42 Interpreting the Results of a Factorial Experiment
Learning Objectives
- Distinguish between main effects and interactions, and recognize and give examples of each.
- Sketch and interpret bar graphs and line graphs showing the results of studies with simple factorial designs.
- Distinguish between main effects and simple effects, and recognize when an analysis of simple effects is required.
Graphing the Results of Factorial Experiments
The results of factorial experiments with two independent variables can be graphed by representing one independent variable on the x-axis and representing the other by using different colored bars or lines. (The y-axis is always reserved for the dependent variable.) Figure 9.3 shows results for two hypothetical factorial experiments. The top panel shows the results of a 2 × 2 design. Time of day (day vs. night) is represented by different locations on the x-axis, and cell phone use (no vs. yes) is represented by different-colored bars. (It would also be possible to represent cell phone use on the x-axis and time of day as different-colored bars. The choice comes down to which way seems to communicate the results most clearly.) The bottom panel of Figure 9.3 shows the results of a 4 × 2 design in which one of the variables is quantitative. This variable, psychotherapy length, is represented along the x-axis, and the other variable (psychotherapy type) is represented by differently formatted lines. This is a line graph rather than a bar graph because the variable on the x-axis is quantitative with a small number of distinct levels. Line graphs are also appropriate when representing measurements made over a time interval (also referred to as time series information) on the x-axis.
Main Effects
In factorial designs, there are three kinds of results that are of interest: main effects, interaction effects, and simple effects. A main effect is the effect of one independent variable on the dependent variable—averaging across the levels of the other independent variable. Thus there is one main effect to consider for each independent variable in the study. The top panel of Figure 9.3 shows a main effect of cell phone use because driving performance was better, on average, when participants were not using cell phones than when they were. The blue bars are, on average, higher than the red bars. It also shows a main effect of time of day because driving performance was better during the day than during the night—both when participants were using cell phones and when they were not. Main effects are independent of each other in the sense that whether or not there is a main effect of one independent variable says nothing about whether or not there is a main effect of the other. The bottom panel of Figure 9.3, for example, shows a clear main effect of psychotherapy length. The longer the psychotherapy, the better it worked.
Interactions
There is an interaction effect (or just “interaction”) when the effect of one independent variable depends on the level of another. Although this might seem complicated, you already have an intuitive understanding of interactions. As an everyday example, assume your friend asks you to go to a movie with another friend. Your response to her is, “well it depends on which movie you are going to see and who else is coming.” You really want to see the big blockbuster summer hit but have little interest in seeing the cheesy romantic comedy. In other words, there is a main effect of type of movie on your decision. If your decision to go to see either of these movies further depends on who she is bringing with her then there is an interaction. For instance, if you will go to see the cheesy romantic comedy if she brings her hot friend you want to get to know better, but you will not go to this movie if she brings anyone else, then there is an interaction. Drug interactions are another good illustration of everyday interactions. Many older men take Viagara to assist them in the bedroom, and many men take nitrates to treat angina or chest pain. So each of these drugs is beneficial on its own (there are main effects of each on older men’s well-being). But the combination of these two drugs can be lethal. In other words, there is a very important interaction between Viagara and heart medication that older men need to be aware of to prevent their untimely demise.
Let’s now consider some examples of interactions from research. It probably would not surprise you to hear that the effect of receiving psychotherapy is stronger among people who are highly motivated to change than among people who are not motivated to change. This is an interaction because the effect of one independent variable (whether or not one receives psychotherapy) depends on the level of another (motivation to change). Schnall and her colleagues also demonstrated an interaction because the effect of whether the room was clean or messy on participants’ moral judgments depended on whether the participants were low or high in private body consciousness. If they were high in private body consciousness, then those in the messy room made harsher judgments. If they were low in private body consciousness, then whether the room was clean or messy did not matter.
In many studies, the primary research question is about an interaction. The study by Brown and her colleagues was inspired by the idea that people with hypochondriasis are especially attentive to any negative health-related information. This led to the hypothesis that people high in hypochondriasis would recall negative health-related words more accurately than people low in hypochondriasis but recall non-health-related words about the same as people low in hypochondriasis. And of course, this is exactly what happened in this study.
Types of Interactions
The effect of one independent variable can depend on the level of the other in several different ways. First, there can be spreading interactions. Examples of spreading interactions are shown in the top two panels of Figure 9.4. In the top panel, independent variable “B” has an effect at level 1 of independent variable “A” (there is a difference in the height of the blue and red bars on the left side of the graph) but no effect at level 2 of independent variable “A.” (there is no difference in the height of the blue and red bars on the right side of the graph). This is much like the study of Schnall and her colleagues where there was an effect of disgust for those high in private body consciousness but not for those low in private body consciousness. In the middle panel, independent variable “B” has a stronger effect at level 1 of independent variable “A” than at level 2 (there is a larger difference in the height of the blue and red bars on the left side of the graph and a smaller difference in the height of the blue and red bars on the right side of the graph). This is like the hypothetical driving example where there was a strong effect of using a cell phone at night and a weaker effect of using a cell phone during the day. So to summarize, for spreading interactions there is an effect of one independent variable at one level of the other independent variable and there is either a weak effect or no effect of that independent variable at the other level of the other independent variable.
The second type of interaction that can be found is a cross-over interaction. A cross-over interaction is depicted in the bottom panel of Figure 9.4, independent variable “B” again has an effect at both levels of independent variable “A,” but the effects are in opposite directions. Another example of a crossover interaction comes from a study by Kathy Gilliland on the effect of caffeine on the verbal test scores of introverts and extraverts (Gilliland, 1980)[1]. Introverts perform better than extraverts when they have not ingested any caffeine. But extraverts perform better than introverts when they have ingested 4 mg of caffeine per kilogram of body weight.
Figure 9.5 shows examples of these same kinds of interactions when one of the independent variables is quantitative and the results are plotted in a line graph. Note that the top two figures depict the two kinds of spreading interactions that can be found while the bottom figure depicts a crossover interaction (the two lines literally “cross over” each other).
Simple Effects
When researchers find an interaction it suggests that the main effects may be a bit misleading. Think of the example of a crossover interaction where introverts were found to perform better on a test of verbal test performance than extraverts when they had not ingested any caffeine, but extraverts were found to perform better than introverts when they had ingested 4 mg of caffeine per kilogram of body weight. To examine the main effect of caffeine consumption, the researchers would have averaged across introversion and extraversion and simply looked at whether overall those who ingested caffeine had better or worse verbal memory test performance. Because the positive effect of caffeine on extraverts would be wiped out by the negative effects of caffeine on the introverts, no main effect of caffeine consumption would have been found. Similarly, to examine the main effect of personality, the researchers would have averaged across the levels of the caffeine variable to look at the effects of personality (introversion vs. extraversion) independent of caffeine. In this case, the positive effects extraversion in the caffeine condition would be wiped out by the negative effects of extraversion in the no caffeine condition. Does the absence of any main effects mean that there is no effect of caffeine and no effect of personality? No of course not. The presence of the interaction indicates that the story is more complicated, that the effects of caffeine on verbal test performance depend on personality. This is where simple effects come into play. Simple effects are a way of breaking down the interaction to figure out precisely what is going on. An interaction simply informs us that the effects of at least one independent variable depend on the level of another independent variable. Whenever an interaction is detected, researchers need to conduct additional analyses to determine where that interaction is coming from. Of course one may be able to visualize and interpret the interaction on a graph but a simple effects analysis provides researchers with a more sophisticated means of breaking down the interaction. Specifically, a simple effects analysis allows researchers to determine the effects of each independent variable at each level of the other independent variable. So while the researchers would average across the two levels of the personality variable to examine the effects of caffeine on verbal test performance in a main effects analysis, for a simple effects analysis the researchers would examine the effects of caffeine in introverts and then examine the effects of caffeine in extraverts. As we saw previously, the researchers also examined the effects of personality in the no caffeine condition and found that in this condition introverts performed better than extraverts. Finally, they examined the effects of personality in the caffeine condition and found that extraverts performed better than introverts in this condition. For a 2 x 2 design like this, there will be two main effects the researchers can explore and four simple effects.
Schnall and colleagues found a main effect of disgust on moral judgments (those in a messy room made harsher moral judgments). However, they also discovered an interaction between private body consciousness and disgust. In other words, the effect of disgust depended on private body consciousness. The presence of this interaction suggests the main effect may be a bit misleading. That is, it is not entirely accurate to say that those in a messy room made harsher moral judgments because this was only true for half of the participants. Using simple effects analyses, they were able to further demonstrate that for people high in private body consciousness, there was an effect of disgust on moral judgments. Further, they found that for those low in private body consciousness there was no effect of disgust on moral judgments. By examining the effect of disgust at each level of body consciousness using simple effects analyses, Schnall and colleagues were able to better understand the nature of the interaction.
As described previously, Brown and colleagues found an interaction between type of words (health related or not health related) and hypochondriasis (high or low) on word recall. To break down this interaction using simple effects analyses they examined the effect of hypochondriasis at each level of word type. Specifically, they examined the effect of hypochondriasis on recall of health-related words and then they subsequently examined the effect of hypochondriasis on recall of non-health related words. They found that people high in hypochondriasis were able to recall more health-related words than people low in hypochondriasis. In contrast, there was no effect of hypochondriasis on the recall of non-health related words.
Once again examining simple effects provides a means of breaking down the interaction and therefore it is only necessary to conduct these analyses when an interaction is present. When there is no interaction then the main effects will tell the complete and accurate story. To summarize, rather than averaging across the levels of the other independent variable, as is done in a main effects analysis, simple effects analyses are used to examine the effects of each independent variable at each level of the other independent variable(s). So a researcher using a 2×2 design with four conditions would need to look at 2 main effects and 4 simple effects. A researcher using a 2×3 design with six conditions would need to look at 2 main effects and 5 simple effects, while a researcher using a 3×3 design with nine conditions would need to look at 2 main effects and 6 simple effects. As you can see, while the number of main effects depends simply on the number of independent variables included (one main effect can be explored for each independent variable), the number of simple effects analyses depends on the number of levels of the independent variables (because a separate analysis of each independent variable is conducted at each level of the other independent variable).
- Gilliland, K. (1980). The interactive effect of introversion-extraversion with caffeine induced arousal on verbal performance. Journal of Research in Personality, 14, 482–492. ↵
Learning Objectives
- Identify and distinguish between micro-, meso-, and macro-level considerations with respect to the ethical conduct of social scientific research
One useful way to think about the breadth of ethical questions that might arise out of any research project is to think about potential issues from the perspective of different analytical levels. In Chapter 1, you learned about the micro-, meso-, and macro-levels of inquiry and how a researcher’s specific point of focus might vary depending on her level of inquiry. Here we’ll apply this ecological framework to a discussion of research ethics. Within most research projects, there are specific questions that arise for researchers at each of these three levels.
At the micro-level, researchers must consider their own conduct and the rights of individual research participants. For example, did Stanley Milgram behave ethically when he allowed research participants to think that they were administering electronic shocks to fellow participants? Did Laud Humphreys behave ethically when he deceived his research subjects about his own identity? Were the rights of individuals in these studies protected? These are the type of questions you will want to ask yourself as a researcher when considering ethics at the micro-level.
At the meso-level, researchers should think about their duty to the community. How will the results of your study impact your target population? Ideally, your results will benefit your target population by identifying important areas for social workers to intervene. However, it is possible that your study may perpetuate negative stereotypes about your target population or damage its reputation. Indigenous people, in particular, have highlighted how social science has historically furthered their marginalization (Smith, 2013). [1] In addition to your target population, you must also consider your responsibilities to the profession of social work. By engaging in social work research, you are standing on the reputation that the profession has worked to build for over a century. Attending to research ethics helps fulfill your responsibilities to the profession, in addition to your target population.
Finally, at the macro-level, a researcher should consider their duty to society and the expectations that society has of them as a social worker. The most troubling and high-profile example of an ethical debate at the macro-level questions whether it is ethical to utilize or cite information obtained by the Nazi's horrendous human experiments during WWII (Moe, 1984). [2] Some argue that because the data were gathered in such an unquestionably unethical manner, they should never be used. Further, some who argue against using the Nazi data point out that not only were the experiments immoral but the methods used to collect data were also scientifically questionable. The data, say these people, are neither valid nor reliable and should therefore not be used in any current scientific investigation (Berger, 1990). [3]
On the other hand, some people argue that data themselves are neutral; that “information gathered is independent of the ethics of the methods and that the two are not linked together” (Pozos, 1992, p. 104). [4] Others point out that not using the data could inadvertently strengthen the claims of those who deny that the Holocaust ever happened. In his striking statement in support of publishing the data, medical ethics professor Velvl Greene (1992) says,
Instead of banning the Nazi data or assigning it to some archivist or custodial committee, I maintain that it be exhumed, printed, and disseminated to every medical school in the world along with the details of methodology and the names of the doctors who did it, whether or not they were indicted, acquitted, or hanged.…Let the students and the residents and the young doctors know that this was not ancient history or an episode from a horror movie where the actors get up after filming and prepare for another role. It was real. It happened yesterday (p. 169–170). [5]
While debates about the use of data collected by the Nazis are typically centered on medical scientists’ use of them, there are conceivable circumstances under which these data might be used by social scientists. Perhaps, for example, a social scientist might wish to examine contemporary reactions to the experiments, or perhaps the data could be used in a study of the sociology of science. What do you think? Should data gathered by the Nazis be used or cited today? What arguments can you make in support of your position, and how would you respond to those who disagree? Table 5.1 summarizes the key questions that researchers might ask themselves about the ethics of their research at each level of inquiry.
| Level of inquiry | Focus | Key ethics questions for researchers to ask themselves |
| Micro-level | Individual | Does my research impinge on the individual's right to privacy? |
| Could my research offend subjects in any way? | ||
| Could my research cause emotional distress to any of my subjects? | ||
| Has my own conduct been ethical throughout the research process? | ||
| Meso-level | Group | Does my research follow the ethical guidelines of my profession and discipline? |
| Could my research negatively impact a community? | ||
| Have I met my duty to those who funded my research? | ||
| Macro-level | Society | Does my research meet the societal expectations of social research? |
| Have I met my social responsibilities as a researcher? |
Key Takeaways
- At the micro-level, researchers should consider their own conduct and the rights of individual research participants.
- At the meso-level, researchers should consider the expectations of their profession, any organizations that may have funded their research, and the communities affected by their research.
- At the macro-level, researchers should consider their duty to and the expectations of society with respect to social scientific research.
Learning Objectives
- Describe common barriers to engaging with social work research
- Identify alternative ways of thinking about research methods
I’ve been teaching research methods for six years and have found many students struggle to see the connection between research and social work practice. Most students enjoy a social work theory class because they can better understand the world around them. Students also like social work practice courses because they are taught how to conduct clinical work with clients, which is what most social work students want to do. On the other hand, it is less common for me to have a student that is interested in becoming a social work researcher. For this reason, I want to end this chapter on a more personal note. Most student barriers to research come from the following beliefs:
Research is useless!
Students are saying something important when they tell me that research methods is not a useful class to them. As a scholar (or student), your most valuable asset is your time. You give your time to the subjects you consider important to you and your future practice. Because most social workers don’t become researchers or practitioner-researchers, students feel like a research methods class is a waste of time.
Social workers play an important role in creating new knowledge about social services, as presented in our previous discussion of evidence-based practice and the use of research methods. On a more immediate level, research methods will also help you become a stronger social work student. The next few chapters of this textbook will review how to search for literature on a topic and write a literature review. These skills are relevant in every classroom during your academic career. The rest of the textbook will help you understand the mechanics of research methods so you can better understand the content of those pesky journal articles your professors force you to cite in your papers.
Research is too hard!
Research methods involves a lot of terminology that is entirely new to social workers. Other domains of social work are easier to apply your intuition towards. In a social work practice course, you may feel more at ease because you understand how to be an empathetic person, and your experiences in life can help guide you through a practice situation or even theoretical or conceptual question. Research may seem like a totally new area in which you have no previous experience. It can seem like a lot to learn. In addition to the normal memorization and application of terms, research methods also has wrong answers. There are certain combinations of methods that just don’t work together.
The fear is entirely understandable. Research is not straightforward. As Figure 1.1 shows, it is a process that is non-linear, involving multiple revisions, wrong turns, and dead ends before you figure out the best question and research approach. You may have to go back to chapters after having read them or even peek ahead at chapters your class hasn’t covered yet.
Moreover, research is something you learn by doing…and stumbling a few times. It’s an iterative process, which means that you must try many times before you get it right. There isn’t a shortcut for learning research, but hopefully your research methods class is one in which your research project is broken down into smaller parts and you get consistent feedback throughout the process. No one just knows research. It’s something you pick up by doing it, reflecting on the experiences and results, redoing your work, and revising it in consultation with your professor.
Research is boring!
We’ve already discussed the arcane research terminology, so I won’t go into it again here, but research methods is regarded as a boring topic by many students. Practice knowledge and even theory are fun to learn because they are easy to apply and give you insight into the world around you. Research just seems like its own weird, remote thing.
I completely understand where this perspective comes from and hope there are a few things you will take away from this course that aren’t boring to you. In the first section of this textbook, you will learn how to take any topic and learn what is known about it. It may seem trivial, but it is actually a superpower. Your social work education will present some generalist material, which is applicable to nearly all social work practice situations, and some applied material, which is applicable to specific social work practice situations. However, there is no education that will provide you with everything you need to know, and there is certainly no education that can tell you what will be discovered over the next few decades of your practice. Our work on literature reviews in the next few chapters will help you to become a strong social work student and practitioner. Following that, our exploration of research methods will help you further understand how the theories, practice models, and techniques you learn in your other classes are created and tested scientifically.
Get out of your own way
Together, the beliefs of “research is useless, boring, and hard” can create a self-fulfilling prophecy for students. If you believe that research is boring, then you won’t find it interesting. If you believe that research is hard, then you will struggle more with assignments. If you believe that research is useless, then you won’t see its utility. While I certainly acknowledge that students aren’t going to love research as much as I do (it’s a career for me, so I like it a lot!), I suggest reframing how you think about research using these touchstones:
- All social workers rely on social science research to engage in competent practice.
- No one already knows research. It’s something I’ll learn through practice, and it’s challenging for everyone.
- Research is relevant to me because it allows me to figure out what is known about any topic I want to study.
- If the topic I choose to study is important to me, I will be more interested in research.
Structure of this textbook
While you may not have chosen this course, you can increase the likelihood of academic gain by reframing your approach to it. To that end, here is the structure of this book:
In Chapters 2-4, we’ll review how to begin a research project. This involves searching for relevant literature, specifically from academic journals, and synthesizing what they say about your topic into a literature review.
In Chapters 5-9, you’ll learn about how research informs and tests theory. We’ll discuss how to conduct research in an ethical manner, create research questions, and measure concepts in the social world.
Chapters 10-14 will describe how to conduct research, whether it’s a quantitative survey or experiment, or a qualitative interview or focus group. We’ll also review how to analyze data that someone else has already collected.
Finally, Chapters 15 and 16 will review the types of research most commonly used in social work practice, including evaluation research and action research, and how to report the results of your research to various audiences.
Key Takeaways
- Anxiety about research methods is a common experience for students.
- Research methods will help you become a better scholar and practitioner.
Learning Objectives
- Define science
- Describe the difference between objective and subjective truth(s)
- Describe the roles of ontology and epistemology in scientific inquiry
Science and social work
Science is a particular way of knowing that attempts to systematically collect and categorize facts or truths. A key word here is "systematically," because it is important to understand that conducting science is a deliberate process. Scientists gather information about facts in a way that is organized and intentional, usually following a set of predetermined steps. More specifically, social work is informed by social science, the science of humanity, social interactions, and social structures. In sum, social work research uses organized and intentional procedures to uncover facts or truths about the social world and it also relies on social scientific research to promote individual and social change.
Philosophy of social science
This approach to finding truth probably sounds similar to something you heard in your middle school science classes. When you learned about the gravitational force or the mitochondria of a cell, you were learning about the theories and observations that make up our understanding of the physical world. These theories rely on an ontology, or a set of assumptions about what is real. We assume that gravity is real and that the mitochondria of a cell are real. With a powerful microscope, mitochondria are easy to spot and observe, and we can theorize about their function in a cell. The gravitational force is invisible, but clearly apparent from observable facts, like watching an apple fall. The theories about gravity have changed over the years, and those improvements in theory were made when existing theories fell short in explaining observations.
If we weren’t able to perceive mitochondria or gravity, they would still be there, doing their thing because they exist independent of our observation of them. This is a philosophical idea called realism, and it simply means that the concepts we talk about in science really and truly exist. Ontology in physics and biology is focused on objective truth. You may have heard the term “being objective” before: it involves observing and thinking with an open mind and pushing aside anything that might bias your perspective. Objectivity also involves finding what is true for everyone, not just what is true for one person. Gravity is certainly true for everyone, everywhere, but let’s consider a social work example. It is objectively true that children who are subjected to severely traumatic experiences will experience negative mental health effects afterwards. A diagnosis of post-traumatic stress disorder (PTSD) is considered objective because it refers to a real mental health issue that exists independent of the social worker’s observations, and it presents similarly in all clients who experience the disorder.
Objective, ontological perspective implies that observations are true for everyone, regardless of whether we are there to observe them or not observe them. Epistemology, or our assumptions about how we come to know what is real and true, helps us to realize these objective truths. The most relevant epistemological question in the social sciences is whether truth is better accessed using numbers or words. Generally, scientists approaching research with an objective ontology and epistemology will use quantitative methods to arrive at scientific truth. Quantitative methods examine numerical data to precisely describe and predict elements of the social world. This is due to the epistemological assumption that mathematics can represent the phenomena and relationships we observe in the social world.
Mathematical relationships are uniquely useful because allow us to make comparisons across individuals as well as time and space. For example, let’s look at measures of poverty. While people can have different definitions of poverty, an objective measurement such as an annual income less than $25,100 for a family of four is insightful because (1) it provides a precise measurement, (2) it can be compared to incomes from all other people in any society from any time period, and (3) it refers to real quantities of money that exist in the world. In this book, we will review survey and experimental methods, which are the most common designs that use quantitative methods to answer research questions.
It may surprise you to learn that objective facts, like income or mental health diagnoses, are not the only facts that are present in the social sciences. Indeed, social science is not only concerned with objective truths, but it is also concerned with subjective truth. Subjective truths are unique to individuals, groups, and contexts. Unlike objective truths, subjective truths will vary based on who you are observing and the context you are observing them in. The beliefs, opinions, and preferences of people are actually truths that social scientists measure and describe. Additionally, subjective truths do not exist independent of human observation because they are the product of the human mind. We negotiate what is true in the social world through language, arriving at a consensus and engaging in debate.
Epistemologically, a scientist seeking subjective truth assumes that truth lies in what people say, in their words. A scientist uses qualitative methods to analyze words or other media to understand their meaning. Humans are social creatures, and we give meaning to our thoughts and feelings through language. Linguistic communication is unique. We share ideas with each other at a remarkable rate. In so doing, ideas come into and out of existence in a spontaneous and emergent fashion. Words are given a meaning by their creator., but anyone who receives that communication can absorb, amplify, and even change its original intent. Because social science studies human interaction, subjectivists argue that language is the best way to understand the world.
This epistemology is based on some interesting ontological assumptions. What happens when someone incorrectly interprets a situation? While their interpretation may be wrong, it is certainly true to them that they are right. Furthermore, they act on the assumption that they are right. In this sense, even incorrect interpretations are truths, even though they are only true to one person. This leads us to question whether the social concepts we think about really exist. They might only exist in our heads, unlike concepts from the natural sciences which exist independent of our thoughts. For example, if everyone ceased to believe in gravity, we wouldn’t all float away. It has an existence independent of human thought.
Let's think through an example. In the Diagnostic and Statistical Manual (DSM) classification of mental health disorders, there is a list of culture-bound syndromes which only appear in certain cultures. For example, susto describes a unique cluster of symptoms experienced by people in Latin American cultures after a traumatic event that focus on the body. Indeed, many of these syndromes do not fit within a Western conceptualization of mental health because Western culture differentiates less between the mind and body. To a Western scientist, susto may seem less real than PTSD. To someone from Latin America, their symptoms may not fit neatly into the PTSD framework developed within Western society. This conflict raises the question: do either susto or PTSD really exist at all? If your answer is “no,” then you are adopting the ontology of anti-realism, which is the belief that social concepts do not have an existence apart from human thought. Unlike realists who seek a single, universal truth, the anti-realist sees a collection of truths that are created and shared within a social and cultural environment.
Let’s consider another example: manels or all-male panel discussions at conferences and conventions. Check out this National Public Radio article for some hilarious examples, ironically including panels about diversity and gender representation. Manels are a problem in academic gatherings, Comic-Cons, and other large group events. Over the last few decades, feminist critique has helped us to realize that manels are a holdover of sexist stereotypes and gender-based privilege that perpetuate the idea that men are the experts who deserve to be listened to by other, less important and knowledgeable people. However, let’s look at an example. We will take the perspective of a few different participants at a hypothetical conference and examine their individual, subjective truths.
Imagine that the conference schedule is announced. Of the ten panel discussions that are announced, only two panels contain women. Mei, an expert on the neurobiology of child abuse, thinks that this is unfair, as she was excluded from a panel on her specialty. Marco, an event organizer, feels that the results could not be sexist because the organizers simply invited those who were most qualified to speak, regardless of gender. Dionne, a professor who specializes in queer theory and indigenous social work, agrees with Mei that manels are sexist. However, she also feels that the focus on gender excludes and overlooks the problems with race, disability, sexual and gender identity, and social class among the conference panel members. Given these differing interpretations, how can we come to know what is true about this situation?
Honestly, there are many truths present in this example. Clearly, Pamela’s truth is that manels are sexist. Marco’s truth is that they are not necessarily sexist, as long as they were chosen in a sex-blind manner. While none of these statements are objectively true, they are subjectively true to the individual who thought of them. Subjective truth consists of the the different meanings, understandings, and interpretations created by people and communicated throughout society. The communication of ideas is important, as it is how people come to a consensus on how to interpret a situation and negotiate the meaning of events, and it informs how people act. Thus, as feminist critiques of society become more accepted, people will behave in less sexist ways. From a subjective perspective, there is no magical number of female panelists that conferences must reach to be sufficiently non-sexist. Instead, we should use language to investigate how people interpret the gender issues at the event and analyze them within a historical and cultural context. How do we find truth when everyone has their own unique interpretation? We must find patterns.
Science means finding patterns in data
Regardless of whether you are seeking objective or subjective truths, research and scientific inquiry aim to find and explain patterns. Most of the time, a pattern will not explain every single person’s experience, and this is a fact about social science that is both fascinating and frustrating. Even individuals who do not know each other and do not coordinate in any deliberate way can create patterns that persist over time. Those new to social science may find these patterns frustrating because they may believe that the patterns that describe their gender, age, or some other facet of their lives don’t really represent their experience. It’s true. A pattern can exist among your cohort without your individual participation in it. There is diversity within diversity.
Let’s consider some specific examples. One area that social workers commonly investigate is the impact of a person’s social class background on their experiences and lot in life. You probably wouldn’t be surprised to learn that a person’s social class background has an impact on their educational attainment and achievement. In fact, one group of researchers [7] in the early 1990s found that the percentage of children who did not receive any postsecondary schooling was four times greater among those in the lowest quartile (25%) income bracket than those in the upper quartile of income earners (i.e., children from high- income families were far more likely than low-income children to go on to college). Another recent study found that having more liquid wealth that can be easily converted into cash actually seems to predict children’s math and reading achievement (Elliott, Jung, Kim, & Chowa, 2010). [8]
These findings—that wealth and income shape a child’s educational experiences—are probably not that shocking to any of us. Yet, some of us may know someone who may be an exception to the rule. Sometimes the patterns that social scientists observe fit our commonly held beliefs about the way the world works. When this happens, we don’t tend to take issue with the fact that patterns don’t necessarily represent all people’s experiences. But what happens when the patterns disrupt our assumptions?
For example, did you know that teachers are far more likely to encourage boys to think critically in school by asking them to expand on answers they give in class and by commenting on boys’ remarks and observations? When girls speak up in class, teachers are more likely to simply nod and move on. The pattern of teachers engaging in more complex interactions with boys means that boys and girls do not receive the same educational experience in school (Sadker & Sadker, 1994). [9] You and your classmates, of all genders, may find this news upsetting.
People who object to these findings tend to cite evidence from their own personal experience, refuting that the pattern actually exists. However, the problem with this response is that objecting to a social pattern on the grounds that it doesn’t match one’s individual experience misses the point about patterns. Patterns don’t perfectly predict what will happen to an individual person, yet they are a reasonable guide. When patterns are systematically observed, they can help guide social work thought and action.
A final note on qualitative and quantitative methods
There is no one superior way to find patterns that help us understand the world. As we will learn about in Chapter 6, there are multiple philosophical, theoretical, and methodological ways to approach uncovering scientific truths. Qualitative methods aim to provide an in-depth understanding of a relatively small number of cases. Quantitative methods offer less depth on each case but can say more about broad patterns in society because they typically focus on a much larger number of cases. A researcher should approach the process of scientific inquiry by formulating a clear research question and conducting research using the methodological tools best suited to that question.
Believe it or not, there are still significant methodological battles being waged in the academic literature on objective vs. subjective social science. Usually, quantitative methods are viewed as “more scientific” and qualitative methods are viewed as “less scientific.” Part of this battle is historical. As the social sciences developed, they were compared with the natural sciences, especially physics, which rely on mathematics and statistics to find truth. It is a hotly debated topic whether social science should adopt the philosophical assumptions of the natural sciences—with its emphasis on prediction, mathematics, and objectivity—or use a different set of tools—understanding, language, and subjectivity—to find scientific truth.
You are fortunate to be in a profession that values multiple scientific ways of knowing. The qualitative/quantitative debate is fueled by researchers who may prefer one approach over another, either because their own research questions are better suited to one particular approach or because they happened to have been trained in one specific method. In this textbook, we’ll operate from the perspective that qualitative and quantitative methods are complementary rather than competing. While these two methodological approaches certainly differ, the main point is that they simply have different goals, strengths, and weaknesses. A social work researcher should choose the methods that best match with the question they are asking.
Key Takeaways
- Social work is informed by science.
- Social science is concerned with both objective and subjective knowledge.
- Social science research aims to understand patterns in the social world.
- Social scientists use both qualitative and quantitative methods. While different, these methods are often complementary.
Glossary
Epistemology- a set of assumptions about how we come to know what is real and true
Objective truth- a single truth, observed without bias, that is universally applicable
Ontology- a set of assumptions about what is real
Qualitative methods- examine words or other media to understand their meaning
Quantitative methods- examine numerical data to precisely describe and predict elements of the social world
Science- a particular way of knowing that attempts to systematically collect and categorize facts or truth
Subjective truth- one truth among many, bound within a social and cultural context
Image Attributions
Science and Technology by Petr Kratochvil CC-0
Abstract art blur bright by Pixabay CC-0
