Posted: February 26th, 2021
PART1- Due Thursday
Respond to the following in a minimum of 175 words:
It is important to look back over what we have learned about synthesize what we have gathered. Take a look back at what you have processed. What are three concepts you think you will use in the future, and how will you use that information to improve your work?
PART2- SEE ATTACHMENT
PART3- Research Proposal
Develop an original research study proposal and describe it in detail in a 10-12 page (APA style) paper. Include at least 10 scholarly references in your proposal. Use the following outline as a guide when writing your paper. Be sure to include detailed information on all of the topics listed below and use headings to organize your thoughts.
1. Statement of the problem: Introduce the reader to the problem to be studied. Provide sufficient background information such that the reader has a grasp of the situation and its importance.
2. Review of the literature: Provide the reader with a review of most relevant literature, beginning with general information, and narrowing the focus to the specific issues under consideration in the study.
3. Purpose of the study: Identify why the study that you are proposing is needed.
4. Hypotheses or research questions: List them as simple statements. Make sure they are measurable.
5. Definition of terms: Operationally define terms the average reader may not know, or that have a specific meaning in your study.
6. Assumptions: Identify issues you assume to be true in order for your study to be valid.
7. Research methods and procedures
a. Population: Describe the population sample to be studied
b. Procedure: Discuss how the study will be carried out.
c. Instruments: Describe the specific measurements (instruments) to be used to test each hypothesis (research question).
d. Data Analysis: Describe the procedures you intend to use to analyze the data produced from your instruments, and how that would answer the hypotheses (research questions).
a. Discussion: Since you are only proposing (not conducting) a research study, you will not have results; however, you can discuss potential outcomes. Review your hypothesis and discuss how this study will address it. For example, if the results allow you to reject the null hypothesis, what are the implications? What would happen if you fail to reject the null hypothesis? Discuss the implications of your proposed study, the limitations of your study, and future research ideas and directions.
b. Since you are only proposing (not conducting) a research study, you will not have results; however, you can discuss potential outcomes. Review your hypothesis and discuss how this study will address it. For example, if the results allow you to reject the null hypothesis, what are the implications? What would happen if you fail to reject the null hypothesis? Discuss the implications of your proposed study, the limitations of your study, and future research ideas and directions.
8. Implications: Provide a brief summary of your proposal and a powerful statement as to how your study would advance the field.
9. References: Include at least 10 scholarly sources in your Reference section. Be sure to use APA style throughout your paper.
Page 292IN THIS CHAPTER, WE WILL CONSIDER THE ISSUE OF GENERALIZATION OF RESEARCH FINDINGS. When a single study is conducted with a particular sample and procedure, can the results then be generalized to other populations of research participants, or to other ways of manipulating or measuring the variables? Recall from Chapter 4 that internal validity refers to the ability to infer that there is a causal relationship between variables. External validity is the extent to which findings may be generalized.
Even though a researcher may randomly assign participants to experimental conditions, rarely are participants randomly selected from the general population. As we noted in Chapters 7 and 9, the individuals who participate in psychological research are usually selected because they are available, and the most available population consists of college students—or more specifically, first- and second-year students enrolled in the introductory psychology course to satisfy a general education requirement. They may also be from a particular college or university, may be volunteers, or may be mostly males or mostly females. So, are our research findings limited to these types of subjects, or can we generalize our findings to a more general population? After considering these issues, we will examine the larger issue of culture and how research findings can be generalized to different cultural groups.
Smart (1966) found that college students were studied in over 70% of the articles published between 1962 and 1964 in the Journal of Experimental Psychology and the Journal of Abnormal and Social Psychology. Sears (1986) reported similar percentages in 1980 and 1985 in a variety of social psychology journals; Arnett (2008) found that 67% of the articles in the 2007 volume of the Journal of Personality and Social Psychology used college student samples. The potential problem is that such studies use a highly restricted population. Sears points out that most of the students are first-year students and sophomores taking the introductory psychology class. They therefore tend to be young and to possess the characteristics of emerging adults: a sense of self-identity that is still developing, social and political attitudes that are in a state of flux, a high need for peer approval, and unstable peer relationships. They are intelligent with high cognitive abilities. Thus, what we know about “people in general” may actually be limited to a highly select and unusual group. Indeed, Peterson (2001) found that students, as a group, are more homogenous than nonstudent samples. That is, students are more similar to each other than adults are similar to other adults in the general population.
Research by Henry (2008) illustrates how the use of college students may affect the external validity of research on prejudice. In his sample of articles Page 293from 1990 to 2005, an increasing percentage of studies used college students as participants. Further, in looking at the actual results of studies on prejudice that compared college students with adults, he reported a variety of differences among adults and college students. For example, college students were less conservative and rated women and ethnic minorities more favorably.
Researchers usually must ask people to volunteer to participate in their research. At many colleges, introductory psychology students are required either to volunteer for research or to complete an alternative project. If you are studying populations other than college students, you are even more dependent on volunteers—for example, asking people at a homeowners’ association meeting to participate in a study of marital interaction or conducting research on the Internet in which people must go to your web page and then agree to participate in the study, or conducting a telephone survey of county residents to determine health care needs. In all these cases, external validity of the findings may be limited because the data from volunteers may be different from what would be obtained with a more general sample. Some research indicates that volunteers differ in various ways from nonvolunteers. In their comprehensive study on the topic, Rosenthal and Rosnow (1975) reported that volunteers tend to be more highly educated, of a higher socioeconomic status, more in need of approval, and more social.
Further, different kinds of people volunteer for different kinds of experiments. In colleges, there may be a sign-up board with the titles of many studies listed or a web page that manages research participants and volunteer opportunities for the university. Different types of people may be drawn to the study titled “problem solving” than to the one titled “interaction in small groups.” Available evidence indicates that the title does influence who signs up (Hood & Back, 1971; Silverman & Margulis, 1973).
Another important consideration arises when asking participants to volunteer for online surveys and experiments. Researchers can find potential participants through online survey design services. Psychologists are increasingly using Amazon Mechanical Turk (https://www.mturk.com; Jacquet, 2011), a website for recruiting people to work on many types of tasks including participating in research for a specified payment. This sort of sampling strategy has important implications for external validity. While the online sample is more diverse than the typical college student sample, there are still generalization issues because Internet users represent a unique demographic. The Pew Research Center’s Internet and American Life Project (Pew Internet, 2010) found that living in an urban/suburban area, being college educated, being younger, and having a higher income are all related to reporting more time online. Thus, by asking Page 294for volunteers for an online survey, researchers are sampling from a particular demographic that may not generalize well to the population of interest.
Sometimes, researchers use only males or only females (or a very disproportionate ratio of males to females) simply because this is convenient or the procedures seem better suited to a particular gender. Given the possible differences between males and females, however, the results of such studies may not be generalizable (Denmark, Russo, Frieze, & Sechzer, 1988). Denmark et al. provide an example of studies on contraception practices that use only females because of stereotypical assumptions that only females are responsible for contraception. They also point out several other ways that gender bias may arise in psychological research, including confounding gender with age or job status and selecting response measures that are gender-stereotyped. The solution is to be aware of possible gender differences and include both males and females in our research investigations. Moreover, it is important to recognize the ways that males and females might differentially interpret independent variable manipulations or questions asked in a questionnaire.
The location that participants are recruited from can also have an impact on a study’s external validity. Participants in one locale may differ from participants in another locale. For example, students at UCLA may differ from students at a nearby state university, who in turn may differ from students at a community college. People in Iowa may differ from people in New York City. Thus, a finding obtained with the students in one type of educational setting or in one geographic region may not generalize to people in other settings or regions. In fact, studies have explored how personality traits like extraversion (the tendency to seek social stimulation) and openness to new experiences vary across geographic areas. Rentfrow, Gosling, and Potter (2008) looked at geographic differences in personality traits among citizens of various U.S. states and found extraversion to vary by state. People in midwestern states tended to be more extraverted than people in northeastern states, and people in western states tended to be more open to new experiences. Thus, a study conducted in one location may not generalize well to another, particularly if the variables in question are related to location in some way.
Whether theories and research findings generalize across cultures is a critically important issue. Some observers of current psychological research have been very critical of the types of samples employed in behavioral research. Based on analyses of published research by Arnett (2008) and others, Henrich, Heine, and Norenzayan (2010) contend that psychology is built on the study of WEIRD Page 295(Western, Educated, Industrialized, Rich, Democratic) people. In many cases, research samples consist primarily of college students from the United States, other English-speaking countries, and Europe. Ultimately, researchers wish to discover aspects of human behavior that have universal applications but in fact cannot generalize beyond their limited samples. This is, at its heart, a critique of the external validity of behavioral research: Does our human behavioral research generalize to all humans, or is it really a study of the WEIRD?
Clearly, if psychologists want to understand human behavior, they must understand human behavior across and among cultures (Henrich et al., 2010; Miller, 1999). Miller described research on self-concept by Kitayama, Markus, Matsumoto, and Norasakkunkit (1997) to illustrate the benefits of incorporating culture into psychological theory. Traditional theories of self-concept are grounded in the culture of the United States and Western Europe; the “self” is an individualistic concept where people are independent from others and self-enhancement comes from individual achievements. Kitayama and his colleagues take a broader, cultural perspective: In contrast to the U.S. meaning of self, in other cultures the “self” is a collective concept in which self-esteem is derived from relationships with others. Often, Japanese engage in self-criticism, which can be seen as relationship-maintaining, whereas Americans work to maintain and enhance self-esteem—thus, very different activities contribute to a positive self-concept in the two cultures (Kitayama et al., 1997). This is a very common theme in research that incorporates culture in psychological processes: “The significance of self-esteem, however, may be much more specific to a culture than has typically been supposed in the literature” (p. 1262).
Much of this cultural research centers on identifying similarities and differences that may exist in personality and other psychological characteristics, as well as ways that individuals from different cultures respond to the same environments (Matsumoto, 1994). Research by Kim, Sherman, and Taylor (2008) provides another example of the limits of external validity across cultural groups. This research focused on how people from different cultures use social support to cope with stress. In reviewing the research on the topic, they concluded that Asians and Asian Americans might benefit from different styles of social support as compared with European Americans. For example, Asian Americans are more likely to benefit from support that does not involve the sort of intense disclosure of personal stressful events and feelings that is the hallmark of support in many European American groups. Rather, they suggest that Asians and Asian Americans may benefit more from support that comes with the comforts of proximity (being with close friends) rather than sharing.
These examples all focused on differences among cultures. Many studies also find similarities across cultures. Evolutionary psychologists, for instance, often conduct studies in different cultural groups because they are looking for similarities across cultures in order to see if a particular behavior or attitude can be tied to our evolutionary past. For example, Singh, Dixson, Jessop, Morgan, and Dixson (2010) wanted to see if a particular aspect of beauty that is tied to greater reproductive success—namely waist-to-hip ratio (e.g., the ratio for Page 296a 25-inch waist and 35-inch hips is .71), which is related to sex hormones and thus fertility—would be seen as attractive across cultures. Diverse groups from Africa, Samoa, Indonesia, and New Zealand evaluated photographs of females with small and large waist-to-hip ratios. The researchers found that indeed, low waist-to-hip ratio among females was seen as more attractive across all these groups. In this example, the results obtained in one culture do generalize to other cultures.
We noted in Chapter 3 that about 7% of psychological research is conducted with nonhuman animals. Almost all of this research is done with rats, mice, and birds. Most research with other species is conducted to study the behavior of those animals directly to gather information that may help with the survival of endangered species and increase our understanding of our bonds with nonhuman animals such as dogs, cats, and horses (http://www.apa-hai.org/human-animal-interaction).
The basic research that psychologists conduct with nonhuman animals is usually done with the expectation that the findings can be generalized to humans. This research is important because the research problems that are addressed require procedures such as long-term observation that could not be done with human samples. We do expect that we can generalize as our underlying biological and behavioral patterns are shared. In fact, the value of studying nonhuman animals has been demonstrated by research that does apply to humans. These applications include the biological bases of memory, food preferences, sexual behavior, choice behavior, and drug addictions. The American Psychological Association has prepared a brochure on animal research: (http://www.apa.org/research/responsible/research-animals.pdf).
It is easy to criticize research on the basis of subject characteristics, yet criticism by itself does not mean that results cannot be generalized. Although we need to be concerned about the potential problems of generalizing from unique populations such as college students (cf. Sears, 1986), we should also keep several things in mind when thinking about this issue. First, criticisms of the use of any particular type of subject, such as college students, in a study should be backed with good reasons that a relationship would not be found with other types of subjects. College students, after all, are human, and researchers should not be blamed for not worrying about generalization to a particular type of subject if there is no good reason to do so. Moreover, college student bodies are increasingly diverse and increasingly representative of the society as a whole (although college students will always be characterized as having the ability and motivation to pursue a college degree). Second, replication of research studies provides a safeguard against the limited external validity of a single study. Studies are replicated at other colleges using different mixes of students, and Page 297many findings first established with college students are later applied to other populations, such as children, aging adults, and people in other countries. It is also worth noting that Internet samples are increasingly used in many types of studies. Although such studies raise their own issues of external validity, they frequently complement studies based on college student samples.
The person who actually conducts the experiment is the source of another external validity problem. In most research, only one experimenter is used, and rarely is much attention paid to the personal characteristics of the experimenter (McGuigan, 1963). The main goal is to make sure that any influence the experimenter has on subjects is constant throughout the experiment. There is always the possibility, however, that the results are generalizable only to certain types of experimenters.
Some of the important characteristics of experimenters have been discussed by Kintz and his colleagues (Kintz, Delprato, Mettee, Persons, & Schappe, 1965). These include the experimenter’s personality and gender and the amount of practice in the role of experimenter. A warm, friendly experimenter will almost certainly produce different results from a cold, unfriendly experimenter. Participants also may behave differently with male and female experimenters. It has even been shown that rabbits learn faster when trained by experienced experimenters (Brogden, 1962)! The influence of the experimenter may depend as well on the characteristics of the participants. For example, participants seem to perform better when tested by an experimenter of the other sex (Stevenson & Allen, 1964).
One solution to the problem of generalizing to other experimenters is to use two or more experimenters. A fine example of the use of multiple experimenters is a study by Rubin (1975), who sent several male and female experimenters to the Boston airport to investigate self-disclosure. The experimenters revealed different kinds of information about themselves to both male and female travelers and recorded the passengers’ self-disclosures in return. One interesting result was that women tended to reveal more about themselves to male experimenters, and men tended to reveal more about themselves to female experimenters.
Researchers are often faced with the decision of whether to give a pretest. Intuitively, pretesting seems to be a good idea. The researcher can be sure that the groups are equivalent on the pretest, and it is often more satisfying to see that individuals changed their scores than it is to look only at group means on a posttest. A pretest also enables the researcher to assess mortality (attrition) effects when it is likely that some participants will withdraw from an experiment. Page 298If you give a pretest, you can determine whether the people who withdrew are different from those who completed the study.
Pretesting, however, may limit the ability to generalize to populations that did not receive a pretest. (cf. Lana, 1969). Simply taking the pretest may cause subjects to behave differently than they would without the pretest. Recall from Chapter 8 that a Solomon four-group design (Solomon, 1949) can be used in situations in which a pretest is desirable but there is concern over the possible impact of taking the pretest. In the Solomon four-group design, half of the participants are given the pretest; the other half receive the posttest only. That is, the same experiment is conducted with and without the pretest. Mortality effects can be assessed in the pretest conditions. Also, the researcher can examine whether there is an interaction between the independent variable and the pretest: Are posttest scores on the dependent variable different depending on whether the pretest was given? Sometimes, researchers find that it is not feasible to conduct the study with all four groups in a single experiment. In this case, the first study can include the pretest; the study can be replicated later without the pretest.
Research conducted in a laboratory setting has the advantage of allowing the experimenter to study the impact of independent variables under highly controlled conditions. The internal validity of the research is the primary consideration. The question arises, however, as to whether the artificiality of the laboratory setting limits the ability to generalize what is observed in the laboratory to real-life settings.
Mook (1983) articulated one response to the artificiality issue: Generalization to real-life settings is not relevant when the purpose of the study was to investigate causal relationships under carefully controlled conditions. Mook is concerned that a “knee-jerk” criticism of laboratory research on the basis of external validity is too common. Good research is what is most important.
Another response to the laboratory artificiality criticism is to examine the results of field experiments. Recall from Chapter 4 that in a field experiment, the researcher manipulates the independent variable in a natural setting—a factory, a school, or a street corner, for example.
Anderson, Lindsay, and Bushman (1999) asked whether laboratory and field experiments that examine the same variables do in fact produce the same results. To answer this question, they found 38 pairs of studies for which a laboratory investigation had a field experiment counterpart. The studies were drawn from a variety of research areas including aggression, helping, memory, leadership style, and depression. Results of the laboratory and field experiments were in fact very similar—the effect size of the independent variable on the dependent variable was very similar in the two types of studies. Thus, even though lab and field experiments are conducted in different settings, the results Page 299are complementary rather than contradictory. When findings are replicated using multiple methods, our confidence in the external validity of the findings increases.
It may seem as if no research can possibly be generalizable! In some ways, this is true. Furthermore, it can be very difficult to understand the extent to which a study is generalizable; external validity is an aspect of a study that we try to assess, but cannot truly know. How, then, can we support good external validity? There are a few ways that external validity can be supported.
The key way that external validity can be supported is related to a study’s methodology. Using a census, or a random sample will always produce better external validity than using a nonrandom sample. This, of course, is not always possible. Next, we will explore a few other ways in which external validity can be supported.
The problem of generalization can be thought of as an interaction in a factorial design (see Chapter 10). An interaction occurs when a relationship between variables exists under one condition but not another or when the nature of the relationship is different in one condition than in another. Thus, if you question the generalizability of a study that used only males, you are suggesting that there is an interaction between gender and the independent variable. Suppose, for example, that a study examines the relationship between crowding and aggression among males and reports that crowding is associated with higher levels of aggression. You might then question whether the results are generalizable to females.
Figure 14.1 shows four potential outcomes of a hypothetical study on crowding and aggression that tested both males and females. In each graph, the relationship between crowding and aggression for males has been maintained. In Graph A, there is no interaction—the behavior of males and females is virtually identical. Thus, the results of the original all-male study could be generalized to females. In Graph B, there is also no interaction; the effect of crowding is identical for males and females. However, in this graph, males are more aggressive than females. Although such a difference is interesting, it is not a factor in generalization because the overall relationship between crowding and aggression is present for both males and females.
Graphs C and D do show interactions. In both, the original results with males cannot be generalized to females. In Graph C, there is no relationship between crowding and aggression for females. In Graph D, the interaction tells us that a positive relationship between crowding and aggression exists for males but that a negative relationship exists for females. As it turns out, Graph D describes the results of several studies on this topic (cf. Freedman, Levy, Buchanan, & Price, 1972).
Outcomes of a hypothetical experiment on crowding and aggression
Note: The presence of an interaction indicates that the results for males cannot be generalized to females.
Researchers can address issues of external validity that stem from the use of different populations by including subject type as a variable in the study. By including variables such as gender, age, or ethnic group in the design of the study, the results may be analyzed to determine whether there are interaction effects like the ones illustrated in Figure 14.1.
Replication of research is a way of overcoming any problems of generalization that occur in a single study. There are two types of replications to consider: exact replications and conceptual replications.
Exact replications An exact replication is an attempt to replicate precisely the procedures of a study to see whether the same results are obtained. A researcher who obtains an unexpected finding will frequently attempt Page 301a replication to make sure that the finding is reliable. If you are starting your own work on a problem, you may try to replicate a crucial study to make sure that you understand the procedures and can obtain the same results. Often, exact replications occur when a researcher builds on the findings of a prior study. For example, suppose you are intrigued by Singh et al.’s (2010) research on waist-to-hip ratio that was mentioned previously. Singh reports that males rate females with a ratio of .70 as most attractive. In your research, you might replicate the procedures used in the original study and expand on the original research. For example, you might study this phenomenon with males similar to those in the original sample as well as males from different cultures or age groups. When you replicate the original research findings using very similar procedures, your confidence in the external validity of the original findings is increased.
The “Mozart effect” provides us with an interesting example of the importance of replications. In the original study by Rauscher, Shaw, and Ky (1993), college students listened to 10 minutes of a Mozart sonata. These students then showed better performance on a spatial-reasoning measure drawn from the Stanford-Binet Intelligence Scale than students exposed to a relaxation tape or simple silence. This finding received a great deal of attention in the press as people quickly generalized it to the possibility of increasing children’s intelligence with Mozart sonatas. In fact, one state governor began producing Mozart CDs to distribute in maternity wards, and entrepreneurs began selling Mozart kits to parents over the Internet. Over the next few years, however, there were many failures to replicate the Mozart effect (see Steele, Bass, & Crook, 1999). We noted above that failures to replicate may occur because the exact conditions for producing the effect were not used. In this case, Rauscher and Shaw (1998) responded to the many replication failures by precisely describing the conditions necessary to produce the Mozart effect. However, Steele et al. (1999) and McCutcheon (2000) were unable to obtain the effect even though they followed the recommendations of Rauscher and Shaw. Research on the Mozart effect continues. Some recent findings suggest that the effect is limited to music that also increases arousal; it is this arousal that can cause better performance following exposure to the music (Thompson, Schellenberg, & Husain, 2001). Bangerter and Heath (2004) present a detailed analysis of the development of the research on the Mozart effect.
A single failure to replicate does not reveal much, though; it is unrealistic to assume, on the basis of a single failure to replicate, that the previous research is necessarily invalid. Failures to replicate share the same problems as nonsignificant results, discussed in Chapter 13. A failure to replicate could mean that the original results are invalid, but it could also mean that the replication attempt was flawed. For example, if the replication is based on the procedure as reported in a journal article, it is possible that the article omitted an important aspect of the procedure. For this reason, it is usually a good idea to write to the researcher to obtain detailed information on all of the materials that were used in the study.
Page 302Several scientific societies are encouraging systematic replications of important scientific findings. The journal Perspectives on Psychological Science (published by the Association for Psychological Science) is sponsoring the publication of Registered Research Replications (http://www.psychologicalscience.org/index.php/replication). Multiple groups of researchers will undertake replications of important studies using procedures that are made public before initiating the research. When completed, all of the replications will be described in a single report. In addition to the Psychological Science initiative, the online journal PLOS ONE (Public Library of Science) has developed the Reproducibility Initiative to encourage independent replication of research in the clinical sciences (Pattinson, 2012). Such developments should lead to greater understanding of the generalizability of research findings.
Conceptual replications A conceptual replication is the use of different procedures to replicate a research finding. In a conceptual replication, researchers attempt to understand the relationships among abstract conceptual variables by using new, or different, operational definitions of those variables. Conceptual replications are even more important than exact replications in furthering our understanding of behavior.
In most research, a key goal is to discover whether a relationship between conceptual variables exists. In the original Mozart effect study, researchers examined the effect of exposure to classical music on spatial reasoning. These are conceptual variables; in the actual study, specific operational definitions of the variables were used. Exposure to classical music was operationalized as 10 minutes of exposure to the Mozart Sonata for Two Pianos in D Major. Spatial reasoning was operationalized as performance on a particular spatial reasoning measure.
In a conceptual replication, the same independent variable is operationalized in a different way, and the dependent variable may be measured in a different way, too. Conceptual replications are extremely important in the social sciences because the variables used are complex and can be operationalized in different ways. Complete understanding of any variable involves studying the variable using a variety of operational definitions. A crucial generalization question is whether the relationship holds when other ways of manipulating or measuring the variables are studied. Sometimes the conceptual replication may involve an alternative stimulus (e.g., a different Mozart sonata, a selection by a different composer) or an alternative dependent measure (e.g., a different spatial-reasoning task). Or as we previously noted, the same variables are sometimes studied in both laboratory and field settings. When conceptual replications produce similar results, our confidence in the generalizability of relationships between variables is greatly increased.
This discussion should also alert you to an important way of thinking about research findings. The findings represent relationships between conceptual variables but are grounded in specific operations. You may read about the specific methods employed in a study conducted 20 years ago and question Page 303whether the study could be replicated today. You might also speculate that the methods used in a study are so unusual that they could never generalize to other situations. These concerns are not as serious when placed within the context of conceptual replications because, although operational definitions can change over time, the underlying conceptual variable often remains more consistent. Admittedly, a specific method from a study conducted at one time might not be effective today, given changes in today’s political and cultural climate. A conceptual replication of the manipulation, however, would demonstrate that the relationship between the conceptual theoretical variables is still present. Similarly, the narrow focus of a particular study is less problematic if the general finding is replicated with different procedures.
Researchers have traditionally drawn conclusions about the external validity of research findings by conducting literature reviews. In a literature review, a reviewer reads a number of studies that address a particular topic and then writes a paper that summarizes and evaluates the literature. The Publication Manual of the American Psychological Association provides the following description: “Literature reviews, including research syntheses and meta-analyses, are critical evaluations of material that has already been published.… By organizing, integrating, and evaluating previously published material, authors of literature reviews consider the progress of research toward clarifying a problem” (APA, 2010, p. 10). The literature review provides information that (1) summarizes what has been found, (2) tells the reader which findings are strongly supported and which are only weakly supported in the literature, (3) points out inconsistent findings and areas in which research is lacking, and (4) discusses future directions for research.
Sometimes a review will be a narrative in which the author provides descriptions of research findings and draws conclusions about the literature. The conclusions in a narrative literature review are based on the subjective impressions of the reviewer. Another technique for comparing a large number of studies in an area is meta-analysis (Borenstein, Hedges, Higgins, & Rothstein, 2009). In a meta-analysis, the researcher combines the actual results of a number of studies. The analysis consists of a set of statistical procedures that employ effect sizes to compare a given finding across many different studies. Instead of relying on judgments obtained in a narrative literature review, you can draw statistical conclusions from this material. The statistical procedures need not concern you. They involve examining several features of the results of studies, including the effect sizes and significance levels obtained. The important point here is that meta-analysis is a method for determining the reliability of a finding by examining the results from many different studies.
Stewart and Chambless (2009) conducted a meta-analysis of research on the effectiveness of cognitive-behavioral therapy (CBT) for anxiety disorders. Page 304Both a traditional literature review and a meta-analysis begin with a body of previous research on a topic; in this case, Stewart and Chambless located 56 studies using CBT with adults diagnosed with an anxiety disorder (including panic disorder, social anxiety, post traumatic stress disorder, generalized anxiety disorder, and obsessive-compulsive disorder). Studies that included an additional medication treatment were excluded. The researchers performed a statistical analysis of the results of these studies and concluded that CBT was effective in treating all of the types of anxiety disorders. In a traditional literature review, it can be difficult to provide the type of general conclusion that was reached with the meta-analysis because it is necessary to integrate information from many studies with different experimental designs, disorders, and measures of anxiety.
One of the most important reasons a meta-analysis can lead to clear conclusions is that meta-analysis studies focus on effect size (recall that an effect size represents the extent to which two variables are associated, see page 256). A typical table in a meta-analysis will show the effect size obtained in a number of studies along with a summary of the average effect size across the studies. More important, the analysis allows comparisons of the effect sizes in different types of studies to allow tests of hypotheses. For example, Miller and Downey (1999) analyzed the results of 71 studies that examined the relationship between weight and self-esteem. Table 14.1 shows a few of the findings. The effect size r averaged across all studies was −.18: Heavier weight is associated with lower self-esteem. However, several variables moderate the relationship between weight and self-esteem. Thus, the effect size is larger when the weight variable is a report of self-perceived rather than actual weight, and the relationship between weight and self-esteem is somewhat larger for females than for males. Finally, the effect is greater among individuals with a high socioeconomic background.
TABLE 14.1 Some meta-analysis findings for weight and self-esteem
Both narrative reviews and meta-analyses provide valuable information and in fact are often complementary. A meta-analysis allows statistical, quantitative conclusions whereas a narrative review identifies trends in the literature and directions for future study—a more qualitative approach. A study by Bushman and Wells (2001) points to an interesting way in which knowledge of meta-analysis can improve the way that we interpret information for literature reviews.
The reviewers in their study were undergraduates who were provided with both titles and information about the findings of 20 studies dealing with the effect of attitude similarity on attraction. Sometimes the titles were salient with respect to the findings (“Birds of a Feather Flock Together”) and others were nonsalient (“Research Studies Who Likes Whom”). Salient titles are obviously easier to remember. When asked to draw conclusions about the findings, naive reviewers with no knowledge of meta-analysis overestimated the size of the similarity–attraction relationship when provided with salient titles. Other reviewers were given brief training in meta-analysis; these reviewers drew accurate conclusions about the actual findings. That is, they were not influenced by the article title. Thus, even without conducting a meta-analysis, a background in meta-analysis can be beneficial when reviewing research findings.
In a presidential address to the American Psychological Association, George Miller (1969) discussed “psychology as a means of promoting human welfare” and spoke of “giving psychology away.” Miller was addressing the broadest issue of generalization, taking what we know about human behavior and allowing it to be applied by many people in all areas of everyday life. Zimbardo’s (2004) presidential address to the American Psychological Association described many ways in which Miller’s call to give psychology away is being honored. The impact of psychological research can be seen in areas such as health (programs to promote health-related behaviors related to stress, heart disease, and sexually transmitted diseases), law and criminal justice (providing data on the effects of 6- versus 12-person juries and showing how law enforcement personnel can improve the accuracy of eyewitness identification), education (providing methods for encouraging academic performance or reducing conflict among different ethnic groups), and work environments (providing workers with more control and improving the ways that people interact with computers and other machines in the workplace). In addition, psychologists are using the Internet to provide the public with information on parenting, education, mental health, and Page 306many other topics—for example, the websites of the American Psychological Association and the Association for Psychological Science (http://www.apa.org; http://www.psychologicalscience.org), national mental health resource websites (http://www.mentalhealth.gov/ and http://www.samhsa.gov/), and many individual psychologists who are sharing their expertise with the public.
We have discussed only a few of the ways that basic research has been applied to improve people’s lives. Despite all the potential problems of generalizing research findings that were highlighted in this chapter, the evidence suggests that we can generalize our findings to many aspects of our lives.
ILLUSTRATIVE ARTICLE: GENERALIZING RESULTS
Driving around in a 4,000-pound automobile is a dangerous thing. Motor vehicle accidents are among the leading preventable causes of death in the United States every year. Distraction is one of the most common causes of automobile accidents, and talking to another person is a very common distraction.
In an effort to observe the impact of conversation on driving, Drews, Pasupathi, and Strayer (2008) conducted a study using a driving simulator that tracks errors committed by drivers. The researchers varied the type of conversation. In one condition, participants had a conversation with a passenger; in another condition, participants talked on a cell phone. There was also a no conversation, control condition. As you would expect, having any conversation resulted in more driving errors. However, the number of driving errors was highest in the cell phone condition.
For this exercise, acquire and read the article:
Drews, F., Pasupathi, M., & Strayer, D. (2008). Passenger and cell phone conversations in simulated driving. Journal of Experimental Psychology: Applied, 14, 392–400. doi:10.1037/a0013119
After reading the article, consider the following:
1. Describe how well you think the sample of participants in this study generalizes to other groups of people. What about age? What about sex?
2. In this study, participants were told to have a conversation about a time when “their lives were threatened.” Do you think that the results of this study would be different if the conversation were about something else? How so? Why?
3. Do you think that the findings from this study would generalize to other cultures? Do you think that a sample of college students in Mexico, Italy, and Germany would generate similar results? Why or why not?
4. How well do you think the driving simulator generalizes to real-world driving? What would you change to improve the generalizability of the simulator?Page 307
5. Evaluate the internal validity of this study. Explain your answer.
6. Evaluate the external validity of this study. Explain your answer.
Conceptual replication (p. 302)
Exact replication (p. 300)
External validity (p. 292)
Literature review (p. 303)
Meta-analysis (p. 303)
Replication (p. 300)
Solomon four-group design (p. 298)
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