Current Research in the Behavioral Sciences: Detecting Psychopathy From Thin Slices of Behavior

(Naturalistic Methods) Current Research in the Behavioral Sciences: Detecting

Psychopathy From Thin Slices of Behavior

Katherine A. Fowler, Scott O. Lilienfeld, and Christopher J. Patrick (2009) used a naturalistic research design to study whether personality could be reliably assessed by raters who were given only very short samples (“thin slices”) of behavior. They were particularly interested in assessing psychopathy, a syndrome characterized by emotional and interpersonal defi cits that often lead a person to antisocial behavior. According to the authors’ defi nition, psychopathic individuals tend to be “glib and superficially charming,” giving a surface-level appearance of intelligence, but are also “manipulative and prone to pathological lying” (p. 68). Many lead a socially deviant lifestyle marked by early behavior problems, irresponsibility, poor impulse control, and proneness to boredom. 

         Because the researchers felt that behavior was likely to be a better indicator of psychopathy than was self-report, they used coders to assess the disorder from videotapes. Forty raters viewed videotapes containing only very brief excerpts (either 5s, 10s, or 20s in duration) selected from longer videotaped interviews with 96 maximum-security inmates at a prison in Florida. Each inmate’s video was rated by each rater on a variety of dimensions related to psychopathy including overall rated psychopathy, as well as antisocial, narcissistic and avoidant characteristics. The raters also rated the prisoners on physical attractiveness, as well as estimates of their violence proneness, and intelligence. To help the coders understand what was to be rated, the researchers provided them with very specifi c descriptions of each of the dimensions to be rated. 

    

  Even though the raters were not experts in psychopathy, they tended to agree on their judgments. Interrater reliability was calculated as the agreement among the raters on each item. As you can see in Table 7.2, the reliability of the codings was quite high, suggesting that the raters, even using very thin slices, could adequately assess the conceptual variables of interest.

Archival Research

  (Naturalistic Methods) Archival Research

As you will recall, one of the great advantages of naturalistic methods is that there are so many data available to be studied. One approach that takes full advantage of this situation is archival research, which is based on an analysis of any type of existing records of public behavior. These records might include newspaper articles, speeches and letters of public figures, television and radio broadcasts, Internet websites, or existing surveys. Because there are so many records that can be examined, the use of archival records is limited only by the researcher’s imagination. 

          Records that have been used in past behavioral research include the trash in a landfi ll, patterns of graffi ti, wear and tear on fl oors in museums, litter, and dirt on the pages of library books (see Webb et al., 1981, for examples). Archival researchers have found that crimes increase during hotter weather (Anderson, 1989); that earlier-born children live somewhat longer than later-borns (Modin 2002); and that gender and racial stereotypes are prevalent in current television shows (Greenberg, 1980) and in magazines (Sullivan & O’Connor, 1988). 

      One of the classic archival research projects is the sociological study of the causes of suicide by sociologist Emile Durkheim (1951). Durkheim used records of people who had committed suicide in seven European countries between 1841 and 1872 for his data. These records indicated, for instance, that suicide was more prevalent on weekdays than on weekends, among those who were not married, and in the summer months. From these data, Durkheim drew the conclusion that alienation from others was the primary cause of suicide. Durkheim’s resourcefulness in collecting data and his ability to use the data to draw conclusions about the causes of suicide are remarkable. 

         Because archival records contain a huge amount of information, they must also be systematically coded. This is done through a technique known as content analysis. Content analysis is essentially the same as systematic coding of observational data and includes the specifi cation of coding categories and the use of more than one rater. In one interesting example of an archival research project, Simonton (1988) located and analyzed biographies of U.S. presidents. He had seven undergraduate students rate each of the biographies on a number of predefi ned coding categories, including “was cautious and conservative in action,” “was charismatic,” and “valued personal loyalty.” The interrater reliability of the coders was assessed and found to be adequate. 

            Simonton then averaged the ratings of the seven coders and used the data to draw conclusions about the personalities and behaviors of the presidents. For instance, he found that “charismatic” presidents were motivated by achievement and power and were more active and accomplished more while in office. Although Simonton used biographies as his source of information, he could, of course, have employed presidential speeches, information on how and where the speeches were delivered, or material on the types of appointments the presidents made, among other records.

Systematic Coding Methods

(Naturalistic Methods) Systematic Coding Methods

You have probably noticed by now that although observational research and case studies can provide a detailed look at ongoing behavior, because they represent qualitative data, they may often not be as objective as one might like, especially when they are based on recordings by a single scientist. Because the observer has chosen which people to study, which behaviors to record or ignore, and how to interpret those behaviors, she or he may be more likely to see (or at least to report) those observations that confirm, rather than disconfi rm, her or his expectations. Furthermore, the collected data may be relatively sketchy, in the form of “fi eld notes” or brief reports, and thus not amenable to assessment of their reliability or validity. However, in many cases these problems can be overcome by using systematic observation to create quantitative measured variables (Bakeman & Gottman, 1986; Weick, 1985).

Deciding What to Observe

          Systematic observation involves specifying ahead of time exactly which observations are to be made on which people and in which times and places. These decisions are made on the basis of theoretical expectation about the types of events that are going to be of interest. Specificity about the  of interest has the advantage of both focusing the observers’ attention on these specific behaviors and reducing the masses of data that might be collected if the observers attempted to record everything they saw. Furthermore, in many cases more than one observer can make the observations, and, as we have discussed in Chapter 5, this will increase the reliability of the measures. 

           Consider, for instance, a research team interested in assessing how and when young children compare their own performance with that of their classmates (Pomerantz et al., 1995). In this study, one or two adult observers sat in chairs adjacent to work areas in the classrooms of elementary school children and recorded in laptop computers the behaviors of the children. Before beginning the project, the researchers had defined a specific set of behavioral categories for use by the observers. These categories were based on theoretical predictions of what would occur for these children and defined exactly what behaviors were to be coded, how to determine when those behaviors were occurring, and how to code them into the computer. 

Deciding How to Record Observations 

         Before beginning to code the behaviors, the observers spent three or four days in the classroom learning, practicing, and revising the coding methods and letting the children get used to their presence. Because the coding categories were so well defi ned, there was good interrater reliability. And to be certain that the judges remained reliable, the experimenters frequently computed a reliability analysis on the codings over the time that the observations were being made. This is particularly important because there are some behaviors that occur infrequently, and it is important to be sure that they are being coded reliably. 

        Over the course of each observation period, several types of data were collected. For one, the observers coded event frequencies—for instance, the number of verbal statements that indicated social comparison. These included both statements about one’s own performance (“My picture is the best.”) and questions about the performance of others (“How many did you get wrong?”). In addition, the observers also coded event duration—for instance, the amount of time that the child was attending to the work of others. Finally, all the children were interviewed after the observation had ended. 

Choosing Sampling Strategies

         One of the difficulties in coding ongoing behavior is that there is so much of it. Pomerantz et al. (1995), used three basic sampling strategies to reduce the amount of data they needed to record. First, as we have already seen, they used event sampling—focusing in on specifi c behaviors that were theoretically related to social comparison. Second, they employed individual sampling. Rather than trying to record the behaviors of all of the children at the same time, the observers randomly selected one child to be the focus child for an observational period. The observers zeroed in on this child, while ignoring the behavior of others during the time period. Over the entire period of the study, however, each child was observed. Finally, Pomerantz and colleagues employed time sampling. Each observer focused on a single child for only four minutes before moving on to another child. In this case, the data were coded as they were observed, but in some cases the observer might use the time periods between observations to record the responses. Although sampling only some of the events of interest may lose some information, the events that are attended to can be more precisely recorded. 

        The data of the observers were then uploaded from laptop computers for analysis. Using these measures, Pomerantz et al. found, among other things, that older children used subtler social comparison strategies and increasingly saw such behavior as boastful or unfair. These data have high ecological validity, and yet their reliability and validity are well established. Another example of a coding scheme for naturalistic research, also using children, is shown in Figure 7.1.

Case Studies

(Naturalistic Methods) Case Studies

Whereas observational research generally assesses the behavior of a relatively large group of people, sometimes the data are based on only a small set of individuals, perhaps only one or two. These qualitative research designs are known as case studies—descriptive records of one or more individual’s experiences and behavior. Sometimes case studies involve normal individuals, as when developmental psychologist Jean Piaget (1952) used observation of his own children to develop a stage theory of cognitive development. More frequently, case studies are conducted on individuals who have unusual or abnormal experiences or characteristics or who are going through particularly diffi cult or stressful situations. The assumption is that by carefully studying individuals who are socially marginal, who are experiencing a unique situation, or who are going through a diffi cult phase in their life, we can learn something about human nature. 

        Sigmund Freud was a master of using the psychological diffi culties of individuals to draw conclusions about basic psychological processes. One classic example is Freud’s case study and treatment of “Little Hans,” a child whose fear of horses the psychoanalyst interpreted in terms of repressed sexual impulses (1959). Freud wrote case studies of some of his most interesting patients and used these careful examinations to develop his important theories of personality. 

        Scientists also use case studies to investigate the neurological bases of behavior. In animals, scientists can study the functions of a certain section of the brain by removing that part. If removing part of the brain prevents the animal from performing a certain behavior (such as learning to locate a food tray in a maze), then the inference can be drawn that the memory was stored in the removed part of the brain. It is obviously not possible to treat humans in the same manner, but brain damage sometimes occurs in people for other reasons. “Split-brain” patients (Sperry, 1982) are individuals who have had the  two hemispheres of their brains surgically separated in an attempt to prevent severe epileptic seizures. Study of the behavior of these unique individuals has provided important information about the functions of the two brain hemispheres

in humans. In other individuals, certain brain parts may be destroyed through disease or accident. One well-known case study is Phineas Gage, a man who was extensively studied by cognitive psychologists after he had a railroad spike blasted through his skull in an accident. An interesting example of a case study in clinical psychology is described by Rokeach (1964), who investigated in detail the beliefs and interactions among three schizophrenics, all of whom were convinced they were Jesus Christ.

           One problem with case studies is that they are based on the experiences of only a very limited number of normally quite unusual individuals. Although descriptions of individual experiences may be extremely interesting, they cannot  usually tell us much about whether the same things would happen to other individuals in similar situations or exactly why these specific reactions to these events occurred. For instance, descriptions of individuals who have been in a stressful situation such as a war or an earthquake can be used to understand how they reacted during such a situation but cannot tell us what particular longterm effects the situation had on them. Because there is no comparison group  that did not experience the stressful situation, we cannot know what these individuals would be like if they hadn’t had the experience. As a result, case studies provide only weak support for the drawing of scientifi c conclusions. They may, however, be useful for providing ideas for future, more controlled research.

Observational Research

(Naturalistic Methods) Observational Research

Observational research involves making observations of behavior and recording those observations in an objective manner. The observational approach is the oldest method of conducting research and is used routinely in psychology, anthropology, sociology, and many other fields. 

        Let’s consider an observational study. To observe the behavior of individuals at work, industrial psychologist Roy (1959–1960) took a job in a factory where raincoats were made. The job entailed boring, repetitive movements (punching holes in plastic sheets using large stamping machines) and went on eight hours a day, five days a week. There was nothing at all interesting about the job, and Roy was uncertain how the employees, some of whom had been there for many years, could stand the monotony. 

           In his first few days on the job Roy did not notice anything particularly unusual. However, as he carefully observed the activities of the other employees over time, he began to discover that they had a series of “pranks” that they played on and with each other. For instance, every time “Sammy” went to the drinking fountain, “Ike” turned off the power on “Sammy’s” machine. And whenever “Sammy” returned, he tried to stamp a piece before “discovering” that the power had been turned off. He then acted angrily toward “Ike,” who in turn responded with a shrug and a smirk. 

              In addition to this event, which occurred several times a day, Roy also noted many other games that the workers effectively used to break up the day. At 11:00 “Sammy” would yell, “Banana time!” and steal the banana out of “Ike’s” lunch pail, which was sitting on a shelf. Later in the morning “Ike” would open the window in front of “Sammy’s” machine, letting in freezing cold air. “Sammy” would protest and close the window. At the end of the day, “Sammy” would quit two minutes early, drawing fire from the employees’ boss, who nevertheless let the activity occur day after day. 

               Although Roy entered the factory expecting to fi nd only a limited set of mundane observations, he actually discovered a whole world of regular, complicated, and, to the employees, satisfying activities that broke up the monotony of their everyday work existence. This represents one of the major advantages of naturalistic research methods. Because the data are rich, they can be an important source of ideas. 

             In this example, because the researcher was working at a stamping machine and interacting with the other employees, he was himself a participant in the setting being observed. When a scientist takes a job in a factory, joins a religious cult (Festinger, Riecken, & Schachter, 1956), or checks into a mental institution (Rosenhan, 1973), he or she becomes part of the setting itself. Other times, the scientist may choose to remain strictly an observer of the setting, such as when he or she views children in a classroom from a corner without playing with them, watches employees in a factory from behind a one-way mirror, or observes behavior in a public restroom (Humphreys, 1975). 

             In addition to deciding whether to be a participant, the researcher must also decide whether to let the people being observed know that the observation is occurring—that is, to be acknowledged or unacknowledged to the population being studied. Because the decision about whether to be participant or nonparticipant can be independent of the decision to be acknowledged or unacknowledged, there are, as shown in Table 7.1, altogether four possible types of observational research designs. There are advantages and disadvantages to each approach, and the choice of which to use will be based on the goals of the research, the ability to obtain access to the population, and ethical principles. 

The Unacknowledged Participant

          One approach is that of the unacknowledged participant. When an observer takes a job in a factory, as Roy did, or infi ltrates the life of the homeless in a city, without letting the people being observed know about it, the observer has the advantage of concealment. As a result, she or he may be able to get close to the people being observed and may get them to reveal personal or intimate information about themselves and their social situation, such as their true feelings about their employers or their reactions to being on the street. The unacknowledged participant, then, has the best chance of really “getting to know” the people being observed.

           Of course, becoming too close to the people being studied may have negative effects as well. For one thing, the researcher may have diffi culty remaining objective. The observer who learns people’s names, hears intimate accounts of their lives, and becomes a friend may fi nd his or her perception shaped more by their point of view than by a more objective, scientific one. Alternatively, the observer may dislike the people whom he or she is observing, which may create a negative bias in subsequent analysis and reporting of the data. 

          The use of an unacknowledged participant strategy also poses ethical dilemmas for the researcher. For one thing, the people being observed may never be told that they were part of a research project or may fi nd it out only later. This may not be a great problem when the observation is conducted in a public arena, such as a bar or a city park, but the problem may be greater when the observation is in a setting where people might later be identifi ed, with potential negative consequences to them. For instance, if a researcher takes a job in a factory and then writes a research report concerning the true feelings of the employees about their employers, management may be able to identify the individual workers from these descriptions.

   Another disadvantage of the unacknowledged participant approach is that the activities of the observer may infl uence the process being observed. This may happen, for instance, when an unacknowledged participant is asked by the group to contribute to a group decision. Saying nothing would “blow one’s cover,” but making substantive comments would change the nature of the group itself. Often the participant researcher will want to query the people being observed in order to gain more information about why certain behaviors are occurring. Although these questions can reveal the underlying nature of the social setting, they may also alter the situation itself. 

The Acknowledged Participant 

        In cases where the researcher feels that it is unethical or impossible to hide his or her identity as a scientist, the acknowledged participant approach can be used. Sociologist W. F. Whyte (1993) used this approach in his classic sociological study of “street corner society.” Over a period of a year, Whyte got to know the people in, and made extensive observations of, a neighborhood in a New England town. He did not attempt to hide his identity. Rather, he announced freely that he was a scientist and that he would be recording the behavior of the individuals he observed. Sometimes this approach is necessary, for instance, when the behavior the researcher wants to observe is difficult to gain access to. To observe behavior in a corporate boardroom or school classroom, the researcher may have to gain offi cial permission, which may require acknowledging the research to those being observed. 

          The largest problem of being acknowledged is reactivity. Knowing that the observer is recording information may cause people to change their speech and behavior, limit what they are willing to discuss, or avoid the researcher altogether. Often, however, once the observer has spent some time with the population of interest, people tend to treat him or her as a real member of the group. This happened to Whyte. In such situations, the scientist may let this habituation occur over a period of time before beginning to record observations. 

Acknowledged and Unacknowledged Observers

The researcher may use a nonparticipant approach when he or she does not want to or cannot be a participant of the group being studied. In these cases, the researcher observes the behavior of interest without actively participating in the ongoing action. This occurs, for instance, when children are observed in a classroom from behind a one-way mirror or when clinical psychologists videotape group therapy sessions for later analysis. One advantage of not being part of the group is that the researcher may be more objective because he or she does not develop close relationships with the people being observed. Being out of the action also leaves the observer more time to do the job he or she came for—watching other people and recording relevant data. 

        The nonparticipant observer is relieved of the burdensome role of acting like a participant and maintaining a “cover,” activities that may take substantial effort. The nonparticipant observer may be either acknowledged or unacknowledged. Again, there are pros and cons to each, and these generally parallel the issues involved with the participant observer. Being acknowledged can create reactivity, whereas being unacknowledged may be unethical if it violates the confidentiality of the data. These issues must be considered carefully, with the researcher reviewing the pros and cons of each approach before beginning the project.

Naturalistic Research

          (Naturalistic Methods) Naturalistic Research

Naturalistic research is designed to describe and measure the behavior of people or animals as it occurs in their everyday lives. The behavior may be measured as it occurs, or it could already have been recorded by others, or it may be recorded on videotape to be coded at a later time. In any case, however, because it involves the observation of everyday behavior, a basic diffi - culty results—the rich and complex data that are observed must be organized into meaningful measured variables that can be analyzed. One of the goals of

this chapter is to review methods for turning observed everyday behavior into measured variables. 

         Naturalistic research approaches are used by researchers in a variety of disciplines, and the data that form the basis of naturalistic research methods can be gathered from many different sources in many different ways. These range from a clinical psychologist’s informal observations of his or her clients, to another scientist’s more formal observations of the behaviors of animals in the wild, to an analysis of politicians’ speeches, to a videotaping of children playing with their parents in a laboratory setting. Although these approaches frequently involve qualitative data, there are also techniques for turning observations into quantitative data, and we will discuss both types in this chapter. 

          In many cases, naturalistic research is the only possible approach to collecting data. For instance, whereas researchers may not be able to study the impact of earthquakes, fl oods, or cult membership using experimental research designs, they may be able to use naturalistic research designs to collect a wide variety of data that can be useful in understanding such phenomena. 

         One particular advantage of naturalistic research is that it has ecological validity. Ecological validity refers to the extent to which the research is conducted in situations that are similar to the everyday life experiences of the participants (Aronson & Carlsmith, 1968). In naturalistic research the people whose behavior is being measured are doing the things they do every day, and in some cases they may not even know that their behavior is being recorded. In these cases, reactivity is minimized and the construct validity of the measures should therefore be increased.

Naturalistic Methods

Naturalistic Methods

As we have seen in Chapter 6, self-report measures have the advantage of allowing the researcher to collect a large amount of information from the respondents quickly and easily. On the other hand, they also have the potential of being inaccurate if the respondent does not have access to, or is unwilling to express, his or her true beliefs. And we have seen in Chapter 4 that behavioral measures have the advantage of being more natural and thus less infl uenced by reactivity. In this chapter, we discuss descriptive research that uses behavioral measures. As we have seen in Chapter 1, descriptive research may be conducted either qualitatively—in which case the goal is to describe the observations in detail and to use those descriptions as the results, or quantitatively— in which the data is collected using systematic methods and the data are analyzed using statistical techniques. Keep in mind as you read the chapter that, as with most descriptive research, the goal is not only to test research  hypotheses, but also to develop ideas for topics that can be studied later using other types of research designs. However, as with survey research, naturalistic methods can also be used to create measured variables for use in correlational and experimental tests of research hypotheses.