked to negative mental health outcomes. However, it is important to note that the causal direction of these relationships remains unclear. Although social media use may contribute to negative mental health outcomes, it is also possible that individuals who are already experiencing symptoms of anxiety and loneliness may use social media as a coping mechanism or to seek social support. Therefore, more research is needed to understand the complex relationship between social media use and mental health outcomes. It can also be concluded that the use of technology-based interventions can provide increased accessibility and convenience, anonymity and privacy, customizable and tailored support, cost-effectiveness, increased awareness and education, and reduced stigma. These findings demonstrate the potential of technology to offer effective and accessible mental health support for individuals in need.

The implications of investigating the relationship between social media usage and students' social anxiety, loneliness, and well-being within the context of digital mindfulness-based intervention are multifaceted. Firstly, as social media becomes increasingly integrated into students' lives, the study underscores the significance of understanding its potential repercussions on mental health. The findings can offer valuable insights to educational institutions, mental health professionals, and policymakers, prompting them to recognize the importance of promoting responsible social media usage among students. Secondly, the study's exploration of the effectiveness of digital mindfulness-based interventions in alleviating social anxiety, loneliness, and enhancing well-being holds significant implications for mental health intervention strategies. If proven efficacious, these interventions could serve as a practical and accessible means of addressing the psychological challenges posed by social media usage. This could potentially guide the development of tailored programs aimed at improving students' mental health and emotional resilience in the digital age. Furthermore, the study's focus on digital mindfulness-based interventions acknowledges the evolving nature of psychological interventions in the digital era. The implications of successful intervention highlight the potential of technology-assisted approaches to bridge the gap between traditional therapeutic methods and the modern digital landscape. This insight could inspire further innovation in mental health care, encouraging the integration of technology to reach wider audiences and promote positive mental well-being [ 51 ].

The current study also provides evidence that the intervention was effective in improving mental health outcomes over time. However, the study design does not allow us to determine the specific mechanisms by which the intervention was effective. Therefore, more research is needed to better understand how interventions can be optimized to improve mental health outcomes. Finally, while technology-based interventions can provide benefits such as convenience and accessibility, concerns about the quality and accuracy of mental health information available online, the lack of personal connection compared to traditional face-to-face therapy, and technical difficulties with accessing support have been reported by participants in this study.

Availability of data and materials

The data will be made available upon request from the author ( email: [email protected]).

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Acknowledgements

The authors would like to thank all participants.

Phased Results of Key Projects of Vocational Education and Teaching Reform in Henan Province in 2021 (Project No.: Yujiao [2021] 57946).

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Li Sun designed the study. Li Sun collected the data. Li Sun analyzed and interpreted the data, drafted the manuscript, proofread the paper, and verified the submitted version.

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The ethical approval committee of Zhoukou Vocational and Technical College approved this study and issued a letter (No. 2023.2623), indicating the study has no side effects on the participants of the study. All experiments were performed in accordance with relevant guidelines and regulations. All methods were carried out in accordance with relevant guidelines and regulations.

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Sun, L. Social media usage and students’ social anxiety, loneliness and well-being: does digital mindfulness-based intervention effectively work?. BMC Psychol 11 , 362 (2023). https://doi.org/10.1186/s40359-023-01398-7

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Received : 29 August 2023

Accepted : 16 October 2023

Published : 31 October 2023

DOI : https://doi.org/10.1186/s40359-023-01398-7

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