Social Work Research Methods. Reginald O. York
qualitative study is more suitable for situations where little is known, so you are not in a good position to develop a study hypothesis and measure variables in a quantitative manner. If there are few theories that guide your understanding of the phenomenon of interest, you will likely choose a qualitative method of measurement. If you are seeking to understand social processes rather than describe or explain reality, you are more likely to select the qualitative method.
The quantitative method of measurement, on the other hand, is more suitable for the testing of a theory or hypothesis, or the careful description of a phenomenon in concrete terms. It is more likely to be used in an evaluative study, which has the purpose of determining if a social work intervention has had the intended effect on the client’s target behavior. In such situations, you will normally have an idea about how to measure variables in a quantitative manner.
The Research Process
There are four steps in the research process that will be discussed in various examples throughout this book. The first entails the development of the research question and the knowledge base that will guide various aspects of the study. The second step is the development of the study methods with regard to themes such as sampling, measurement, and so forth. The third step entails the collection and analysis of data, while the final step engages the researcher in the presentation of the study conclusions.
Step 1: Developing the Research Question and Knowledge Base
The research study starts with a particular interest. You may want to know what causes client no-shows for appointments. Perhaps you want to know if women have better outcomes than men. Maybe your question is whether the clients of your program are satisfied with their services or have achieved the objectives of the intervention.
Here are some research questions you could examine:
1 Do those who engage in regular aerobic exercise have less of a tendency to experience minor illnesses (e.g., colds, flu) than those who do not?
2 What traits of a good work manager are viewed as more valuable than other traits?
3 Do those with higher scores for stressors have higher scores for stress?
4 Do those with higher scores for social support have lower scores for stress?
5 Do the clients of the New Horizons Program have lower scores for depression at the end of the treatment than before?
Can you characterize each of the above questions with regard to purpose? In other words, which ones are descriptive, explanatory, evaluative, or exploratory? Before you go further, give it a try. Select a label for each of these questions.
What about the first question? Is it descriptive? If so, it is a question that attempts only to describe one variable, even though it may have several variables that are to be described, such as age, income, race, or gender. You will notice that two variables are identified—exercise and illness. Does this question attempt to describe exercise by itself or examine the relationship of this variable with the other variable? Well, it requires the examination of the relationship between exercise and illness, so it is an explanatory study question. You cannot answer this question by reporting that 40% of your study subjects say that they engage in aerobic exercise. You must compare this rate with the rate for those who do not exercise.
What about the second question? Is it a descriptive question? Even though it lists traits, it is attempting to find out the rate at which the study subjects value a particular trait, so it is a descriptive study. The results may show that 34% favor Trait 1, 55% favor Trait 2, and so forth. It attempts to describe each trait one by one, not to examine the relationship between the traits and another variable.
Is the third question descriptive? It lists two variables (stressors and stress) and seeks to see if there is a relationship between the two in an attempt to examine whether one of these variables explains the other. So it is an explanatory research question. The same is true for the fourth question. It examines the relationship between stress and social support.
What about the last question? Is it descriptive, explanatory, evaluative, or exploratory? This study will examine two sets of scores (pretest and posttest) for the purpose of determining if an intervention has improved depression in the clients. This makes it an evaluative study. Whenever your intent is to evaluate an intervention, you are engaged in evaluative research.
The knowledge base for a research study has several functions. One is to define critical variables so that measurement is facilitated. Another function is to examine the relevant literature that will guide the analysis of the behavior or the theme of the research question. This clarification can assist with the identification of the variables to be measured. It can also assist with the identification of theories that suggest what kinds of relationships we would expect to find between the variables.
Step 2: Determining the Study Methods
Your study methods indicate how you will examine your research question in your study. From whom will you collect data? How will you measure your study variables? What is your study design? These are all about the how of your study.
You will decide on the study population that is relevant to your study. This might be as broad as anybody or as narrow as persons with a certain type of eating disorder. If you are examining a very broad question, such as whether those who exercise are better off regarding health, you have a broad study population, because this question is relevant to everyone. But if you are evaluating a treatment program for those suffering from bulimia, you will have a small study population.
You will select a group of people from that study population from whom you will collect data. This is your study sample. The method you use to select the sample from the population determines how well you can generalize your study findings from the sample to your population. This will be discussed in more detail in a later chapter. To generalize means that you would expect similar results from another sample of people from the same population. So what you found in your study is relevant to other people in your study population.
You will select a means of measuring each of the variables in your study. This might be a scale for measuring self-esteem, school records on school absences, or agency records on whether a client followed the suggestions on the discharge plan.
If you are conducting an evaluative study, you will determine the research design. This design instructs you on the procedures for the collection of your data on client outcome. One design, for example, calls on you to measure a group of clients once before treatment begins and once at the end of treatment. This design measures client progress.
Step 3: Collecting and Analyzing Data
You will collect data according to the relevant protocol. The term data refers to the discrete information that you have, such as the age of each client, the depression score for each client, and so forth. You must have data for each variable in your study. You cannot have a research question that contains age as a variable unless you collect data on age for each study subject.
Your data collection procedure may mean giving a questionnaire to a group of people at one point in time. It might entail the administration of a tool more than once to the same group of people. In this book, you will have exercises where you will collect data from a group of people (perhaps the members of your class) at one point in time. The instrument used will have items designed to measure each of the variables in your study. One of the variables may designate the group the respondent is in, so that two groups can be compared.
You will select a statistic for each of your research questions. Some of these statistics will be descriptive in nature, such as a frequency or a mean. Some will be explanatory in nature because the statistic helps you determine if there is a relationship between two variables that cannot be explained by chance (i.e., the data are statistically significant). Later in this book, guidance is provided on how to find the appropriate statistic and how to employ it in the examination of your data.
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