PPT presentation PSY applied project

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PSY 496 apply project

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In this discussion, you will create a presentation from the point of view of two specific professionals who are experts on the topic suicide .

For this discussion:

  • Consider the psychological career alternatives available and determine from which fields of expertise your two points of view will come.
  • Select the two professionals you will use with expertise on the topic you selected. Your professionals’ identity may be based on a real person that you know, or they may be made-up based on the job description of a professional in the field. The titles of your professionals should represent actual jobs (based on job descriptions) from categories in two different areas of mental health (e.g., psychiatry and psychology, social work and counseling).
  • In one or two sentences, briefly introduce your experts by describing their current careers as well as their backgrounds. The experts will be providing scholarly information on your selected topic based on the point-of-view of their respective professions.
    Provide evaluations from the experts in the course of the presentation, regarding contributions of psychological research on the chosen topic in an applied context.
  • Include information from at least two peer-reviewed articles that were published within the last five years to substantiate your experts’ claims. You must select these two articles on your own. You may not use resources listed within this course.
  • To begin, create a presentation using the Sample Presentation Template, of at least five slides (not including the title and reference slides).

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A Presentation by Experts [Your Name] [Date] PSY 496  [Provide a brief, general explanation of the topic chosen in Week One (2-3 sentences).]  [The topic is…]  [The reason it is important]  [Issues and controversies]  [At least 2 key questions about the topic] [Replace the pictures with others of your own choosing.] [Name, Degrees, Profession]  Expert  1 [Background/Brief Biography: 1-2 sentences] [Name, Degrees, Profession]  Expert  2 [Background/Brief Biography: 1-2 sentences] [You may use up to 2 slides for this section.]  Describe her or his evaluation of the contributions of psychological research on the chosen topic in an applied context.  Be sure to include information from at least one peer-reviewed, journal article or chapter from a an edited scholarly book of your choice, published within the last 5 years, to substantiate your experts’ claims.  Include a website recommended by the expert. [You may use up to 2 slides for this section.]  Describe her or his evaluation of the contributions of psychological research on the chosen topic in an applied context.  Be sure to include information from at least one peer-reviewed, journal article or chapter from a an edited scholarly book of your choice, published within the last 5 years, to substantiate your experts’ claims. This article should be different from the article you used with Expert 1.  Include a website recommended by the expert. Expert 1’s Name 1. Point 1 2. Point 2 3. Point 3 [Use 1-2 words to describe each point.] At least one idea both have in common Expert 2’s Name 1. Point 1 2. Point 2 3. Point 3 [Use 1-2 words to describe each point.] [List all references used in alphabetical order in accordance with APA guidelines.]  [Peer-reviewed journal article 1, in APA format]  [Peer-reviewed journal article 2, in APA format]  Piotrowski, C. (2012). Research areas of emphasis in professional psychology: Past and current trends. Journal of Instructional Psychology, 39(2), 131-135. Retrieved from the ProQuest database.  [Website 1, in APA format]  [Website 2, in APA format] 4 Associated Press Quasi-Experimental Designs Chapter Learning Outcomes After reading and studying this chapter, students should be able to: • understand the important role that quasi-experimental designs play in answering research questions of interest when participants in a research study cannot be randomly assigned to conditions. • articulate the appropriate research scenarios for a number of quasi-experimental design approaches, including nonequivalent control groups, time series, cohort/panel, and regression discontinuity designs, as well as the applications of program evaluation. • appreciate the practical applications and limitations of observational designs such as case studies and naturalistic observation. • understand the contexts in which archival research approaches, such as content analysis and meta-analysis, can answer interesting questions based on the availability of pre-existing data. lan66845_04_c04_p101-130.indd 101 4/20/12 2:47 PM CHAPTER 4 Introduction Introduction I n the ideal world, psychology researchers would like to be able to understand causeand-effect relationships as they pertain to attitudes and behaviors. Cause-and-effect conclusions are powerful, because they provide insight as to how positive behaviors can be promoted and how negative behaviors can be lessened. Not all research situations lend themselves to laboratory controls and randomization of participants to conditions. So outside of the laboratory (and even sometimes in the laboratory), we apply research methods as best we can, but without random assignment. Much of the research conducted in the social sciences is conducted using quasi-experimental designs. In fact, there are times where random assignment is inappropriate, such as withholding health care services from children for the sake of an experimental study (Bawden & Sonenstein, n.d.). Say that I wanted to study how effective the use of clickers (student response systems) might be in the classroom. I’m teaching two sections of introductory psychology, and I decide that I will use clickers in one of the sections, and I won’t use clickers in the other section. At the end of the semester, I want to see if students earned more points in the section with clickers than in the section without clickers. This would be a quasi-experimental design, because I am unable to randomly assign students to sections (students usually like selecting their own classes). In fact, using X and O, here’s what the design would look like (remember, X represents the independent variable manipulation and O represents the dependent variable measure): X clickers   O points O points If I had been able to randomly assign participants to conditions, there would have been an R (for randomization) at the beginning of each line. This design is called a nonequivalent control groups posttest only design. Although it is a good idea to have a control group, because of the lack of randomization, we are less confident that the groups were equivalent even before the start of the study—thus, we label the design as nonequivalent. This is one example of the types of designs that are collectively known as quasi-experimental designs. In this chapter, we’ll investigate the advantages and disadvantages of quasi-experimental designs, observational designs, and archival research. Voices from the Workplace Your name: James K. Your age: 47 Your gender: Male Your primary job title: Co-Director of Community Living Your current employer: Village Northwest Unlimited How long have you been employed in your present position? 27 years (continued) 102 lan66845_04_c04_p101-130.indd 102 4/20/12 2:47 PM CHAPTER 4 Introduction Voices from the Workplace (continued) What year did you graduate with your bachelor’s degree in psychology? 1982 Describe your major job duties and responsibilities. I am responsible for coordinating services for nearly 60 clients. Our clients are all adults with physical or mental disabilities or both. I also help oversee the 60 staff that provides care and services for these individuals, including meeting with them on a quarterly basis to review the care programs being provided, conducting performance reviews. I help develop new training goals, and provide guidance to staff and clients on how to effectively complete their work and grow. I conduct Quality Assurance on documentation samples that are written by our staff, and perform follow-up reports to the various staff teams that we supervise. One of our goals is to encourage and support our staff, and we make this a priority in our work. What elements of your undergraduate training in psychology do you use in your work? I would say the training we received in counseling and helping techniques is probably the most beneficial and frequently used education from my undergraduate training. What do you like most about your job? The flexibility of schedule. What do you like least about your job? Bureaucracy and poor communication with and from the various funding streams that we work with and those hired to oversee this. Poor wages for staff. What is the compensation package for an entry-level position in your occupation? It would be a range of $19,000–$25,000 for a middle management person, $15,000–$18,000 for a fulltime direct care staff. What benefits (e.g., health insurance, pension, etc.) are typically available for someone in your profession? Major Medical Health Insurance, Life Insurance, various perks offered by our agency such as reduced costs for various items like newspaper subscriptions, wellness or fitness memberships. What are the key skills necessary for you to succeed in your career? Patience, good listening abilities, creativity understanding, integrity, honesty, and willingness to go the extra mile. Thinking back to your undergraduate career, what courses would you recommend that you believe are key to success in your type of career? Abnormal Psychology, Theories of Counseling, Developmental Psychology. As an undergraduate, do you wish you had done anything differently? If so, what? I don’t think so, I was adequately prepared in my education for my job. What advice would you give to someone who was thinking about entering the field you are in? Be focused and dedicated to the people you are serving or trying to help. They are someone else’s son or daughter and have tremendous value. Try to instill ways of making your job FUN and enjoyable. Encourage and support those that work with you. Create a climate of participative decision-making so that everyone feels invested in what is being decided. Show honor and respect to those above you and to those you come into contact with each day, make them feel valued and important. (continued) 103 lan66845_04_c04_p101-130.indd 103 4/20/12 2:47 PM CHAPTER 4 Section 4.1 Quasi-Experimental Design Types Voices from the Workplace (continued) If you were choosing a career and occupation all over again, what (if anything) would you do differently? I can’t think of anything that I would choose to do differently. Copyright . 2009 by the American Psychological Association. Reproduced with permission. The official citation that should be used in referencing this material is R. Eric Landrum, Finding Jobs With a Psychology Bachelor’s Degree: Expert Advice for Launching Your Career, American Psychological Association, 2009. The use of this information does not imply endorsement by the publisher. No further reproduction or distribution is permitted without written permission from the American Psychological Association. 4.1 Quasi-Experimental Design Types A quasi-experiment is “a design that manipulates the presumed case and measures the presumed outcome but does not randomly assign participants to conditions” (Shadish & Cook, 2009, p. 619). The example with the clickers is a nonequivalent control groups design, but sometimes there isn’t even a control group (these types of designs are sometimes referred to as pre-experimental designs; Morgan, Gliner, & Harmon, 2000). Using our X’s and O’s, here is an example: X   O The above is a posttest only design (commonly used) but yields very little information that can be generalized beyond the participants being tested. A common example would be the teaching evaluations you provide at the end of the semester. The instructor taught the class (X), and you provided an evaluation (O) at the end of the semester. Although helpful to the instructor, there is not much we can say about whether this instructor is effective as compared to other instructors, if one class learned better than another class, and so on. Another pre-experimental design is the one group pretest-posttest design: O1   X   O2 In this case, we can observe if there was change from pre to post, but little else. Staying in class, perhaps at the beginning of a math course you are given a comprehensive pretest (O1), and at the end of the course (X) you are given the same test again (O2). This design will allow us to detect change over time, but that may not provide much useful information to the instructor. What if you were a math wizard coming into the course, and over the semester you didn’t learn much? That might make it look like the instructor didn’t do a very good job, when it was your excellent preparation that explains why your scores didn’t increase much over time. Note that in discussions about K–12 teacher salaries and meritbased pay, the ability to demonstrate student learning over time is a huge issue. So this pre-experimental design does allow us to inquire about change over time, but it provides little insight as to why changes may have occurred. We could also add a pretest to this nonequivalent control groups design, making it a pretest-posttest design, as depicted below: O   X   O O O 104 lan66845_04_c04_p101-130.indd 104 4/20/12 2:47 PM CHAPTER 4 Section 4.1 Quasi-Experimental Design Types Although random assignment is not achieved with this design, the existence of a pretest does allow us to explore whether the groups were different at the start on the variables that were measured. This is not the same as randomization, but at least if the groups were roughly equivalent prior to the introduction of the independent variable, then our confidence increases as to what the possible implications of the results mean. Nonequivalent Control Groups The nonequivalent control groups design is quite common throughout the social sciences and psychology, and here we’ll discuss just a sampling of practical applications of this design. For example, to measure the impact of a computer-based training program for nurses, Hart et al. (2008) administered a pretest questionnaire, delivered information about evidence-based practice, and then administered a posttest questionnaire. This is the classic pretest-posttest design, and here’s what it would look like graphically: Oevidence-based practice pretest Xcomputer based education program Oevidence-based practice posttest This type of design lets the researchers know if the participants changed over time. However, it’s hard to gauge the effectiveness of the intervention (X) without a control group. Sometimes the constraints of the situation make random assignment impractical. For example, a medical school decided to implement a new form of ethics training for its students based on small-group ethics teaching (Goldie, Schwartz, McConnachie, & Morrison, 2001) but wanted to compare this new approach with the previous lecture-style largegroup ethics instruction. Rather than randomly assign students to different instructional conditions, new incoming medical students received the new curriculum, and students from the previous year were utilized as the control condition. The experimental design would look like this: Osurvey score   Xnew curriculum   Osurvey score   (experimental group) Osurvey score   Xold curriculum    Osurvey score   (control group) Luckily, under the old curriculum, an ethics and health care survey had been administered both pretest and posttest. These same instruments were utilized with the new small group ethics discussion sections. Goldie et al. (2001) found that the new curriculum led to greater consensus in considering ethical situations and concluded that “small-group ethics teaching, in an integrated medical curriculum, had a positive impact on first-year students’ potential ethical behavior. It was more effective than a lecture and a large-group seminar-based course in developing students’ normative identification with the profession of medicine” (p. 295). Even though a true experiment was not conducted here, you can see the benefit of the outcomes of the quasi-experimental design—we can learn much from these types of designs, even if we cannot draw a cause-and-effect conclusion. Time Series Design In its simplest form, quasi-experimental research using a time series design “. . . is simply a set of repeated observations of a variable on some entity or unit, where the number of repetitions is relatively large” (Mark, Reichardt, & Sanna, 2000, p. 353). For example (Garson, 2008), the monthly calculation of the national unemployment index by the 105 lan66845_04_c04_p101-130.indd 105 4/20/12 2:47 PM CHAPTER 4 Section 4.1 Quasi-Experimental Design Types Bureau of Labor Statistics would be considered a simple time series design. In essence, you can think of this as an extended sequence of dependent variable measurements (O). A simple time series would look like this: O   O   O   O   O   O   O   O   O   O   O   O The above 12 observations could be the monthly reporting of the unemployment index, for example. As you can imagine, the time series design allows for the assessment of change over time—trends—but it can do much more than that (Mark et al., 2000). A time series design can also be used for forecasting. For example, if an economist is tracking unemployment rates, he or she may use this data to try to predict what will happen six months from now, based on the data accumulated leading up to this point in time. Time series designs can become more complex as we introduce independent variables (X) in to the mix, such as a particular treatment or intervention. These types of designs are sometimes called interrupted time series designs (Cook & Campbell, 1979; Mark et al., 2000) because of the interruption (X) over the series of observations (O’s). This type of design might look like this: O   O   O   O   O   O   X   O   O   O   O   O   O Note the independent variable manipulation in the middle of the sequence of observations. This interrupted time series design is often used to measure the impact of legislation and public policy, such as the implementation of a mandatory seat belt law or a ban on cigarette smoking on a college campus. Let’s say you were interested in determining the impact of a smoking ban on your college campus. You might utilize a research design where observers are trained to collect data at various points on campus during different days of the week at different times of day. The dependent variable of interest (O) is the number of smokers observed. You implement this data collection program well If you wanted to study the impact of a smoking ban on a college before the announcement of the campus, you could collect data by observing the number of new smoking ban on campus people smoking throughout the day. that begins on July 1. Here’s iStockphoto/Thinkstock what that design might look like: OJan  OFeb  OMar  OApr  OMay  OJun  XJul  OAug  OSep  OOct  ONov  ODec  OJan Notice that there are six observations before and after the ban takes effect. The goal of the smoking ban would be to reduce the number of smokers, at least the number of smoking incidents observed on campus. One of the benefits of this type of design is that it tracks 106 lan66845_04_c04_p101-130.indd 106 4/20/12 2:47 PM CHAPTER 4 Section 4.1 Quasi-Experimental Design Types changes over time. So after the ban is publicized and implemented July 1, there might be an immediate decrease in observed smokers (maybe they stopped smoking, or are hiding it better). But after a while, say a couple of months, the numbers of observed smokers might increase. (Ever received a speeding ticket? Did you decrease your speeds for the short term, only to return to your regular habits a short time later?) So you can see the benefit of the interrupted time series design, to assess the impact of an intervention. But the drawback of the quasi-experimental design is that we cannot be overly confident about causality—a decrease in observed smokers could mean many things—some stopped smoking, some hid their smoking better, some switched to chewing tobacco, and so on. Time series designs can be expanded to examine the relationship between multiple levels of an independent variable manipulation (Mark et al., 2000). This design might look like this: O   O   O   O   O   O   X   O   O   O   O   O   O O   O   O   O   O   O      O   O   O   O   O   O In fact, this is very similar to the non-equivalent control groups pretest-posttest design, but it includes multiple pretests and multiple posttests. An example of this type of design is the work of Ivancevich (1974) looking at the impact of a management-by-objectives (MBO) approach as well as reinforcement schedules in the performance of a manufacturing corporation with multiple plant sites. Ivancevich measured multiple dependent variables, such as the quantity of output, quality of output, grievance rates by employees, and absenteeism. Three different plants were utilized, as indicated below. Plant 1    O    XMBO   O    O    O    O Plant 2    O    XMBO   O    O    O    XReinf.    O Plant 3    O        O    O    O    O From this research, Ivancevich concluded that the benefit of the reinforcement observed in Plant 2 tended to overshadow the MBO effects. In considering time series designs, there are three factors to keep in mind (Garson, 2008a): age, period, and cohort. In the time series design, variables are repeatedly measured over time. Given that people can naturally change over time without any exposure to an independent variable, sometimes it will be difficult to disentangle a change due to the independent variable, or just the passage of time. There are also period effects as well, meaning that individuals from a particular historical period may be impacted similarly. Garson suggested that those individuals who lived through the Great Depression, the Challenger explosion, or 9/11 may have similar beliefs and behaviors. Thus, recording times series data over long periods of time (e.g., decades), the researcher must understand that historical events may be impacting the change or lack of change seen in a time series design. Finally, cohort effects should be considered. A cohort effect occurs when people from a particular age range are impacted differentially by a historical event. For instance, Garson (2008) suggested that after World War II, young adults at this time (a cohort) reacted differently than past generations to the challenges of the later Vietnam War. Thus, the idea of a cohort effect is the intersection of a group of people in time with a historical event that impacts that group; the post–World War II cohort appeared to be more suspicious of the U.S. government and its policies as compared to earlier cohorts. Some quasi-experimental studies are specifically designed to examine cohort effects, and these types of designs are called cohort designs and panel studies. 107 lan66845_04_c04_p101-130.indd 107 4/20/12 2:47 PM CHAPTER 4 Section 4.1 Quasi-Experimental Design Types Cohort Designs and Panel Studies As Alwin, McCammon, and Hofer (2006) pointed out, cohorts can take on a number of identities. Sometimes researchers think of cohorts as generations, such as baby boomers or millennials. The term birth cohort is used to identify a group of people who were all born in the same year. But a general definition of cohort is a group of people who have shared critical experiences over the same span of time; however, a cohort may not be equivalent to a generation, nor may a collection of adjacent cohorts necessarily be considered a generation (Alwin et al., 2006). In thinking about the three keys to time series (age, period, cohort), we can construct a standard cohort table that depicts these factors simultaneously (Alwin et al., 2006; Garson, 2008). In the cohort study, individuals are randomly sampled for each of the “cells,” thus a measure of net change over time (period), age, and cohort can be acquired (see Figure 4.1). Figure 4.1: Standard cohort approach for a longitudinal study Year of Study (Period) Age 1980 1990 2000 2010 20–29 30–39 40–49 50–59 60–69 70–79 80–89 This figure depicts the complexity of a standard cohort approach over time. In 1980, there are random samples of individuals from each of the age groupings on the leftmost column. Ten years later, additional random samples are taken for each of the age groupings depicted in the leftmost column. Note that this study would take 30 years to complete. Source: Wuench (2003) As you can see from above, age is depicted across the rows, period is depicted down the columns, and the cohorts are identified by the diagonal lines crossing individual cells. For just a moment, think about the complexity of this design. First, your study takes 30 years to complete (launched in 1980, completed in 2010). Second, you recruit many people from many age ranges, from 20-year-olds to 89-year-olds. In the typical cohort study, participant selection is random; that is, different people participate at the different periods of time. To follow a cohort, you would follow the diagonal line as time passes and participants age. You should know that not all quasi-experimental cohort designs involve 10-year time periods where the study spans 30 years. Many, if not most, cohort designs are based on shorter 108 lan66845_04_c04_p101-130.indd 108 4/20/12 2:47 PM CHAPTER 4 Section 4.1 Quasi-Experimental Design Types periods. In fact, relatively short (6 months to 1 year) cohort studies have been used to examine the effectiveness of new therapeutic approaches to help couples (Epstein et al., 2007), minor depressive disorders, and miscarriage (Klier, Geller, & Neugebauer, 2000) and to monitor the development of social skills in kindergartners (Hall, Jones, & Claxton, 2008). Panel studies, also called prospective cohort studies, add an interesting twist to the standard cohort study—they follow the same individuals over time. In a typical cohort study, like the one depicted previously, different individuals are recruited and studied in 1980, 1990, 2000, and 2010. In the panel study/prospective cohort study, using this same structural example, the same people would be tracked for 30 years, which would take enormous effort, expense, and organization. These types of studies are relatively rare, yet particularly informative. To illustrate a panel study, the chart has been modified to add start points and arrows to indicate that the same individuals are being studied over time (see Figure 4.2). Figure 4.2: Panel study or prospective cohort study for longitudinal research Year of Study (Period) Age 1980 1990 2000 2010 20–29 30–39 40–49 50–59 60–69 70–79 80–89 This figure depicts the complexity of a panel study approach over time. In 1980, there are samples of individuals from each of the age groupings on the leftmost column selected. These same individuals are tracked over time and tested 10, 20, and 30 years later. Thus one age grouping is followed over time. Note that this study would also take 30 years to complete, but is much more complicated than a standard cohort table design because in the panel study the same individuals are tracked and tested over time. Source: Wuench (2003) An impressive example of this type of study was conducted by Wilson and Widom (2008), who studied individuals who had been victims of abuse and neglect during childhood. These researchers conducted a 30-year follow up with the original participants using a prospective cohort design. Although the results are complex, the major finding was that individuals who were maltreated as children were more likely to report sexual contact before age 15, participate in prostitution by their young adult years, and test positive for HIV during middle adulthood as compared to individuals who were not maltreated as children. These types of studies are invaluable in helping psychologists understand the role of childhood experiences and how these experiences may shape choices and behaviors in various stages of adulthood. 109 lan66845_04_c04_p101-130.indd 109 4/20/12 2:47 PM CHAPTER 4 Section 4.1 Quasi-Experimental Design Types Regression Discontinuity Designs The regression discontinuity design (RDD) is a unique member of the quasi-experimental design family in that it leads to conclusions that are similar in strength to randomized controlled trials (Lesik, 2006; Rutter, 2007). Regression discontinuity designs are sometimes called cutoff-based designs because assignment into the treatment group or the control group is based on a predetermined cutoff (Shadish & Cook, 2009). From a population of individuals, a cutoff score is set before the study begins, and then the trends (regression lines) are followed to see if they are continuous or not. Think about it this way—an RDD is a good choice if you are working in a situation where some remediation may be helpful to a subgroup of the population (Lesik, 2006), such as students who need extra help with math, or employees who may be facing layoffs in a weak economy. Rather than randomly assigning participants to conditions, such as with a coin toss, the RDD sets a cutoff score, and scores above the cutoff are assigned to one condition of the study, while scores below the cutoff are assigned to the other condition of the study (Lesik, 2006). Figure 4.3: The first part of a regression discontinuity design 22 C C 20 C 18 C C C C Posttest C C C C C T T T T T T 14 C T C T C C C T T T C C C T 12 T T TT 10 Cutoff T 8 2 3 4 5 6 7 8 9 10 11 Pretest This graphic depicts the first part of a regression discontinuity design, where the relationship between two variables (here: pretest and posttest) is identified. Now, an intervention is about to be applied to the T (treatment) individuals. Source: Lesik (2006) 110 lan66845_04_c04_p101-130.indd 110 4/20/12 2:47 PM CHAPTER 4 Section 4.1 Quasi-Experimental Design Types An example with pictures might be helpful here (Wuensch, 2003). Look at the graph in Figure 4.3. On the x-axis is the pretest, and on the y-axis is the posttest score. The T’s and C’s represent individual people, graphically depicting their placement with regard to their pretest and posttest scores. The solid blue line is the regression line—this is the line of best fit, the line that best captures the linear relationship between the pretest and posttest scores. As you can see, there is no “discontinuity”—the line is solid and continuous. The vertical black line just below the pretest score of 6 represents the cutoff. Thus every person scoring just below a 6 is placed into the treatment group (depicted by T’s), and everyone scoring above the cutoff is a control participant (C’s). If, after the study was complete, the results looked like this graph, this would tell us that there was no effect of the intervention/independent variable on the treatment group—in other words, the regression line shows continuity. But what if there had been an effect? What would that look like? Well, as in most research, we are looking for the independent variable to influence the dependent variable. In RDD we have that evidence when we see a regression discontinuity—a break in line (and/ or different line slopes) on either side of the cutoff. See the example in Figure 4.4 from Wuensch (2003). Figure 4.4: The second part of a regression discontinuity design 22 C 20 C Posttest C C C C 18 T T T T 16 CC C C CC C CCC T T CC T 14 C C T T T C T T T T C T 12 T Cutoff 10 0 2 4 6 8 10 12 Pretest This is a hypothetical example of a regression discontinuity design where the intervention (the treatment, T) was effective. Rather than a linear (straight-line) relationship between the pretest and the posttest, the lines are now broken (i.e., discontinuous). Source: Wuensch (2003) 111 lan66845_04_c04_p101-130.indd 111 4/20/12 2:47 PM CHAPTER 4 Section 4.1 Quasi-Experimental Design Types The dashed line to the left of the cutoff reminds us about the original continuous regression line, and the break in the solid lines on either side of the cutoff demonstrates a regression discontinuity. In this case, the treatment worked—posttest scores are higher (the new red line) for the lowest-scoring pretest participants as compared to where we would have expected them to be. You can see where RDD could be very useful when scores are used to determine membership in programs or receipt of benefits, such as need-based programs for scholarships, or scores that are used as cutoffs to determine which children are enrolled in gifted and talented programs in elementary schools. One key consideration to remember is that the cutoff score must be determined prior to the beginning of the study (Lesik, 2006; Rutter, 2007; Shadish & Cook, 2009). RDD adds another useful approach to studying behavior outside the laboratory in the use of quasiexperimental designs. Program Evaluation Quasi-experimental approaches are often employed in program evaluation efforts because of the emphasis on evaluating a program in its context, not in the laboratory. The basic idea of program evaluation is to assess the impact of a program based on its pre-stated goals (Rose & Fiore, 1999). But what do we mean by a program? A program tends to serve a known population, is long-lasting, and attempts to solve a limited set of problems (Greene, 2003). Examples of programs that would be suitable for program evaluation would be a local Head Start program, the McNair Scholarship program, or perhaps the ongoing performance of your Department of Psychology. Greene (2003) provided excellent examples of what program evaluation is not: it is not a single methodology or data collection instrument, not data collection that occurs at the end of a program cycle, and not decisions made about the value or worth of a program. Program evaluation efforts tend to follow in three distinct phases, as outlined by Greene (2003). In the generation phase, a needs assessment may be conducted prior to the implementation of a program, to see if the need justifies the implementation of a program, followed by program development and refinement. In the implementation phase, the program begins, provides services to clients and the community, and hopefully has a positive impact. In the causation phase, the program evaluator attempts to demonstrate and measure the impact of the program, such as the delivery of services to clients, clients’ evaluation of services, and the impact felt by other agencies or the community in general. For example, a legislator might be concerned about reports of unplanned teenage pregnancy in his or her legislative district. Following a program evaluation approach, the first step would be to generate possible programs that could address the concern of unwanted teenage pregnancies, using local or national programs that promote abstinence, contraception, or both strategies. The needs analysis conducted prior to program implementation would provide baseline data as to the true nature and scope of the issue—is the teen pregnancy rate on the rise, or are there just some well-publicized recent events that bring this topic to light? Following a needs analysis, a public relations (PR) campaign may be implemented to try to change teenagers’ attitudes and opinions about sexual activity, with the ultimate goal to influence behavior. This might be implemented, for example, by a state agency such as a Health and Welfare District, which might provide workshops for middle school and 112 lan66845_04_c04_p101-130.indd 112 4/20/12 2:47 PM CHAPTER 4 Section 4.1 Quasi-Experimental Design Types high school sex educators to offer curriculum material for teaching teenagers strategies to avoid unwanted pregnancy. Throughout the program, evaluations may be conducted, asking local sex education teachers about their perception of how the program is working. Additionally, teens might be surveyed about program perceptions and any possible behavior changes. In addition, the program evaluator might examine epidemiological data from the county or legislative district to examine if the rate of teen pregnancy did decline over the period of the implementation of the program. Although it continues to be difficult to draw causality conclusions when using a quasi-experimental design (Rose & Fiore, 1999), this convergence of data might be used by citizens and legislators alike to evaluate the effectiveness of the program and determine whether the program should continue. In fact, program evaluation and other quasi-experimental approaches are often used to help answer public policy questions, as well as to generate new ideas on how to solve complex social issues. Case Study: Answering Public Policy Questions Although naturally implied, public policy questions should hopefully lead to public policy answers, and this is just one of the domains of program evaluation and the use of experimental and quasiexperimental designs. The need for increased program evaluation services comes, in part, with the necessity for agencies to be held accountable for government-sponsored human services programs. According to Hosie (1994), “program evaluation plays an extremely important role in policy-making. Outcome data is [sic] provided to decision makers who determine the value and worth of programs based on outcome and available financial resources” (p. 349). McCartney and Weiss (2007) took this notion (at least) one step further when they stated “policies designed to improve the life chances of children and families often live or die on the basis of the findings from evaluation research” (p. 59). It seems clear that program evaluations are used to affect federal, state, and local agency policy decisions (Hosie, 1994). Given this weight, it should be obvious how important it is to get appropriate answers in the course of addressing public policy questions. Historically, psychologists have had some success in helping to answer public policy questions, but as you’ll see, psychology can do much more. Lodzinski, Motomura, and Schneider (2005) suggested that the best public policy influence in psychology was the role psychological science played in 1954 in influencing the Brown v. Board of Education Supreme Court ruling, which essentially made racial segregation in public schools unconstitutional. The contributions of psychologists, especially Kenneth B. Clark, made the argument that segregating White and African-American students led to poorer self-esteem for African-American students and that segregation was a source of interracial prejudice. In the U.S. Supreme Court ruling, psychological research was openly credited with influencing the decision, and this case has been credited with forever connecting psychology and public policy (Lodzinski et al., 2005). Critical Thinking Questions 1. Quasi-experimental designs are complex yet allow for research conclusions to be drawn outside of the laboratory. Thinking about your current or future work environment, can you think of one real-world situation where you could use a nonequivalent control groups design, times series design, cohort design or panel study, and regression discontinuity design? 2. The research methods presented in this chapter provide you with impressive additions to your toolkit or Swiss Army knife regarding how research methods can allow for the study of challenging, real-world questions. However, good science communicates outcomes, especially if the goal is to influence public policy. How would you present one of the methodologies (continued) 113 lan66845_04_c04_p101-130.indd 113 4/20/12 2:47 PM CHAPTER 4 Section 4.1 Quasi-Experimental Design Types Case Study: Answering Public Policy Questions (continued) discussed so far, say regression discontinuity design, to the general public? That is, how would you translate the benefits of this design approach to actual data such that others can see the benefit and comprehend the impact? Note: This is a valuable skill—if you want to see if you understand a concept, attempt to teach that concept to someone else. 3. Large social issues, such as public schooling, unemployment, teen pregnancy, universal health care, poverty, and homelessness, are complex on many levels. How might different aspects of research methods (that is, different features in your ever-growing Swiss Army knife of available tools) be used to address such large, complex societal concerns? There are some fundamental lessons that evaluators and public policy makers can keep in mind when examining the effectiveness of a program evaluation (McCartney & Weiss, 2007): • • • • • Use mixed method designs—in other words, use different approaches to attempt to capture the totality of the program. If true experiments (e.g., randomized controlled trials) are not possible, then use quasi-experimental methods to help measure the effectiveness of programs and public policy implementations. Interpret effect size in a research context—when conducting statistical analyses on the data from program evaluation research, one must go beyond the typical inferential/null hypothesis significance testing and look at effect sizes. This helps researchers distinguish between statistically significant artifacts and conditions where the results indicate practical significance. Synthesize all research findings—this chapter ends with a presentation of metaanalysis, which is a methodological procedure that allows researchers to combine the results of many studies into broad recommendations and findings. Adopt fair and reasonable scientific expectations—scientific data may go only so far in helping to answer public policy questions. Researchers must be careful not to overstate the relative impact or contribution of a set of data. Encourage peer and public critique of the data—we need to invite our peers and the public to scrutinize our work and the resulting impact that our work has in impacting the research community. Ultimately, the success that psychologists have in influencing public policy decisions may heavily rest on the public’s ability to interpret what we do. In the day-to-day functioning of a scientist, data are paramount, but policy makers and the public may not similarly appreciate a data-driven approach. McCartney and Weiss (2007) reminded us that in addition to empirical data, policy makers and citizens consider anecdotal evidence and testimonies, newspaper features, politics as usual, and so forth. Add to this mix the influence of blogs and cable news programs that feature partisan approaches, and there are many voices that contribute to the complexity of decisions to be made. Public policies, whether we like it or not, are political entities, and the success or failure of public policy can lead to the success or failure of those in government. Psychology needs to inform the public on what it can provide to public policy table, for the potential contributions are formidable. In 2002, Philip Zimbardo, president of the American Psychological Association, made this statement not long after the tragic events of 9/11 regarding relevance of psychology to the shaping of public policy: 114 lan66845_04_c04_p101-130.indd 114 4/20/12 2:47 PM CHAPTER 4 Section 4.1 Quasi-Experimental Design Types Even before the September 11th tragedy, most of the major problems facing the United States were psychological in cause, correlates, or consequence: for example, AIDS and sexually transmitted diseases; drug addiction, as well as addictions to smoking, gambling, alcohol, and food; prejudice and discrimination; delinquency; violent crimes; educational failures for too many minority youth; and the full range of physical illnesses that are influenced by lifestyle and behavioral functioning. Psychologists have much to say about more effective ways of dealing with these problems at both individual and community levels of action. Psychologists need to be heard and to be at the table of influential leaders and policymakers because psychologists have more to say about these issues than do members of any other discipline (p. 432). Classic Studies in Psychology: Work Decisions and Absenteeism (Lawler & Hackman, 1969) If you had the chance to develop a program at work that could add to your paycheck, would you take that opportunity, or would you be skeptical and cynical about what management was up to? If the plan were designed by coworkers at another location but imposed on you, would you gladly accept the opportunity to earn more, or would you not invest your efforts into the program, since you had no hand in designing it? These are some of the real questions that Edward Lawler and Richard Hackman began to answer in 1969. These researchers worked with a large service that cleaned buildings in the evenings, and there were various groups of employees who did not work in similar locations but performed similar tasks. Essentially, there were three groups in this quasi-experimental design. It should be noted that Lawler and Hackman (1969) purposely chose this design because conducting the study in the field would increase the probability that the results of this research could be generalized to other settings (i.e., enhance external validity). The first group in the study is labeled the “participaFlirt/SuperStock tive” group, and these workers designed their own pay-for-performance incentive plan, with the help of researchers and the supervision of management. The second group in the study is the “imposed” group, which received the exact same incentive plan as the participative group, although the imposed group had no say in its development; thus, it was imposed upon them. The third group was the control group, and in actuality, there were two different versions of control group. One control group talked to researchers about the pay for performance plans, absenteeism, and turnover, but no changes were made to its incentive plan. Another control group received no information at all about the study and was not contacted by researchers or top management about the study. As you can see in Figure 4.5, the researchers looked at the percentage of scheduled hours worked, both before the intervention (pay plans) and after. The graph presents the data for the participative group. For example, if an employee were scheduled to work 40 hours in a week but was only present for 32 hours, on the y-axis this would yield a score of 80%. When averaged together, employees in the participative group worked 88% of their scheduled hours before the incentive plan was introduced. After the incentive plan, they worked 94% of their scheduled hours (a statistically significant increase). (continued) 115 lan66845_04_c04_p101-130.indd 115 4/20/12 2:47 PM CHAPTER 4 Section 4.1 Quasi-Experimental Design Types Classic Studies in Psychology: Work Decisions and Absenteeism (Lawler & Hackman, 1969) (continued) Figure 4.5: An example of quasi-experimental data Percent of Scheduled Hours Actually Worked 100 95 90 85 80 75 70 12 11 10 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 10 11 1213141516 Before After Weeks Participative group results from Lawler and Hackman study. Source: Lawler and Hackman (1969) Now consider the results of the “imposed” group, displayed in Figure 4.6. This group received the same incentive plan, with the only difference being that its members did not design it or contribute to its creation. The data for the imposed group are below. Before the incentive plan was introduced, employees in the imposed group worked 83% of their scheduled hours; after the incentive plan, they also worked 83% of their scheduled hours—no change. Both control groups saw no change either from pre–incentive plan to post–incentive plan. Figure 4.6: Another example of quasi-experimental data Percent of Scheduled Hours Actually Worked 100 95 90 85 80 75 70 12 11 10 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Before After Weeks “Imposed” group results from the Lawler and Hackman study. Source: Lawler and Hackman (1969) (continued) 116 lan66845_04_c04_p101-130.indd 116 4/20/12 2:47 PM CHAPTER 4 Section 4.2 Observational Designs Classic Studies in Psychology: Work Decisions and Absenteeism (Lawler & Hackman, 1969) (continued) Because this study was so well designed, it leads to some fascinating conclusions. Lawler and Hackman (1969) found that “the data show that employee attendance improved only in those groups that participatively developed their own incentive plans. Neither the incentive plan alone nor participation and discussion alone yielded any changes in attendance” (p. 470). Clever design, including the control groups, leads to this meaningful conclusion. If the incentive plan were all that was needed, then the imposed group would have seen increases too. If just discussion were enough, one of the control groups would have shown increased in the percentages of hours worked. The conclusion here was that participation and implementation of the plan were necessary to see significant increases in work; either option alone was ineffective. This study has been influential in informing the literature about how top management teams operate (e.g., West & Anderson, 1996), as well as in educating us on when pay-for-performance works, and when it may not (Beer & Cannon, 2004). Critical Thinking Questions 1. It is one thing to talk about abstract ideas in the context of a textbook, but when people start to discuss personal issues like salaries, you can imagine there might be some concern when researchers want to enter a situation and implement programs that could affect an employee’s paycheck. What role do researchers have in educating the public (and educating research participants) about the potential beneficial role (as well as potential drawbacks) to experimentation? 2. Completing coursework in a 5-week session requires diligence, motivation, and determination. Think about the courses you have completed in this mold, and the different design features of those courses. Were there conditions or scenarios in some classes that motivated you to work harder than in other classes? Was that due to the content of the course, the design of the course, or both? Using a quasi-experimental approach, how might a researcher study how a course is structured and its relationship to student learning? 3. Can you look at a graph, study it, and decipher its meaning, or do you just gloss over graphs and figures? Are you more convinced by a persuasive story when in is presented in words (text) or pictures (graphs)? Why is that? What steps do you think you would need to take to become better versed in your non-preferred modality? 4.2 Observational Designs W ithin the scope of this chapter, a thorough and comprehensive review of observational research is just not possible. We’ll focus here on two key approaches— case studies and naturalistic observation, with a brief overview of the terminology most relevant to this topic (Brown, n.d.; Garson, 2008; Pope & Mays, 2006). Some designs are summarized in Table 4.1. 117 lan66845_04_c04_p101-130.indd 117 4/20/12 2:47 PM CHAPTER 4 Section 4.2 Observational Designs Table 4.1: Terminology Type Brief Description Field experiments A field experiment involves a research study where the actual data collection occurs in natural settings (in the field). Case study An extensive observation of an individual or a single group is the hallmark of the case study approach. Case studies tend to look at a limited set of behaviors rather than the totality of the person or group. Naturalistic observation Using naturalistic observation, the researcher is involved in the direct observation of behavior as it occurs in its natural setting. In principle, the researcher does not interact within the environment being observed, but only observes. Participant observation In participant observation, the researcher inserts him- or herself into the environment being studied, which can be especially useful when studying group processes. Researchers using this technique must be careful to remain objective and avoid observer effects (those who know they are being observed may change their own behavior due to the observation). Action research Action research is a subset of participant observation in which the researcher in the natural environment works to change some aspect of behavior or the organization. These actions are designed to improve conditions for the participants or the organization. Rather than test a hypothesis, action research attempts to overtly change behavior. Archival research Archival researchers study the records that already exist that were originally recorded in natural settings. Surveys Surveys are a versatile methodological approach because they can be administered to individuals in natural settings as part of a fieldwork approach. Program evaluation Program evaluation involves the evaluation of systematic programs in applied settings. That is, program effectiveness is determined by how patients or clients are served in the field. Ethnography Ethnography involves the direct observation of people during daily life. This term is sometimes used interchangeably with case study, and ethnography refers to both a research process and the type of report that is written as a product of that research. Case Studies The case study approach focuses on a particular case of interest, and this case may be a person, a group, or perhaps an organization. Case studies can utilize qualitative and quantitative methods. In fact, a research strategy called triangulation encourages researchers to study the variable of interest from multiple perspectives, and not over-rely on any one research approach. Researchers using a case study approach can be forward-looking (prospective) or look back in time (retrospective); they can approach theories inductively or deductively; and they can strive to describe, evaluate, or explain behavior (Garson, 2008b; Walsche, Caress, Chew-Graham, & Todd, 2004). Because the approach is so diverse, it is 118 lan66845_04_c04_p101-130.indd 118 4/20/12 2:47 PM CHAPTER 4 Section 4.2 Observational Designs often difficult to define the case study, but the overriding concern may be the case of interest, rather than the methodological approach used (Stake, 1994): Case study is not a methodological choice, but a choice of object to be studied. We choose to study the case. We could study it in many ways. The physician studies the child because the child is ill. The child’s symptoms are both qualitative and quantitative. The physician’s record is more quantitative than qualitative. The social worker studies the child because the child is neglected. The symptoms of neglect are both qualitative and quantitative. The formal record the social worker keeps is more qualitative than quantitative. In many professional and practical fields, cases are studied and recorded. As a form of research, case study is defined by interest in individual cases, not by the methods of inquiry used. (p. 236) Case studies can be very influential in helping to understand the historical background of the topic under study, explore unexpected outcomes, delve into the complexity of interrelationships among people and entities, explore gaps between what is intended and what happens, and in general obtain a comprehensive look at the big picture. Although there are limitations to the case study approach, such as the inability to broadly generalize, case studies can be particularly useful in generating hypotheses and theories in newer fields (Garson, 2008b). In other words, when we know little about a topic, the case study can be extremely useful in providing context about a new idea and about how variables may affect behavior. Naturalistic Observation The term naturalistic observation typically implies an observational situation where the researcher does not interact in the environment, but merely A social worker makes a case study of observes it. However, observation-based research a neglected child and will record both is much more complicated. Naturalistic observaqualitative and quantitative data. tion tends to fall into the category of qualitative Liquidlibray/Thinkstock research, and the goal of qualitative research is to understand human behavior holistically (rather than analytically), and consider the social and cultural context in which we behave (Angrosino, 2007). The development of systematic observational protocols is a key component in naturalistic observation research, and these studies tend to fall into one of three broad categories: (a) non-reactive (unobtrusive) research, where the researcher does not participate in the events under observation; (b) reactive research, in which the research is immersed and clearly present in the environment but strives for the role of outside observer; and (c) participant research, where the researcher embeds him- or herself into the environment and participants as an active member of the group being studied (Angrosino, 2007). 119 lan66845_04_c04_p101-130.indd 119 4/20/12 2:47 PM CHAPTER 4 Section 4.2 Observational Designs Observational research, including naturalistic observation, strives for some of the same goals as experimental research, but it also faces unique challenges. Validity and reliability are challenges to observational research (Adler & Adler, 1994). Because data recording and interpretation are key in naturalistic observation, validity may be threatened by an overreliance on any one particular approach. One suggestion that Adler and Adler (1994) offered is to employ a multiple observer A marine biologist observes a shark in the ocean. Naturalistic strategy such that there is not observation implies that the researcher does not interact with overreliance on any one mem- the environment or participants but just watches and records ber of the research team. Reli- observations. ability is also a concern in natFlirt/SuperStock uralistic observation, for if a phenomenon is not stable and consistent, then it is difficult to interpret the impact of the singular observation on overall behavior. Observations that are made over varying times and places may yield higher confidence in the reliability of the findings, or as Adler and Adler (1994) put it, “like many qualitative methods, naturalistic observation yields insights that are more likely to be accurate for the group under study and unverified for extension to a larger population. Observations conducted systematically and repeatedly over varying conditions that yield the same findings are more credible than those gathered according to personal patterns” (p. 381). So what would a naturalistic observation look like, or, in other words, what are the basic steps that are followed? Angrosino (2007) described a typical sequence of events that is followed in naturalistic observation research: • • • In the descriptive phase, the researcher is interested in reporting initial observations that are related to the general research questions under study, as well as providing descriptions of the environment being studied, including the people and the place. At this point, observations should be as value-free as possible, without interpretation—the goal would be statements of fact based on direct observation. Once a broad base is established, the focusing phase begins as researchers strive to sort out relevant observations from irrelevant observations, especially in how these observations relate to the hypotheses and key questions under study. These observations would be more focused on well-defined activities (e.g., traditions, rituals, events) rather than one-time random occurrences. The goal here is to identify patterns, especially how the observed patterns relate the research question of interest. The selective phase might be analogous to a “highway merge” in a large city, where six lanes of traffic are funneled into two lanes. There are still observations to be recorded, but now the key behaviors have been focused on and are under careful scrutiny. Although the entire field of the environment is still under observation, selected observations are used to help provide possible explanations for behaviors. 120 lan66845_04_c04_p101-130.indd 120 4/20/12 2:47 PM CHAPTER 4 Section 4.3 Archival Research • Finally, by the time the saturation point is reached, no new findings are being discovered. The major patterns of behavior are well established and rarely change. Further observation after reaching the saturation point has a relatively low probability of discovering anything new. At this point the data analysis and interpretation phase is about to begin. Success during this phase of the observational research will very much depend on the coding scheme used and the researcher’s attention to detail in following the protocols established before beginning the naturalistic observation. Naturalistic observations can be great sources of new ideas. Take, for example, the study by Chiang (2008) where children with autism were studied using naturalistic observation. Children with autism often can be taught communication skills, but these children often lack the ability to spontaneously utilize verbal and nonverbal skills. The goal of Chiang’s research was to document and categorize the levels of communicative spontaneity in autistic children. Thirty-two diagnosed autistic children, ranging in age from 3 to 16, were videotaped in their natural settings, which included special schools for autistic children, special education classrooms, and general education classrooms. One of the key findings from this research was that autistic students exhibited higher levels of communicative spontaneity in non-symbolic forms (e.g., keeping an item, pushing) than symbolic forms (e.g., writing, speech). These types of results, while interesting on their own merit, can provide fertile grounds for additional researchers to formulate ideas about how to better understand autistic children and their communication patterns. As with every methodological approach to studying human behavior, case studies and naturalistic observations have drawbacks as well. Because the participants studied may not be representative of the population, these types of studies lack external validity— the ability to be generalized beyond the participants studied. Case studies and naturalistic observations are typically difficult to replicate unless extreme care has been taken to explicitly record the procedures used. Since these approaches do not follow a true experimental protocol (including random assignment), causal inferences are not possible, even those with compelling data. Finally, these types of studies rely on highly skilled researchers, because the potential for influencing the outcome of the study is great, whether it would be experimenter bias in a case study or experimenter reactivity (Brown, n.d.). 4.3 Archival Research A rchival research is a broad term that can be used to describe a wide range of studies. Essentially, archival research involves analysis of data from existing records that were made in natural settings. For instance, by reviewing records from professional baseball and basketball championship games, Baumeister (1995) found that home teams are more likely to choke (i.e., perform badly), perhaps due to the burden of high expectation made by playing in front of hometown fans. Riniolo, Koledin, Drakulic, and Payne (2003) used archival records from 1912 United States Senate hearings (and from the British Board of Trade) to compare eyewitness accounts of the Titanic sinking to the forensic data we now have, particularly examining the claim that the Titanic was breaking apart as it sank. Riniolo et al. (2003), after carefully screening testimony that indicated clear observations, found that 15 of 20 eyewitnesses accurately reported this tragic event. Related to more recent events, Martz, Bodner, and Livneh (2009), in using archival data available from the National Vietnam Veterans 121 lan66845_04_c04_p101-130.indd 121 4/20/12 2:47 PM CHAPTER 4 Section 4.3 Archival Research Readjustment Study (a national random sample of over 3,000 veterans drawn from 8.2 million veterans who served in Vietnam), found that for veterans with disabilities, teaching them problemsolving skills was beneficial only for veterans with mild to moderate disabilities (the intervention was ineffective for those veterans with severe disabilities). These three studies illustrate the versatility of archival research. None of these researchers actively collected data; these researchers examined baseball box scores, congressional testimony, and preexisting survey data, respectively. Archival research uses data from previous studies. Hemera/Thinkstock Although there are many different forms of archival research, we’ll end this chapter by reviewing two major approaches to analyzing archival data—content analysis and meta analysis. What is the relative contribution that archival research can make to our understanding of human behavior? Baumeister (1995) rightly pointed out that archival data may not the best choice for testing and building theories in psychology; the laboratory probably remains the best environment for achieving those goals. However, archival research can be invaluable in providing real-world examples of phenomena that are studied in controlled laboratory settings. As Baumeister put it, “perhaps the best compromise is that these [archival studies] should be regarded as extending, illustrating, and confirming laboratory studies rather than as primary, direct tests of theory” (p. 646). Content Analysis In some ways, content analysis bridges the worlds of qualitative research and quantitative research (Duriau, Reger, & Pfarrer, 2007). A typical approach to content analysis would be to identify key textual information. Content analysis takes qualitative statements, writings, and other forms of language and quantifies that data. For example, a conceptual analysis approach means that the frequency of representation of a particular word or concept is quantified in content analysis (Busch et al., 2009). Thus, you could examine presidential inaugural speeches and count the number of mentions of freedom, a free society, and so on. After identifying the research question and selecting the samples to be analyzed, the content is coded into predetermined categories, where frequency counts are now possible. A second approach within content analysis is called relational analysis, where other words are found in the text and then examined for their proximity to key concepts being analyzed (Busch et al., 2009). Thus, when freedom is mentioned in inaugural addresses, what other concepts are mentioned within close proximity to mentions of freedom, such as liberty, taxation, or civil rights? Because of the versatility of content analysis, this methodological approach can be used to study a wide variety of topics. For example, Sonpar and Golden-Biddle (2008) looked at 122 lan66845_04_c04_p101-130.indd 122 4/20/12 2:47 PM CHAPTER 4 Section 4.3 Archival Research adolescent theories of cognitive organization and found that content analysis was helpful in elaborating on pre-existing theories. Chancey and Dumais (2009) used content analysis in a more longitudinal approach. Their interest was in how couples who purposely choose to be childless (“voluntarily childless”) have been depicted in marriage and family textbooks ranging from the 1950s through 1990s. In this archival research using content analysis, Chancey and Dumais discovered that different decades presented different themes. Content analysis revealed that marriage and family textbooks in the 1950s depicted the voluntarily childless as individuals who understood that child-rearing was a challenge and to be feared, and those rejecting becoming parents were preemptively avoiding causing harm in children. In the 1960s, the voluntarily childless were seen as actively promoting marital satisfaction, whereas texts of the 1970s tended to say very little about the voluntarily childless. Content analysis of textbooks revealed that in the 1980s there was increased scholarly focus on the voluntarily childless, as well as discovering that there was often a disparity in opinions within a couple of the voluntarily childless decision. In the 1990s, content analysis revealed that the most effort was aimed at dispelling the myths surrounding the voluntarily childless and sometimes characterized these couples’ decisions as brave in the face of societal expectations. Clearly Chancey and Dumais would not be able to go back in time and interview voluntarily childless couples, but the content analysis of marriage and family textbooks over time provided insight into prevalent thought processes at the time. There are a number of advantages available to researchers who elect to use a content analysis approach. This listing combines the advantages as stated by Busch et al. (2009) and Duriau et al. (2007)—content analysis (a) allows for both qualitative and quantitative analysis; (b) can use a longitudinal approach that allows for the examination of historical contexts over time; (c) is an unobtrusive method of analyzing interactions; (d) can provide insight into complex cognitive operations, such as language and thought; and (e) uses an approach that can be replicated by others interested in the same phenomenon. Some of the disadvantages to content analysis include the labor intensiveness of obtaining and coding texts, that it can sometimes operate without a theoretical base, the reduction of complex human thoughts into parsed words, the oversimplification of the complexity of language by its reduction into frequency counts, and even the inability to capture the totality of context, such as the historical period or geographical context of what is spoken and written. Even with these drawbacks, content analysis is a powerful tool for the analysis of language. Meta-Analysis Within a single year, multiple studies are published on the same topic, and when thinking about a topic over a long range of time (like you would do if you were reviewing the literature), discrepancies appear in the interpretation of data. For instance, there are claims in the literature that a moderate amount of red wine can be very healthy for you with regard to cardiovascular function, but there are conflicting reports about the effect of red wine, especially if you consider the risk of alcoholism. So if you had to make an overall decision about whether or not to consume red wine, how would you combine the results of the previous studies to make a decision? This is precisely the dilemma than then-senator Walter Mondale faced in 1970 (Walter Mondale later went on to serve as vice president of the United States under President Jimmy Carter from 1977–1981). When Mondale addressed the 1970 convention of the American Psychological Association, he wanted some insight into the impact government programs were having on children’s development, and here’s what he said (Attwood, 2009): 123 lan66845_04_c04_p101-130.indd 123 4/20/12 2:47 PM CHAPTER 4 Section 4.3 Archival Research I had hoped to find research to support or to conclusively oppose my belief that quality-integrated education is the most promising approach. But I have found very little conclusive evidence. For every study, statistical or theoretical, that contains a proposed solution or recommendation, there is always another, equally well documented, challenging the assumptions or conclusions of the first. No one seems to agree with anyone else’s approach. But more distressing, no one seems to know what works. As a result, I must confess, I stand with my colleagues confused and often disheartened. (¶s 18–19) The contribution of meta-analysis is that it provides an approach for combining the results of multiple studies so that general effects can be summarized (Bangert-Drowns & Rudner, 1991). Although the idea of combining the results of studies can be traced back to Pearson and Fisher (Cooper & Lindsay, 1998), the 1970s saw an enhanced effort to combine studies to answer complex questions. For example, in looking at the results of studies of class size and academic achievement, Glass and Smith (1979) combined the results of 725 studies that estimated that relationship. Smith and Glass (1977) looked at the effectiveness of psychotherapy by examining 833 estimates of the effect, and Hunter, Schmidt, and Hunter (1979) looked at how employment tests may or may not differentiate between white and African-American employees. For each of these broad questions (class size, psychotherapy, employment testing), meta-analysis combined the results of hundreds of studies to allow for overall conclusions to be There are numerous studies that are drawn. In fact, Glass (1976) is credited for the completed and published about the same term meta-analysis (Cooper & Lindsay, 1998), and topic. Using meta-analysis provides an Glass (1976) defined meta-analysis as “the statisti- approach that combines the results of these cal analysis of a large collection of analysis results studies into a summary. from individual studies for purposes of integratage fotostock/SuperStock ing the findings” (p. 3). There are at least four different types of meta-analyses that a researcher could conduct (Bangert-Drowns & Rudner, 1991; Cooper & Lindsay, 1998), and you might see more than one analytical approach used in a report of meta-analytic findings. Here are brief descriptions of the approaches that are used: • • Using the vote count method, the overall impact of the study is counted as a “vote” in showing that the intervention has a positive (beneficial) effect, a negative (detrimental) effect, or no effect at all. The results are tallied to come to an overall conclusion about the topic under study. The classic method (combining probabilities across studies) might involve the summation of all the p values in used in significance testing, and then using a statistical procedure to determine if the overall result is likely to occur by chance or not. 124 lan66845_04_c04_p101-130.indd 124 4/20/12 2:47 PM CHAPTER 4 Section 4.3 Archival Research • • Rather than vote count, now each study contributes a degree of impact to the overall conclusion. Since p values are relatively common in published studies, this approach is straightforward, but sometimes overestimates the impact of the effect. When using the effect size method in meta-analysis, the degree of impact is more precise. With the p value approach above, studies with large Ns are more likely to have small p values—effect size is not as influenced by the N as p values are. There are procedures that can weigh the impact of an effect size when that effect size comes from a larger-scale study. Meta-analysis can also examine the relative contribution of variables within studies using effect size indices. Sometimes called homogeneity analysis or tests of homogeneity, the researcher can examine the degree to which different aspects of the research design impacted the effect sizes observed. This is a brief overview of the types of approaches available to the researcher utilizing meta-analysis. If you were to perform a meta-analysis, the steps you would follow might look like this: (1) clearly define the hypothesis and the operations under study; (2) conduct a thorough literature search; (3) categorize the studies; (4) transform to a common metric; (5) analyze the data; (6) formulate discussion and draw conclusions; and (7) generate a report (Botella & Gambara, 2006). Even from this description, you can see multiple metaanalytic approaches being used, such as vote counting and calculating effect sizes. One of the benefits of the development and use of meta-analysis is that it has increased the rigor with which research is discussed and published (Hedges, 1990). The meta-analytic approach is not without drawbacks, however (Bangert-Drowns & Rudner, 1991; Nugent, 2009). Three of the most commonly mentioned challenges in meta-analysis are (a) missing data on effect size, (b) missing data on study characteristics, and (c) publication bias. In some cases, published research may not fully present the statistical results needed for a researcher using meta-analysis to be able to calculate an effect size for each study, and in other studies, such as a case study, there may be no statistical information at all. The complexity of the design might also make extracting relevant information about the effect size complicated (Hedges, 1990). If too many data are missing from the studies on a particular topic, this poses a threat to the value of the interpretation of the remaining studies. Quality meta-analyses also need information about how the study was conducted, especially information about the procedures used in the study, how participants were assigned to groups, precisely how the dependent variables were measured, and so on (Hedges, 1990). If this type of information is not included in the studies being reviewed, then it is difficult to determine the relative contribution of the study to the meta-analysis. Because journal space is typically at a premium, sometimes key information that meta-analysis researchers need might not be included in published accounts. Another area of concern for meta-analytic research involves what is called publication bias. Typically, to publish an article in the psychological literature, you need to reject the null hypothesis—that is, find a significant difference between groups, relationship, or association between variables or predictors of a criterion. Thus, studies that accept the null hypotheses are difficult to publish. A researcher conducting a meta-analysis would prefer to have a complete picture of all the research conducted on the topic (regardless of outcome), but this is unlikely due to this publication bias. If what is in the literature is not representative of the totality of the research, then the results of the meta-analysis from an unrepresentative sample must be interpreted with caution. Here is an example of a meta-analytic strategy that demonstrated the benefit of this approach. Blinn-Pike, Worthy, and Jonkman (2007) wanted to arrive at an estimate of the 125 lan66845_04_c04_p101-130.indd 125 4/20/12 2:47 PM CHAPTER 4 Chapter Summary approximate percentage of college students who exhibit a serious gambling disorder. Rather than conduct an entirely new study to examine this issue, they conducted a metaanalysis of 15 college student gambling studies through 2005. One of the beneficial features of studying this topic is that there is a common metric used to measure gambling disorders, the South Oaks Gambling Screen (SOGS). Thus, each of the 15 studies had to use (at least) the SOGS as an outcome (dependent) variable. Other screening criteria for inclusion in the meta-analysis included (a) the percentage of disordered gambling in students had to be reported; (b) the study had to come from a peer-reviewed publication or dissertation; and (c) the study had to be conducted in the United States or Canada. Blinn-Pike et al. (2007) were able to estimate that the percentage of disordered gamblers when considering a college student population is 7.89%. The results of 15 studies to arrive at this estimate may provide a more accurate estimate of the overall existence of gambling problems among college students as compared to a study conducted on one campus. Blinn-Pike, Worthy, and Jonkman used a meta-analytical strategy approach to analyze 15 studies on college gambling to approximate the percentage of college students with a serious gambling disorder. Hemis.fr/SuperStock In the next chapter, we’ll look at a very different type of research design—the single subject design—and we’ll explore the insights achievable from this valuable research method. Chapter Summary R esearch conducted in controlled settings, such as a laboratory, can often lead to powerful conclusions about behavior, and at times may yield insights into causeand-effect relationships, the gold standard desired by scientists. However, people do not live in laboratories, but rather the real world, so a number of additional research approaches are necessary to better understand complex behaviors influenced by numerous variables in social settings. Quasi-experimental designs offer many different approaches to understanding these potential influences to behaviors, beliefs, and perceptions. Observational designs and archival research strategies can lead us to insightful revelations about the multitudinous factors that influence each of us. A psychologist equipped to conduct research in an applied setting wants to be as prepared as possible, and this means that he or she should have access to multiple methodologies to ensure that the questions of interest are answered with the strongest approach available, given the constraints of collecting data in the real world. 126 lan66845_04_c04_p101-130.indd 126 4/20/12 2:47 PM CHAPTER 4 Chapter Summary Research designs from this chapter Type of Study QuasiExperimental QuasiExperimental QuasiExperimental Design Name Nonequivalent Control Groups Time Series Cohort Symbolic Representation X = treatment or intervention O = observation, dependent variable measurement O X O O O Brief Features This design is superior to the pretestposttest only design comparing the effect of the independent variable to a control group, but because of the lack of random assignment, the groups may not be roughly equivalent at pretest. O O O X O O O Repeated observations pre and post the independent variable manipulation allow for the tracking of trends. N/A This design tracks a similar group of people over time, such as an age cohort of a generation or a period cohort such as young adults during the time of the Vietnam War. QuasiExperimental Regression Discontinuity N/A Starting with a large number of individuals, an intervention is applied to some individuals in the group based on a cutoff score, and the key outcome is whether or not the trends occurring before the intervention occur after the intervention (that is, continuous or discontinuous). Observational Case Study N/A This involves the intensive study of one individual while examining a limited set of specific behaviors. N/A Participants are studied in their natural environment by the researcher, but the researcher only observes and does not interact with participants. N/A This set of techniques allows for the analysis of qualitative data such that trends can be analyzed and conclusions can be drawn from the data. N/A This methodology allows for the outcomes of multiple studies on the same topic to be combined meaningfully and statistically to form overall, general conclusions. Observational Archival Archival Naturalistic Observation Content Analysis Meta-Analysis 127 lan66845_04_c04_p101-130.indd 127 4/20/12 2:47 PM CHAPTER 4 Concept Check Concept Check 1. The following symbols would be described in words as X O O A. two groups; only one gets the treatment, and both get the posttest. B. one group gets two treatments. C. randomly assign participants to two groups; both get treatments, and one gets posttest. D. two groups get the same treatment. 2. In an interrupted time series design, the treatment is done A. B. C. D. before observations. in the middle of observations. after the observations. after a single observation. 3. A group of people who share a critical experience over the same span of time defines a A. B. C. D. time series. cohort. control group. treatment group. 4. According to Greene (2003), the sequence of program evaluation phases is A. B. C. D. causation, implementation, generation. causation, generation, implementation. implementation, generation, causation. generation, implementation, causation. 5. Fundamental lessons for program evaluation (McCartney & Weiss, 2007) include all of the following EXCEPT A. B. C. D. adopt a fair and reasonable scientific explanation. use mixed-methods designs. discourage critique of the data. synthesize all research findings. Answers 1. A. Two groups; only one gets the treatment, and both get the posttest. The answer can be found in the Introduction. 2. B. In the middle of observations. The answer can be found in Section 4.1. 3. B. Cohort. The answer can be found in Section 4.1. 4. D. Generation, implementation, causation. The answer can be found in Section 4.1. 5. C. Discourage critique of the data. The answer can be found in Section 4.1. 128 lan66845_04_c04_p101-130.indd 128 4/20/12 2:47 PM CHAPTER 4 Key Terms to Remember Questions for Critical Thinking 1. Think about the variety of research approaches studied to date. How will you know what research approach is more appropriate than another with a particular research question or population of interest? How do psychologists come to have confidence in making these types of decisions? What will you need to do to build your confidence in your ability to select a methodological approach that matches the research questions you are interested in? 2. As you reflect back on your undergraduate career, you may see now that a particular sequence of courses might have been more helpful than others. Thinking about quasi-experimental designs, how might you design a study to show that one sequence of prerequisites is superior to a different set of prerequisites? How would you select one quasi-experimental design over another? How would you determine the superiority of one particular course sequence compared to another? 3. You may have conversations from time to time with students who are attending college a different way from how you are attending college currently. You might make the argument that an online education is superior, listing the advantages you have experienced. Another person who attended a “brick-and-mortar” campus may not think as highly of online coursework, and may provide his or her list of advantages for that type of learning experience. How might you design a quasi-experimental study to systematically examine the similarities and differences that exist among online, classroom, and hybrid educational approaches? Key Terms to Remember archival research A research methodology that involves analysis of data from existing records that were made in natural settings. content analysis A method of analysis that takes qualitative statements, writings, and other forms of language and quantifies those data. case study A research methodology that focuses on a particular case of interest. This case may be a person, a group, or perhaps an organization. Case studies can utilize qualitative and quantitative methods. generation phase The phase of program development where a needs assessment may be conducted prior to the implementation of a program, to see if the need justifies the implementation of a program, followed by program development and refinement. causation phase The phase of program evaluation in which the program evaluator attempts to demonstrate and measure the impact of the program. cause and effect An analysis that attempts to examine the causes and results of actions or behaviors. cohort A group of people who have shared experiences over the same span of time. implementation phase The phase of program development where the program begins, provides services to clients and the community, and hopefully has a positive impact. meta-analysis A method of analysis that provides an approach for combining the results of multiple studies so that general effects can be summarized. 129 lan66845_04_c04_p101-130.indd 129 4/20/12 2:47 PM CHAPTER 4 Web Resources naturalistic observation An observational situation where the researcher does not interact in the environment, but merely observes it. quasi-experiment When a participant is not randomly assigned to a group but instead assigned to a group based on characteristics that he or she already possesses. nonequivalent control groups design A design in which an experimenter is unable to randomly assign participants to the different groups due to external factors. regression discontinuity design A study design in which assignment into the treatment group or the control group is based on a predetermined cutoff. panel studies Studies that are designed to measure the same participants at different points over time. time series design A study design that includes consistent and multiple observations of a variable that is repeated a substantial number of times. program evaluation An assessment of the impact of a program based on its prestated goals. Web Resources Explanation and examples relating to quasi-experimental design; explains the lack of randomization in these designs and how that can affect research. http://allpsych.com/researchmethods/quasiexperimentaldesign.html Outline and definition of the regression-discontinuity design, which measures the effectiveness of a treatment or program that a psychological researcher may be investigating in his or her research project. http://www.socialresearchmethods.net/kb/quasird.php 130 lan66845_04_c04_p101-130.indd 130 4/20/12 2:47 PM 5 Science Faction/Superstock Single Subject Designs Chapter Learning Outcomes After reading and studying this chapter, students should be able to: • identify different types of reversal/withdrawal designs and understand the benefits and drawbacks of each. • comprehend the appropriate usage of more complex single-subject designs, such as the multiple baseline and changing criterion designs. • summarize the challenges to analyzing data from single-subject designs as well as appreciate the applications and limitations of these designs. lan66845_05_c05_p131-156.indd 131 4/20/12 2:48 PM CHAPTER 5 Introduction Introduction A t the close of the last chapter, you read about case studies and archival research. So what’s the difference between a case study involving one participant and a single-subject design involving one participant? In a single-subject design (SSD), there is more experimental control of the presentation and withdrawal of the independent variable levels. That is, the single-subject design can do true experimental manipulations, whereas case studies are typically observation-based or based on archival records. Thus, the advantage of the single-subject design is that cause-and-effect conclusions can be approximated but with limited generalizability since the data are typically based on one participant. The history of the single-subject design comes from the traditions of behaviorism, behavior therapy, and behavior analysis (Freeman, 2003). However, the applications of single-subject designs are diverse and not limited to those with a behavioristic A machine records brain waves as a participant performs a task orientation—this methodologion a computer. Single-subject designs allow more experimental cal approach has been used in control and manipulation of the independent variables than social work, education, cognicase studies. tive rehabilitation, sport psyAge fotostock/SuperStock chology, counseling, and occupational therapy, to name a few examples (Freeman, 2003). SSDs were used to modify the behavior of Little League baseball coaches (Martin, Thompson, & Regehr, 2004) and to help those with autism develop better independent work and play skills (Hume & Odom, 2007). Voices from the Workplace Your name: Jennifer B. Your age: 35 Your gender: Female Your primary job title: Director of Operations Your current employer: Creative Community Options How long have you been employed in your present position? 1 month What year did you graduate with your bachelor’s degree in psychology? 1994 (continued) 132 lan66845_05_c05_p131-156.indd 132 4/20/12 2:48 PM CHAPTER 5 Introduction Voices from the Workplace (continued) Describe your major job duties and responsibilities. Operate a community-based residential program for adults with intellectual and developmental disabilities, as well as chronic mental illness. Also operate a supported employment program for the same population groups. Both programs provide support to approximately 140–150 individuals. The operations involve overseeing 10 to 12 coordinators who complete the program planning and provide the direct supervision to the direct support professionals. In that oversight is managing service rates, contracts, ensuring programs are operating within the state and federal regulations, providing support to the coordinators with challenging staff issues as well as concerns with the individuals we provide support to. There is also significant involvement with the budgeting process of the organization, working to develop and maintain relationships with stakeholders of the organization and assisting in team meetings when there are significant challenges in providing service to an individual. What elements of your undergraduate training in psychology do you use in your work? In my current position, one of the programs provides services to individuals with chronic mental illness. My degree is helpful in providing support to the coordinator of those individuals. Many of the intellectually disabled individuals also have varying degrees of mental illness. The oversight, both directly and indirectly of 170+ employees requires regular use of the training I received in my undergraduate work as well. What do you like most about your job? I have been in the human service field since leaving undergraduate school. I have always worked with individuals that have some form of a disability. I have a strong passion to see that individuals with intellectual disabilities are given the same opportunities in their life as those without. I get to support the individuals we serve, through the administration of our programs, in living their life as they want to in their own homes, apartments and in jobs at businesses in their own community. Through my experiences as a direct support professional, program manager/coordinator, and Medicaid case manager, I can now develop current coordinators and assist them in learning new skills through which will provide the highest of quality of service to the individuals who receive support from our agency. What do you like least about your job? In this field, there are many regulations both federal and through our state which impact the job that we do daily. I feel the regulations are necessary due to past injustices our field allowed to occur. However, many times the regulations go too far and impact the quality of service as we must focus on items which don’t directly impact the people we serve. I now have a strong desire to begin to work with legislators and representatives in an effort to impact the laws and regulations surrounding this field. Beyond your bachelor’s degree, what additional education and/or specialized training have you received? Various training regarding the support of individuals with Autism: TEACCH, PECS, Training in Positive Behavior Support, MANDT, many conferences on supervision of employees What is the compensation package for an entry-level position in your occupation? $28,000–$34,000 salary for a coordinator or case manager. $9.00–$11.00/ hour for direct support staff. What benefits (e.g., health insurance, pension, etc.) are typically available for someone in your profession? Health insurance with dental and vision in many places. 401K. Holidays off—unless you are working as a direct support professional. Vacation, sick time or PTO. Emergency leave time. Flexible hours. (continued) 133 lan66845_05_c05_p131-156.indd 133 4/20/12 2:48 PM CHAPTER 5 Introduction Voices from the Workplace (continued) What are the key skills necessary for you to succeed in your career? Passion for the individuals served; Organization skills; Ability to manage large amounts of paperwork, tight deadlines, and time to handle immediate person-served needs. Soft skills—working well with people, developing resources and information, teaching as opposed to counseling. Thinking back to your undergraduate career, what courses would you recommend that you believe are key to success in your type of career? Social Work courses would have been very helpful to me. I had to learn how to develop assessments on the job and didn’t get that in a psychology degree. The assessments in the human service field are looking at the main life domains—where you live, work, your finance situation, social life, spiritual life, etc. Classes to learn how to develop a thorough social history and how to work with parents, guardians or family to get that delicate information. For my current place in my career, management classes are key. Thinking back to your undergraduate career, can you think of outside of class activities (e.g., research assistantships, internships, Psi Chi, etc.) that were key to success in your type of career? My degree in psychology did not require an internship as the social work degree did. I firmly believe that there should be an internship requirement for a psychology degree. Getting out during undergraduate work and obtaining an entry-level position which doesn’t require a degree is a great way to start to gain experience as well as to identify what field you want to work in. Psychology is a rather general degree at this point, which is a great cornerstone to further graduate work but is starting to be difficult to use in the human service field. If I were to graduate now with my psychology degree, I would have a difficult time getting to this level in my field. Many positions are requiring a social work license. I am fortunate that the state of Iowa doesn’t require it as often as many states do at this time. As an undergraduate, do you wish you had done anything differently? If so, what? I would have kept my study in psychology and sociology; however I would have at least minored, if not had a triple major in Social Work. That would allow me to now obtain my Social Work license. What advice would you give to someone who was thinking about entering the field you are in? Obtain a job with an organization that provides services to individuals with a disability. Get a direct support job and learn the field directly with the individuals we support. They are your greatest teachers and will help establish the passion for what we do. Many of the positions in my field require that you have at least a year or two of direct support experience. It is crucial. Attempt to vary the disability ranges. It is best to have experience with individuals that have a brain injury, individuals with an intellectual disability and individuals with a chronic mental illness. Substance abuse is also an area of this field which is helpful to have experience with. If you were choosing a career and occupation all over again, what (if anything) would you do differently? Absolutely nothing. I am very fortunate to be where I am at in my career at this time. Every position I have had, has given me critical experience and information which has allowed me to develop to this place in my professional life. Copyright © 2009 by the American Psychological Association. Reproduced with permission. The official citation that should be used in referencing this material is R. Eric Landrum, Finding Jobs With a Psychology Bachelor’s Degree: Expert Advice for Launching Your Career, American Psychological Association, 2009. The use of this information does not imply endorsement by the publisher. No further reproduction or distribution is permitted without written permission from the American Psychological Association. 134 lan66845_05_c05_p131-156.indd 134 4/20/12 2:48 PM CHAPTER 5 Section 5.1 Reversal/Withdrawal Designs 5.1 Reversal/Withdrawal Designs M ost SSDs begin with a phase where baseline data are collected concerning the behavior of interest; this phase is labeled the A phase in a single-subject design. After multiple observations to establish a stable baseline (more on this later), some sort of intervention (i.e., independent variable manipulation) is introduced with th...
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