# 8.3 Quantitative research questions

### Learning Objectives

• Describe how research questions for exploratory, descriptive, and explanatory quantitative questions differ and how to phrase them
• Identify the differences between and provide examples of strong and weak explanatory research questions

# Quantitative descriptive questions

The type of research you are conducting will impact the research question that you ask. Quantitative descriptive questions are arguably the easiest types of questions to formulate. For example, “What is the average student debt load of MSW students?” is an important descriptive question. We aren’t trying to build a causal relationship here. We’re simply trying to describe how much debt MSW students carry. Quantitative descriptive questions like this one are helpful in social work practice as part of community scans, in which human service agencies survey the various needs of the community they serve. If the scan reveals that the community requires more services related to housing, child care, or day treatment for people with disabilities, a nonprofit office can use the community scan to create new programs that meet a defined community need.

Quantitative descriptive questions will often ask for figures such as percentages, sums, or averages. Descriptive questions may only include one variable, such as ours included the variable of student debt, or they may include multiple variables. When asking a descriptive question, we cannot investigate causal relationships between variables. To do that, we need to use a quantitative explanatory question.

# Quantitative explanatory questions

Most studies you read in the academic literature will be quantitative and explanatory. Why is that? If you recall from Chapter 7, explanatory research tries to build nomothetic causal relationships. They are generalizable across space and time, so they are applicable to a wide audience. The editorial board of a journal wants to make sure their content will be useful to as many people as possible, so it’s not surprising that quantitative research dominates the academic literature.

Structurally, quantitative explanatory questions must contain an independent variable and dependent variable and they should ask about the relationship between these variables. My standard format for an explanatory quantitative research question is: “What is the relationship between [independent variable] and [dependent variable] for [target population]?” You should play with the wording for your research question, revising it as you see fit. The goal is to make the research question reflect what you really want to know in your study.

Let’s look at a few more examples of possible research questions and consider the relative strengths and weaknesses of each. While reading the Table 8.1, keep in mind that I have only noted what I view to be the most relevant strengths and weaknesses of each question. Certainly each question may have additional strengths and weaknesses not noted in the table.

 Sample question Question’s strengths Question’s weaknesses Proposed alternative What are the internal and external effects/problems associated with children witnessing domestic violence? Written as a question Not clearly focused How does witnessing domestic violence impact a child’s romantic relationships in adulthood? Considers relationships among multiple concepts Not specific and clear about the concepts it addresses Contains a population What causes foster children who are transitioning to adulthood to become homeless, jobless, pregnant, unhealthy, etc.? Considers relationships among multiple concepts Concepts are not specific and clear What is the relationship between sexual orientation or gender identity and homelessness for late adolescents in foster care? Contains a population Not written as a yes/no question How does income inequality predict ambivalence in the Stereo Content Model using major U.S. cities as target populations? Written as a question Unclear wording How does income inequality affect ambivalence in high-density urban areas? Considers relationships among multiple concepts Population is unclear Why are mental health rates higher in white foster children then African Americans and other races? Written as a question Concepts are not clear How does race impact rates of mental health diagnosis for children in foster care? Not written as a yes/no question Does not contain a target population

# Making it more specific

Table 8.2 contains some “watch words” that indicate you may need to be more specific about the concepts in your research question.

 Watch words How to get more specific Factors, Causes, Effects, Outcomes What causes or effects are you interested in? What causes and effects are important, based on the literature in your topic area? Try to choose one or a handful that you consider to be the most important. Effective, Effectiveness, Useful, Efficient Effective at doing what? Effectiveness is meaningless on its own. What outcome should the program or intervention have? Reduced symptoms of a mental health issue? Better socialization? Etc., and so forth Get more specific. You need to know enough about your topic to clearly address the concepts within it. Don’t assume that your reader understands what you mean by “and so forth.”

In social work research, it can be challenging to be this specific, particularly when you are just beginning to investigate your topic. If you’ve only read one or two articles on the topic, it can be hard to know what you are interested in studying. Broad questions like “What are the causes of chronic homelessness, and what can be done to prevent it?” are common at the beginning stages of a research project. However, social work research demands that you examine the literature on the topic and refine your question over time to be more specific and clear before you begin your study. Perhaps you want to study the effect of a specific anti-homelessness program that you found in the literature. Maybe there is a particular model to fighting homelessness that you want to investigate further, like Housing First or transitional housing. You may want to focus on a potential cause of homelessness that you find interesting or relevant to your practice, like LGBTQ discrimination. As you can see, the possibilities for making your question more specific are almost infinite.

# Quantitative exploratory questions

In exploratory research, the researcher doesn’t quite know the lay of the land yet. If someone is proposing to conduct an exploratory quantitative project, the watch words highlighted in Table 8.2 are not problematic at all. In fact, questions such as “What factors influence the removal of children in child welfare cases?” are good because they will explore a variety of factors or causes. In this question, the independent variable is less clearly written, but the dependent variable, family preservation outcomes, is quite clearly written. The inverse can also be true. If we were to ask, “What outcomes are associated with family preservation services in child welfare?”, we would have a clear independent variable, family preservation services, but an unclear dependent variable, outcomes. Because we are only conducting exploratory research on a topic, we may not have an idea of what concepts may comprise our “outcomes” or “factors.” Only after interacting with our participants will we be able to understand which concepts are important.

### Key Takeaways

• Quantitative descriptive questions are helpful for community scans but cannot investigate causal relationships between variables.
• Quantitative explanatory questions must include an independent and dependent variable.