assessment

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The direction and magnitude of a correlation are often calculated numerically

and expressed by a statistical term called the correlation coefficient. The correlation coefficient can vary from +1.00, which indicates a perfect positive correlation between two variables, down to −1.00, which represents a perfect negative correlation. The sign of the coefficient (+ or −) signifies the direction of the correlation; the number represents its magnitude. An r of .00 reflects a zero correlation, or no relationship between variables. The closer r is to .00, the weaker, or lower in magnitude, the correlation. Thus correlations of +.75 and −.75 are of equal magnitude and equally strong (just in opposite directions),

whereas a correlation of +.25 is weaker than either.

Everyone’s behavior is changeable, and many human responses can be measured only approximately. Most correlations found in psychological research, therefore, fall short of a perfect positive or negative correlation. For

example, hundreds of studies of life stress and depression, conducted over the past half-century, have found correlations as high as +.53 (Krishnan, 2019; Miller, Ingham, & Davidson, 1976). Although hardly perfect, a correlation of this magnitude is considered large in psychological research.

When Can Correlations Be Trusted? Scientists must decide whether the correlation they find in a given sample of participants accurately reflects a real correlation in the general population. Could the observed correlation have occurred by mere chance? Scientists can never know for certain, but they can test their conclusions with a statistical analysis of their data, using principles of probability. In essence, they ask how likely it is that the study’s particular findings have occurred by chance. If the statistical analysis indicates that chance is unlikely to account for the correlation they found, researchers may conclude that their findings reflect a real correlation in the general population.

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A cutoff point helps researchers make this decision. By convention, if there is less than a 5 percent probability that a study’s findings are due to chance (signified as p < .05), the findings are said to be statistically significant and are thought to reflect a true correlation in the larger population. In one of the life

stress and depression studies described earlier, a statistical analysis indicated a probability of less than 5 percent that the +.53 correlation found in its sample was due to chance. Therefore, the researchers concluded with some confidence that among adults in general — that is, not just those in the study sample — depression does tend to rise along with the amount of recent stress in a person’s life. Generally, a researcher’s confidence increases with the magnitude of the correlation and the size of the sample. The larger they each are, the more likely it is that a correlation will be statistically significant.

Stress and depression A woman rendered homeless by the 2018 “Camp Fire” in Paradise, California, the deadliest of the state’s 25,000 wildfires from 2017 through

2019, ponders her ordeal and uncertain future at a tent city formed for victims in a nearby Walmart parking lot. Studies find that the stress produced by this and similar

natural disasters has been accompanied by depression and other psychological symptoms in many victims.

What Are the Merits of the Correlational

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Method? The correlational method has certain advantages over the case study (see Table 2-1). First, it possesses higher external validity. Because correlation researchers measure their variables, observe large samples, and apply statistical analyses, they are in a better position to generalize their conclusions to people beyond the ones they have studied. Furthermore, researchers can easily repeat correlational studies using new samples of participants to check the results of earlier studies.

TABLE: 2-1

Relative Strengths and Weaknesses of Research Methods

Provides Individual Information

Provides General Information

Provides Causal Information

Statistical Analysis Possible

Replicable

Case Study Yes No No No No

Correlational Method

No Yes No Yes Yes

Experimental Method

No Yes Yes Yes Yes

On the other hand, correlational studies, like case studies, lack internal validity. Although correlations allow researchers to describe the relationship between

two variables, they do not explain the relationship. When we look at the positive correlation found in many life stress studies, we may be tempted to conclude that increases in recent life stress cause people to feel more depressed. In fact, however, the two variables may be correlated for any one of three reasons: (1) Life stress may cause depression. (2) Depression may cause people to experience more life stress (for example, a depressive approach to life may cause people to perform poorly at work or may interfere with social relationships). (3) Depression and life stress may each be caused by a third

variable, such as financial problems.

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Twins, correlation, and inheritance Two twins prepare to participate in a 5K race in

Kalamazoo, Michigan, organized by Girls on the Run, a program designed to help foster the physical, psychological, and social development of preteen girls. Although

these twins are perfectly healthy—physically and psychologically—correlational studies of many pairs of twins have suggested a link between genetic factors and certain psychological disorders. Identical twins (who have identical genes) display a

higher correlation for some disorders than do fraternal twins (whose genetic makeup is not identical).

Can you think of other correlations in life that are interpreted mistakenly as causal?

Although correlations say nothing about causation, they can still be of great use to clinicians. Clinicians know, for example, that suicide attempts increase as people become more depressed. Thus, when they work with severely depressed clients, they stay on the lookout for signs of suicidal thinking. Perhaps depression directly causes suicidal behavior, or perhaps a third variable, such as a sense of hopelessness, causes both depression and suicidal thoughts. Whatever the cause, just knowing that there is a correlation may enable clinicians to take measures (such as hospitalization) to help save lives.

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Of course, in other instances, clinicians do need to know whether one variable causes another. Do parents’ marital conflicts cause their children to be more anxious? Does job dissatisfaction lead to feelings of depression? Will a given treatment help people to cope more effectively in life? Questions about causality

call for the experimental method.

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The Experimental Method

AN EXPERIMENT IS a research procedure in which a variable is manipulated and the manipulation’s effect on another variable is observed (Cherry, 2019b). In fact, most of us perform experiments throughout our lives without knowing that we are behaving so scientifically. Suppose that you go to a party on campus to celebrate the end of midterm exams. As you mix with people at the party, you begin to notice many of them becoming quiet and gloomy. It seems the more you talk, the more subdued the other guests become. As the party falls apart before your eyes, you decide you have to do something, but what? Before you

can eliminate the problem, you need to know what’s causing it.

Your first hunch may be that something you’re doing is responsible. Perhaps your remarks about academic pressures have been upsetting everyone. You decide to change the topic to skiing in the mountains of Colorado and to watch

for signs of dejection in the next round of conversations. The problem seems to clear up; most people now smile and laugh as they chat with you. As a final check of your suspicions, you could go back to talking about school with the next several people you meet. Their dark and dismal reaction would probably convince you that your tendency to talk about school was indeed the cause of the problem.

You have just performed an experiment, testing your hypothesis about a causal relationship between your topic of conversation and the gloomy mood of the people around you. You manipulated the variable that you suspected to be the cause (the topic) and then observed the effect of that manipulation on the other variable (the mood of the people around you). In scientific experiments, the

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manipulated variable is called the independent variable and the variable being observed for change is called the dependent variable.

To examine the experimental method more fully, let’s consider a question that is often asked by clinicians (Armour, Ee, & Steiner, 2019; Comer & Bry, 2019): “Does a particular therapy relieve the symptoms of a particular disorder?” Because this question is about a causal relationship, researchers may use an experiment to answer it (see Table 2-2). They may give the therapy in question to people who are suffering from a disorder and then observe whether they improve. In this experiment, the therapy is the independent variable, and psychological

improvement is the dependent variable.

TABLE: 2-2

Most Investigated Questions in Clinical Research

Most Common Correlational Questions Most Common Causal Questions

Are stress and onset of mental disorders related? Does factor X cause a disorder?

Is culture (or gender or race) generally linked to mental disorders?

Is cause A more influential than cause B?

Are income and mental disorders related? How do family communication and structure affect family members?

Are social skills tied to mental disorders? How does a disorder affect the quality of a person’s life?

Are family conflict and mental disorders related? Does treatment X alleviate a disorder?

Is treatment responsiveness tied to culture? Is treatment X more helpful than no treatment at all?

Which symptoms of a disorder appear together? Is treatment A more helpful than treatment B?

How common is a disorder in a particular population? Why does treatment X work?

  Can an intervention prevent abnormal functioning?

If the true cause of changes in the dependent variable cannot be separated from

other possible causes, then an experiment gives very little information (see InfoCentral). Thus, experimenters must try to eliminate all confounds from their studies — variables other than the independent variable that may also be

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affecting the dependent variable. When there are confounds in an experiment, they, rather than the independent variable, may be causing the observed changes.

INFOCENTRAL RESEARCHING RESEARCH

Clinical researchers have conducted an enormous number of studies and investigated behavior,

thinking, and feeling from every angle. But one thing they have not studied much is the process of

research itself. That has begun to change in recent years, as investigators have looked increasingly at

the participants, scientists, and behind-the-scene factors that comprise the research enterprise.

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For example, situational variables, such as the location of the therapy office (say, a quiet country setting) or soothing background music in the office, may have a therapeutic effect on participants in a therapy study. Or perhaps the participants are unusually motivated or have high expectations that the therapy will work, factors that thus account for their improvement. To guard against confounds,

researchers should include three important features in their experiments — a

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control group, random assignment, and a masked design (Comer & Bry, 2019; Manohar et al., 2019).

Is animal companionship a form of therapy? A ring-tailed lemur at Serengeti Park near Hodenhagen, Germany, is part of a monthly program called “Psychiatric Animal Days,” based on the premise that animals — even lemurs — have a calming effect on

people. More than 400 kinds of intervention are currently used for psychological problems. An experimental design is needed to determine whether this or any other

treatment causes clients to improve.

The Control Group A control group is a group of research participants who are not exposed to the independent variable under investigation but whose experience is otherwise

similar to that of the experimental group, the participants who are exposed to the independent variable. By comparing the two groups, an experimenter can better determine the effect of the independent variable.

To study the effectiveness of a particular therapy, for example, experimenters

commonly divide participants into two groups after obtaining their consent to participate in the study. The experimental group may come into an office and receive the therapy for an hour, while the control group may simply come into

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the office for an hour. If the experimenters find later that the people in the experimental group improve more than the people in the control group, they may conclude that the therapy was effective, above and beyond the effects of time, the office setting, and any other confounds. To guard against confounds,

experimenters try to provide all participants, both control and experimental, with experiences that are identical in every way — except for the independent variable.

Of course, it is possible that the differences observed between an experimental group and control group have occurred simply by chance. Thus, as with

correlational studies, investigators who conduct experiments must do a statistical analysis on their data and find out how likely it is that the observed differences are due to chance. If the likelihood is very low — less than 5 percent (p < .05) — the differences between the two groups are considered to be statistically significant, and the experimenter may conclude with some confidence that they are due to the independent variable. As a general rule, if the sample of participants in an experiment is large, if the difference observed between groups is great, and if the range of scores within each group is small,

the findings of the study are likely to be statistically significant.

An additional point is worth noting with regard to clinical treatment experiments. It is always important to distinguish between statistical significance and a notion called clinical significance (Comer & Bry, 2019). As you have just

read, statistical significance indicates whether a participant’s improvement in functioning — large or small — occurred because of treatment. Clinical significance indicates whether the amount of improvement is meaningful in the individual’s life. Even if the moods of depressed participants improve because of treatment, the individuals may still be too unhappy to enjoy life.

Random Assignment Researchers must also watch out for differences in the makeup of the experimental and control groups since those differences may also confound a

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study’s results. In a therapy study, for example, the experimenter may unintentionally put wealthier participants in the experimental group and poorer ones in the control group. This difference, rather than their therapy, may be the cause of the greater improvement later found among the experimental

participants. To reduce the effects of preexisting differences between groups, experimenters typically use random assignment. This is the general term for any selection procedure that ensures that every participant in the experiment is as likely to be placed in one group as the other (Armour et al., 2019; Comer & Bry, 2019), as though group assignments are being determined by flipping a coin or picking names out of a hat. In practice, researchers typically use a computer program that assigns participants to groups randomly.

Masked Design A final confound problem is bias. Participants may bias an experiment’s results by trying to please or help the experimenter. In a therapy experiment, for example, if those participants who receive the treatment know the purpose of the study and which group they are in, they might actually work harder to feel better or to fulfill the experimenter’s expectations. If so, subject, or participant, bias rather than therapy could be causing their improvement.

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Why might sugar pills or other kinds of placebo treatments help some people feel better?

To avoid this bias, experimenters can prevent participants from finding out which group they are in. This experimental strategy is called a masked design (previously termed a blind design) because the individuals are kept unaware of their assigned group (Armour et al., 2019). In a therapy study, for example, control participants could be given a placebo (Latin for “I shall please”), something that looks or tastes like real therapy but has none of its key ingredients. For example, control participants might receive an “imitation” therapy, called placebo therapy, such as attending weekly “sessions” to discuss life events with a therapist, but not being taught the same coping skills as those taught to participants in the true therapy condition. If the experimental (true

therapy) participants then improve more than the control (placebo therapy) participants, experimenters have more confidence that the true therapy has caused their improvement.

An experiment may also be confounded by experimenter bias — that is,

experimenters may have expectations that they unintentionally transmit to the participants in their studies. In a drug therapy study, for example, the experimenter might smile and act confident while providing real medications to the experimental participants but frown and appear hesitant while offering placebo drugs to the control participants. This kind of bias is sometimes referred to as the Rosenthal effect, after the psychologist who first identified it (Rosenthal, 1966). Experimenters can eliminate their own bias by arranging to be unaware themselves. In a drug therapy study, for example, an aide could make sure that

the real medication and the placebo drug look identical. The experimenter could then administer treatment without knowing which participants were receiving true medications and which were receiving false medications.

While either the participants or the experimenter may be kept unaware in an experiment, it is best that both be unaware — a research strategy called a

double-masked design. In fact, most medication experiments now use double-

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masked designs to test promising drugs. Many experimenters also arrange for judges to assess and statistically analyze the patients’ improvement independently, and the judges too are kept unaware of the group assignments.

 

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Alternative Research Designs

IT IS NOT ALWAYS EASY to devise an experiment that is fully controlled and that randomly assigns participants to groups. Prevention of every possible confound is rarely achievable. Moreover, because psychological experiments typically use living beings, ethical and practical considerations limit the kinds of manipulations one can do. Thus clinical scientists must often settle for research designs that are less than ideal. These alternative designs are often called quasi- experimental designs — designs that fail to include key elements of a “pure” experiment and/or intermix elements of both experimental and correlational

studies (Fetters, 2019). Such variations include the matched design, natural experiment, analogue experiment, single-case experiment, longitudinal study, and epidemiological study.

Matched Designs In many studies, investigators must make use of groups that already exist in the world at large. Consider, for example, research into the effects of child abuse. Because it would be unethical for investigators of this issue to create an experimental group by actually abusing a randomly chosen group of children, they must instead compare children who already have a history of abuse with children who do not. Though necessary for ethical reasons, this strategy violates

the rule of random assignment and so introduces possible confounds into the study. Children who receive excessive physical punishment, for example, more commonly come from more highly stressed and larger families than children who are punished verbally. Any differences found later in the moods or self- concepts of the two groups of children may be the result of differences in family stress or size rather than physical abuse.

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Child-abuse researchers often try to minimize such confound problems by using a matched design (Guha et al., 2019). They match the experimental participants with control participants who are similar in age, sex, race, family size, socioeconomic status, type of neighborhood, or other characteristics. When the

data from studies using this kind of design show that abused children are typically sadder and have lower self-esteem than matched control participants who have not been abused, the investigators can conclude with some confidence that abuse is causing the differences (Chan, Chen, & Chen, 2019; Saito et al., 2019).

Natural Experiments In natural experiments, nature itself manipulates the independent variable, while the experimenter observes the effects. Natural experiments must be used for studying the psychological effects of unusual and unpredictable events, such as floods, earthquakes, plane crashes, and fires. Because the participants in

these studies are selected by an accident of fate rather than by the investigators’ design, natural experiments are in fact quasi-experiments.

of NOTE … People Who Purchased This Participant Also Purchased …

Many researchers are now finding study participants on Amazon’s Mechanical Turk digital platform.

The researchers (known as Requesters) post their studies (online surveys and the like) on this Internet marketplace, and participants (called Providers or Turkers) choose which studies they want to sign up

for. Participants receive payment (usually a small amount) via an Amazon.com gi� certificate, and

Amazon receives 10 percent of the participant’s reimbursement.

On December 26, 2004, an earthquake occurred beneath the Indian Ocean off

the coast of Sumatra, Indonesia. The earthquake triggered a series of massive tsunamis that flooded the ocean’s coastal communities, killed more than 228,000 people, and injured and left millions of survivors homeless, particularly in Indonesia, Sri Lanka, India, and Thailand. Within months of this disaster,

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researchers conducted natural experiments in which they collected data from hundreds of survivors and from control groups of people who lived in areas not directly affected by the tsunamis. The disaster survivors scored significantly higher on anxiety and depression measures (dependent variables) than the

controls did. The survivors also experienced more sleep problems, feelings of detachment, arousal, difficulties concentrating, startle responses, and guilt feelings than the controls did (Adebäck, Schulman, & Nilsson, 2018; Reid, 2018). Over the past decade, other natural experiments have focused on survivors of Haiti’s earthquake in 2010, Japan’s massive earthquake in 2011, and the Northeast’s Superstorm Sandy in 2012, as well as the devastating hurricanes in Houston, Florida, Puerto Rico, and the Bahamas and the raging wildfires in California in 2018 and 2019 (Dick et al., 2019; Furr et al., 2018). These studies

have also revealed lingering psychological symptoms among survivors of those disasters (Gonzalez et al., 2019; Pittman et al., 2019).

Because each natural event is unique in certain ways, broad generalizations drawn from a single study could be incorrect. Nevertheless, catastrophes have provided opportunities for hundreds of natural experiments over the years,

enabling clinical scientists to identify patterns of reactions that people often have across such situations. You will read about these patterns — acute stress disorders and posttraumatic stress disorders — in Chapter 6.

Analogue Experiments There is one way in which investigators can manipulate independent variables relatively freely while avoiding some of the ethical and practical limitations of clinical research. They can induce laboratory participants to behave in ways that seem to resemble real-life abnormal behavior and then conduct experiments on the participants in the hope of shedding light on the real-life abnormality. This is

called an analogue experiment.

Analogue studies often use animals as participants. While the needs and rights of animal subjects must be considered, most experimenters believe that the

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insights gained from such experimentation outweigh the discomfort of the animals, as long as their distress is not excessive or unnecessary (Hvitved, 2019). In addition, experimenters can, and often do, use human participants in analogue experiments.

Do outside restrictions on research — either animal or human studies — interfere with necessary investigations and thus limit potential gains for human beings?

As you’ll see in Chapter 7, investigator Martin Seligman, in a classic body of work, has used analogue studies with great success to investigate the causes of human depression. Seligman has produced depression-like symptoms in laboratory participants — both animals and humans — by repeatedly exposing them to negative events (shocks, loud noises, task failures) over which they have

no control. In these “learned helplessness” analogue studies, the participants seem to give up, lose their initiative, and become sad — suggesting to some clinicians that human depression itself may indeed be caused by loss of control over the unpleasant events in one’s life.

Of course, the laboratory-induced learned helplessness produced in Seligman’s

analogue experiments is not known with certainty to be analogous to human depression. If this laboratory phenomenon is actually only superficially similar to depression, then the clinical inferences drawn from such experiments may be misleading. This, in fact, is the major limitation of all analogue research: researchers can never be certain that the phenomena they see in the laboratory are the same as the psychological disorders they are investigating.

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Similar enough? Seven-year-old chimpanzee Rudi and his trainer get ready to play a

round of golf. Despite their shared interest and despite the fact that chimps and humans share more than 90 percent of their genetic material, the brains and bodies

of the two species are very different, as are their perceptions and experiences. Thus, abnormal-like behavior produced in animal analogue experiments may differ from

the human abnormality under study.

Single-Case Experiments Sometimes scientists do not have the luxury of experimenting on many participants. They may, for example, be investigating a disorder so rare that few participants are available. Research is still possible, however, with a single-case experimental design, also called a single-subject experimental design (Byiers, 2019; Kazdin, 2019). Here a single participant is observed both before and after the manipulation of an independent variable. Single-case experiments rely first on baseline data — information gathered prior to any manipulations. These data set a standard with which later changes may be compared. The experimenter next introduces the independent variable and again observes the participant’s behavior. Any changes in behavior are attributed to the effects of the independent variable.

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For example, using a particular kind of single-case experimental design, called an ABAB, or reversal, design, one researcher sought to determine whether the systematic use of rewards would reduce a teenage boy’s habit of disrupting his special education class with loud talk (Deitz, 1977). He rewarded the boy, who

suffered from intellectual disability, with extra teacher time whenever he went 55 minutes without interrupting the class more than three times. In condition A, the student was observed prior to receiving any reward, and he was found to disrupt the class frequently with loud talk. In condition B, the boy was given a series of teacher reward sessions (introduction of the independent variable); as expected, his loud talk decreased dramatically. Next, the rewards from the teacher were stopped (condition A again), and the student’s loud talk increased once again. Apparently the independent variable had indeed been the cause of

the improvement. To be still more confident about this conclusion, the researcher had the teacher apply reward sessions yet again (condition B again). Once again the student’s behavior improved.

of NOTE … Their Words

“All life is an experiment.”

Ralph Waldo Emerson

Obviously, single-case experiments are similar to individual case studies in their focus on one participant. In single-case experiments, however, the independent

variable is manipulated systematically so that the investigator can, with some degree of confidence, draw conclusions about the cause of an observed effect (Kazdin, 2019). At the same time, because only one person is investigated in a single-case experiment, the researcher cannot be sure that the participant’s reaction to the independent variable is typical of people in general.

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Longitudinal Studies In longitudinal studies (also called high-risk or developmental studies), researchers observe the same individuals on many occasions over a long period of time (Anderson, 2019). In several such studies, investigators have observed the progress over the years of normally functioning children whose mothers or

fathers suffered from schizophrenia (Vargas et al., 2019; Yung et al., 2019). The researchers have found, among other things, that the children of the parents with the most severe cases of schizophrenia were particularly likely to develop a psychological disorder and to commit crimes at later points in their development.

As with some of the other quasi-experiments, researchers do not directly manipulate the independent variable or randomly assign participants to conditions in a longitudinal study, and so they cannot definitively pinpoint causes. However, because longitudinal studies report the order of events, they do provide compelling clues about which events are more likely to be causes and which are more likely to be consequences. Certainly, in the above example, the children’s problems did not cause their parents’ schizophrenia.

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Life is a longitudinal study These similarly posed photos of the same individuals at different points in their lives underscore the logic behind longitudinal studies. Just as the individuals’ eyes, noses, and smiles in childhood

predict similar facial features in adulthood, so too might a person’s early temperament, sociability, or other psychological features sometimes predict adult characteristics or difficulties.

Epidemiological Studies Epidemiological studies reveal how often a problem, such as a particular psychological disorder, occurs in a particular population (McBride, Ogbo, & Page, 2019). More specifically, they determine the incidence and prevalence of the problem. Incidence is the number of new cases that emerge in a population during a given period of time. Prevalence is the total number of cases in the population during a given period; prevalence includes both existing and new

cases.

Over the past 50 years, clinical researchers throughout the United States have worked on one of the largest epidemiological studies of mental disorders ever conducted, called the Epidemiologic Catchment Area Study (McDonald, 2019;

Munro et al., 2019). They have interviewed more than 20,000 people in five cities to determine the prevalence of many psychological disorders in the United States and the treatment programs used. Three other large-scale epidemiological studies in the United States — the National Comorbidity Survey, the National Comorbidity Survey Replication, and the National Epidemiologic Survey on Alcohol and Related Conditions — have collectively questioned almost 60,000 individuals (Coccaro, 2019; Olfson et al., 2019; Kessler, 2017, 1990). Findings from these broad-population studies have been further compared with

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epidemiological studies of specific sub-populations, such as Hispanic Americans and Asian Americans, or with epidemiological studies conducted in other countries, to see how rates of mental disorders and treatment programs vary from population to population and from country to country (Loo, 2019; Sibrava

et al., 2019; Woo et al., 2019).

Such epidemiological studies have helped researchers identify groups at risk for particular disorders. Women, it turns out, have a higher rate of anxiety disorders and depression than men, while men have a higher rate of alcoholism than women. Elderly people have a higher rate of suicide than young people. Hispanic

Americans, African Americans, and American Indians experience posttraumatic stress disorder more than non-Hispanic white Americans in the United States. And persons in Western countries have higher rates of eating disorders than those in non-Western ones. These trends may lead researchers to suspect that something unique about certain populations or settings is helping to cause particular disorders. Declining health in elderly people, for example, may make them more likely to consider and complete suicide. Similarly, the pressures or attitudes common in one country may be responsible for a rate of mental

dysfunction that differs from the rate found in another. Yet, epidemiological studies alone cannot confirm such suspicions of causation.

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Protecting Human Participants

LIKE THE ANIMAL SUBJECTS that you read about earlier, human research participants have needs and rights that must be respected (see MindTech). In fact, researchers’ primary obligation is to avoid harming the human participants in their studies — physically or psychologically.

MINDTECH The Use and Misuse of Social Media

Over the past several years, more and more researchers have been turning to social networks for

their studies. One pioneering study demonstrated the power and potential of using social media

data (Kosinski et al., 2016; Kosinski, Stillwell, & Graepel, 2013). In this investigation, 58,000 Facebook

subscribers allowed the researchers access to their list of “likes,” and the subscribers further filled

out online personality tests. The study found that information about a participant’s likes could

predict with some accuracy the individual’s personality traits, level of happiness, use of addictive

substances, and level of intelligence, among other variables. Similarly, other studies have predicted

individuals’ traits, attitudes, feelings, and the like based on information from their Facebook posts

and their tweets (Matz, Appel, & Kosinski, 2020).

What a great resource, right? Not so fast. This study did ask subscribers whether they were willing to

participate. However, in a number of other such studies, social media users do not know that their

posted data are being examined and tested. The researchers in such studies typically assert that

because posted information is already publicly available, users need not be informed that their data

are under examination — a view that has produced enormous debate.

In what ways should ethical standards for Internet and social media studies be different from those applied to other kinds of research?

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An area that has raised additional ethical concerns involves the direct and secret manipulation of

social media users by researchers — an approach illustrated in a controversial study conducted by a

team of researchers from Facebook and academia several years ago (Kramer, Guillory, & Hancock,

2014). The investigators wanted to determine whether the content of Facebook news feeds

influences its users’ moods. Without informing users, the researchers reduced the number of positive

news feed posts seen by around 350,000 users and reduced the number of negative posts seen by

another 350,000 users over a one-week period. As a result, the moods of the former users became

slightly (but significantly) more negative than those of the latter users.

One concern with this study was, once again, that the users were unaware of and did not give proper

informed consent for their participation. Critics were unimpressed with the claim that signing on to

Facebook’s lengthy, small-print, and sophisticated user agreement represents a sufficient form of

informed consent for this or similar social media studies (Pagoto & Nebeker, 2019). Another

significant concern was that, by inducing negative moods, the researchers in this study might have

been feeding into the clinical depressions of some negative news feed users.

A core problem for all social media studies is that most social media sites do not have clear policies

prohibiting researchers from studying subscribers or subscriber profiles without clear permission.

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Moreover, the federal regulations that are in place to protect human research participants do not yet

adequately address the ethical use of social media data (Pagoto & Nebeker, 2019). Such deficiencies

were highlighted recently when a political consulting firm named Cambridge Analytica

acknowledged that while working for one of the presidential campaigns in 2016, its researchers had

misled 300,000 Facebook users into believing they were participating in a personality study and

releasing their user data for academic purposes. Actually, when the users downloaded an app in the

study, it opened up both their own data and that of their friends, revealing the private user data of

around 50 million Facebook members. The consulting firm then derived psychological profiles of

those members and produced and applied personalized advertisements favoring the candidate for

whom they were consulting, that appealed to the users’ emotions, attitudes, and needs — a strategy

called psychological targeting (Matz et al., 2020).

Partly in response to studies that target user data for political advertising, Facebook has recently

joined with the Social Science Research Council (a national institution) to develop an oversight

program for reviewing, approving, and monitoring studies in which Facebook user data are

requested (SSRC, 2019). This collaborative undertaking, called the Social Data Initiative, is in its early

stages and only focuses on the release of data that may impact elections and politics. However,

many researchers hope that it will eventually lead to effective ethical guidelines for other kinds of

social media studies as well, including academic psychology studies. In the meantime, while the

technology-driven questions of what’s public, what’s private, and what’s a proper use of data are

under debate, it is probably best that social media users follow an increasingly sacred rule of our

digital world — “poster beware.”

of NOTE … Ethically Challenged Research Designs

Symptom-Exacerbation Studies In some studies, patients are given drugs to intensify their

symptoms so that researchers may learn more about the biology of their disorder.

Medication-Withdrawal Studies In some studies, researchers prematurely stop medications for patients who have been symptom-free for a while, hoping to learn more about when patients can be

taken off particular medications.

The vast majority of researchers are conscientious about fulfilling this obligation. They try to conduct studies that test their hypotheses and further scientific knowledge in a safe and respectful way (Gelling, 2019). But there have been

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some notable exceptions to this over the years, particularly several infamous studies conducted in the mid-twentieth century. Partly because of such exceptions, the government and the institutions in which research is conducted now take careful measures to ensure that the safety and rights of human

research participants are properly protected.

Who, beyond researchers themselves, might directly watch over the rights and safety of human participants? For the past few decades, that responsibility has been given to Institutional Review Boards, or IRBs. Each research facility has an IRB — a committee of five or more members who review and monitor every

study conducted at that institution, starting when the studies are first proposed (Balon et al., 2019). The institution may be a university, medical school, psychiatric or medical hospital, private research facility, mental health center, or the like. If research is conducted there, the institution must have an IRB, and that IRB has the responsibility and power to require changes in a proposed study as a condition of approval. If acceptable changes are not made by the researcher, then the IRB can disapprove the study altogether. Similarly, if over the course of the study, the safety or rights of the participants are placed in

jeopardy, the IRB must intervene and can even stop the study if necessary. These powers are granted to IRBs (or similar ethics committees) by nations around the world. In the United States, for example, IRBs are empowered by two agencies of the federal government — the Office for Human Research Protections and the Food and Drug Administration.

It turns out that protecting the rights and safety of human research participants is a complex undertaking. Thus, IRBs often are forced to conduct a kind of risk– benefit analysis in their reviews. They may, for example, approve a study that poses minimal or slight risks to participants if that “acceptable” level of risk is offset by the study’s potential benefits to society. In general, IRBs try to ensure that each study grants the following rights to its participants:

The participants enlist voluntarily. Before enlisting, the participants are adequately informed about what the study entails (“informed consent”).

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A national disgrace In a 1997 White House ceremony,

President Bill Clinton offers an official apology to 94- year-old Herman Shaw and other African American

men whose syphilis was purposefully le� untreated by government doctors and researchers in the Tuskegee

Syphilis Study, a research undertaking conducted from 1932 to 1972, prior to the emergence of Institutional

Review Boards. In this infamous study on the natural course of untreated syphilis, 399 participants were not

informed that they had the disease, and they continued to go untreated even a�er it was discovered

that penicillin is an effective intervention.

The participants can end their participation in the study at any time. The benefits of the study outweigh its costs/risks to participants. The participants are protected from physical and psychological harm. The participants have access to information about the study. The participants’ privacy is protected by principles such as confidentiality or anonymity.

Unfortunately, even with IRBs on the job, these rights can be in jeopardy. Consider, for example, the right of informed consent. To help ensure

that participants understand what they are getting into when they enlist for a study, IRBs typically require that the individuals read and sign an “informed consent form” that spells out everything they need to know. But how clear are such forms? Not very, according to some

investigations (Nathe & Krakow, 2019; Young, 2019; Le et al., 2018).

It turns out that most such forms — the very forms deemed acceptable

by IRBs — are too long and/or are written at a college level, making them incomprehensible to a large percentage of participants. In fact, fewer than half of all participants may fully understand the informed

consent forms they are signing. Still other investigations indicate that only a minority of human participants ask questions of researchers during the

informed consent phase of a study and fewer still carefully read the informed

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consent forms before signing them. The Office for Human Research Protections has tried to address such issues — through better researcher education, advice to researchers, and even new regulations. For example, the federal agency instituted a formal requirement in 2019 that all informed consent forms must

begin with a clear and concise summary of the most important information about the study — information that would most affect an individual’s decision to participate or not.

In short, the IRB system is flawed, much like the research undertakings it oversees. One reason for this is that ethical principles are subtle notions that do

not always translate into simple guidelines. Another reason is that ethical decisions — whether by IRB members or by researchers — are subject to differences in perspective, interpretation, decision-making style, and the like. Despite such problems, most observers agree that the creation and work of IRBs have helped improve the rights and safety of human research participants over the years.

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SUMMING UP

What Do Clinical Researchers Do?

Researchers use the scientific method to uncover nomothetic principles of abnormal psychological functioning. They attempt to identify and examine relationships between variables and depend primarily on three methods of investigation: the case study, the correlational method, and the experimental method. p. 26

The Case Study

A case study is a detailed account of a person’s life, psychological problems, and, in some instances, treatment. It can serve as a source of ideas about behavior, provide support for theories, challenge theories, clarify new treatment

techniques, or offer an opportunity to study an unusual problem. However, case studies tend to have low internal validity and low external validity. pp. 27–29

The Correlational Method

Correlational studies are used to systematically observe the degree to which

events or characteristics vary together. This method allows researchers to draw broad conclusions about abnormality in the population at large.

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A correlation may have a positive or negative direction and may be high or low in magnitude. Researchers perform a statistical analysis to determine whether the correlation found in a study is truly characteristic of the larger population or due to chance. Correlational studies generally can have high external validity but lack

internal validity. pp. 30–33

The Experimental Method

In experiments, researchers manipulate suspected causes to see whether expected effects will result. The variable that is manipulated is called the

independent variable, and the variable that is expected to change as a result is called the dependent variable. Experimental studies generally have high internal validity inasmuch as they enable researchers to control variables and determine causation. They have relatively high external validity as well.

To minimize the possible influence of confounds, experimenters use control groups, random assignment, and masked designs. The findings of experiments, like those of correlational studies, must be analyzed statistically. pp. 34–37

Alternative Research Designs

Clinical scientists must often settle for alternative research designs that are less than ideal, called quasi-experimental designs. These include the matched design, natural experiment, analogue experiment, single-case experiment, longitudinal study, and epidemiological study. pp. 37–42

Protecting Human Participants

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Each research facility has an Institutional Review Board (IRB) that has the power and responsibility to protect the rights and safety of human participants in all studies conducted at that facility. Members of the IRB review each study before participant recruitment and can require changes in the study before granting

approval for the undertaking. Among the important participant rights that the IRB protects is the right of informed consent, an acceptable risk–benefit balance, and privacy (confidentiality or anonymity). pp. 42–44

Keeping an Eye on Research Methods

To help address the many practical, logistical, and ethical factors that often make properly designed research difficult to do, clinical investigators must use multiple research approaches. p. 44

Visit LaunchPad to access the e-book, Clinical Choices, videos, activities, and

LearningCurve, as well as study aids including flashcards, FAQs, and research exercises.

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C H A P T E R 3

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Models of Abnormality

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TOPIC OVERVIEW

The Biological Model How Do Biological Theorists Explain Abnormal Behavior? Biological Treatments Assessing the Biological Model

The Psychodynamic Model How Did Freud Explain Normal and Abnormal Functioning? How Do Other Psychodynamic Explanations Differ from Freud’s? Psychodynamic Therapies Assessing the Psychodynamic Model

The Cognitive-Behavioral Model The Behavioral Dimension The Cognitive Dimension The Cognitive-Behavioral Interplay New Wave Cognitive-Behavioral Therapies Assessing the Cognitive-Behavioral Model

The Humanistic-Existential Model Rogers’ Humanistic Theory and Therapy Gestalt Theory and Therapy Spiritual Views and Interventions Existential Theories and Therapy Assessing the Humanistic-Existential Model

The Sociocultural Model: Family-Social and Multicultural Perspectives How Do Family-Social Theorists Explain Abnormal Functioning? Family-Social Treatments How Do Multicultural Theorists Explain Abnormal Functioning? Multicultural Treatments Assessing the Sociocultural Model

Integrating the Models: The Developmental Psychopathology Perspective

Philip Berman, a 25-year-old single unemployed former copy editor for a large publishing house …

had been hospitalized a�er a suicide attempt in which he deeply gashed his wrist with a razor blade. He

described [to the therapist] how he had sat on the bathroom floor and watched the blood drip into the

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bathtub for some time before he [contacted] his father at work for help. He and his father went to the

hospital emergency room to have the gash stitched, but he convinced himself and the hospital

physician that he did not need hospitalization. The next day when his father suggested he needed help,

he knocked his dinner to the floor and angrily stormed to his room. When he was calm again, he

allowed his father to take him back to the hospital.

The immediate precipitant for his suicide attempt was that he had run into one of his former girlfriends

with her new boyfriend. The patient stated that they had a drink together, but all the while he was with

them he could not help thinking that “they were dying to run off and jump in bed.” He experienced

jealous rage, got up from the table, and walked out of the restaurant. He began to think about how he

could “pay her back.”

Mr. Berman had felt frequently depressed for brief periods during the previous several years. He was

especially critical of himself for his limited social life and his inability to have managed to have sexual

intercourse with a woman even once in his life. As he related this to the therapist, he li�ed his eyes from

the floor and with a sarcastic smirk said, “I’m a 25-year-old virgin. Go ahead, you can laugh now.” He

has had several girlfriends to date, whom he described as very attractive, but who he said had lost

interest in him. On further questioning, however, it became apparent that Mr. Berman soon became

very critical of them and demanded that they always meet his every need, o�en to their own detriment.

The women then found the relationship very unrewarding and would soon find someone else.

During the past two years Mr. Berman had seen three psychiatrists briefly, one of whom had given him a

drug, the name of which he could not remember, but that had precipitated some sort of unusual

reaction for which he had to stay in a hospital overnight…. Concerning his hospitalization, the patient

said that “It was a dump,” that the staff refused to listen to what he had to say or to respond to his

needs, and that they, in fact, treated all the patients “sadistically.” The referring doctor corroborated

that Mr. Berman was a difficult patient who demanded that he be treated as special, and yet was

hostile to most staff members throughout his stay. A�er one angry exchange with an aide, he le� the

hospital without [permission], and subsequently signed out against medical advice.

Mr. Berman is one of two children of a middle-class family. His father is 55 years old and employed in a

managerial position for an insurance company. He perceives his father as weak and ineffectual,

completely dominated by the patient’s overbearing and cruel mother. He states that he hates his

mother with “a passion I can barely control.” He claims that his mother used to call him names like

“pervert” … when he was growing up, and that in an argument she once “kicked me in the balls.”

Together, he sees his parents as rich, powerful, and selfish, and, in turn, thinks that they see him as lazy,

irresponsible, and a behavior problem. When his parents called the therapist to discuss their son’s

treatment, they stated that his problem began with the birth of his younger brother, Arnold, when Philip

was 10 years old. A�er Arnold’s birth Philip apparently became [a disagreeable] child who cursed a lot

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and was difficult to discipline. Philip recalls this period only vaguely. He reports that his mother once

was hospitalized for depression, but that now “she doesn’t believe in psychiatry.”

Mr. Berman had graduated from college with average grades. Since graduating he had worked at three

different publishing houses, but at none of them for more than one year. He always found some

justification for quitting. He usually sat around his house doing very little for two or three months a�er

quitting a job, until his parents prodded him into getting a new one. He described innumerable

interactions in his life with teachers, friends, and employers in which he felt offended or unfairly treated

… and frequent arguments that le� him feeling bitter … and [he] spent most of his time alone, “bored.”

He was unable to commit himself to any person, he held no strong convictions, and he felt no allegiance

to any group.

The patient appeared as a very thin, bearded … young man with pale skin who maintained little eye

contact with the therapist and who had an air of angry bitterness about him. Although he complained

of depression, he denied other symptoms of the depressive syndrome. He seemed preoccupied with his

rage at his parents, and seemed particularly invested in conveying a despicable image of himself….

(Spitzer et al., 1983, pp. 59–61)

Philip Berman, the subject of this classic case study, is clearly a troubled person, but how did he come to be that way? How do we explain and correct his many

problems? To answer these questions, we must first look at the wide range of problems we are trying to understand: Philip’s depression and anger, his social failures, his lack of employment, his distrust of those around him, and the problems within his family. Then we must sort through all kinds of potential causes — internal and external, biological and interpersonal, past and present.

of NOTE … Their Words

“Help! I’m being held prisoner by my heredity and environment.”

Dennis Allen

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Although we may not realize it, we all use theoretical frameworks as we read about Philip. Over the course of our lives, each of us has developed a perspective that helps us make sense of the things other people say and do. In science, the perspectives used to explain events are known as models, or

paradigms. Each model spells out the scientist’s basic assumptions, gives order to the field under study, and sets guidelines for its investigation (Kuhn, 1962). It influences what the investigators observe as well as the questions they ask, the information they seek, and how they interpret this information. To understand how a clinician explains or treats a specific set of symptoms, such as Philip’s, we must know that clinician’s preferred model of abnormal functioning.

Until relatively recently, clinical scientists of a given place and time tended to agree on a single model of abnormality — a model greatly influenced by the beliefs of their culture. The demonological model that was used to explain abnormal functioning during the Middle Ages, for example, borrowed heavily from medieval society’s concerns with religion, superstition, and warfare. Medieval practitioners would have seen the devil’s guiding hand in Philip Berman’s suicide attempts and his feelings of depression, rage, jealousy, and

hatred. Similarly, their treatments for him — from prayers to whippings — would have sought to drive foreign spirits from his body.

Today several models are used to explain and treat abnormal functioning. This variety has resulted both from shifts in values and beliefs over the past half-

century and from improvements in clinical research. At one end of the spectrum is the biological model, which sees physical processes as key to human behavior. In the middle are three models that focus on more psychological and personal aspects of human functioning: the psychodynamic model looks at people’s unconscious internal processes and conflicts; the cognitive-behavioral model emphasizes behavior, the ways in which it is learned, and the thinking that underlies behavior; and the humanistic-existential model stresses the role of values and choices. At the far end of the spectrum is the sociocultural model, which looks to social and cultural forces as the keys to human functioning. This model includes the family-social perspective, which focuses on an individual’s

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family and social interactions, and the multicultural perspective, which emphasizes an individual’s culture and the shared beliefs, values, and history of that culture.

Given their different assumptions and principles, the models are sometimes in conflict. Those who exclusively follow one perspective often scoff at the “naïve” interpretations, investigations, and treatment efforts of the others. Yet none of the models is complete in itself. Each focuses mainly on one aspect of human functioning, and none can explain all aspects of abnormality.

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The Biological Model

PHILIP BERMAN IS a biological being. His thoughts and feelings are the results of biochemical and bioelectrical processes throughout his brain and body. Proponents of the biological model believe that a full understanding of Philip’s thoughts, emotions, and behavior must therefore include an understanding of their biological basis. Not surprisingly, then, they believe that the most effective treatments for Philip’s problems will be biological ones.

How Do Biological Theorists Explain Abnormal Behavior? Adopting a medical perspective, biological theorists view abnormal behavior as an illness brought about by malfunctioning parts of the organism. Typically, they point to problems in the brain as the cause of such behavior.

Brain Chemistry and Abnormal Behavior

The brain is made up of approximately 86 billion nerve cells, called neurons, and thousands of billions of support cells, called glia (from the Greek word for

“glue”) (Servick, 2019). Information is communicated throughout the brain in the form of electrical impulses that travel from one neuron to one or more others. An impulse is first received by a neuron’s dendrites, antenna-like extensions located at one end of the neuron. From there it travels down the neuron’s axon, a long fiber extending from the neuron’s body. Finally, it is transmitted through the nerve ending at the end of the axon to the dendrites of other neurons (see Figure 3-1). Each neuron has multiple dendrites and a single axon. But that axon

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can be very long indeed, often extending all the way from one area of the brain to another.

FIGURE 3-1

A Neuron Communicating Information

A message in the form of an electrical impulse travels down the sending neuron’s axon to its nerve ending, where neurotransmitters are released and carry the

message across the synaptic space to the dendrites of a receiving neuron.

How do messages get from the nerve ending of one neuron to the dendrites of another? After all, the neurons do not actually touch each other. A tiny space, called the synapse, separates one neuron from the next, and the message must somehow move across that space. When an electrical impulse reaches a neuron’s ending, the nerve ending is stimulated to release a chemical, called a neurotransmitter, that travels across the synaptic space to receptors on the dendrites of the neighboring neurons. After binding to the receiving neuron’s receptors, some neurotransmitters give a message to receiving neurons to “fire,”

that is, to trigger their own electrical impulse. Other neurotransmitters carry an inhibitory message; they tell receiving neurons to stop all firing. Researchers have identified dozens of neurotransmitters in the brain, and they have learned that each neuron uses only certain kinds.

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Studies indicate that abnormal activity by certain neurotransmitters is sometimes tied to mental disorders. Depression, for example, has been linked in part to low activity of the neurotransmitters serotonin, norepinephrine, and glutamate. Perhaps low serotonin activity is at play in Philip Berman’s pattern of

depression and rage.

In addition to neurotransmitters, researchers have learned that mental disorders are sometimes related to abnormal chemical activity in the body’s endocrine system. Endocrine glands, located throughout the body, work along with neurons to control such vital activities as growth, reproduction, sexual

activity, heart rate, body temperature, and responses to stress. The glands release chemicals called hormones into the bloodstream, and these chemicals then propel body organs into action. During times of stress, for example, the adrenal glands, located on top of the kidneys, secrete the hormone cortisol to help the body deal with the stress. Abnormal secretions of this chemical have been tied to anxiety and depression.

Brain Anatomy, Circuitry, and Abnormal Behavior

Within the brain, large groups of neurons form distinct regions, or brain structures. The neurons in each of these brain structures help control important functions. Clinical researchers have sometimes linked particular psychological disorders to problems in specific structures of the brain. For example, Huntington’s disease — a disorder marked by involuntary body movements, violent emotional outbursts, memory loss, suicidal thinking, and absurd beliefs — has been linked in part to a loss of neurons in two brain structures, the basal ganglia and the cerebral cortex.

Over the past decade, researchers have increasingly focused on brain circuits as the key to psychological disorders rather than on dysfunction within a single brain structure or by a single brain chemical. A brain circuit is a network of particular brain structures that work together, triggering each other into action

to produce a distinct behavioral, cognitive, or emotional reaction. The structures

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of a given circuit work together through their neurons. The long axons of the neurons from one structure bundle together and extend across the brain to communicate with the neurons of another structure, setting up a fiber pathway between the structures. The structures and neurotransmitters that make up a

given brain circuit are, as you read above, important individually, but research indicates that it is usually most informative to look at the operation of the entire circuit, including its interconnecting fiber pathways, to fully understand human functioning. Proper interconnectivity (communication) among the structures of a circuit tends to result in healthy psychological functioning, whereas flawed interconnectivity may lead to abnormal functioning.

One of the brain’s most important circuits is the “fear circuit” (see Figure 3-2). As you will see in Chapter 5, this circuit consists of a number of specific structures (including the prefrontal cortex, anterior cingulate cortex, insula, and amygdala) whose interconnecting fiber pathways enable the structures to trigger each other into action and to produce our everyday fear reactions. The neurons in this circuit further use particular neurotransmitters to communicate with each other. Studies suggest that this circuit functions improperly (that is, displays

flawed interconnectivity) in people suffering from certain anxiety disorders (Fullana et al., 2020). Perhaps dysfunction by Philip Berman’s fear circuit is contributing to his repeated concerns that things will go badly and that other people will have low opinions and negative motives toward him, concerns that keep triggering his depression and anger.

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FIGURE 3-2

The Biology of Fear

The “fear circuit” — the brain circuit that helps produce fear reactions — includes structures such as the prefrontal cortex, anterior cingulate cortex, insula, and amygdala. The illustration on the le� shows where these structures

are located throughout the brain (the insula is not visible from this particular view of the brain). The illustration on the right highlights how the structures of this circuit actually work together and trigger each other into action to produce fear reactions. The long axons of the neurons from each structure form fiber-like pathways that extend to

the other structures in the circuit.

Sources of Biological Abnormalities

Why might the neurotransmitters or brain circuits of some people function differently from the norm? As you will see throughout this book, a wide range of factors can play a role — from prenatal events to brain injuries, viral infections, environmental experiences, and stress. Two factors that have received particular attention in the biological model are genetics and evolution.

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More than coincidence? Identical twins Julian and Joaquin Castro, shown here with

proud mother Marie “Rosie” Castro in 2006, have both gone on to have storied careers in government service — Julian (le�) as the mayor of San Antonio, Texas, and

U.S. Secretary of Housing and Urban Development, and Joaquin (right) as a member of the U.S. House of Representatives. Like the Castros, many identical twins display

similar tastes, behaviors, and career choices — supporting the notion that certain aspects of behavior and personality are influenced, in part, by genetic factors.

GENETICS AND ABNORMAL BEHAVIOR

Each cell in the typical human brain and body contains 23 pairs of chromosomes, with each chromosome in a pair inherited from one of the person’s parents. Every chromosome contains numerous genes — segments that control the characteristics and traits a person inherits. Altogether, each cell contains around 20,000 genes (Posey, 2019). Scientists have known for years that genes help determine such physical characteristics as hair color, height, and eyesight. Genes can make people more prone to heart disease, cancer, or diabetes, and

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perhaps to possessing artistic or musical skill. Studies suggest that inheritance also can play a part in certain mental disorders.

In most instances, several or more genes combine to help produce our actions and reactions, both functional and dysfunctional. The precise contributions of various genes or gene combinations to mental disorders have become clearer in recent decades, thanks in part to the completion of the Human Genome Project in 2000, a major undertaking in which scientists used the tools of molecular biology to map, or sequence, all of the genes in the human body.

EVOLUTION AND ABNORMAL BEHAVIOR

Genes that contribute to mental disorders are typically viewed as unfortunate occurrences — almost mistakes of inheritance. The responsible gene may be a mutation, an abnormal form of the appropriate gene that emerges by accident. Or the problematic gene may be inherited by an individual after it has initially entered their family line as a mutation. According to some theorists, however, many of the genes that contribute to abnormal functioning are actually the result of normal evolutionary principles (Nesse, 2019).

In general, evolutionary theorists argue that human reactions and the genes responsible for them have survived over the course of time because they have helped individuals to thrive and adapt. Ancestors who had the ability to run fast, for example, or the craftiness to hide were most able to escape their enemies

and to reproduce. Thus, the genes responsible for effective walking, running, or problem solving were particularly likely to be passed on from generation to generation to the present day.

Similarly, say evolutionary theorists, the capacity to experience fear was, and in

many instances still is, adaptive. Fear alerted our ancestors to dangers, threats, and losses so that persons could avoid or escape potential problems. People who were particularly sensitive to danger — those with greater fear responses — were more likely to survive catastrophes, battles, and the like and to

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reproduce and pass on their fear genes. Of course, in today’s world, pressures are more numerous and often more subtle