Chapter 4
Program Evaluation and Policy Implementation
Minorities in Research: The Political Context of Problem Selection
Shaping and Refining the Problem
Qualitative versus Quantitative Research
Cross.Sectional versus Longitudinal Research
Feasibility of a Research Project
Anticipating and Avoiding Problems
Class Exercises for Competency Assessment
Suppose you were required, as many students in social research courses are, to design and conduct a research project. Our experience teaching research courses in the social sciences and human services is that some students respond to this assignment by drawing a total blank. Others, however, grasp eagerly onto a topic, such as “the cause of drug addiction,” and rush off with total confidence that they are about to solve this enduring problem. In each case, the student is having difficulty adequately formulating a research problem. In the first case, the difficulty is in locating a problem to investigate, whereas in the second, the trouble lies in formulating a problem sufficiently specific that it is amenable to scientific research.
We assure you this problem is not unique to students. Every researcher must grapple with problem formulation. Because it is the initial step and provides the basis for the complete research project, problem formulation is of crucial importance. Many potentially serious difficulties can be avoided—or at least managed—by careful problem formulation. In this chapter, we present the major issues to be considered in problem formulation, beginning with how to select a problem on which to conduct research. Then we analyze how to refine the research question so it can be answered through research. Finally, we discuss factors relating to the feasibility of research.
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4.1 Selecting a Research Problem
4.1 SELECTING A RESEARCH PROBLEM
The first hurdle confronting a researcher is to select an appropriate topic for scientific investigation. Actually, this is not as difficult as it may first appear, because the social world around us is teeming with unanswered questions. Selecting a problem calls for some creativity and imagination, but researchers can turn to a number of places for inspiration.
Research topics often are selected because a researcher has an interest in some aspect of human behavior, possibly owing to some personal experience. One social scientist, for example, conducted research on battered women and women's shelters in part because of her own earlier experience of being abused by her husband; another researcher, who had grown up in the only African-American family of a small rural town, did research on prejudice, discrimination, and the experience of minorities (Higgins & Johnson, 1988). Research sometimes focuses on behavior that is unique or bizarre, and thus compelling to some. Examples of such research abound, including studies of nudist colonies, pool hustlers, juvenile gangs, striptease dancers, burglars, homeless heroin addicts, and body piercers (Bourgois, Lettiere, & Quesada, 1997; Miller & Tewksbury, 2001; Polsky, 1967; Weinberg, 1968).
Researchers who select topics from their personal interests must be careful to demonstrate the scientific worth of their projects. Recall from Chapter 1 that the goals of scientific research are to describe, explain, predict, and evaluate. The purpose of research is to advance our knowledge, not just satisfy personal curiosity. For example, in her study of female strippers, psychologist Tania Israel (2002) was interested in learning how people adapt to a job that many consider to be deviant. Such a focus placed her research firmly in an established area of study and amplified its scientific contribution. A researcher who chooses a topic based on personal interest—especially if it deals with some unusual or bizarre aspect of human behavior—should be prepared for the possibility that others will fail to see the worth of that research. Even though Israel, as noted, established a legitimate scientific rationale for her study of strippers, she was subjected to considerable criticism by those who failed to appreciate its scientific value; critics derided her research as lacking in rigor, illegitimate, and embarrassing.
In selecting a topic, researchers often need look no farther than the daily newspaper, which is full of the many social problems that our society faces. Such problems as crime, delinquency, poverty, pollution, overpopulation, drug abuse, alcoholism, mental illness, sexual deviance, discrimination, and political oppression have all been popular sources of topics for social research. The Society for the Study of Social Problems—a professional organization to which many social scientists and human service providers belong—publishes the journal Social Problems, whose sole purpose is to communicate the results of scientific investigations into current social problems.
Each of these general categories of social problems encompasses a range of issues for study. Many studies, for example, focus on the sources of a problem. Others are concerned with the consequences these problems have for individuals or society. Still others deal with the outcomes of social programs and other intervention efforts intended to ameliorate these problems. People in the human services, who are routinely involved with many of these problems, can find opportunities for research that are directly related to their professional activities.
Some researchers select problems on the basis of their use in testing and verifying a particular theory. We noted in Chapter 2 that theoretical concerns should be at issue to some degree in all research. Nearly all research has some implications for existing theory. Certain research topics, however, are selected specifically to test some aspect of a given theory. Many theories relevant to the human services have not been thoroughly tested. In some cases, this means we do not know how valid the theories are; in others, it means we do not know how wide the range of human behavior is to which the theory can be applied.
One of the most fruitful sources of research problems is prior research, because the findings of all research projects have limitations. Some questions are answered, but others always remain. In addition, new questions may be raised by the findings. It is, in fact, common for investigators to conclude research reports with a discussion of the weaknesses and limitations of the research, including suggestions for future research that follow from the findings that have been presented. Focusing on these unanswered questions, or expanding on previous research, is a good way to find research problems.
Prior research also can lead to new research problems if we have reason to question the findings of the original research. As emphasized in Chapter 2, it is imperative that we not complacently accept research findings, especially when conclusions are based on a single study, because opportunities exist for error or bias to influence results. If we have reason to suspect research findings, we have a ready-made problem on which to conduct research ourselves. One of our own students, in fact, found his topic in just this way when faced with the course assignment of conducting a research project. The student had read a research article suggesting a number of differences between the social settings in which marijuana is used and those in which alcohol is used. The student disagreed, partly because of his own experiences, believing instead that the social environments in which the two substances were used were, in fact, quite similar. He designed a study that allowed him to determine whether his hypotheses—or those presumably verified by the previous investigation—would better predict what he would observe. As it turned out, many of his hypotheses were supported by his findings.
Program Evaluation and Policy Implementation
Program evaluation focuses on assessing the effectiveness or efficiency of some policy, program, or practice. As noted in Chapter 1, program and practice effectiveness evaluations have become increasingly important activities for human service professionals. Today, agencies or organizations that fund the human services typically demand that evaluation research be conducted if funding is to be granted or continued. Such research, developed for practical reasons, can take many forms. A social agency, for example, may require some needs assessment research to gather information about its clients if it is to deliver services to them efficiently. Or, a practitioner may need to know which intervention strategy—group work, psychotherapy, behavior therapy, or some other— will be most effective with a particular problem. Prison officials need to know which criminal offenders are the riskiest to parole. Home health care workers need information about how to ensure that people will take medications as prescribed. In all these cases, the practical information required by an agency or practitioner determines the focus of the research effort. Research in Practice 4.1 presents examples of research ideas being generated by reviews of how well social policies are being implemented.
RESEARCH IN PRACTICE 4.1 Policy Planning and Development: Current Policy Implementation as a Source of Research Problems
Anne holds a master's degree in public policy and is a researcher and policy analyst for the Office of the Inspector General (OIG) of the Department of Health and Human Services (HHS), a large federal agency that administers major health and social service programs across the United States. According to Anne, the IG regularly searches for any apparent problems with the implementation of HHS programs. “Research ideas come from a variety of places—legislators, service professionals, and even IG staff. When we see a major issue that is getting a good deal of public attention, we often respond by drafting a research proposal and asking for approval from the head of our office. We are nonpartisan, so our goal is to create unbiased reports on the effectiveness of our programs and offer sound recommendations for increasing efficiencies and improving services. Legislative staffers regularly meet with IG staff for further information related to the programs we investigate and use this information in making recommendations to legislators.” So this illustrates current policy implementation—or problems with it—as a rich source of research problems.
One of the major investigations Anne led in 2009 pertained to the Indian Health Service (IHS) which provides health services to 1.9 million Americans who are members of federally recognized tribes (American Indian or Alaskan Natives) through small health clinics offering routine care (Office of Inspector General, 2009). When required services are not available through these clinics, IHS and the tribes purchase services through Contract Health Services (CHS) which are delivered primarily through hospitals. When CHS are purchased through Medicare-participating hospitals, HHS sets reimbursement caps at Medicare rates. However, the IG found that, in some cases, CHS payments paid more than Medicare rates (either because they were overpayments or because services were delivered outside of Medicare-participating hospitals). This was expensive for the government as well as for the service recipients, who were required to pay some of this overage. The research was designed to show what levels of cost savings would be created by requiring all CHS units to accept Medicare caps for reimbursements and how to strictly monitor and enforce these rates.
As Anne explains, “Working for an agency like the IG gives us a very rich set of data. We can access all medical claims for Medicare, Medicaid and other programs and performance data for any number of client groups.” With access to this set of data, Anne and her coworkers examined all CHS payments and compared all medical expense claims to established Medicare rates for similar services. They found that 22 percent of hospital claims between January and March 2008 were above Medicare rates, and that preventing overpayments to Medicare-participating providers and also capping all CHS services to Medicare rates would have created a savings of $13 million during the three-month period being investigated.
So, based on their research, they recommended that the Indian Health Service and tribes take action to prevent overpayments to Medicare-participating health care providers and that all CHS payments—including those of non-Medicare-participating providers—be capped at Medicare rates.
(Based on personal interviews conducted in January 2012.)
The ability to find problems in practice settings that could be the focus of program evaluation research is limited only by the creativity and imagination of the practitioner. This was brought home to us by two of our students during a recent social research course. They were doing a field placement in a community mental health clinic while taking our research course, so they decided to search for some problem at the clinic to serve as the focus of their research paper. These students noticed that one problem the clinic faced was the failure of clients to show up for appointments. In addition to creating difficulties in achieving effective intervention, this also resulted in an inefficient use of staff resources, because counselors were left idle because of missed appointments. The students designed a very simple investigation in which some clients were given a reminder phone call a day or so before their appointment and other clients were not contacted, as had been the previous practice. The researchers' concern was to establish whether the reminder call increased the rate at which people showed up for their appointments. After implementing this procedure for a while, the students concluded that the phone call did help, and would be a useful and efficient addition to the functioning of the agency.
The linkage between human service practice and evaluation research is obvious, but service delivery can serve as the catalyst for basic research as well. During the course of working in human service programs, practitioners confront social problems and human diversity daily as they interact with clients who are struggling with life problems. Often, human service workers encounter client behavior that is unusual or even dramatic, and it stimulates questions about human behavior and society. The protective service worker who faces child abuse and neglect may derive research questions about parent—child bonding or human development. Hospice staff may generate questions about the dying process and grieving. Although answers to these questions may have practice implications, research that addresses issues such as these also has important implications for social science theory.
It is not only the behavior or characteristics of clients that generate research questions in practice settings; the mode and process of human service practice itself may even be the topic of research. For example, the mechanisms by which some human service agencies differentially allocate services according to social class or race might be a research issue. In fact, study of the human service delivery system has generated many of the major theoretical advances in our understanding of human behavior and social environments. For instance, Glaser and Strauss (1965) based their classic studies concerning death and social worth on observations of hospital patient care. More recently, controversy has surfaced in the human services over what appears to be the intergenerational transmission of family violence, suggesting that experiencing or observing violence during childhood results in subsequent violent behavior as a parent or spouse. Not only does research into this issue have practical implications for intervention programs, it also is directly relevant to developing our understanding of learning, human development, the family, and society as well (Burgess & Youngblade, 1988).
Minorities in Research: The Political Context of Problem Selection
From the preceding discussion of how to select a research problem, one could get the impression that the problem selection process is largely a matter of personal preference. Guided by personal interest or experience, the prospective researcher identifies a worthy problem and then sallies forth in the pursuit of knowledge. Like most other types of human activity, however, problem selection cannot be explained solely in such individual terms. In fact, if we asked students in research courses why they chose the term paper topics they did, we might find that, in addition to personal interest, theoretical orientation, or practice interest, their choices were governed by factors such as these: “My instructor had a data set available on this problem.” “I got financial aid to work as a research assistant.” “I knew my prof was interested in this topic, so I hoped studying it might help me get a better grade.” In other words, issues of political efficacy can influence problem selection as well.
In the world of professional research, the situation is not unlike that of the student. The stakes are much higher, however, and the consequences much greater. Although the number of possible research problems may be infinite, the resources that society can allocate to research them are not. Research is a major societal enterprise in which universities, governmental organizations, private research corporations, and independent researchers compete with each other for limited resources. At the same time, societal forces are working to make sure that the concerns of vested interest groups receive attention from the research community. Thus, problem selection is very much a political issue, and the problems that affect minorities and other groups with little clout may not receive the research attention they deserve.
Consider the example of spousal abuse. Men have been assaulting their wives since long before there was social research. Before the 1970s, however, one would have been hard pressed to find much research on the topic. Today, the social science and human service literature is replete with studies on spousal abuse, and the research endeavor in this area has expanded into a focus on intimate-partner violence. What explains the change? There is no single answer, but a major factor has been the rise of the women's movement. Before the 1960s, women as a group had considerably less political power than they have today, and the special problems of this minority often received little research attention. Woman battering is now an important issue to the women's movement, and this politically powerful group has been able to translate its concerns into public policy. Partly because of its pressure, the government has allocated money specifically for research on intimate-partner violence. In addition, with the changing roles of women in society, more women during the past three decades have chosen to pursue careers as researchers in the social sciences. One consequence of more women in research positions is that, given the role of personal interest in the selection of research topics, women are more likely to identify woman battering as a problem warranting research investigation. As the topic gained more prominence in the social science and human service fields, editors of journals became more receptive to publishing research articles on the topic. All these factors, over time, had a snowball effect. The availability of funds, the potential for publication, and the desire to contribute knowledge to an area of public concern attracted researchers seeking problems to study to this area.
So, one major factor influencing the allocation of research funds is the existence of a powerful, articulate, and effective interest group that can push for research on a particular problem (Lally, 1977; Varmus, 1999). Other factors include the following:
Support for research by influentials at the national policy-making levels
Definition of a condition as a social problem by national influentials
Public awareness of and concern about the condition
Severity, extent, and economic costs of the condition
Amount of publicity about the condition
Amount of support for research on the condition by the major funding agencies
On this last point, it is important to recognize that major agencies of the government, such as the Department of Health and Human Services (DHHS) and the National Science Foundation (NSF), dispense millions of dollars for research each year. Support from congressional leaders and key personnel in these major departments is essential for problem areas to be deemed worthy of financial backing for research. Typically, funding sources publish requests for proposals (RFPs), which outline the organization's funding priorities and requirements. Researchers are invited to submit proposals for competitive consideration. Proposals may be for millions of research dollars, and the competition for funding is as intense and high pressure as any major business deal.
Given that the political process plays a major role in determining which problems are sufficiently important to warrant research attention, it is not surprising that those people who lack access to social power in our society also are those whose interests are least likely to be served by the research conducted. One recent—and particularly disturbing—example of minority status influencing funding was with AIDS research. During the early years of the spread of AIDS in the United States, almost all people contracting the virus were men who had sex with other men. Today, this has changed: Currently, only 68 percent of new HIV infections involve male-to-male sexual contact or intravenous drug use, and 31 percent result from heterosexual contact (Centers for Disease Control and Prevention, 2011). In the earlier years, however, AIDS was associated in many people's minds with two groups of people—homosexuals and intravenous drug users—who were seen as marginal and highly stigmatized by many Americans, especially those in positions of power. In fact, people widely defined AIDS for a number of years as a “gay disease,” and thus as something that most Americans need not worry about. The attitude of many was summed up by the comment of a person who was later to be a staff member at the White House: “Those poor homosexuals. They have declared war on nature, and nature is exacting an awful retribution” (Shilts, 1987, p. 311). As long as AIDS was defined as a disease of deviants, funds for research on its cause and prevention were slow in coming.
Other reasons for the delayed response to the AIDS crisis existed beyond the marginality and stigma the early victims suffered (Shilts, 1987). For instance, the Reagan administration, which entered office in 1981, expressed as policy the emphasis on smaller government and austerity in social and health programs. The first AIDS victims in the United States appeared in 1980. The competition for government funds during the early 1980s was fierce, and AIDS researchers typically lost the battle, partly because those suffering from AIDS had less clout in the policy-making process than other groups competing for dwindling funds.
In short, society's response to the minority status of those afflicted with AIDS, along with other political factors, contributed to a significant delay in attacking the problem. It wasn't until AIDS began to threaten the supply of blood available for transfusions and fear arose that AIDS was entering the heterosexual population that considerable research support was forthcoming.
The selection of research problems is thus a highly political process. Although powerful interest groups will always play a role in this process, researchers need to avoid the perceptual blinders that often hinder the ability of the powerful to see which problems are sufficiently important or serious to warrant attention. Human service professionals, whether they actually conduct research or not, can play an important role in the political issues surrounding problem selection. In the course of practice, human service providers deal directly with the poor, with those labeled as deviant, with minorities, and with the powerless. This puts these providers in a position to serve as advocates for inclusion on the societal research agenda of problems relevant to their clientele.
We have discussed numerous sources of research topics for practitioner—researchers. Although we have discussed them separately, more than one of these factors often influences a given choice of a research topic. Finding a research topic, however, is only the first step in problem formulation. The next step is to shape it into a problem that empirical research can solve.
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4.2 Shaping and Refining the Problem
4.2 SHAPING AND REFINING THE PROBLEM
As we mentioned, a frustrating trap in which novice researchers often become ensnarled is choosing a topic that is so broad and encompassing that, by itself, it offers little guidance in terms of how to proceed. Finding the “causes of juvenile delinquency” or the “weaknesses of the modern family” sounds intriguing, but these topics provide little direction concerning where to begin to look. The next step in the research process, then, is to begin translating a general topical interest into a precise, researchable problem by narrowing the scope of the problem to manageable proportions. A single investigation is unlikely to uncover the causes of juvenile delinquency, but it might provide some insight regarding the influence of particular variables on the emergence of particular delinquencies. Refining, narrowing, and focusing a research problem do not occur all at once, but rather form a continuous process involving a number of procedures.
In Chapter 2, we discussed the role of theories and hypotheses in the research process, pointing out that concepts are one of the central components of theories. In the refining of a research problem, one of the key steps is conceptual development: identifying and properly defining the concepts on which the study will focus. In exploratory studies, of course, we are entering areas where there is little conceptual development, and a major purpose of the research itself may be to identify and define concepts. In cases where theory and research already exist, however, some conceptual development occurs as a part of formulating a research problem. One part of this process, already discussed in Chapter 2, is to clearly define the meaning of concepts. Another part of the process is to narrow the focus of the concept so it encompasses a topic that is feasible to research in a single study. For example, practitioners in a youth home who had an interest in juvenile delinquency might ask themselves, “Are we interested in all forms of delinquent behavior or only in some types?” In reality, the concept of delinquency is an extremely broad category that includes all actions by juveniles that violate criminal or juvenile codes. We have no reason to assume that a single cause can explain all types of delinquency. The focus of the research therefore might be narrowed to include only certain behaviors, such as violence or truancy. The goal of this specification process, then, is to make clear exactly what the focus of the research effort is.
Once the key concepts are clearly defined, the next consideration is their measurability. Only concepts that are in some way measurable can be used in the research process. Eventually, of course, concepts will have to be operationalized, as discussed in Chapter 2, so any that cannot be readily measurable will have to be dropped. Measuring concepts sometimes can be difficult, as we note in more detail in Chapter 5. In fact, theories at times include concepts that are difficult to operationalize. However, if the concepts in a proposed study cannot be measured, then some modification in the project—and, possibly, in the theory—is necessary. This process of refining and developing concepts as a part of the research process illustrates a point made in Chapter 2 regarding the interplay between theory and research: Theories provide concepts and hypotheses for research, whereas research modifies theories through conceptual development. The Eye on Ethics section explores some of the ethical dimensions of selecting and conceptualizing research problems.
With concepts clarified and deemed measurable, we are ready to conduct a review of previous research that relates to our research problem. This review of the literature is a necessary and important part of the research process (Locke, Silverman, & Spirduso, 2010). We do it to familiarize ourselves with the current state of knowledge regarding the research problem and to learn how others have delineated similar problems. Unless we are planning a replication, it is unlikely that we will formulate our problem precisely like any one of these previous studies; rather, we are likely to pick up ideas from several that we can integrate to improve our own. Through reviewing the relevant literature, we can further narrow the focus of the research project and ensure that we do not unnecessarily duplicate what others have already done. Researchers undoubtedly will find that pitfalls can be avoided by learning from others' experiences. For example, suppose that one or more specific approaches to a topic have proven unproductive—that is, several studies have failed to find significant results or strong relationships. In this case, unless there is good reason to believe that these earlier studies contained methodological weaknesses, the same approach is likely to lead to failure once again. Future research is likely to be more productive if it focuses on studies that have achieved some positive results.
A thorough literature review calls for familiarity with basic library utilization skills (including how to locate books, professional journals, and public documents) as well as online search skills. To help with this important aspect of doing research, we have included Appendix A in this book, which deals with the basic information retrieval skills. This appendix shows how to find the books, journals, government documents, and other sources for finding reports of research. Even those with some experience using both the library and online searches likely will find some helpful new information in this appendix.
In a literature review, we conduct a systematic search of each research report for certain kinds of information. First, the reviewer pays attention to theoretical and conceptual issues: What concepts and theories are used, how well developed are they, and have they been subjected to empirical tests before? If the theories and concepts are well developed, they can serve as an important guide in designing the planned research and explaining the relationships between variables. If they are not well developed, one will have to rely more on personal insight and creativity. In this case researchers sometimes consider doing exploratory research, which may involve loosely structured interviews and less quantitative measuring devices, as a way of advancing conceptual and theoretical development.
EYE ON ETHICS The Ethics of Selecting and Conceptualizing Research Problems
Social research has an impact on people's lives. Sometimes it brings them advantages, but other times the consequences are negative. Yet some groups have more social and economic resources, and these resources can mean that these groups are better equipped to sponsor research that may bring them benefits. Disadvantaged groups may find an inordinately small share of research resources being devoted to their concerns. In addition, more powerful groups are more likely to control the political and economic structures that enable them to influence how research problems are conceptualized. Should a problem such as poverty or drugs be conceptualized in an individualistic way (due to the weaknesses or failings of the poor or the addicted) or a systemic way (due to breakdowns in familial, political, or economic structures)? Answers to these questions will shape how research is done and how victims of poverty and drugs will be treated. As one psychologist put it: “The ethical implications come on board when we reframe the political as personal, and in so doing become complicit in agendas that maintain oppressive and neglectful social conditions” (O'Neill 2005, p. 19).
One way of addressing this problem focuses on basic issues of defining and conceptualizing problems: Ask whose agenda is served by the research we conduct and the way in which we conduct it. This may help us decide whether we are complicit in maintaining social conditions that are viewed as negative by some groups.
A second way to address this problem is for researchers to seek out research problems that are not on the agenda of more powerful groups (Bonacich, 1990). This is essentially what happened, over a period of years, with the topic of spouse abuse discussed earlier in the chapter.
A third way to approach this problem is for researchers to listen to the voices of all the stakeholders in the research, irrespective of who is funding the research. A stakeholder is any person or group who stands to gain or lose from the research. The powerful stakeholders, of course—especially those who are funding the research—will have their voices heard. It is the less powerful stakeholders that the researcher needs to seek out and listen to. So, for example, if a state department of corrections funds a study on some aspect of prison life, then the corrections administrators will certainly have an influence on what is researched and how it is done. But other stakeholders to this research include the prisoners themselves and their families as well as the correctional officers who are in daily contact with them. What kind of research might benefit or work to the disadvantage of these groups? Social science and human service researchers who strive to make research more ethical would make efforts to ensure that the voices of the inmates and correctional officers are heard in the design and conduct of the research.
The research hypotheses, including identification of the independent and dependent variables, represent a second component of a literature review. Are the hypotheses clearly stated and testable? Are they related to the variables and hypotheses being considered in the planned study? Existing research can provide some fairly specific direction in terms of already tested relationships between independent and dependent variables.
The measurement and the operational definitions used in previous research are a third focus of a literature review. As noted, successful operationalization of concepts often is difficult. Previous work in this area is invaluable in finding workable measures for concepts. Past measures may require modification to meet current needs, of course, but making these modifications probably is easier than developing completely new measures, which is a difficult and time-consuming process.
A literature review also informs us about a fourth important element of research—the most appropriate research technique for a particular research problem. Successful approaches by others should be noted and unsuccessful approaches avoided. It is of the utmost importance that the problem determines the research technique that is used, and not the other way around. Many data-gathering techniques exist, because no single method is always best. As we note in subsequent chapters, each technique has its own strengths and weaknesses, and each is suitable for answering some questions but not others.
The sampling strategy is a fifth element of a literature review. Previous research can be useful in determining the sampling strategy to use and avoiding sampling problems that others have encountered. For example, suppose the study we propose calls for the use of mailed questionnaires. An ever present problem with mailed questionnaires is making sure that a sufficient number of people complete and return them. It would be useful for us to know what other investigators have experienced with people like those we plan to survey. Not all groups respond to mailed questionnaires with the same degree of enthusiasm. If the group we are proposing to sample has exhibited notoriously low return rates during the previous studies, we have to plan accordingly: We would probably increase the number of questionnaires mailed, and we would certainly use all available means of obtaining the highest possible response rate. Or, if we anticipate very low return rates, we may want to search for another group to study—or even consider whether this particular project is feasible at all.
Statistical technique is a sixth element of a literature review. In Chapters 5, 14, and 15, we will discuss issues relating to appropriate use of statistics. In the literature review, we must be aware of whether the appropriate procedures were used, if any inappropriate procedures were used, and what constraints the concepts, variables, and hypotheses placed on the kind of statistics that would be appropriate.
Finally, a literature review notes the findings and conclusions of the studies that are examined. Which hypotheses were confirmed, and what guidelines for future research were presented? One aspect of the findings to watch for is the effect size, which refers to how big an effect an independent variable has on a dependent variable. Although we discuss this concept more fully in Chapter 15, we need to assess whether a dependent variable is affected in only a small but measurable way, or whether the impact is dramatic (Gibbs, 1991).
A thorough literature review involves evaluating and comparing many research reports, identifying where they used similar procedures and reached similar outcomes, and where there were discrepancies between studies. This can be a complicated process, especially when hundreds of studies may be involved. It sometimes is helpful to produce a summary table, such as Table 4.1, to make comparisons. Notice that the table cites each separate study in the left-hand column, along with a brief description of the intervention model used in the study. The next three columns give information about the research design, sampling procedures, and measurement devices. Then, a column contains a summary of the results of each study. The final column on the right addresses any limitations found in the research. A systematic literature review of this sort provides the most useful information from previous studies. One can see at a glance how many studies came to similar conclusions and how commonly certain measuring devices were used. The ability to compile and summarize succinctly the features of studies in this fashion is essential to formulating a research problem and refining it into a research question that can be empirically investigated.
An important element in the process of shaping and refining a research problem is the decision regarding the unit of analysis to be investigated. Units of analysis are the specific objects or elements whose characteristics we wish to describe or explain and about which we will collect data. Although there are many units of analysis, five that are commonly used in human service research are individuals, groups, organizations, programs, and social artifacts (see Table 4.2). Different units of analysis are used in studying documents; these are discussed in Chapter 8.
TABLE 4.1 A Summary Table of a Literature Review of Research on Rural Homelessness
TABLE 4.2 Possible Units of Analysis in Research on Juvenile Delinquency
|
Unit of Analysis |
Example |
Appropriate Variables |
Research Problem |
|
Individuals |
Adolescents arrested for larceny |
Age, sex, prior arrests |
Do males receive different penalties than females for similar offenses? |
|
Groups |
Delinquent gangs |
Size, norms on drug usage |
Are gangs involved in drug trafficking more violent than other gangs? |
|
Organizations |
Adolescent treatment agencies |
Size, auspices, funding level |
Do private agencies serve fewer minority and lower-class delinquents than public agencies? |
|
Programs |
Delinquency prevention programs |
Theoretical model, type of host setting |
What services are most frequently included in prevention programs? |
|
Social artifacts |
Transcripts of adjudication hearings |
Number of references to victim injury |
To what extent does the level of violence in the offense affect the kind of penalty imposed? |
Much social research focuses on the individual as the unit of analysis. The typical survey, for example, obtains information from individuals about their attitudes or behavior. Whenever we define a population of inquiry with reference to some personal status, we are operating at the individual level of analysis. For example, unwed mothers, welfare recipients, mental patients, retarded children, and similar categories all identify individuals with reference to a status they occupy.
If we identify our unit of analysis as individuals, then it is important to recognize that the entire analysis will remain at that level. For the sake of describing large numbers of individuals, it is necessary to use summarizing statistics, such as averages. For example, we might, as part of a study of unwed mothers, note that their average age when giving birth was 16.8 years. Aggregating data in this fashion in no way changes the unit of analysis. We are still collecting our data about individuals.
Social scientists sometimes focus on social groups as their unit of analysis and collect data on some group characteristic or behavior. Some groups consist of individuals who share some social relationship with the other group members. For example, in families, peer groups, occupational groups, or juvenile gangs, the members have some sense of membership or belonging to the group. If we study families in terms of whether or not they are intact, then we are investigating the characteristics of a group—the family—and not the characteristics of individuals. Other groups of interest to social scientists are merely aggregates of individuals with no necessary sense of membership, such as census tracts, cities, states, or members of a particular social class. For example, we might study the relationship between poverty and delinquency by comparing the rates of delinquency in census tracts with low income and census tracts with high income. In this case, we have collected data regarding the characteristics of census tracts rather than data regarding individuals.
Social scientists also deal with organizations as the unit of analysis. Formal organizations are deliberately constructed groups that are organized to achieve specific goals. Examples of formal organizations include corporations, schools, prisons, unions, government bureaus, and human service agencies. For example, our experience may lead us to suspect that organizations providing substance abuse services can more effectively serve their clients if they have an open and democratic communication structure rather than a closed and rigidly stratified one. If we compare the success rates of organizations with different communication structures, then our study would use organizations, not individuals or groups, as the unit of analysis. Although individuals may experience success at overcoming substance abuse, only organizations can have a success rate.
Research in the human services also can focus on programs as the basic unit of analysis. The program may provide services for individuals, and it may exist as part of an organization. However, it is still a separate unit of analysis about which data can be collected. Like organizations, programs can have success rates or be assessed in terms of overall costs. For example, one research project investigated 25 programs that provided services for pregnant and parenting teenagers (Fernandez & Ruch-Ross, 1998). This research assessed each program according to its overall success rate: A successful program was one in which the clients were more likely to stay in school or stay employed and less likely to get pregnant than were clients in the other programs. Note that a program can have a success rate (in other words, a certain proportion of their clients succeeding) but an individual can only succeed or fail (rather than show a rate of success). The researchers compared the programs to determine the characteristics of successful and unsuccessful programs. Programs might cut across a number of different organizations, such as social service agencies, in which case the unit under observation is the effectiveness of the combination of services provided by these organizations.
Finally, the unit of analysis may be social artifacts, which are simply any material products that people produce. Examples are virtually endless: newspapers, buildings, movies, books, magazines, ipads, automobiles, songs, graffiti, and so on. Of all the units of analysis, social artifacts are the least frequent focus of human service research, but as reflections of people and the society that produces the artifacts, analysis of social artifacts is useful. Books and magazines, for example, can be used as artifacts in the assessment of sex-role stereotyping. Children's books have been attacked for allegedly reinforcing traditional gender roles through their presentations of men and women (Crabb & Bielewski, 1994). Any kind of legal or administrative statute also is an artifact worthy of study. One effort, for instance, used state juvenile codes as the independent variable in a study of whether legal statutes made a difference in how courts handled juvenile cases (Grichting, 1979).
Clearly specifying the unit of analysis in research is important to avoid a serious problem: an illegitimate shift in the analysis from one unit to another. Jumping from one level to another can result in erroneous conclusions being drawn. One way this can happen is called the ecological fallacy: inferring something about individuals based on data collected at higher units of analysis, such as groups. In other words, a mismatch occurs between the unit of analysis about which data are collected and about which conclusions are drawn. Suppose, for example, a study found that census tracts with high rates of teenage drug abuse also had a large percentage of single-parent families. We might be tempted to conclude that single-parent families are a factor promoting teenage drug abuse. Such a conclusion, however, represents an illegitimate shift in the unit of analysis. The data have been collected about census tracts, which are at the group level. The conclusion being drawn, however, is at the individual level—namely, that teenage drug abusers live in single-parent families. The data, however, do not show this. In fact, the data only show the association of two rates—substance abuse and single parenthood—in census tracts. (Perhaps two-parent families are a minority in a census tract, but a high proportion of children in these families abuse drugs.) It is, of course, possible that relationships found at the group level will hold at the individual level, but they may not. In our hypothetical study, some other characteristic of census tracts may lead to both high rates of drug abuse and single-parent families. The error comes in the automatic assumption that correlations at the group level necessarily reflect relationships at the individual level.
Fallacious reasoning can occur in the opposite direction as well; in this case, it is called the reductionist fallacy: inferring something about groups or other higher levels of analysis based on data collected from individuals. Suppose we collected data from individual teenagers about their drug use and family environments and found an association—namely, that teens from single-parent families are more likely to abuse drugs. Could we then conclude that communities with high rates of single-parent families would have high rates of teenage drug abuse? The answer, once again, is that we could not draw that conclusion about the group level (communities) with any certainty, because the data we have is about social process at the individual level (what happens in the lives of individual teens). It may well be that the social process that produces high rates of drug abuse in communities is different from the social process that leads individuals to use drugs. When data are collected at one level of analysis, it is always an empirical question as to whether conclusions can be drawn from that data about other levels of analysis. A clear awareness of the unit of analysis can help ensure that we do not make such illegitimate shifts.
A final point needs to be made about the unit of analysis in contrast to the source of data. The unit of analysis refers to the element about which data are collected and inferences made, but it is not necessarily the source from which data are collected. A common example is the U.S. Census, which reports data for households. We speak of household size and income, but households don't fill out questionnaires—people do. In this case, individuals, such as the heads of households, are the source of the data, but the household is the unit of analysis about which data are collected. When the unit of analysis is something other than the individual, attention must be paid to the source of that data, because this might introduce bias into the data analysis. For example, when the household is the unit of analysis, we often collect data from one member of the household. In single-parent families, headed primarily by women, we would be gathering data mostly from women. In two-parent families, we would be obtaining data from both men and women, because either could be the head of the household. In some cases, men might be the majority of those from whom we collect data. If men tend to answer some questions differently from women, then there could be a sex bias in the results even though our unit of analysis was not linked to sex. A difference that we attribute to single-parent as compared to two-parent families may result from the fact that the former involves mostly women answering questions while the latter involves mostly men.
The issue of reactivity is another consideration in refining a research problem. The term reactivity refers to the fact that people can react to being studied and may behave differently than when they don't think they are being studied. In other words, the data we collect from people who know they are the objects of study might be different from the data we collect from the same people if they do not know. So, a reactive research technique changes the very thing that is being studied. Suppose, for example, that you are a parent. A researcher enters your home and sets up videotaping equipment to observe your interactions with your children. Would you behave in the same way you would if the observer were not present? You might, but most people would feel strong pressures to be “on their toes” and present themselves as good parents. You might be more forgiving of your child, for instance, or give fewer negative sanctions.
Reactivity in research can take many forms, and it is a problem for virtually all sciences. It is especially acute in social research, however, because human beings are self-conscious and aware of what is happening to them. Refining a research problem and choosing a research design are done with an eye toward reducing as much as possible the extensiveness of reactivity. We consider this in assessing the various research strategies during later chapters.
Qualitative versus Quantitative Research
Another aspect of refining a research problem is to decide whether to use one of two broad strategies toward research: qualitative research, or quantitative research. Qualitative research involves data in the form of words, pictures, descriptions, or narratives. Quantitative research uses numbers, counts, and measures of things (Berg & Lune, 2012; Wakefield, 1995). In general, two factors come into play in deciding whether to conduct qualitative or quantitative research: the state of our knowledge on a particular research topic, and the individual researcher's position regarding the nature of human social behavior. Regarding the first factor, when knowledge is sketchy or there is little theoretical understanding of a phenomenon, it may be impossible to develop precise hypotheses or operational definitions. In such cases, researchers often turn to qualitative research, because it can be more exploratory in nature. The research can be descriptive, possibly resulting in the formulation of hypotheses rather than the verification of them. When enough previous research exists on a topic, however, it may be more feasible precisely to state concepts, variables, and hypotheses. It also may be possible to develop quantifiable operational definitions of what the researcher is interested in, which then allows research to take on a more quantitative nature.
RESEARCH IN PRACTICE 4.2 Behavior and Social Environments: Feminist Research Methods: Do Males and Females Have Different “Voices”?
Positivism assumes that “one size fits all”—that there is one way to know the world, and that the diversity of people in the world is irrelevant to how we gain knowledge. One of the areas in which the debates over the scientific paradigms discussed in Chapter 2 probably have been most intense is feminist research. Feminist researchers have argued that one size does not fit all—that the diversity in the world also produces diverse ways of gaining knowledge of the world. This has led some feminist researchers to explore the nonpositivist paradigms for a more complete and complex methodology to understand human behavior (Olsen, 1994; Reinharz, 1992; Schiebinger, 1999). One profound question that feminists have raised is whether ways of knowing are gendered: Are males and females socialized to perceive the world and acquire knowledge in fundamentally different ways? Furthermore, is positivism merely one of several ways of knowing rather than the only way of knowing?
The basic argument is that, because of differences between the genders—either due to biology or socialization—there is a male model of knowledge development and a female one, and the two are, to an extent, alien to each other (DeVault, 1999; Nielson, 1989). In developing some of these ideas, Carol Gilligan (1982) used the term “voice” to mean modes of thinking about the world, and tried to describe the differences between male and female “voices.” Women emphasize the importance of relationships and the danger of being separated from others. Women see connectedness between people and feel obliged to protect and nurture those to whom they feel connected. This leads to a concern about the needs of others, but the needs of self and others exist primarily in the context of relationships with other people. So women's voices focus on the individual who is embedded in a social network. This emphasis on connectedness and relationships means that problems and people are inextricably intertwined. Neither problems nor the people they affect can be fully understood if they are separated from one another.
By contrast, men's voices speak of separation and autonomy. They emphasize independence and, to an extent, alienation—at least in the sense that people can be abstracted from their relationships, from their context, and even from their own uniqueness. For men, the separate individual has some meaning and importance and, possibly, even more value than a person who is encumbered by relationships and connections. This view treats these abstracted individuals the same, ignoring the unique needs or contexts of each person. To this extent, men's voices are abstract and formal. People and their problems can be separated.
Proponents of the male-female distinction argue that these male and female voices are fundamentally contrasting ways of perceiving and developing knowledge about the world. The distinction suggests a paradigm that differs from the positivist one, with some affinities to a variety of nonpositivist paradigms. The male voice tends to be logical and objective and to avoid or downplay feelings while focusing on accomplishing practical goals. It tends to view the world in terms of separation: The researcher extracts data from the “subject” or “respondent” and, in the interests of objectivity, avoids any personal relationship (or connectedness) between them. All contact except that necessary to collect data is avoided. The male researcher prefers a more quantitative approach, with standardized measuring instruments and procedures, on the assumption that treating all people alike will produce the most valid and objective data. A number of procedures commonly used in positivist research can be seen as efforts to strip away the context from the individual: placing them in laboratory settings; using random assignment to conditions; using aggregate responses from large-scale surveys; and isolating variables for study. All these procedures assume that the context in which a person lives is merely interfering “noise,” and that more meaningful information can be obtained without it. Through quantification, the male voice minimizes the uniqueness and subjectivity of experiences by providing summary responses of the aggregate; so the fact that Jane Doe got pregnant at age 13 under a certain set of unique and meaningful circumstances gets lost when we conclude that the average teenage pregnancy in a high school occurs at 14.7 years of age.
The female voice, on the other hand, stresses feeling, empathy, and the subjective side of life, and emphasizes connectedness: Researcher and respondent are tied together in a relationship that influences the data produced. Objectivity, in the positivist sense, is impossible, because the meaning and importance of data relate to specific individuals and their relationships with one another. The researcher and subject are partners in the relationship of producing research. Subjects are collaborators. The feminist researcher also disdains the notion of the objective, impartial researcher in favor of involvement with the topics of their research. In the feminist view of gaining truth, researcher and subject work together, although in different ways, to develop understanding; truth-seeking is a mutual, cooperative effort on their part. Research questions emphasize connectedness: keeping people in their social contexts, and studying the complexity of the whole. In short, qualitative approaches are preferred. People can be studied in their homes or where they work and play. Some research methods, such as the field methods we will discuss in Chapter 9, are better suited to emphasizing this connectedness. Feminist research also emphasizes in-depth interviews, where people have an opportunity to express the fullness and complexity of their lives in their own words.
Obviously, it is possible for men to speak with a “female” voice and for women to speak with a “male” voice. The point is that these are fundamentally different ways of knowing the world. Feminist researchers do not reject positivism; they recognize that it is different but not superior. In fact, some critics argue that researchers in the social sciences, whether male or female, generally have been trained in graduate schools with a male voice, because that is what has dominated over the years among graduate faculty. Yet, neither voice is inherently superior, and neither is complete or totally objective. Each is a valid way of gaining knowledge about the world, and each involves a perspective that has some limitations. The basic insight of feminist researchers is that all people, including researchers, are fundamentally gendered beings and—whether we admit it or not—this shapes how we perceive and think about the world, how we do research, and what research results are produced.
The second consideration in choosing between quantitative and qualitative research stems from a more fundamental controversy over the nature of human social behavior. We saw in Chapter 2 that the choice between qualitative and quantitative research is related to whether one follows positivist or nonpositivist paradigms toward science. This complicated issue, which is discussed in more detail in Chapters 2 and 9, basically involves debate over whether we can meaningfully reduce the human experience to numbers and measures. Some social scientists argue that the human experience has a subjective dimension—that is, the personal meanings and feelings that people have about themselves and what they do. These meanings or feelings cannot be captured very well through numbers or measures. Instead, narrative descriptions of people going about their daily routines or lengthy and broad-ranging interviews with them better express those meanings and feelings. Such techniques are better able to capture the critical subjective meanings that are an essential element of understanding human behavior. Quantitative research, on the other hand, provides us with much more precise statements about human behavior.
The line between qualitative and quantitative approaches is not always completely clear, and the choice between the two can be difficult. Many research projects incorporate both approaches to gain the most benefit. Research in Practice 4.2 presents some additional elaboration on this issue.
Cross.Sectional versus Longitudinal Research
In addition to deciding on the unit of analysis to investigate, refining a research problem also requires a decision about the time dimension. Here, the basic issue is whether the researcher wants a single snapshot in time of some phenomenon or an ongoing series of photographs over time. The former is called cross-sectional research , and it focuses on a cross section of a population at one point in time. Many surveys, for example, are cross-sectional in nature.
Although researchers collect all the data in cross-sectional research at one time, we can use such studies to investigate the development of some phenomena over time. For example, to study the developmental problems of children of alcoholic parents, one could select groups of children of varying ages—say, one group at age 5, another group at age 10, and a third group at age 15. By observing differences in developmental problems among these groups, we may infer that a single youngster would experience changes as he or she grew up similar to the differences observed among these three groups. Yet one of the major weaknesses of such cross-sectional studies is that we have not actually observed the changes an individual goes through; rather we have observed three different groups of individuals at one point in time. Differences among these groups may reflect something other than the developmental changes that individuals experience. Because of this disadvantage, researchers sometimes resort to the other way of handling the time issue: longitudinal studies.
Longitudinal research involves gathering data over an extended period, such as months, years, or even, in a few cases, decades. One type of longitudinal approach is the panel study , in which the same people are studied at different times. This allows us to observe the actual changes these individuals go through over time. For example, a study of the social, psychological, and familial characteristics that influence whether drug addicts can successfully remain free of drugs followed the same 354 narcotics addicts for more than 24 years, collecting data on their family experiences, employment records, and a host of other factors (Bailey et al., 1994). Another longitudinal approach is the trend study , in which different people are observed at different times. Public opinion polling and research on political attitudes often are trend studies.
Both the nature of the research problem and practical considerations typically determine the decision about whether to use a longitudinal or a cross-sectional approach. Longitudinal studies, especially panel studies, have the advantage of providing the most accurate information regarding changes over time. A research question regarding such changes, then, probably would benefit from this approach. A disadvantage of panel studies is that they can be reactive: People's responses or behavior at one time may be influenced by the fact that they have been observed earlier. For example, a person who stated opposition to abortion in one survey may be inclined to respond the same way six months later so as not to appear inconsistent or vacillating, even if his or her attitudes had changed in the interim. Another disadvantage of panel studies is that people who participated early in a panel study may not want to—or may be unable to—participate later. People die, move away, grow uninterested, or become unavailable in other ways as panel studies progress. This loss of participants can adversely affect the validity of the research findings. The disadvantages of all longitudinal studies are that they can be difficult and expensive to conduct, especially if they span a very long period of time.
Cross-sectional research is cheaper and faster to conduct, and one need not worry about the loss of participants. However, cross-sectional research may not provide the most useful data for some research questions. Thus, the decision regarding the issue of the time dimension should be based on considerations of both the nature of the research problem and practical issues. There are times, of course, when practical feasibility plays a large part in the decision.
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4.3 Feasibility of a Research Project
4.3 FEASIBILITY OF A RESEARCH PROJECT
By the time researchers have selected, shaped, and refined a research problem, the problem should be sufficiently clear that a consideration of practical issues involving the feasibility of the project is in order. Practical considerations of what the research can reasonably accomplish given the time and resources available can force researchers to reduce— sometimes painfully—the scale of a project. A careful and honest appraisal of the time and money required to accomplish a project is useful in determining the feasibility of that project as envisioned, and it can reveal whether a change in goals is called for. In making a feasibility assessment, one should keep in mind a couple of axioms that apply to research projects: “Anything that can go wrong will” (Murphy's Law), and “Everything will take longer than possibly imagined.”
The practical aspects of a project's feasibility center primarily on two related concerns: time and money (Kelly & McGrath, 1988).
In developing a research project, one of the major considerations is whether there will be sufficient time to adequately complete what you hope to do. In later chapters, as we consider specific research techniques, we will see how different techniques vary in terms of how much time they take. Here we want to mention some of the major factors related to time considerations.
One factor concerns the population that is the focus of the research. If that population has characteristics that are fairly widespread, then a sufficient number of people will be readily available from which to collect data. For instance, if we were studying the differing attitudes of men and women toward work-release programs for prison inmates, we could select a sample of men and women from whatever city or state we happened to be in. If, however, our study focuses on people with special characteristics that are somewhat rare, problems may arise. In general, the smaller the number of people who have the characteristics needed for inclusion in a study, the more difficult and time-consuming it will be to contact a number sufficient to make scientifically valid conclusions. For example, a study of incestuous fathers—even in a large city—may encounter problems obtaining enough cases, because relatively few such people will be openly known.
A second problem relating to time constraints involves the proper development of measuring devices. Researchers should test all techniques used for gathering data before the actual study is conducted, and this can be very time-consuming in itself. A pretest, as we saw in Chapter 1, refers to the preliminary application of the data-gathering techniques to assess their adequacy. A pilot study is a small-scale “trial run” of all the procedures planned for use in the main study. In some studies we may need to conduct several pretests as we modify data-collection devices based on the results of earlier pretests. All in all, the refining of data-gathering procedures can consume a lot of time.
A third major factor related to time considerations is the amount of time required for actual data collection, which can range from a few hours for a questionnaire administered to a group of “captive” students to the years that are necessary in many longitudinal studies. Because the amount of time required for data collection is so variable, the issue of time requires close scrutiny when addressing the question of the feasibility of a particular research design.
A fourth consideration related to the time issue is the amount of time necessary to complete the analysis of the data. In general, the less structured the data, the more time will be required for its analysis. The field notes that serve as the data for some observational studies, for example, can be very time-consuming to analyze (see Chapter 9). Likewise, videotapes collected during an experiment or during single-subject research may need several viewings before they are adequately understood (see Chapters 10 and 11). Highly structured data in quantified form, however, also can be time-consuming to analyze (see Chapters 14 and 15). Although some quantitative data can be quickly entered into a computer file if it is in a form that can be optically scanned or submitted from a website, other data must be manually entered. Even optically scanned or web data, however, require considerable advance programming and preparation before the data can actually be submitted. Also, raw data often must be manipulated and transformed before they are ready for analysis, and this can be time-consuming as well. So, the time needed for data analysis requires careful consideration owing to wide variation in the amount of time that may be necessary.
The fifth area in which time becomes a factor is the writing of the report itself. The amount of time this consumes depends on the length and complexity of the report and the skills of the investigator. Each researcher is in the best position, based on past writing experiences, to assess the amount of time he or she requires. As a final reminder, it will likely take longer than you expect.
The financial expenditures associated with a research project are another constraint on feasibility. Good research is not always expensive. In many instances, students and human service practitioners can get by with only modest costs, because data are easy to obtain, analysis procedures are simple, and the labor is either voluntary or provided at no additional charge. Even small projects, however, are likely to require money for telephone calls, typing and duplicating questionnaires, computer equipment, Internet access, and other services that can quickly stress the tight resources of a small human service agency. At the other extreme, it is not unusual for the price tag of major research and demonstration projects in the human services to run into six figures or more. For example, between 1997 and 2003, the National Institute of Justice (2003) provided annual grants of about $1 million for the development and evaluation of educational programs to assist teenagers in developing skills to avoid drug use or other forms of delinquency and to avoid becoming victims of crime. Table 4.3 shows the budget for a hypothetical survey research project of modest scale and indicates some of the general expenditure categories to consider when assessing the feasibility of any project.
The salaries of those who conduct the study are potentially the most expensive item, especially for studies that require large interviewer staffs. Such expenses include not only the interviewers' wages, but also transportation costs and living expenses, which can be sizable. Interviewers may require hours of training before they can begin to collect data. If respondents are not available, callbacks may be necessary, which further increases the cost of each interview. To get the work done in a timely fashion and ensure reliability, investigators may need to hire people or contract with an organization to code the raw data into an analyzable format.
Computer expenses also can be formidable. A few decades ago, data analysis comprised the bulk of computer costs, but now computing services of one kind or another are used for questionnaire design, project management, data collection, literature searches, and report preparation. A significant cost here is for the software packages and Internet access that actually perform these procedures, in addition to the cost of the computer itself and peripherals like printers, scanners, zip drives, and so on.
TABLE 4.3 An Illustrative Budget for Conducting Face-To-Face Interviews of 400 People
|
ELEMENTS OF THE INTERVIEW |
COST |
% OF TOTAL |
|
Materials for Interview: print or electronic maps; interviewer manuals; printed questionnaires; |
$500 |
2% |
|
Interviewer Training Sessions: 2 days of training, wages for trainer and interviewers |
$2,400 |
9.8% |
|
Conduct Interview: Travel Costs: travel to and locate residence (inc. 60 callbacks for people not home); 1 hour per interview; $10 per completed interview |
$4,000 |
16.3% |
|
Conduct Interview: contact respondent; 1.5 hours per interview |
$9,000 |
36.7% |
|
Clerical and Data Entry Tasks: code or transcribe interviews; enter data into an electronic data file (1 hour per interview at $10 per hour) |
$4,000 |
16.3% |
|
Professional Supervision: coordinating and supervising all of the above tasks (160 hours at $60,000 total annual compensation) |
$4,620 |
18.8% |
|
TOTAL: |
$24,520 |
100% |
Another major cost consideration is expenditures for office supplies and equipment. Under this category are such items as paper, envelopes, postage, tape, printing, and the like. Paper products might seem to be inexpensive at first glance, but given the large samples that are used for some surveys, this cost can be substantial. For example, suppose we conduct a survey of approximately 500 people. Each person receives a large envelope containing a letter of introduction; a professionally printed, four-page questionnaire; and a postage-paid return envelope. In addition, all members of the sample receive a reminder letter urging them to respond, and about 250 nonrespondents receive a second questionnaire. The cost for printing, envelopes, and postage could easily exceed $2,000. Different kinds of studies present different cost issues. For example, studies based on direct observation of behavior may necessitate high-cost equipment, such as video cameras, recorders, and videotape. Unless these are already available, the project will require substantial outlays.
Providing incentives to ensure the cooperation of people in the study also may be a cost factor. This may range from giving stickers or balloons to schoolchildren for completing a questionnaire to paying respondents in recognition of the large time commitment required for a longitudinal study. A study evaluating the effectiveness of advocacy services to women leaving their abusive partners (Sullivan, 1991) illustrates participant incentive costs. Women were interviewed before the program and at 5, 10, and 20 weeks following the program. Not only was it difficult to maintain contact with this highly mobile population, completing a survey form was a low priority for these women, given the stress and disruption in their lives. To encourage the women to participate, the 46 participants were paid $10, $20, $30, and $40, respectively, for the four interviews, for a total cost of$4,600. Payment of subjects is more of an issue in experiments that require more time investment and greater commitment from participants than usually is required in most surveys or observational studies.
Dissemination of research findings also generates costs. Besides the additional printing and office supplies for preparing reports, this expense category may include travel to professional meetings to present papers. Program evaluation studies also may entail hosting workshops or conferences with sponsors and other interested parties to ensure that the findings are incorporated into the policy and intervention planning process.
Finally, some costs associated with a research project are difficult to specify. When research is conducted under the auspices of a university, a human service agency, or a research center, some organizational resources will partially or indirectly support the research. For example, money will be spent to heat and light the building where the research project is housed, but this cost is difficult to assess precisely. A major factor in awarding a research project to a particular organization may be the fact that the organization has an extensive research library, sophisticated computer facilities, or an extensive research laboratory. The organization maintains these facilities for general use, not just for a particular research project, so it is difficult to ascertain how much of the overall cost of supporting the facilities should be assigned to a given project. Consequently, the concept of “indirect cost,” typically a percentage of the total grant request, is employed to cover these real but hard-to-specify costs. Each organization negotiates its rate with the granting agency on the basis of the facilities and equipment that the organization has for research. The amount charged to indirect costs varies from 15 percent to well in excess of 100 percent of the basic grant.
Anticipating and Avoiding Problems
Problems related to time and financial considerations arise during virtually all research projects, but their impact on the outcome of the research can be minimized if they are anticipated as much as possible, especially during the planning stage, when the details of the project are easier to change. A number of steps can be taken to anticipate problems. First, learn as much as possible from the experiences of others through the studies consulted during the literature review. We mentioned earlier that finding problems other researchers encountered is one purpose of the literature review. Also, solicit personal advice from experienced researchers who might be available for consultation. A knowledgeable researcher may be able to identify potential trouble spots in the plans and suggest modifications to avoid them.
INFORMATION TECHNOLOGY IN RESEARCH Searching the Literature: Lessons from Evidence-Based Practice
Whether one is a researcher seeking to hone a research idea into a feasible project or a human service practitioner seeking the best means to help a client, efficient access to the literature is essential. In fact, literature access represents one of the linkages between practice and research, and developments along these lines in evidence-based practice serve the needs of researchers and practitioners alike.
Evidence-based practice means integrating individual human service expertise with the best available external evidence from systematic research. A major challenge for evidence-based practice is to provide a means whereby practitioners and researchers can find the evidence in a readily useable form. To meet this challenge, social scientists from around the world developed the Campbell Collaboration. It has three main review groups: social welfare, education, and criminology. Formally organized in 2000, it was inspired by a similar group that focused on research in the health field, the Cochrane Collaboration (Hannes & Claes, 2007). Although the Campbell Collaboration Library is designed for both practitioners and researchers, each may use it for different purposes. The attraction for practitioners is that the Library provides rapid access to the latest research to help answer questions such as “Howwell does the intervention I'm considering work with problems like those I'm confronting?” The researcher might want to know “How well defined is the knowledge about my topic? What measurement tools have been used? What recommendations for further research have previous studies identified?”
The Cochrane Collaboration (2003) points out that the major bibliographic databases cover less than half the world's literature for health care and are biased toward English language publications. A similar situation holds true for the human service fields. Although common online literature databases such as Sociological Abstracts or Social Work Abstracts enable the user to locate studies, the user must sort through all the studies and draw relevant conclusions. A central feature of the Campbell Collaborative is not simply that it provides access to studies, but that it includes a database of systematic reviews, which consists of full-text articles reviewing the research available on human service. Each review follows a highly structured and systematic format and covers particular content areas, such as the methodologies used on a particular area of research, the criteria for including studies in the review, and the conclusions from the research. The plan for conducting a systematic review is developed according to guidelines from the Campbell Collaboration, and the resulting review is itself peer-reviewed before it is included in the Campbell Library topics (http://www.campbellcollaboration.org/library.php). The Library can be searched by title, author, and keyword. Consequently, researchers and practitioners can have confidence in the quality and findings of each Campbell review.
Of course, having the empirical data available in readily useable form is still only one part of the equation. The other part is accessing the data, and the key to access is asking the right questions for the database search. In addition to the Campbell review, practitioners and researchers may also need to locate actual studies. Whether searching for a review or for individual research studies, evidence-based practice experts point out that a good question for a systematic search must be clear and describe exactly what is being sought—just as a good research hypothesis clearly specifies the independent and dependent variables (Sackett et al., 2000). A widely accepted evidence-based practice principle for framing search questions is the acronym “PICO,” which stands for:
P—People or patient population of interest. The demographic characteristics, the problem or condition, and the particular setting (such as community or institution) should be specified.
I—Intervention. The intervention should be specified as clearly as possible, such as cognitive behavioral therapy, couples counseling, or bipolar support group.
C—Comparisons which will be made. This category would be included if the reviewer wishes to specifically limit inclusion of studies to those using control groups, placebos, or alternate treatments in the research design.
O—Outcomes. Here the reviewer specifies the kinds of outcomes such as behavior change, prevention, reduced cost, etc., that are of interest.
For example, an evidence-based literature search related to unintended pregnancy included the following key questions (identify the PICO elements in each of these questions):
1. How effective is counseling in a clinical setting at changing knowledge, skills, and attitudes about unintended pregnancies?
2. What is the association between behaviors that support fertility desires and the prevention of unintended conceptions?
3. What are the potential harms of contraception counseling?
4. What is the cost-effectiveness of counseling in the clinical setting to prevent unintended pregnancy? (Moos, Bartholomew, and Lohr, 2003, p. 116)
The questions provide the road map for navigating through the various databases appropriate to the practitioner's interest. In addition to helping identify search terms, the questions provide guidance for including and excluding studies from the plethora of articles one is likely to encounter. (See Appendix A for databases useful to the human services that are widely available online.)
Second, obtain whatever permissions or consents may be needed early in the planning stages of the project. Depending on the people the researcher wishes to study, it may be necessary to obtain permission from them to collect data. For example, some studies are aimed at school-age children and seek to gather data while the children are in school. To protect students from undue harassment and themselves from parental complaints, school administrators frequently are cool to allowing researchers into their schools. It may take considerable time to persuade whatever authorities are involved to grant the permissions needed—if they are granted at all. It certainly is wise to obtain any needed permissions before expending effort on other phases of the project; that effort might be wasted if permissions cannot be obtained.
The final—and, perhaps, most important—suggestion for avoiding problems is to conduct a pilot study. As noted, a pilot study is a preliminary run-through, on a small scale, of all the procedures planned for the main study. For surveys, contact and interview a small part of the sample—say, 20 people. Then, analyze the data as you would for the complete project. In experiments, the researcher should run a few groups through all procedures, looking for any unexpected reactions from participants. Observational researchers should visit the observation sites and make observations as planned for the larger study. The focus is, again, on problems that might force modifications in research plans. Deal with any problems that surface during the pilot study before the main project is launched.
Given all the pitfalls a project might encounter, it is quite possible that, at some point, the researcher may conclude the project is not feasible as planned. Before calling it quits, however, give careful consideration to possible modifications that would enhance the project's feasibility. If inadequate time or money is the problem, perhaps the project can be scaled down. It might be possible to reduce the sample size or the number of hypotheses tested to make the experiment manageable. If face-to-face interviews were originally planned, consider a mailed questionnaire or even a telephone survey as cost-cutting and time-reducing measures. If the problem is with procedures, such as may occur in an experiment, consider how they might be changed so the project can proceed. The point is that a project should not be abandoned until all efforts to make it feasible have been investigated.
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4.4 Review and Critical Thinking
4.4 REVIEW AND CRITICAL THINKING
Suitable topics for research come from a variety of sources, including personal interest, social problems, theory testing, prior research, program evaluation and policy implementation, and human service practice.
Political factors also influence problem selection: Powerful interest groups encourage the expenditure of research resources on issues that are of interest to them and that may not serve the interests of less advantaged or minority groups.
A general topic for research must be narrowed and focused into a precise, researchable problem.
An important part of refining a research problem is conceptual development: identifying and defining the concepts on which the study will focus.
Reviewing previous research related to the selected topic is a crucial step in problem development and preparing to conduct a research project. This review should produce information about theoretical and conceptual issues, research hypotheses and variables, measurement and operational definitions, research techniques, sampling strategies, statistical techniques, and findings and conclusions.
The units of analysis must be clearly specified as individuals, groups, organizations, programs, or social artifacts.
Continual awareness of the operative unit of analysis ensures avoidance of such errors as the ecological fallacy and the reductionist fallacy.
Reactivity refers to the fact that people may behave differently when they are being watched than when they are not being watched, and the effects of reactivity must be considered when shaping a research problem.
Qualitative research emphasizes the description of how people experience the world; it relies on data in the form of words, pictures, descriptions, and narratives. Quantitative research uses numbers, counts, and measures to assess statistical relationships between variables.
Cross-sectional research is based on data collected at one point in time, which makes accurate conclusions about trends or behavioral changes difficult. Longitudinal studies are based on data collected over a period of time and are particularly useful for studying trends or behavioral changes.
Once fully refined, the practical feasibility of a proposed research project requires realistic assessment.
Critical thinking calls for the careful assessment of the nature, extent, and various facets of a problem to be addressed. So human service practitioners, policymakers, and people in their everyday lives need to devote attention to formulating, shaping, and refining a problem. It doesn't have to be a scientific problem, which is the focus of this book; it could be a problem confronting an individual, a family, or an organization. Careful and systematic thinking about a problem can pay off in a much more clear view of the problem:
1. Why is this problem considered to be a problem at all? Are there some personal interest or political issues that lead some people to see it as a problem?
2. Are the nature and terms of the problem clear and precise? Could you engage in the equivalent of what researchers call “conceptual development” to produce a clearer and sharper focus on exactly what the nature of the problem is?
3. What have others said about this problem? Is there some equivalent to what researchers call a “review of the literature” that could uncover other ideas, perspectives, or data about the problem and its solution?
4. How do people's subjective perceptions shape how they formulate a problem? Do you tend to perceive the problem differently if you take a “quantitative” approach versus a “qualitative” approach?
Search for websites that focus on issues such as poverty or drug abuse. An initial perusal of such sites can help identify important issues for developing the research problem such as the following: “How is the concept defined?” “Does there appear to be consensus on what the concept is?” “What controversies or issues are being debated about the topic?” You also may find organizations and resources, such as measurement tools, that may prove useful during later steps in the research process. Select a topic to research, and explore some of the websites that the search locates.
The Internet can be extremely useful in discovering prior research. Many websites consist of bibliographies or include them as a special section. One example is the National Criminal Justice Reference Service. Access this site (at http://www.ncjrs.gov) and select “Victims,” which is listed under “Topics.” This will lead to a diverse listing of sources on victims of crime. Select one of the victim categories, such as “Special Populations,” and peruse some of the available sources. As another example, the Substance Abuse and Mental Health Services Administration (http://store.samhsa.gov/home) provides immediate access to a wealth of articles related to substance abuse. Try out this site by entering a combination of terms, such as “alcohol” and “violence.”
Berg, B. L., & Lune, H. (2012). Qualitative Research Methods for the Social Sciences, 8th ed. Boston: Pearson. Although this book focuses primarily on how to conduct good qualitative research, it also contains a good comparison of qualitative and quantitative research and assesses when each is the most appropriate design.
Bransford, J. D. & Stein, B. S. (1995). The Ideal Problem Solver: A Guide for Improving Thinking, Learning, and Creativity, 2nd ed. New York: Freeman. Sound thinking combined with creativity clearly are important to formulating research problems. This guide assists in improving thought processes, drawing logical deductions, enhancing creativity, and even improving communication skills.
Gross, R. (1993). The Independent Scholar's Handbook. Berkeley, Calif.: Ten Speed Press. This book contains many examples of how successful scholars developed personal hunches and notions into serious research inquiries. It also is filled with practical advice about such things as obtaining resources and communicating with other researchers who share similar research interests.
Higgins, P. C. & Johnson, J. M. (1988). Personal Sociology. New York: Praeger. This book includes many illustrations of how personal life events and experiences shaped the research interests of a variety of sociologists.
Hunt, M. (1985). Profiles of Social Research: The Scientific Study of Human Interactions. New York: Basic Books. As its title implies, this book presents a series of descriptions of major research projects. Follow these projects from inception to completion, and see successful social scientists at work.
Locke, L. F., Silverman, S. J., & Spirduso, W. (2010). Reading and Understanding Research, 3rd ed. Thousand Oaks, Calif.: Sage. This is an excellent and thorough overview of how to do a good literature review and extract the appropriate information from it in an organized fashion.
Menard, S. (2002). Longitudinal Research, 2nd ed.
Newbury Park, Calif.: Sage. This book provides a readable overview of both longitudinal and cross-sectional research. It discusses when each is an appropriate design and some of the problems that arise in doing good longitudinal research.
Reinharz, S. (1992). Feminist Methods in Social Research. New York: Oxford University Press. This book is a massive compilation of examples for all types of research conducted by researchers identified as feminists. Anyone interested in conducting research from this perspective is well advised to consult this impressive work.
Class Exercises for Competency Assessment
In working through the exercises in this chapter, we suggest that you review Appendix A, which covers the basic issues involved when conducting research in a library. We also have found it helpful for students in our research classes to schedule a one- or two-hour workshop with the reference personnel to help familiarize themselves with the materials available in their library, especially the human service resource material.
4.1. [Critical Thinking] [Research & Practice] Following are several broad topic areas relevant to the human services. Select one that has the greatest personal appeal to you. Identify why this topic interests you. How do your selection and the reasons for it compare with those of other students?
a. child abuse
b. dementia
c. emotionally disturbed children
d. victims of crime
e. violence in the family
f. alcoholism and drug addiction
g. discrimination against minorities
h. homelessness
i. community living for the developmentally disabled
j. effects of unemployment
k. recipient rights for mental health clients
4.2. [Research & Practice] Use your library's resources to locate several research studies published in the professional literature on the topic you selected. Your search efforts should include—but need not be limited to—the following: a popular search engine such as Google; a specialized social science service such as socINDEX, or Social Work Abstracts; government documents through the Federal Digital System, (http://www.gpo.gov/fdsys); and the library's public catalog or a service such as WorldCAT. Be prepared to discuss with the class how you located your studies.
4.3. [Critical Thinking] [Research & Practice] For each research study you locate, do the following:
a. Indicate which factors seemed to influence the researcher's selection of topic in the study—that is, personal interest, social problems, theory testing, program evaluation and policy implementation, prior research, or practice experience.
b. What was the unit of analysis for each study? Was it the same as or different from the source of the data? If different, indicate the source. Can you think of any reasons for selecting a different unit of analysis?
c. What specific problem did the study address? From the presentation of the study, what factors influenced the final, actual problem formulation? In particular, were there issues of cost, time, or feasibility that necessitated a modification of the problem from the initial proposal?
4.4. [Ethics] [Critical Thinking] [Research & Practice] Chapter 3 presented a discussion of ethical issues in research. Did a concern for ethics influence what specific research problem emerged from an interest in studying the general topic? If so, what ethical issues confronted the researchers in studying the problem?
4.5. [Diversity] [Research & Practice] We have made the point that problem selection in research is a social process in which power, interest groups, and other factors play significant roles. One practice issue that has received considerable attention in recent years is transracial adoption—the placement of minority children, especially Native-American children, in foster and adoptive homes with white families. A quick Internet search on the key words “transracial adoption” will generate sufficient information for this exercise.
a. Have one group of students imagine that they are members of an adoptive/foster parent association that has been asked to provide suggestions to the DHHS for research priorities. What research problems would this group want to have studied?
b. Have a second group of students imagine that they are tribal leaders representing the interests of Native Americans. What priorities would they have, and what questions might this group suggest? Contrast the problems suggested by each group.
· Notebook
Chapter 4
Issues in Problem Formulation
Selectin
g a Research Problem
Personal Interest
Social Problems
Testing Theory
Prior Research
Program Evaluation and Policy Implementation
Human Service Practice
Minorities in Research: The Political Context of Problem Selection
Shap
ing and Refining the Problem
Conceptual Development
Review of the Literature
Units of Analysis
Reactivity
Qualitative versus Quantitative Research
Cross.Section
al versus Longitudinal Research
Feasibility of a Research Project
Time Constraints
Financial Considerations
Anticipating and Avoiding Problems
Chapter 4
Issues in Problem Formulation
Selecting a Research Problem
Personal Interest
Social Problems
Testing Theory
Prior Research
Program Evaluation and Policy Implementation
Human Service Practice
Minorities in Research: The Political Context of Problem Selection
Shaping and Refining the Problem
Conceptual Development
Review of the Literature
Units of Analysis
Reactivity
Qualitative versus Quantitative Research
Cross.Sectional versus Longitudinal Research
Feasibility of a Research Project
Time Constraints
Financial Considerations
Anticipating and Avoiding Problems
Chapter 2
Theories in Research and Practice
Concepts and Operational Definitions among Minority Populations
Cause-and-Effect Relationships
Class Exercises for Competency Assessment
After dashing through the Looking-glass House to view its garden,
Alice says, I should see the garden far better … if I could get to the top of that hill: and here's a path that leads straight to it—at least, no, it doesn't do that … but I suppose it will at last. But how curiously it twists! It's more like a corkscrew than a path! Well this turn goes to the hill, I suppose—no it doesn't! This goes straight back to the house! Well then, I'll try it the other way. (Carroll, 1946, pp. 21–22)
Understanding the world—especially human behavior—sometimes bears a striking resemblance to Alice's convoluted and frustrating journey in Wonderland. People do what we least expect, and without any apparent rhyme or reason: A prisoner on parole who appeared to be “making it on the outside” suddenly commits another offense and goes back to jail; a marriage of 25 years that seemed to be quite solid suddenly ends in divorce; a respected and successful business executive commits suicide. Human service providers, in particular, are familiar with experiences such as these, and the path to understanding often mirrors Alice's corkscrew.
Science, however, provides a method for mapping and understanding that corkscrew. In this chapter, we discuss the basic logic underlying scientific research, beginning with an assessment of how science differs from other ways of gaining knowledge. Then, we analyze the importance of theories and their role in scientific research, drawing a parallel with the use of theories in human service practice. Following this, we discuss the role of concepts and hypotheses, showing how hypotheses serve to link theory and research. Finally, we analyze the nature of causality, because research is, at its core, a search for cause-and-effect relationships among phenomena.
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2.1 Sources of Knowledge
2.1 SOURCES OF KNOWLEDGE
Human service practice is based on knowledge of human behavior and the social environment. There are numerous ways of gaining such knowledge, but all sources of knowledge have their pitfalls. We argued in Chapter 1 that practice knowledge should be grounded in scientific research. This does not mean that science is infallible, but science does have advantages as a source of knowledge that makes it superior to other ways of gaining knowledge.
To see why this is the case, we contrast science with four other common sources of knowledge: tradition, experience, common sense, and journalism. We then discuss how science can improve professional practice.
Traditional knowledge is knowledge based on custom, habit, and repetition. It is founded on a belief in the sanctity of ancient wisdom and the ways of our forebears. People familiar with the musical Fiddler on the Roof will recall how the delightful character Tevye, a dairyman in the village of Anatevka, sang the praises of tradition:
Because of our traditions, we've kept our balance for many, many years. Here in Anatevka we have traditions for everything—how to eat, how to sleep, how to wear clothes …. You may ask, how did this tradition start? I'll tell you—I don't know! But it's a tradition. Because of our traditions, everyone knows who he is and what God expects him to do. Tradition. Without our traditions, our lives would be as shaky as—as a fiddler on the roof! (Stein, 1964, pp. 1, 6)
For Tevye and the villagers of Anatevka, where traditions come from is unimportant. Traditions provide guidance; they offer “truth”; they are the final word. Traditions tell us that something is correct because it has always been done that way.
Traditional knowledge is widespread in all societies. Many people, for example, believe that a two-parent family is preferable to a single-parent family because the former provides a more stable and effective socializing experience for children and reduces the likelihood of maladjustment. In some cases these beliefs are grounded in religious traditions, whereas in other cases they are accepted because “everybody knows” how important two parents are to a child's development. In fact, some human service providers accept these beliefs about the traditional two-parent family despite the existence of considerable research suggesting that the two-parent family may not always be essential for high-quality adoption or foster care. For example, one review of research into this issue concluded, “In the studies reviewed here, single-parent families were found to be as nurturing and viable as dual-parent families. In fact, single-parent adoption emerged as a good plan for children” (Groze 1991, p. 326).
Human service providers can be affected in other ways by traditional beliefs. For example, the works of a Sigmund Freud or an Erik Erikson might be accepted without question, and emphasis might be placed on remaining true to their words rather than on assessing the accuracy or utility of their ideas.
Tradition can be an important source of knowledge, especially in such areas as moral judgments or value decisions, but it can have some major disadvantages. First, tradition is extremely resistant to change, even for those cases in which change might be necessary because new information surfaces or new developments occur. Second, traditional knowledge easily confuses knowledge (an understanding of what is) with values (a preference for what ought to be). For many people, the traditional emphasis on the two-parent family actually is based on a value regarding the preferred family form rather than on a knowledge of the effect that such a family has on child development.
Experience as a source of knowledge refers to firsthand, personal observations of events. Experiential knowledge is based on the assumption that truth and understanding can be achieved through personal experience, and that witnessing events will lead to an accurate comprehension of those events.
Experience is a common source of knowledge for human service workers, who have numerous opportunities to make firsthand observations of emotionally disturbed children, people with physical disabilities, foster children, and other service populations. From these contacts, practitioners can develop an understanding—not necessarily an accurate one—of what motivates their clients and what social or psychological processes have influenced them.
For example, a person working in a spousal abuse shelter will have considerable contact with women whose husbands have physically and psychologically abused them. Because of this, the worker likely is sensitive to the harm that can come to women from their husbands. After seeing women who have been so abused, this worker may conclude that marital counseling with such spouses cannot work in a climate of violence and anger, and may even be dangerous. In fact, social worker Liane Davis (1984) found that shelter workers were much less likely to recommend marital counseling than were family court judges. Family court judges did not have the powerful experience of seeing women when the effects of their abuse were most visible; moreover, family court judges have a mandate to maintain the integrity of the family. For them, marital counseling seems to be both a feasible and an appropriate way to keep the family intact. So we see that the experiences of shelter workers and judges in different settings can lead them to perceive problems and assess solutions differently.
This experiential knowledge about family dynamics and abuse may be reinforced by traditional knowledge about the importance of family life. Armed with this knowledge, a practitioner might shape an intervention effort that focuses on individual counseling or on marital counseling.
Experiential knowledge, however, has some severe limitations that can lead to erroneous conclusions. First, human perceptions are notoriously unreliable. Perception is affected by many factors, including the cultural background and the mood of the observer, the conditions under which something is observed, and the nature of what is being observed. Even under the best conditions, some misperception is likely; thus, knowledge based on experience often is inaccurate.
Second, human knowledge and understanding do not result from direct perception but, rather, from inferences that are made from those perceptions. The conclusion that marital counseling doesn't work is an inference—that is, it is not directly observed. All that has been observed is that these women have been battered by their husbands. There is no observation of the effectiveness of any type of counseling. (We discuss making inferences from observations in more detail when we address the issue of causality later in this chapter.)
Third, the very people in positions to experience something directly frequently have vested interests in perceiving that thing in a certain way. Teachers, for example, observe that the students who do poorly are the ones who do not pay strict attention during class. However, teachers have a vested interest in showing that their teaching techniques are not the reason for poor performance among students. Therefore, teachers probably would be inclined to attribute students' failings to the students' lack of effort and inattentiveness rather than to their own inadequacies as educators.
A final limitation on experiential knowledge is that it is difficult to know if the people directly available to you are accurate representatives of all the people about whom you wish to draw conclusions. If they are not, then any conclusions drawn from your observations may be in error. To use our earlier example, are the battered women who contact a spousal abuse shelter representative of all battered women? If the women who contact a shelter are different in some way, and if these differences influence the effectiveness of counseling in the shelter, then you cannot generalize conclusions from their outcomes in counseling to the experiences of all battered women. Battered women who go to a shelter may be more affluent or less isolated and, therefore, might demonstrate different outcomes in counseling than less affluent or more isolated women would.
The accumulation of knowledge from tradition and experience often blends to form what people call common sense : practical judgments based on the experiences, wisdom, and prejudices of a people. People with common sense are presumed to be able to make sound decisions even though they lack specialized training and knowledge. Yet, is common sense an accurate source of knowledge? Consider the following contradictory examples. Common sense tells us that people with similar interests and inclinations will be likely to associate with one another. When we see a youngster who smokes marijuana associating with others who do the same, we may sagely comment, “Birds of a feather flock together.” Then, however, we see an athletic woman become involved with a bookish, cerebral man, and we say, “Opposites attract.”
In other words, common sense often explains everything—even when those explanations contradict one another. This is not to say that common sense is unimportant or always useless. Common sense can be valuable and accurate, which is not surprising, because people need sound information as a basis for interacting with others and functioning in society. However, common sense does not normally involve a rigorous and systematic attempt to distinguish reality from fiction. Rather, it tends to accept what “everyone knows” to be true and to reject contradictory information. Furthermore, common sense often is considered to be something that people either have or don't have, because it is not teachable. In fact, it often is contrasted with “book learning.” This discourages people from critically assessing their commonsense knowledge and tempering it with knowledge acquired from other sources. For this reason, commonsense knowledge should be accepted and used cautiously. As a basis for human service practice, knowledge needs to be based on the rigorous and systematic methods used in scientific research. Common sense or a vague feeling of “helping” is not enough.
The materials prepared by journalists for newspapers, magazines, television, websites, or other media are another important source of knowledge about the world for most people. With the explosion of news sources available on cable television and the Internet, people now have access to vast amounts of journalistic information. Though some journalism consists of opinion pieces based on the speculations and inferences of the journalist, much of it, like science, is grounded in observation: Reporters interview people or observe events and write their reports based on those observations. In addition, with modern technology, journalists often are in a position to provide a video and/or audio record of what happened at a scene.
So it may seem, at first glance, that science and journalism have much in common as sources of knowledge, and significant similarities between the two endeavors can be identified. Both use observation to seek out accurate knowledge about the world. In fact, some journalism can, at times, take on many of the characteristics of social science research. Some journalistic output, for example, can look a lot like the in-depth interviews and case studies we will discuss in Chapter 9. However, although scientific standards require that scientists use the systematic procedures discussed in this book, journalism can—and often does—fall far short of meeting these standards.
A key difference between science and journalism is that the observations of scientists are much more systematic in nature. This means that scientists utilize far more careful procedures than journalists to reduce the chances that their conclusions will be inaccurate. For example, a journalist interested in the experiences of prison inmates probably will interview a few inmates who are made available to him by prison authorities and then use these interviews to draw conclusions, at least implicitly, about the experiences of all prisoners. Social scientists would recognize that prisoners selected by the authorities are likely to differ from other prisoners in some important ways: They may have been selected because they committed less serious offenses or were model prisoners. Their experience of prison also is likely to be very different from that of a more serious offender or someone who has chronic confrontations with prison authorities. Recognizing this, social scientists would be very careful about how they selected inmates on whom to make observations, and usually would not accept a sample selected by prison authorities. The best sampling procedures, which will be discussed in Chapter 6, would be those that ensure that all types of prisoners have a chance to appear in the sample. This could be done, for example, by interviewing all the prisoners or, if that were not feasible, interviewing a randomly selected group of prisoners. If sampling procedures fall short of these standards, then social scientists have reduced confidence in the resulting conclusions. Journalists often do not use such rigorous sampling procedures.
A second key difference between science and journalism is that journalism is not concerned with theory building and verification as a way of developing an abstract explanation of people's behavior. Journalists are much more focused on, as the saying goes, “just the facts.” Scientists, on the other hand, recognize that facts often don't speak for themselves—they need to be interpreted in the context of a theoretical understanding to fully comprehend their meaning.
Winston Churchill, the prime minister of Britain during World War II, is reported to have said that democracy is an imperfect form of government, but that it is far superior to all other forms. Many scientists have a similar view of science: They realize it is imperfect and limited, but they also recognize that it is far superior to other sources of knowledge for gaining an understanding of the world. Science is a method of obtaining objective knowledge about the world through systematic observation. (The term science also sometimes is used to refer to the accumulated body of knowledge that results from scientific inquiry.) Science has five distinguishing characteristics that, taken together, set it apart from the other sources of knowledge.
First, science is empirical, which simply means that science is based on direct observation of the world. Science is not, as some people mistakenly believe, founded in theorizing, philosophizing, or speculating. At times, scientists do all these things; but eventually, they must observe the world to see whether their theories or speculations agree with the facts. Because of this, the topics that can be subjected to scientific scrutiny are limited; any issue that cannot be resolved through observation is not within the scope of science. For example, the questions of whether God exists or what values should underlie a human service profession are not scientific issues, because it is impossible to determine their truth (or lack thereof) through observation. These are matters of faith or preference, not of science.
Second, science is systematic, meaning that the procedures used by scientists are organized, methodical, public, and recognized by other scientists. One dimension of the systematic nature of science is that scientists report, in detail, all the procedures used in coming to a conclusion. This enables other scientists to assess whether the inferences and conclusions drawn are warranted given the observations made. A second dimension of the systematic nature of science is replication—that is, repeating studies numerous times to determine if the same results can be obtained. Scientists are very cautious about drawing hard-and-fast conclusions from a single observation or investigation. In fact, and quite at variance with experiential knowledge, scientists assume that a single direct observation is as likely to be incorrect as correct. Only repeated observations can reduce the chance of error and misinterpretation (Rosenthal, 1991).
Third, science is the search for causes. Scientists assume that there is order in the universe, that there are ascertainable reasons for the occurrence of all events, and that scientists can discover the orderly nature of the world. If we assumed there was no order, no pattern, then there would be no need to search for it. We could write off events as the result of chance or the intervention of some benevolent (or malevolent, or indifferent) otherworldly force that we can never understand.
Fourth, science is provisional, which means that scientific conclusions are always accepted as tentative, as subject to question and possible refutation. There are no ultimate, untouchable, irrevocable truths in science. There are no scientists whose work is held in such esteem that it cannot be criticized or rejected. As the philosopher Jacob Bronowski (1978, pp. 121–122) put it, “Science is not a finished enterprise…. The truth is [not] a thing that you could find … the way you could find your hat or your umbrella.” Science is a process of continuous movement toward a more accurate picture of the world, and scientists fully realize that we will never achieve the ultimate and final picture.
Finally, science strives for objectivity, which means that scientists try to avoid having their personal biases and values influence their scientific conclusions. This is a controversial and complicated characteristic of science, because many social scientists would argue that true objectivity is impossible for human beings to achieve. We will discuss this issue at a number of points in this book, but it is sufficient to say here that all scientists are concerned that their scientific conclusions are not solely (or merely) a product of their own personal biases and values. This doesn't mean that scientists should be devoid of values. Quite the contrary, they can be as passionate, concerned, and involved as any other group of citizens. However, they realize that their values and biases can—and probably will—lead to erroneous scientific conclusions. To address this problem, science incorporates mechanisms to reduce the likelihood of biased observations becoming an accepted part of the body of scientific knowledge. For example, publicizing all research procedures enables others to assess whether the research was conducted in a way that justifies the conclusions reached. Furthermore, such detailed reporting permits replication so that other researchers, with different values, can see if they come to the same conclusions regarding a set of observations.
Despite these checks, of course, values and biases will still be found in research. The very decision of what topics to investigate, for example, often is shaped by the researcher's values: One person studies family violence because a close friend was the victim of spousal abuse, and another studies factors contributing to job satisfaction because of a personal belief that work is central to identity. Values and biases also enter research through the interpretation of observations. For personal reasons, one researcher may desperately want to show that the criminal justice system rehabilitates (or does not rehabilitate). This may well influence how he or she goes about conducting research and interpreting the results. There are even a few cases (most commonly in biomedical research) of outright falsification of data to show a certain conclusion. The point is that values and biases commonly intrude on scientific research, but the overall scientific enterprise is organized to reduce their impact on the body of scientific knowledge.
The scientific method, then, with the characteristics just described, is viewed by scientists as preferable to other ways of gaining knowledge, because it is more likely to lead to accurate knowledge of the world. To return to our earlier example of single-parent families and adoption, science views all knowledge regarding the family as provisional and open to question, and there have been many scientific investigations of the role of the family in these matters. Child adjustment and development in two-parent and single-parent families have been compared in both adoptive and biological families as well as in stepfamilies.
The conclusion from these various studies is that the traditional, two-parent family does not seem to play the indispensable role that much commonsense knowledge would accord it—or at least that the role of parents in families is more complicated than was once thought. For example, the research shows that adoption by a single parent is not always detrimental when compared with two-parent adoptive settings; some adoptees with one parent do quite well (Groze & Rosenthal, 1991; Shireman & Johnson, 1986). A related finding is that nontraditional family structure (having one rather than two parents) probably is less critical to children's development than is family process (warm relationships and low conflict between parents and children). The negative consequences often associated with single-parent families may arise from the conflict that often accompanies divorce, because divorce is how many single-parent families are produced (Amato & Booth, 1997; Jekielek, 1998; Lansford et al., 2001). Also, single-parent families often experience certain negative factors: low income, inadequate parental guidance, and less access to community resources. Single-parent families that overcome these difficulties do as well as other family forms in raising children (McLanahan & Sandefur, 1994). So the commonsense or traditional view that the two-parent family is always superior to the single-parent setting is shown by research to be vastly oversimplified at best.
In this fashion, then, scientific knowledge overcomes many of the weaknesses of traditional, experiential, and commonsense knowledge. In particular, it enables us to accumulate accurate information despite the personal biases of individual researchers or practitioners. These positive attributes of science do not mean, however, that science is perfect. Scientists do make errors. But, as Jacob Bronowski (1978, p. 122) so aptly put it, “Science is essentially a self-correcting activity.” If proper scientific procedures are followed, today's errors will be corrected by researchers in the future, whose errors in turn will be corrected by still more research.
With this more detailed understanding of science and its characteristics, we can return to the concept of evidence-based practice introduced in Chapter 1 and elaborate on what this approach says about the parallels between science and practice. Basically, this approach argues that effective human service practice should have characteristics that parallel those of science (Hayes, Barlow, and Nelson-Gray, 1999; Rosen, 1996). Human service practice would be enhanced if it was shaped by a consideration of each of the five characteristics of science just discussed. First, practice, like science, should be empirical, stressing problem assessment involving direct observation of client problems, actual counts of behaviors, and independent observations from multiple data sources. Such data are less subject to distortion and bias than self-reports, speculations, and philosophizing. Second, practice, like research, should be systematic. To the extent that practice procedures are well organized, clearly specified, and made public, they can be replicated and tested by others. In this manner, ineffective procedures can be eliminated, and promising ones can be refined and improved. One of the recurring criticisms of many human service interventions is that the intervention itself is not well specified. Consequently, research evaluating the intervention cannot clearly indicate what did (or did not) work. Practice models also involve causality in terms of specifying a clear link between cause and effect or explaining why a proposed intervention should work with the particular identified problem. Again, a criticism of human service projects in the past has been that many of them have consisted of a conglomeration of intervention efforts without a clearly articulated linkage between cause and effect.
Practice theory, like science, should be provisional. All practice models and techniques should be viewed as fair game for criticism and refutation. Through such a process of testing and challenging existing practices, healthy growth can occur in practice methodology.
Finally, human service professionals must deal with the problem of professional objectivity. The determination of the utility and effectiveness of practice procedures needs to be done under objective conditions. Just as the researcher must attempt to safeguard against the intrusion of values into the conduct of research, so practitioners must guard against the intrusion of values into practice. This issue of values and objectivity is particularly difficult for human service practitioners, who often approach problems with a strong set of values, both personal and professional. Personally, practitioners may have strong feelings about such matters as abortion, alcohol use, or domestic violence that may clash with those of the groups with which they work. Furthermore, some human service providers are conventional and middle class in their personal lives, which may influence what they see as successful social functioning. In addition to these personal values, human service practice itself is heavily imbued with professional values. In fact, as one human service educator put it, “Social work is among the most value based of all professions.…. [It] is deeply rooted in a fundamental set of values that ultimately shapes the profession's mission and its practitioners' priorities” (Reamer, 2006, p. 3).
At times, these values may emphasize a conservatism or pressure to preserve the status quo; at other times, the values may reflect a commitment to support vulnerable or oppressed populations. In either event, it is challenging to satisfy the recommendation that human service providers not let their values intrude into the provision of services to clients. In fact, it probably is impossible to mount an effective change effort without some imposition of values, either implicit or explicit. Even more, some therapeutic approaches, such as those of Carl Rogers, Albert Ellis, and Hobart Mowrer, include as one of their goals the acceptance by the client of new—and more realistic—values.
So even though professional practice in the human services is clearly oriented toward the fulfillment of certain values, practicing in the profession requires that the worker establish checks on the intrusion of values into practice, much as the researcher does in the conduct of research. In later chapters, we will discuss research techniques that are less subject to biases in observation and measurement. Application of these principles in practice also can help restrict the unwanted intrusion of personal values into service delivery. Another way to control the influence of values is to do research on the role of values in practice and to design agency procedures that help provide services objectively. As Research in Practice 2.1 illustrates, the influence of values on the actual conduct of practice cannot be totally eliminated. However, by relying on a practice approach that is empirically based, employing procedures supported by research, and incorporating rigorous evaluation procedures, it is possible to sensitize professionals to the impact of their value positions and, thus, enhance the objectivity of service delivery.
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2.2 Theories in Research and Practice
2.2 THEORIES IN RESEARCH AND PRACTICE
Theory is a word that is misunderstood by many people. To the neophyte, theories often are associated with the abstract, the impractical, or the unreal. In actuality, nothing could be further from the truth. In both research and practice settings, theories play a critical role in our understanding of reality and our ability to cope with problems. In fact, people commonly use theories in their daily lives without recognizing that they do so.
A theory is a set of interrelated, abstract propositions or statements that offers an explanation of some phenomenon (Skidmore, 1979). Three key elements in this definition are important to understanding theories. First, theories are made up of propositions , which are statements about the relationship between some elements in the theory. For example, a proposition from the differential association theory of crime is that a person becomes criminal because of an excess of definitions favorable to the violation of the law over definitions unfavorable to the violation of the law. Elements in this proposition include “criminal” and “definitions favorable to the violation of the law” (Sutherland, 1939). Behavior modification theory also contains numerous propositions, such as: Behavior change can occur through a reorganization of the environmental cues that reward and punish behavior (Sulzer-Azaroff & Mayer, 1991). The elements in this proposition include “behavior change,” “environmental cues,” and “reward and punish behavior.”
RESEARCH IN PRACTICE 2.1 Practice Effectiveness: Providing Services to Gays and Lesbians
Human service practitioners often deal with clients or situations that involve value-laden controversies. One area where this clearly is the case is the issue of whether gays or lesbians should be permitted to have custody of their children or to adopt. Traditional—and, in some cases, religious—values lead some people to the conclusion that only intact, heterosexual, married couples provide a suitable environment for child rearing and that being raised by a gay or lesbian parent would be harmful to a child. The difficult problem for the human service provider is how to serve clients within the context of one's own personal and professional values.
The movement toward evidence-based practice in the human services suggests that it is possible to use scientific research to assess whether personal or professional values are unreasonably influencing the services provided to clients. One of the primary features of evidence-based practice involves identifying general trends gleaned from a review of studies that are applicable to practice. The provision of child welfare services to gay and lesbian clients offers an excellent example of this feature. A human service professional charged with making recommendations about child custody and adoption would approach this situation by systematically searching the literature and asking the question: How well do gays and lesbians perform in the role of parent?
Marcus Tye (2003) summarizes the theoretical and empirical evidence currently available to answer this question. Over the past quarter century, beginning with the work of Karen Lewis (1980), a considerable body of research has accumulated on the development and experiences of the children of lesbians and gay men (Stacey & Biblarz, 2001). For the most part, this research does not support the negative developmental outcomes for the children that would be predicted by much traditional and experiential knowledge or some people's personal values. Children raised by gay or lesbian parents do not differ in their sexual orientation or personal development from children raised by heterosexual parents (Goldberg, 2009; Gottman, 1990).
By the 1990s the research focus had shifted from looking at the quality of family life after a parent had acknowledged his or her homosexuality toward the examination of gay men and lesbians who, often in the context of a committed homosexual relationship, were opting to have children via the processes of adoption, artificial insemination, or surrogate mothers. This research also has found no negative effects for adopted children raised in gay- or lesbian-headed families. These adoptive families exhibited a level of family functioning that, by many measures, was at least as high as that found in other types of families (Erich et al. 2005; Leung, Erich, & Kanenberg, 2005).
So this evidence-based review suggests that children can be reared into healthy adults in families parented by homosexuals and sexual orientation should not preclude individuals from serving as adoptive or foster parents. Thus the general trends in the existing data help provide direction for shaping agency policy. Science cannot inform human service workers regarding what their personal values ought to be, but it can point out practice situations in which personal values seem to be unreasonably intruding on intervention decisions. Such research also safeguards against the danger that decisions based on personal values will masquerade as “in the client's best interest” by providing an empirical knowledge base for decision making.
A second important part of our definition of theory is that theories are abstract systems, meaning they link general and abstract propositions to particular, testable events or phenomena. In many cases, these abstract systems are deductive systems, a general set of propositions that can be used to deduce further, more concrete relationships between the elements of the theory. Differential association theory is again illustrative. As noted, this theory relates definitions favorable to the violation of the law with the greater likelihood of criminal behavior. This means that the theory is supposed to apply to all specific types of crimes, such as robbery, larceny, and auto theft. So it would be logical to deduce from the theory that greater exposure to definitions favorable to the violation of the law would be associated with higher incidences of robbery, larceny, and auto theft. Theories are abstract, because they have this deductive power: The broader and more abstract the propositions and their related concepts, the more numerous the specific relationships that can be deduced from them.
The third key aspect of theories is that they provide explanations for the phenomena they address. Indeed, the ultimate purpose of a theory is to explain why something occurred. In differential association theory, the phenomenon to be explained is criminal behavior, and the explanation is that criminality is learned through much the same process as noncriminal behavior is. The content of what is learned—namely, definitions favorable to violation of the law—makes the difference. Thus differential association provides an explanation for the development of criminal behavior.
In comprehending theories and the roles they play, it is helpful to realize that we all use theories in our everyday lives, although we may not call them theories or even be consciously aware of using them. Nonetheless, we base our decisions and behavior on our past experiences and what we have learned from others. From these experiences, we generalize that certain physical, psychological, and social processes are operative and will continue to be important in the future, with predictable consequences. This is our “commonsense theory” about how the world operates and forms the basis for our decisions. For example, most people have certain general notions—that is, personal theories—about what causes poverty. Some personal theories emphasize poverty as an individual problem: People are poor because of their individual characteristics, such as laziness, low intelligence, poor education, or lack of marketable skills. Others' theories of poverty emphasize structural features of the American economy dictating that, even in times of economic expansion, some people will be left impoverished through no fault of their own. Which of these theories people identify with most closely determines, in part, how they react to poor people and which public policy provisions toward poverty they support. Advocates of the individualistic theory might be hostile toward the poor and programs to aid them, because they believe the poor are undeserving people who suffer only from their own shortcomings. Supporters of the structural theory may view the poor as victims and tend to be more benevolent toward them.
Personal theories like these concerning poverty may be extreme and misleading, because they are based on casual observations, personal experience, or other information lacking the rigorous concern for accuracy of scientific investigations. Unlike commonsense theories, the theories in research and practice are precise, detailed, and explicit. It is important, however, to recognize that a theory is always tentative in nature—that is, any theory is best viewed as a possible explanation for the phenomenon under investigation. By conducting research, scientists gather evidence that either supports or fails to support a theoretical explanation or practice intervention. No theory stands or falls on the basis of one trial. Theories are tested over a long period of time by many investigations. Only with the accumulation of research outcomes can one begin to have confidence concerning the validity of a theory.
We have all heard the refrain “It's only a theory” or “That's your theory.” Such phrases often are used in the context of deflating an argument. Actually, these comments, though often intended in a disparaging sense, convey some truth regarding theories. In particular, they point out that theories are sometimes untested (but testable) assertions about reality and that theories are not the end product of scientific investigation but, rather, a part of the process of science. Theories have particular purposes in both research and practice settings. In fact, the same theories often are used in both research and practice, because both researchers and practitioners turn to them for similar reasons. We can identify three major functions of theories in research and practice.
Explanation of Phenomena. As we have seen, theories provide an explanation for phenomena. They say not only what will happen under certain conditions (which is what hypotheses also do, but more concretely) but also why it will happen. This provides a much more powerful understanding of human behavior. In differential association theory, for example, the phenomenon to be explained is criminal behavior, and the explanation is that criminal behavior is a product of learning appropriate behaviors from others who are important to us. Thus, differential association theory provides a broad, abstract explanation for the development of criminal behavior that links such behavior with general processes of conformity and group process. People learn to be criminals in the same way they learn to be doctors, nurses, or lawyers—namely, by learning through association with other people.
Guide for Research and Practice. Theories guide and direct research and practice. They focus attention on certain phenomena as relevant to the issues of concern. If we were to dispense with theories altogether, as some would suggest, then what would we study? What data would be collected? What intervention strategy would be adopted? Theories help us find answers to these questions.
Imagine that a counseling center wants to attack the problem of teenage alcohol consumption at a particular high school and the staff decides to study the problem. Where to begin? What variables are important? As a first step, it is essential to fall back on some theory related to these issues. We might, for example, use the theory of differential association, which posits that alcohol consumption results from attitudes and patterns of behavior that are learned in association with other people, particularly peers. To test this theory, we could determine whether alcohol consumption is more common when it is viewed as an acceptable form of behavior among peers. We are then in a position to collect data on attitudes toward alcohol and patterns of alcohol consumption in peer groups. If the theory is confirmed, then it supports the idea that effective intervention will need to focus on attitudes toward alcohol consumption in peer groups.
We could have selected a different theory regarding alcohol consumption. For example, some theories posit an inherited predisposition toward alcoholism. Other theories suggest that alcoholism results from a nutritional deficiency that is satiated by alcohol consumption. We do not presume to suggest which theory is more accurate—future research will settle that issue, one hopes. The same thing occurs in practice intervention. If a practitioner used crisis intervention theory to deal with the disruption caused by an alcoholic parent, then the theory would direct attention to such factors as family coping strengths and emotional adaptation. Community-organization practice theory, on the other hand, would focus on the community resources available to recovering alcoholics and community services for their families. The point is that the theories used by researchers and practitioners guide their approaches and focus their attention on particular phenomena.
Integration of Multiple Observations. Theories help integrate and explain the many observations made in diverse settings by researchers and practitioners. They tell us why something happened, and they enable us to link the outcomes of numerous studies and interventions made in a variety of settings. As long as the findings of these efforts remain individual and isolated, they are not particularly valuable to science. Recall that a single observation is viewed with considerable skepticism. Single research findings may be in error, may be passed over and forgotten, or their broader implications may be missed entirely. Theories enable us to organize these dispersed findings into a larger, explanatory scheme. For example, someone investigating problem pregnancies among teenagers might observe that the groups of teenagers among whom such pregnancies are common tend to view an out-of-wedlock parenthood in a positive fashion. A familiarity with differential association theory would suggest that the social learning processes important in teenage drinking also may be relevant in problem pregnancies among teenagers. If this is the case, practitioners working in one area may be able to borrow strategies for intervention from the other area. Thus, theories integrate the findings from independent research endeavors and provide implications for intervention strategies.
Theories, then, play an important part in both research and practice, but one point needs to be reiterated: The utility of theories must be based on their demonstrated effectiveness. Theories should never be allowed to become “sacred cows,” the use of which is based on tradition or custom. Most authorities would agree with this conclusion: “The most important criterion to consider is the extent to which a given theory has been supported by empirical research” (Hepworth & Larsen, 1990, p. 18). In other words, has the intervention been shown to produce the desired results? In scientific research, this is called the verification of theories. Researchers approach the problem of verification by developing and testing hypotheses. This process of verification is diagrammed in Figure 2.1, which also shows a parallel process as it occurs in human service practice.
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2.3 Concepts and Hypotheses
2.3 CONCEPTS AND HYPOTHESES
An important part of theories is concepts: mental constructs or images developed to symbolize ideas, persons, things, or events. Concepts are the elements of theories discussed earlier; they are the building blocks that are interrelated in propositions to form the explanatory statements of a theory (Alford, 1998). Some of the concepts in behavior modification theory, for example, are reinforcement, conditioning, learning, and behavior change.
Concepts are similar in function to the words we use during everyday communication. The word automobile, for example, is the agreed on symbol for a particular object that is used as a mode of transportation. The symbol or word is not the object itself, but, rather, something that stands for or represents that object. Scientific concepts, like words in everyday language, also are symbols that can refer to an extremely broad range of referents. They may refer to something fairly concrete, like gender, or to something highly abstract, like reinforcement or cohesion.
Despite the similarities between scientific concepts and ordinary words, some differences are critical to the scientific endeavor. In particular, concepts used in scientific research must be defined very carefully. We can get along quite well with the words we use for everyday communication, having only a general idea of how these words are defined. In fact, it is doubtful whether most people could give a dictionary-perfect definition of even the most commonly used words. Such imprecision in the use of scientific concepts, however, is totally inadequate. Scientists, who are widely scattered both geographically and temporally, carry on research that tests various aspects of theories. For these disconnected research projects to produce information of maximum utility, all the bits of knowledge need to be integrated into an explanatory scheme—namely a theory. This accumulation of knowledge is severely hampered—in fact, it becomes practically impossible—if these isolated scientists use different definitions of the same concepts.
FIGURE 2.1 The Process of Theory Verification in Research Compared with Practice Intervention
For example, many studies of the relationship between reinforcement and learning have been conducted. If the results of different studies are to be comparable, then the concepts of reinforcement and learning should be defined the same way. Learning, for instance, can be defined in behavioral terms (as the performance of a new behavior) or in cognitive terms (as the understanding of how a particular behavior might be performed). When defined in these two different ways, the concept refers to something quite different in the world, and the results from two investigations using the different definitions would not be directly comparable. Perhaps, for example, behavioral learning occurs under quite different conditions than cognitive learning does.
Scientific analysis involves two types of definitions of concepts, each functioning at a different level of analysis and each serving a different purpose. At the theoretical or abstract level, concepts are given nominal definitions: verbal definitions in which scientists agree that one set of words or symbols will be used to stand for another set of words or symbols. Nominal definitions are directly analogous to the dictionary definitions of ordinary words in which a phrase is designed to give meaning to the word or concept being defined (Cohen & Nagel, 1934). For example, a nominal definition of “poverty” might be a deficiency in resources to the extent that people are not able to maintain a lifestyle considered to be minimally acceptable in a particular society (Sullivan, 2012).
An important step in moving from the abstract level of theory to the concrete level of research is to give concepts operational definitions: definitions that indicate the precise procedures or operations to be followed in measuring a concept. For example, Mollie Orshansky developed one of the most widely used operational definitions of poverty for the Social Security Administration (Ruggles, 1990). Her measure, still used by the government as a basis for policy decisions, is based on what it costs to purchase a low-budget, nutritious diet for a family. If we use U.S. Department of Agriculture figures, the poverty line is determined by the cost of food, the size of the family, and other factors. This operational definition of poverty yields a series of income cutoffs below which families are defined as poor. This is a precise definition that lists the exact operations—in this case, mathematical operations—to follow in defining poverty. Anyone using this definition measures the same thing in the same way.
The process of moving from nominal to operational definitions can be complex, because concepts are very general and abstract and controversy often arises over exactly what they refer to. Some concepts that have been a part of the literature for decades have yet to be operationalized in a way that is fully satisfactory. For example, “alcoholism” has proved to be extremely difficult to operationalize, especially in terms of establishing where social drinking leaves off and alcoholism begins (Schuckit, 2006). Because of substantial individual and cultural differences, simple measures relying on the amount and frequency of consumption are inadequate. Researchers have been forced to operationalize alcoholism on the basis of such symptoms as family or work problems, morning drinking, poor eating, and recurrent blackouts. Whereas symptom-based measures of alcoholism avoid the errors inherent in consumption measures, substantial controversy remains concerning which symptoms are the best indicators, how many symptoms must be evident, and how serious they must be before the label of alcoholic may be meaningfully applied.
Even the concept of poverty, which may seem straightforward and easy to operationalize, has proven to be controversial. There is, of course, the issue of where to set the income cutoffs. Orshansky's cutoffs are based on the assumption that the average American family spends one third of its income on food; some critics have argued that this results in poverty thresholds that are too low. Furthermore, Orshansky's definition sets a fixed income level as the poverty level; thus, it is unaffected by changing levels of affluence within society as a whole. Some have argued for a relative definition of poverty that defines as poor those who earn one third or one half of the median family income (Bell, 1987). With such a definition, the poverty thresholds would rise automatically if the affluence of society as a whole increased. So it should be evident that operationalizing concepts can be difficult, complex, and sometimes, controversial. The process of moving from the nominal to the operational level is called measurement, and it is treated extensively in Chapters 5 and 13.
A common strategy in scientific investigations is to move from a general theory to a specific, researchable problem. A part of this strategy is to develop hypotheses , which are testable statements of presumed relationships between two or more concepts. Hypotheses state what we expect to find rather than what has already been determined to exist. A major purpose of developing hypotheses in research is to test the accuracy of a theory (see Figure 2.1). The concepts and propositions of which theories are composed usually are too broad and abstract to be directly tested. Concepts such as reinforcement and learning, for example, need to be specified empirically through operational definitions before they are amenable to testing. Once operationally defined, these concepts generally are referred to as variables , or things that are capable of taking on more than one value. If hypotheses are supported, then this supplies evidence for the accuracy of the theory on which they are based.
In the construction of hypotheses, the relationship between variables is stated in one of two possible directions: a positive relationship, or a negative (also called an inverse) relationship. In a positive relationship, the values of the variables change in the same direction, such as both increasing or both decreasing. For example, we might hypothesize that the acceptance of the use of alcohol among an adolescent's peers will lead to an increased likelihood that the adolescent will consume alcohol. In other words, as acceptance of the use of alcohol by one's peers increases, so does the adolescent's own use of alcohol. In a negative relationship, or an inverse relationship, the values of variables change in opposite directions. We might hypothesize, for example, that, among adolescents, reduced parental supervision will lead to an increase in the likelihood of substance abuse. In this case, as the value of one variable (parental supervision) declines, the value of the other (substance abuse) is predicted to increase.
Useful guidelines to keep in mind for developing hypotheses include the following:
1. Hypotheses are linked to more abstract theories. Although generating hypotheses without deriving them from theories is possible, hypotheses are always linked to theories because the theories provide explanations for why things happen.
2. It is important that the independent and dependent variables in hypotheses be clearly specified. The independent variable is the presumed active or causal variable—the one believed to be producing changes in the dependent variable. The dependent variable is the passive variable, or the one that is affected. In the previous examples, peer acceptance of alcohol and parental supervision are the independent variables, and alcohol use and substance abuse are the dependent variables.
3. It is important that the precise nature and direction of the relationship between variables be specified in the hypothesis. Students sometimes are tempted to state hypotheses like this: “Parental supervision will have an effect on teenage alcohol use.” However, although this statement says that there is a relationship, it doesn't say what the nature or direction of the relationship is. A proper hypothesis, as above, would state how changes in one variable will be associated with particular changes in the other: “As parental supervision decreases, teenage alcohol use increases.”
4. Hypotheses should be stated in such a way that they can be verified or refuted. If this is not the case, then they are not hypotheses. Hypotheses, after all, are statements about which we can gather empirical evidence to determine whether they are correct or false. A common pitfall is to make statements that involve judgments or values rather than issues of empirical observation. For example, we might hypothesize that investigations should be increased to reduce the incidence of welfare fraud. On the surface, this statement might appear to be a hypothesis, because it relates to investigations and welfare fraud in a negative direction. As stated, however, it is not a testable hypothesis. The problem is the evaluative “should be.” What should or should not be social policy has no place in hypotheses. However, the statement can be modified so that it qualifies as a testable hypothesis: “Increased levels of investigation tend to reduce the incidence of welfare fraud.” The hypothesis now makes an empirical assertion that can be checked against fact.
5. All the concepts and comparisons in hypotheses must be clearly stated. For example, consider the following hypothesis: “Southern Baptists have superior moral standards.” The concept of “moral standards” is so abstract and vague that it is impossible to know what it means. This would have to be clearly specified in terms of what is considered to be a moral standard. In addition, to say that someone's standards are superior requires a referent for comparison: superior to whom or what? It could mean higher than some other religious group, or it could mean higher than some chosen, absolute standard.
Developing hypotheses from theories is a creative process that depends, in part, on the insight of the investigator. Because hypotheses link theories to particular, concrete settings, the researcher's insight often is the trigger for making such connections. In addition, researchers, at times, combine two or more theories to develop hypotheses that neither theory alone is capable of generating.
Concepts and Operational Definitions among Minority Populations
When conducting research on minority populations, considerable opportunity for bias exists if concepts and operational definitions are not carefully developed. This has been a chronic problem with research on crime. For example, many people believe that nonwhites commit crimes at a higher rate than we would expect, given their numbers in the population. Although this is partly true, it greatly oversimplifies a complex reality, and it reflects how crime is typically operationalized. Official crime statistics from the Federal Bureau of Investigation (Federal Bureau of Investigation, 2012) are an important source of data on crime. The FBI operationalizes some crimes as “offenses cleared by arrest” and others as “offenses known to the police.” In other words, an occurrence is not officially considered to be a crime until it is “known to the police” or “cleared by arrest.” These official crime statistics show that nonwhites commit more crimes, proportionate to their numbers in the population, than whites do. However, this is a function, in part, of how the official statistics operationalize the concept of crime. We know that nonwhites are more likely to be arrested for a given offense, suggesting that it may be arrest that is more common among nonwhites rather than the actual commission of crimes. It has been proposed that nonwhites also are more likely to commit highly visible crimes, such as armed robbery or assault, that are more frequently reported to the police and result in an arrest. Some suggest that whites, on the other hand, commit more “hidden” crimes, such as embezzlement or fraud, that are less likely to come to the attention of the police. Research suggests that there may be no class difference in the amount of hidden crimes that are committed (Elliott & Huizinga, 1983). In addition, there are other ways to operationalize crime, such as through victimization studies (asking people if they have been a victim of a crime) and self-reports (having people anonymously report their own involvement in crime). Studies based on these operational definitions tend to show much smaller differences between white and nonwhite crime rates.
Another area in which poorly constructed operational definitions have produced misleading conclusions is that of intimate partner violence (Lockhart, 1991). Most studies have found rates of intimate partner violence to be considerably higher among African Americans than among whites. Typically, these studies have used one of the following as an operational definition for the occurrence of abusive violence: a homicide involving a domestic killing, a battered woman seeking care in an emergency room or social service setting, a wife-abuse claim handled by a domestic court, or a domestic dispute call to a police department. It is well known, however, that African Americans are overrepresented among people who come to the attention of police, emergency room personnel, or social service workers. Because they generally are overrepresented among these populations, they will appear to have higher rates of abuse than whites will when abuse is operationalized in this fashion. These problems can be reduced by selecting a sample of people from a community and having them answer questions about the amount of conflict and violence that occurs in their own families. This avoids the biased effect of looking only at certain locales. The National Family Violence Resurvey, for example, employed a sampling strategy that selected about 6,000 cases representing all racial and ethnic groups (Straus & Gelles 1988).
The Committee on the Status of Women in Sociology (1986) has indicated another area in which operational definitions have led to misleading results: studies of work and social contribution. Often, work is operationalized in terms of paid employment, but this excludes many other types of work from consideration, such as community service or home-based work. With this kind of operational definition, if an employee of a carpet-cleaning firm shampoos the carpets in a home for a fee, that counts as work, but if a woman does the same activity on her own time in her own home, that is not classified as work. Such an operationalization of work tends to underestimate the extent of productive activity engaged in by women, because women are less likely than men to be paid for their social contributions.
So in developing operational definitions, care must be taken to assess whether these definitions might lead to a distorted view of minorities. In some cases, this calls for careful consideration of what a concept is intended to mean. For example, is the focus of the research on paid employment, or is it on social contribution? In other cases, it calls for careful assessment of whether a definition will lead to an inaccurate, over- or underrepresentation of minorities.
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2.4 Perspectives on Science
2.4 PERSPECTIVES ON SCIENCE
Up to this point in these first two chapters, we have presented science as if it is a coherent, unified activity about which all scientists are in agreement. It isn't. Or, more accurately, we should say that some people believe it is a coherent and unified activity, whereas others are critical of that claim. Scientists vigorously debate a number of issues concerning the best ways to engage in scientific work. One such debate is whether science should be deductive or inductive in nature.
We mentioned earlier that theories often are deductive systems. This means that hypotheses can be logically derived from the propositions that make up a theory. So deductive reasoning involves deducing or inferring a conclusion from some premises or propositions. If the propositions—or the theory—are correct, then hypotheses logically derived from them also will be correct. In Figure 2.1, deduction involves moving from the level of theory to that of hypotheses or an intervention plan. Deductive reasoning is central to the scientific process.
Inductive reasoning, however, enables us to assess the validity of the hypotheses and the theory. Inductive reasoning involves inferring something about a whole group or class of objects from our knowledge of one or a few members of that group or class. We test one or a few hypotheses derived from a theory, and then we infer something about the validity of that theory as a whole. Thus, inductive reasoning carries us from the observations or interventions in Figure 2.1 to some assessment regarding the validity of the theory. The logic of scientific analysis involves an interplay between deduction, or deriving testable hypotheses, and induction, or assessing theories based on tests of hypotheses derived from the theories.
At times, inductive research is conducted without the benefit of previous deductive reasoning. This occurs in descriptive or exploratory research, where no theory exists from which to deduce hypotheses. In the absence of theory, we begin to make observations and then develop some theoretical propositions that would be plausible given those observations. For example, practitioners may observe that clients with problem pregnancies tend to come from families with low socioeconomic status. Based on the assumption that the parent-child bond is weaker in low socioeconomic families and, therefore, that such parents have less control over their children, the practitioners could inductively conclude that a weak parent-child bond leads to an increased risk of unwanted pregnancy. In other words, the observations are used to infer a proposition regarding the causes of unwanted pregnancies. In fact, as we will explore in more detail in Chapter 9, some researchers claim that such inductive approaches can be superior to deductive approaches, because the former can involve fewer hidden assumptions or preconceived notions on the part of the scientist. Some of these inductive approaches permit the data to shape the theory rather than having a preconceived theory impose meaning on the data. Inductive research of this sort can serve as a foundation for building a theory, and that theory, in turn, can serve as a source of testable hypotheses through deductive reasoning. Thus, induction and deduction are key links in the chain of scientific reasoning, and they parallel the reasoning process that is found in practice intervention.
Research in Practice 2.2 describes research projects that highlight many of the issues discussed in the previous two sections regarding the use of theories and hypotheses in research and the importance of inductive and deductive reasoning.
Beyond deciding whether to use deductive or inductive approaches, scientists also need to decide what type of explanations will be contained in the theory. Earlier in this chapter, we defined theories as involving explanations of some phenomena. An explanation is one way of gaining knowledge of something; it tells why something happens or specifies the conditions under which something occurs. Theories can focus on two different types of explanations (Miller, 1987; Nagel, 1961).
Nomothetic Explanations. Nomothetic explanations focus on a class of events and attempt to specify the conditions that seem common to all those events. We will use the social control theory of deviant behavior as an illustration. Social control theory argues, in part, that delinquent behaviors such as shoplifting are produced by weak attachments to parents. A nomothetic explanation, then, might attempt to prove that all juveniles who shoplift have weak attachments to their parents. The focus of the explanation is on understanding the entire category of youth who shoplift. These explanations do not focus on understanding all the causes of a phenomenon. In fact, control theory would recognize that a complex behavior such as shoplifting probably has many causes other than weak social bonds, and that other theories would be necessary to locate and identify those factors. For nomothetic explanations, knowledge results from an understanding of a particular cause in relation to a class of events.
Nomothetic explanations attempt to develop knowledge that can be generalized beyond a single study or set of circumstances. In a sense, a nomothetic explanation is designed to produce the conclusion that weak attachment to parents in all cases increases the likelihood that shoplifting will result. This doesn't mean that every person who experiences weak attachment will shoplift; however, it does mean that those people have a higher probability of engaging in shoplifting. To put it another way, a randomly selected group of teens with weak parental attachments will have a higher rate of shoplifting than a randomly selected group with strong attachments. The explanation or knowledge that is gained is probabilistic in nature: It tells us something about the probability of events occurring. The knowledge gained is about the aggregate, or the whole group, rather than about specific individuals in the group.
RESEARCH IN PRACTICE 2.2 Practice Effectiveness: Social Theory and Burnout among Social Workers
A social worker: I began to despise everyone and could not conceal my contempt.
A psychiatric nurse: Sometimes you can't help but feel “Damn it, they want to be there, and they're fuckers, so let them stay there.” You really put them down …
A social worker: I find myself caring less and possessing an extremely negative attitude.
[Maslach, 1979, p. 217]
These are hardly the caring, empathic reactions one would expect from human service workers, yet negative attitudes toward clients are expressed at some point by many social workers, nurses, psychologists, and others. The problem of burnout is of considerable concern to human service professionals, because it can impair their ability to deal with client problems. Burnout refers to a service worker's emotional disengagement from clients, dissatisfaction with his or her job, feelings of worthlessness, and physical and interpersonal problems (Arches, 1991). Commonsense approaches often focus on the personal abilities of human service workers to explain why they suffer burnout: They lack sufficient emotional strength or distance from clients, or they overidentify or overempathize with their clients. Rather than relying on such intuition, scientific researchers turn to theories for direction in identifying variables that might play a part.
When social work researcher W. David Harrison (1980) approached these issues, he turned to role theory, which views human behavior as resulting from conformity to expectations that are associated with particular roles. One of the tenets of role theory is that role expectations should be clear, unambiguous, and achievable. Furthermore, the various expectations associated with a role should not conflict with one another. Previous research suggested that situations in which role expectations are conflicting, incompatible, or unclear lead to personal stress and dissatisfaction. Role theory enabled Harrison to identify two different kinds of role difficulty: Role conflict refers to a situation in which conflicting and incompatible demands are placed on a person in a role, and role ambiguity refers to a lack of clarity in terms of what is expected of a person in a particular role. Harrison's research on child protective service workers showed that role difficulties, especially role ambiguity, produced job dissatisfaction and burnout among these social workers.
In contrast, Joan Arches (1991) turned to theories of organizational structure and change, reasoning that recent developments in social service organizations might have an impact on burnout. These theories suggest that increasing bureaucratization and centralization in organizations can reduce workers' feelings of autonomy, and, in turn, this can contribute to the job dissatisfaction that often is a part of burnout. Arches's research then provided evidence that this was the case, offering further verification for those organizational theories.
Burnout continues to be a topic of interest to social scientists and human service practitioners throughout the world. Peter Janssen and his colleagues at Utrecht University in the Netherlands reviewed the extensive body of research on burnout that has accumulated over the past few decades and designed a study of Dutch nurses (Janssen, Schaufeli, & Houkes, 1999). Their research examined work-related and individual determinants of burnout by using conservation of resources theory as a framework. This theory focuses on the impact of work-related demands and resources on different dimensions of burnout. They found that a scarcity of resources, in the form of excess job demands and work overload, increased emotional exhaustion (one dimension of burnout) but not depersonalization (another dimension of burnout).
Thus, the theoretical considerations of role theory, organizational theory, and conservation of resources theory do not point toward excessive empathy or emotional weakness as the culprits in burnout among human service workers. Rather, the organizational and role structures that surround them are important. These investigations illustrate the importance of grounding research in theory, because it is theory that suggests which variables might be important and how they might relate to one another. Theory also shows how hypotheses can be developed through deductive reasoning. Once confirmed, the hypotheses of these researchers provide support, through inductive reasoning, for the interpretations of these theories in regard to the causes of burnout in the human services. Based on this slow, methodical accumulation of knowledge, we should eventually establish a solid foundation from which to develop programs to alleviate the problem of burnout among human service workers.
Once you understand what nomothetic explanations consist of, you can begin to see their weaknesses. One weakness is that you cannot say for sure what will happen in any particular case or to any specific person. You cannot say whether Joe Smith, who has experienced weak parental attachment, will become a shoplifter. A second weakness is that you cannot make any claims of knowing the totality of causes that produced some event or phenomenon. So the knowledge, though valuable, is incomplete. There may be, for example, some key factors that must occur in combination with weak parental attachments to produce shoplifting.
Idiographic Explanations. Idiographic explanations focus on a single person, event, or situation and attempt to specify all the conditions that helped produce it. An idiographic explanation of shoplifting, for example, might focus on one juvenile who shoplifts and attempt to understand the multiple factors that contributed to bringing about the shoplifting behavior in that person. The focus of the explanation is on a particular, unique individual or situation. These explanations do not attempt to understand all instances of shoplifting; in fact, they recognize that other shoplifters may be propelled by a different combination of causes. For idiographic explanations, knowledge results from a thorough understanding of the particular.
Idiographic explanations see causality in terms of a complex pattern of factors that combine over a period of time to produce an outcome. To truly understand something, researchers need to comprehend that whole patterned sequence, the whole complex context in which something occurs. When the nomothetic approach isolates particular variables for study, knowledge is incomplete for two reasons: First, some factors or variables have not been included in the investigation. Second, the isolating approach cannot see how the combination of, or the interaction among, the various elements plays a critical role in producing an outcome. It may be, for example, that weak parental bonds produce shoplifting only when they combine or interact with a host of other factors. In fact, it may be that the particular combination of factors that produces shoplifting in one person is unique and does not occur in other cases. It also may be that each distinct case of shoplifting is produced by a unique combination of factors. In other words, the explanation or knowledge that we gain is idiosyncratic.
Nomothetic explanations are probabilistic in nature, but idiographic explanations are deterministic in that the event being studied, such as shoplifting, actually did occur in the case being studied. In addition, the idiographic explanation identifies the causes that determined that outcome.
As with nomothetic explanations, idiographic explanations have weaknesses. One major fault is their limited generalizability. With such explanations, it is difficult to determine whether knowledge can be extended beyond the particular case or situation being studied.
Combining Explanations. Because each type of explanation has its strengths and its limitations, you might have guessed that our conclusion is going to be that neither type is inherently better than the other. As we alluded to in the beginning of this chapter with the excerpt from Through the Looking Glass, numerous routes to gaining knowledge about the world exist, and each type of explanation provides us with a valuable, though incomplete, route. In later chapters, we will see that some research methodologies, such as surveys and experiments, tend to be used to develop nomothetic explanations and that other methodologies, such as field research, in-depth interviewing, and historical comparative research, often are used to develop idiographic explanations. The point is to understand the logic of each type of explanation and be aware that conclusions supported by research using both types of explanations are more complete than if the research only uses one type.
Over the centuries, philosophers and scientists have debated the nature of reality and how people can know that reality (Couvalis, 1997; Miller, 1987). These have been controversial issues for scientists who study the physical world, but they are even more contentious among social scientists, who study human beings and their psychological and social reality. Part of the reason for this heightened contention is the belief that human beings are different from the natural world of physical objects and events. People emote, remember, speculate, love, and hate—they think about what is happening to them and have feelings about it. People refuse to behave the way a scientist hypothesizes that they might. People do the unexpected or the unpredictable. Atoms, molecules, and chemical compounds do not have these elusive properties, and this is one of the reasons why natural scientists often can make certain nonprobabilistic predictions about what will happen: Under a certain set of conditions, all water molecules, for example, will freeze when the temperature drops below zero degrees centigrade. Thus far, however, social scientists have been unable to make such statements about social reality.
Another reason that the issue of how we know the world has been controversial among social scientists is that the scientists who study social reality are people themselves, with personal values, goals, desires, and reactions to what they observe. These personal matters may interfere with their ability to comprehend the world accurately. Going a step further, the scientific endeavor is itself a social process, part of the social world that social scientists attempt to understand. After all, scientific work can advance one's career, help one make a living, and move one up (or down) in the stratification system. In doing their scientific work, scientists may be influenced by a variety of social and psychological factors that routinely influence other human beings in their social endeavors.
What does all this mean? For one thing, science is a much more complicated—and, in many respects, a much messier—enterprise than many people recognize. For another, a number of competing perspectives exist concerning the issues of how society works and what implications this has for how the scientific endeavor works. In fact, historian Thomas Kuhn (1970), in a groundbreaking study of scientific work over many centuries, concluded that scientific activity is shaped by paradigms , which are general ways of thinking about how the world works and how we gain knowledge about the world. Paradigms are fundamental orientations, perspectives, or world views that often are not questioned or subjected to empirical tests. People may not even be aware that their thinking about the world is shaped by an orientation or world view. In his study of the history of science, Kuhn discovered that, although paradigms change over time, scientific research at any given moment was shaped by the paradigm that was dominant at the time. Research that fell outside that paradigm was considered to be inappropriate, irrelevant, oddball, or just plain wrong. In a sense, the world of paradigms falls outside the scientific realm in that issues are not accepted or rejected on the basis of empirical evidence; instead, some things are considered true—and others false—because it is obvious that that is how things work. Evidence supporting the paradigm will be accepted and competing evidence either ignored or rejected.
At the risk of oversimplification, we can classify the paradigms in the social sciences into two general categories: positivist approaches, and a number of different approaches that we will call nonpositivist approaches (Alford, 1998; Benton, 1977; Smart, 1976). Keep in mind that these viewpoints are not necessarily mutually exclusive; people may adopt ideas from more than one of them at the same time. In addition, one could agree with some parts of a paradigm but disagree with other parts of the same paradigm. We address this issue early in the book because it is a debate that arises repeatedly as we discuss different research methodologies.
Positivist Approaches. Positivism (sometimes also called logical empiricism ) argues that the world exists independently of people's perceptions of it and that science uses objective techniques to discover what exists in the world (Blaikie, 1993; Durkheim, 1938; Halfpenny, 1982). Astronomers, for example, use telescopes to discover stars and galaxies, which exist regardless of whether we are aware of them. So, too, scientists can study human beings in terms of observable behaviors that can be recorded using objective techniques. Recording people's gender, age, height, weight, or socioeconomic position are legitimate and objective measurement techniques—the equivalent of the physicist measuring the temperature, volume, or mass of some liquid or solid. For the positivist, quantifying these measurements—for example, assessing the average age of a group or looking at the percentage of a group that is male—is merely a precise way of describing and summarizing an objective reality. Such measurement provides a solid, objective foundation for understanding human social behavior. Limiting study to observable behaviors and using objective techniques, positivists argue, is most likely to produce systematic and repeatable research results that are open to refutation by other scientists.
The natural and social world is governed by natural and social rules and regularities that give it pattern, order, and predictability. The goal of research in the natural and social sciences is to discover laws about how the world works and to express those discovered regularities in the deductive theories and propositions that are discussed in this chapter. As scientists conduct research, they move progressively closer to the truth, which involves uncovering the laws and patterns that underlie objective reality. So, at least in its ideal form, science is an objective search for the truth in which human values are a hindrance whose impact should be limited if not eliminated. Values can only interfere with the objective search for truth. For example, Emile Durkheim, an early sociologist, was a strong believer that sociologists could study the social world in much the same way that physical scientists could study the physical world. Durkheim believed that there were “social facts” that social scientists could observe and then use those observations to discover the social laws that govern the social world. He believed that once we discover these social laws, we will be able to both explain and predict human social behavior.
Of the various paradigms that we will review, positivism clearly is the most widely held view among natural scientists and, to a lesser degree, among social scientists. Among social scientists, those who adopt the positivist stance often tend to use certain kinds of research methodologies. For example, they tend toward quantitative research , which involves measurement of phenomena using numbers and counts. They also tend to use deductive and nomothetic explanations, experimental designs, and survey research. It is important not to oversimplify the link between a paradigm and the preferred research methodology, however, because positivists at times use qualitative research , which involves data in the form of words, pictures, descriptions, or narratives rather than numbers and counts. They also use inductive or idiographic explanations and field observations when these are appropriate to a research question.
Despite the popularity and dominance of the positivist paradigm, it has been subject to considerable criticism over the years. Some of this criticism arises out of empirical studies by social scientists of exactly how science operates (Galison & Stump, 1996; Lynch & Bogen 1997; Shapm 1995). What many of these researchers find is that what scientists actually do looks quite different from what the positivist paradigm says science should look like. This has led some critics to conclude that the positivist model is an idealized conception of science rather than an accurate description of it. Based on these and other concerns, alternative paradigms have emerged.
Nonpositivist Approaches. One prominent nonpositivist approach to science is what is called the interpretive approach. Interpretive approaches (also called interactionist or verstehen approaches) posit that social reality has a subjective component that arises out of the creation and exchange of social meanings during the process of social interaction. Social science must have ways to understand this subjective reality (Holstein & Gubrium, 1994; Smith, 1989; Wilson, 1970). Interpretivists argue that the objective, quantitative approaches of positivism miss this very important part of the human experience: the subjective and personal meanings that people attach to themselves and what they do. Reality is seen as something emergent and in constant flux that arises out of the creation and exchange of social meanings during the process of social interaction. Rather than seeing reality as something apart from human perceptions, interpretive social science sees reality—or, at least, social reality—as created out of human perception and the interpretation of meaning. These kinds of ideas led many nineteenth-century and early twentieth-century theorists, such as Wilhelm Dilthey, Ernst Troeltsch, and Max Weber, to conclude that social life cannot be understood by the same method that is used to study the natural world (Barnes, 1948).
Weber, for example, argued that we need to look not only at what people do but also at what they think and feel about what is happening to them (Weber, 1957, orig. pub. 1925). This “meaning” or “feeling” or “interpretive” dimension cannot be adequately captured through objective, quantitative measurement techniques. Researchers need to gain what Weber called verstehen , or a subjective understanding. They need to view and experience the situation from the perspective of the people themselves, “to walk a mile in their shoes.” They need to talk to the people at length and immerse themselves in their lives so they can experience the highs and lows, the joys and sorrows, the triumphs and tragedies as seen from the perspective of the people being studied. Researchers need to see how individuals experience and give meaning to what is happening to them. Interpretive research methods provide an understanding through empathy or fellow feeling, whereas positivist methods provide understanding through abstract explanation. Yet, the important point is that both methods provide an understanding of the world, and both are a part of the scientific enterprise.
Qualitative research methods attempt to gain access to that personal, subjective experience; for interpretivists, quantitative research by its very nature misses this important dimension of social reality. Positivists, for their part, do not necessarily deny the existence or importance of subjective experiences, but they do question whether the subjective interpretations of the verstehen method have scientific validity.
According to the interpretivist approach, regularity and pattern in social life does not result from objective social laws that exist apart from the human experience and are discovered by scientists. Instead, pattern and predictability arise out of mutually created systems of meaning that emerge from social interaction (Rabinow & Sullivan, 1987; Roscoe, 1995). Regularity and pattern are created and maintained by people; they are not imposed by external force. Proponents of interpretive approaches argue that qualitative research methods enable the researcher to approximate verstehen, an understanding of the subjective experiences of people. Of course, actual access to such experience is impossible; thoughts and feelings, by their very nature, are private. Even when someone says how he or she feels, the speaker has objectified that subjective experience into words and, thus, changed it. Researchers, however, can gain some insight into subjective experiences by immersing themselves in the lives and daily experiences of the people they study. By experiencing the same culture, the same values, the same hopes and fears, researchers are in a better position to take on the point of view of these people. Despite its focus on subjective experiences, however, such research is still empirical in the sense that it is grounded in observation. Qualitative researchers consider their qualitative observations and conclusions to be no less systematic or scientific than the more positivistic quantitative research techniques. Although positivists would argue that subjective meaning is difficult to quantify and study objectively, interpretive researchers would argue that it is, nonetheless, a key part of human social reality.
Another important difference between positivists and interpretivists has to do with the role of science: Positivists argue that scientists merely discover what exists in the world, but some interpretivists claim that scientists actually help create social reality through their scientific work (Knorr, 1981). As researchers make observations, gather data, and draw conclusions, their activities contribute to the construction of patterns of meaning. Scientific principles and laws about social behavior become another aspect of reality that can influence people's behavior. Even something as simple as computing the average age of a group creates a new reality: Instead of recognizing that some people in the group are 22 years old, others 34 years old, and still others 43 years old, we now say that the “average age of the group is 36.7 years.” This summary statement gives the impression—and creates the reality—that the group members share something in common in terms of age and that we know something very precise about their ages. That sense of commonality or precision, however, comes from the numbers created by the scientist, not from reality. In addition, though the average appears to be very precise, it actually is less precise than listing all the ages of the group members.
The interpretive approach focuses more on inductive and idiographic theory construction than on deductive and nomothetic approaches, considering the theories to emerge out of people's experiences rather than viewing them as abstractions developed by scientists. Understanding and truth come from an empathic grasp of the social meanings of a setting rather than from statistical analysis and abstract generalization to large numbers of cases. Once again, however, the link between paradigms and research approaches is not mutually exclusive. At times, interpretive social scientists do deductive and nomothetic theory construction, and they have even been known to use quantitative methods when appropriate.
Other nonpositivist characterizations of science exist as well. For example, critical and feminist approaches to research argue that science is inevitably linked to inequitable distributions of power and resources. These approaches posit that groups can and do use science to enhance their position in society, and that patterns of dominance and subordination may exist between researchers and those on whom they conduct research. Other nonpositivist critiques will be addressed in later chapters. At this point, we simply want to raise the controversy regarding positivist and nonpositivist views of science to stress that science and scientific research are more complicated than you might have originally thought. The goal for the student should not be to attempt to resolve these disputes or choose among the paradigms. Instead, the goal should be to understand the dimensions of the debate, recognize how the paradigms are similar to or different from one another, and comprehend the implications of each paradigm for the research process. In addition, the paradigms are not completely exclusionary of one another. All the paradigms agree with much of what will be covered in this book. For example, all the paradigms base their search for knowledge on systematic observation, and all agree that scientific work should be open and public. Of course, they may not always agree on what makes observations systematic, but there is not total agreement within each paradigm about that issue, either.
Another reason why the student need not adopt a preferred paradigm is that many researchers do not choose a particular perspective to follow exclusively (Alford, 1998). Many researchers find that each of the approaches offers some insights into social life and the scientific process that the others ignore. They move back and forth among the paradigms, using the best that each has to offer in understanding a particular aspect of human social life.
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2.5 Cause-and-Effect Relationships
2.5 CAUSE-AND-EFFECT RELATIONSHIPS
One of the more important yet difficult tasks in scientific research is the search for causes—that is, the reasons why particular forms of behavior occur. Why do child abuse and spousal abuse occur? Why do some juveniles become delinquent, whereas others present no behavior problems? Why do some people exhibit symptoms of mental illness and others appear to be psychologically stable?
Discovering causal relationships is a difficult task, because causality cannot be directly observed. Rather, it must be inferred from the observation of other factors. Because of this, the philosopher John Kemeny has labeled causality “the mysterious force” (1959, p. 49). We cannot see it, feel it, or hear it, but we often assume that it is there—and many scientists search for causality with hopefulness and tenacity. This search is a controversial task, because some philosophers, notably Bertrand Russell (1953), have argued for excluding the notion of causality from scientific investigation altogether. These people opt for restricting ourselves to description and analysis of “associations” without the implication that a “mysterious force” called causality lurks behind the scenes and orchestrates the actions of people and things. This controversy is longstanding; we do not presume to resolve it here. Nonetheless, it is important to understand the criteria that need to be satisfied if one wants to infer that one event caused another.
By causality , we mean that some independent variable (X) is the factor, or one of several factors, whose change produces variation in a dependent variable (Y). As noted, causality can only be inferred. We can observe the relationships among things in the world, and from that we can infer or deduce that changes in one factor are causing changes in another. However, it is always an inference. To infer the existence of a causal relationship, one must demonstrate the following:
1. A statistical association between the independent and dependent variables must exist.
2. The independent variable must occur prior in time to the dependent variable.
3. The relationship between independent and dependent variables must not be spurious; that is, the relationship must not disappear when the effects of other variables are taken into account.
TABLE 2.1 Effectiveness of Reading Media Reports on Smoking Cessation
|
|
|
Person Reads Report |
|
|
|
|
Yes |
No |
|
Person Quits |
Yes |
200 (50%) |
135 (27%) |
|
Smoking |
No |
200 (50%) |
365 (73%) |
|
|
Totals |
400 (100%) |
500 (100%) |
We will consider each requirement of causal inference in the context of an issue that is much in the news today—the campaign to reduce cigarette smoking. Over the years, there have been reports in the media about the negative impact of cigarette smoking on people's health. Some argue that making these reports public as part of a health campaign can motivate people to quit smoking. Table 2.1 presents hypothetical data that seems to show a link between reading such reports about smoking and actually quitting smoking: 50 percent of those who read the reports quit smoking, compared to only 27 percent of those who do not read the reports. Finding such a statistical relationship satisfies the first criterion for establishing a causal relationship.
The second requirement, that the independent variable occurs prior in time to the dependent, often is not as easy to establish. A major factor in this is the nature of the study. Some research techniques, such as the experiment or participant observation, are inherently longitudinal, which means that the researcher is in a position to trace the development of behavior as it unfolds over time. In these cases, establishing the time sequence of events generally is simple. Questions of temporal order are more difficult to resolve when dealing with cross-sectional data, such as surveys, in which measurements of the independent and dependent variables occur at the same time. This is especially true if the question of temporal sequence is not addressed until after the data have been collected. It is sometimes possible to sort out the time sequence of variables in survey data by asking additional questions. If the researcher does not gather the necessary information at the time of the survey, however, then establishing the appropriate time order of the variables may be impossible—hence the emphasis on the importance of carefully considering issues of data analysis when originally developing a research design.
The data in our illustration may suffer from this problem. One interpretation is that reading reports is the independent variable that influences whether people quit smoking, the dependent variable. For this interpretation to be correct, the reports would have to have been publicized before the people quit smoking. If the respondents were not asked when they quit smoking, then it would be impossible to say whether they quit smoking before or after reading the reports. Obviously, if they quit smoking before reading the reports, then such health campaigns could not have caused their change in behavior. In our example, without knowing the temporal sequence, one could argue logically for either factor being the cause of the other. Obviously the health campaign could encourage people to quit smoking if they become frightened by learning the dire consequences of their habit. However, those who quit smoking also could be happy with and proud of their victory and might enjoy reading reports on what could have happened to them had they not quit smoking. In this second scenario, quitting smoking would be the independent variable that increases the likelihood that people will read reports about the health threat of smoking, the dependent variable.
The final criterion necessary for inferring causality is that the relationship between the independent and dependent variables not be spurious, or disappear when the effects of other variables are considered. The logic of causal and spurious relationships is compared in Figure 2.2 . This often is the most difficult of the three criteria to satisfy. In fact, one is never totally sure that some other variable—one you have not even considered—might not confound an apparent causal relationship. All that can be accomplished is to rule out as many extraneous variables as we can to the point where it is unlikely a variable exists that could render a given relationship spurious or noncausal.
FIGURE 2.2 Causal and Spurious Relationships
Considerable effort is expended during the design stage of research to control as many potentially troublesome extraneous variables as possible. Experiments, for example, are particularly good for avoiding spurious relationships because of the high degree of control that the experimental situation affords the researcher. Surveys, on the other hand, provide far less control, such that several variables capable of producing spuriousness typically have to be considered during data analysis. Several statistical techniques exist to control extraneous variables when the data are analyzed.
Returning to our example of smoking cessation, suppose we had solved the time sequence problem and, thus, had satisfied the first two requirements for establishing a causal relationship. We would now begin to consider variables that might render the relationship spurious. One variable that might do this is the level of education of the people studied. (The logic of this is outlined in Figure 2.3 .) Considerable research links education with health behavior. Generally, people with higher levels of education engage in more health-promoting activities, such as quitting smoking or getting regular exercise. How do we determine whether the link between report reading and smoking cessation is spurious? We introduce the level of education as a control variable, which is illustrated with our hypothetical data in Table 2.2 , in which we have divided the respondents in Table 2.1 into those with at least a high school education and those with less than a high school education. First, we can see by examining the row totals in each table that education is related to health behavior: 60 percent of the better-educated group have quit smoking, compared to only 19 percent of the less-educated group. However, we are really interested in what happens to the link between report reading and smoking cessation, and Table 2.2 shows that the relationship largely disappears: Within each educational group, the same percentage of people quit smoking among those who read the report as among those who did not. So educational level, not whether one has read the report, influences a person's likelihood of quitting smoking. Furthermore, in our hypothetical example, educational level also influences whether one reads the report: 300 out of 400, or 75 percent, of those with a high school education read the report, compared with only 100 of 500, or 20 percent, of those with less than a high school education. So in our example, the link between reading the report and quitting smoking is spurious; it occurs only because each of those two variables is affected by the same third variable.
FIGURE 2.3 Causal and Spurious Relationships between Reading a Report and Quitting Smoking
If we had found the link between report reading and smoking cessation to be nonspurious when we controlled for education, could we conclude that the relationship was causal? The answer is no. We could not come to that conclusion—at least not yet. All that we would know was that the relationship remained when one alternative explanation was ruled out. Any other variables that could render the relationship spurious also would have to be investigated—and the relationship still hold—before we could argue with any confidence that it was, in fact, causal. (More intricacies of this sort of analysis are addressed in Chapter 15 .)
TABLE 2.2 Effectiveness of Reading Media Reports on Smoking Cessation, Controlling for Education
We said at the outset that establishing the existence of causal relationships is difficult. Statistical relationships are easy to find but, on further investigation, all too frequently turn out to be spurious. The appropriate time sequence also can be problematic, especially with survey data. All in all, establishing causal relationships is a difficult but an important and challenging task.
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2.6 Review and Critical Thinking
2.6 REVIEW AND CRITICAL THINKING
Science is one source of knowledge, along with tradition, experience, common sense, and journalism; but it is a superior source of objective and accurate knowledge about the world.
The five key characteristics of science are that it is empirical, systematic, provisional, objective, and searches for the causes of events. These crucial characteristics also are central features of scientifically based practice.
Theories are sets of interrelated, abstract propositions that explain phenomena. Theories perform three major functions: They provide explanations, they guide research and practice, and they integrate observations from research.
Concepts are mental constructs that symbolize ideas, persons, things, or events, and form the basis for propositions and theories.
Concepts are given both nominal definitions, which explain their meaning, and operational definitions, which indicate how they are measured. Care must be taken in developing operational definitions in research on minorities to ensure that such definitions do not lead to a distorted view of these populations.
Hypotheses are statements that predict relationships between two or more variables and are tested through research.
Theories are developed and elaborated by going back and forth between the abstract, conceptual level and the concrete, empirical level, using either deductive reasoning or inductive reasoning.
Theories also differ in the types of explanations they seek, some nomothetic and others idiographic.
Two paradigms, or ways of understanding how we know the world, are predominant in the social sciences: positivism, and nonpositivism. Each tends to be associated with particular research methodologies. The goal for the student in this debate should be to understand the dimensions of the debate, to recognize how the paradigms are similar to or different from one another, and to comprehend the implications of each paradigm for the research process.
Causality means that some independent variable produces variation in a dependent variable.
To demonstrate a causal relationship, one must establish a statistical association between two variables, show that the independent variable occurs first temporally, and demonstrate that the relationship is not spurious.
This chapter covers some of the building blocks of the scientific method: theories, propositions, hypotheses, concepts, variables, and so on. In using these building blocks, scientists try to be very careful when describing and analyzing the world in order to avoid misunderstanding. You can utilize some of these same building blocks in trying to critically analyze information for policy or practice purposes or for your everyday life.
Consider the following when reading or hearing something.
1. What sources of knowledge serve as the basis for a claim or assertion? What are the strengths or weaknesses of those sources of knowledge?
2. Specify any theories, concepts, or hypotheses that are contained in the information. Keep in mind that, in practice, policy, or everyday realms, these elements may be implicit in what people say and you may have to figure out what they are.
3. Is there any evidence that theories have been verified? How much verification?
4. Are there claims to objectivity (positivism)? Is there any indication that subjectivity, values, or interests play a part in shaping the knowledge?
5. Are there any causal statements being made? Does the evidence presented satisfy the criteria that warrant a causal inference?
One of the central themes of this book is how research can inform practice. For Internet resources on applying research to human service practice, we suggest you use a search engine and search for such phrases as “children's mental health” or “evaluation outcomes.” A site we found from such a search was the home page of the Office of Alcoholism and Substance Abuse Services (OASAS) of New York state (http://www.oasas.ny.gov). In this chapter, we discussed the development of hypotheses and introduced the ideas of operational definition, dependent variable, and independent variable. As a way of applying these concepts to actual research, select several of the research studies reported at the OASAS site. For each study you find, identify one or more hypotheses that the study addressed. Determine if the review identifies how the dependent and independent variables were operationally defined. Finally, if the review describes how the independent and dependent variables are measured, state whether success in the program would be expected to show an inverse or direct relationship between the dependent and independent variables.
We covered some fairly core and controversial issues in social research in this chapter, especially in relation to the positivist and nonpositivist paradigms. Suppose that you work for a research organization and your boss wants you to create an online discussion of these paradigms. You need to locate people, organizations, or resources on the web that espouse one position or another on these issues. Use a search engine and enter one or more of the terms used to identify the paradigms or that have some relationship to the paradigms: “positivism,” “logical positivism,” “subjectivism,” “relativism,” “postmodernism,” “feminism,” and so on. From your search, discuss how many different social sciences address issues having to do with these paradigms. Do some social sciences address different issues than other social sciences? Do the same kind of analysis for the natural sciences. Also address whether fields that are nonscientific, such as the humanities, address these issues. Can you put together the online discussion your boss has requested?
Bengtson, V. L., Acock, A. C., Allen, K. R., Dilworth-Anderson, P., & Klein, D. M. (2005) Sourcebook of Family Theory and Research. Thousand Oaks, Calif.: Sage. This reference work on theory and methods for family scholars demonstrates how the development of theory is crucial to the future of family research. The work focuses on the process of theory building and designing research.
Glaser, B.G., & Strauss, A. L. (1967). The Discovery of Grounded Theory. New York: Aldine. An excellent book about the virtues and procedures of developing theoretical propositions from data. This approach emphasizes qualitative research and induction.
Hoover, K. R., & Donovan, T. (2011). The Elements of Social Scientific Thinking. 10th ed. Belmont, Calif.: Wadsworth/Cengage Learning. A brief and readable initiation into social science thinking and research. It is intended for those who use the results of research and for those just getting into the field.
Merton, R. K. (1968). Social Theory and Social Structure. 2nd ed. New York: Free Press. A classic statement by a sociologist on the relationship between theory and research.
Shoemaker, P. J., Tankard, J. W. Jr., & Lasorsa, D. L. (2004). How to Build Social Science Theories. Thousand Oaks, Calif.: Sage. This book traces theories from their most rudimentary building blocks (terminology and definitions) through
multivariable theoretical statements, models, the role of creativity in theory building, and how theories are used and evaluated. The book includes a discussion of concepts and their theoretical and operational definitions.
Turner, J. H., ed. (1989). Theory Building in Sociology: Assessing Theoretical Accumulation. Newbury Park, Calif.: Sage. In this collection of essays, one of the foremost U.S. theoreticians in sociology addresses a key assertion of the positivist approach: Does knowledge accumulate through the deductive approach of theory building and hypothesis testing?
Van de Ven, A. H. (2007). Engaged Scholarship: A Guide for Organizational and Social Research. Oxford: Oxford University Press. The author is a leading management researcher and writes from that perspective, but the issues he addresses are relevant to human service research as well. He especially addresses the issue of whether research findings and knowledge should be useful for science, practice, and policy. He also discusses how such research should be designed, carried out, and disseminated to achieve the twin goals of rigor and relevance.
Watts, D. J. (2011). Everything Is Obvious⋆ (⋆Once You Know the Answer). New York: Crown. This is an entertaining and insightful exploration of common sense as a source of knowledge—pointing to its weaknesses and failures as a foundation for thinking, reasoning, and planning.
Class Exercises for Competency Assessment
2.1. [Critical Thinking] Many commonsense beliefs relate to child development, such as “spare the rod and spoil the child,” or the belief that age-graded schools enhance learning. Through class discussion, develop a list of such “known” principles of child development. For each such principle, decide whether it is based on traditional knowledge, experiential knowledge, or a combination of both. How might you conduct systematic observations to determine the worth of these statements as scientific knowledge?
2.2. A mental health worker assigned to a large residential facility for senior citizens receives a request from staff members to “do something” about a new resident, a 72-year-old woman. From the information provided, the woman has apparently been assigned to an eighth-floor room, but she refuses to take the elevator alone or if it is crowded. The woman becomes terrified of the enclosed space and uses the stairs unless she can ride the elevator with a staff member. The woman's husband died about six months ago, and she is now living alone for the first time.
a. [Critical Thinking] [Evidence-Based Evaluation] Consider this case from the alternative theoretical positions of behavior modification versus traditional Freudian psychology. (You may substitute some other relevant theories of human behavior with which you are familiar.) What are some major theoretical concepts from each theory that apply to this case?
b. [Research & Practice] For the concepts you identified in part (a), use the illustrative case to develop operational definitions for each concept.
2.3. [Evidence-Based Evaluation] [Research & Practice] Using each theory from Exercise 2.2, construct a possible explanation for the woman's behavior. Now try to state your explanations in terms of testable hypotheses. Can you foresee any problems in assessing causality when testing these hypotheses? Compare the hypotheses you developed with those of other students in terms of the theory used, the concepts selected, and the variables identified. How are the concepts and variables that are derived from the same theory alike? How do they differ from those derived from the other theory?
2.4. [Research & Practice] We have made the point that the same theories can be useful to both practitioners and researchers. Using the hypotheses developed in Exercise 2.3, explain how they could be used either to help the worker change the woman's behavior or to conduct a study. How might the hypotheses need to be changed to be useful in both practice and research?
2.5. [Critical Thinking] [Diversity] A clinician in a treatment program for woman batterers notices that about 75 percent of the individuals who are mandated by the court to participate in group therapy also have a history of substance abuse problems, such as arrests for drunk driving. Furthermore, a large proportion of the clients had been drinking prior to committing the assault. Can the clinician conclude that substance abuse causes woman battering? Identify what conditions would need to be met to support this contention. Prepare a diagram involving a third variable that might show that the relation between substance abuse and woman battering is spurious.
· Notebook
Chapter 2
The Logic of Social Research
Sources of Knowledge
Tradition
Experience
Common Sense
Journalism
Science
Scientific Practice
Theories in Research and Practice
What Is a Theory?
The Functions of Theories
Concepts and Hypotheses
Defining Concepts
Developing Hypotheses
Concepts and Operational Definitions among Minority
Populations
Perspectives on Science
Deduction versu
s Induction
Types of Explanations
Paradigms in
Science
Cause
-
and
-
Effect Relationships
Chapter 2
The Logic of Social Research
Sources of Knowledge
Tradition
Experience
Common Sense
Journalism
Science
Scientific Practice
Theories in Research and Practice
What Is a Theory?
The Functions of Theories
Concepts and Hypotheses
Defining Concepts
Developing Hypotheses
Concepts and Operational Definitions among Minority Populations
Perspectives on Science
Deduction versus Induction
Types of Explanations
Paradigms in Science
Cause-and-Effect Relationships
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