 The goal of an empirical study is to answer research questions through observation or experimentation. Empirical studies can be quantitative or qualitative, and it's important to understand the difference. In this video, we'll compare quantitative and qualitative scholarly articles. In order to understand these different approaches to your research, let's start by comparing the goals of quantitative and qualitative approaches. When you think quantitative, think experimental and statistical. The goal here is to measure, test, predict, and describe using statistics. If you conduct a statistical analysis of the correlation between a hospital's promotion of hand-washing hygiene and their rate of healthcare-associated infections, you're taking a quantitative approach. But if you go into a long-term care facility, observe interactions between residents and caregivers, and conduct open-ended interviews with residents about the quality of care they receive, you're taking a qualitative approach. You might hear terms like ethnographic or phenomenological to describe qualitative research. The goal here is to richly describe people's behaviors and realities rather than to measure them. Since the goals of quantitative and qualitative studies are different, their methods and data are different too. A quantitative study might use experiments, surveys or questionnaires, analysis of large datasets like Statistics Canada data, or structured interviews and observations where questions and observation criteria are exactly the same for each participant. Quantitative studies tend to focus on numbers and things that can be measured. The qualitative study might use field research case studies or more open-ended interviews and observations where there's more room for flexibility and follow-up. The data in a qualitative study might be interview or focus group transcripts, observation notes, or journal entries. Because methods are different, data analysis techniques also vary. Between quantitative and qualitative studies, quantitative studies will feature statistical analyses, while qualitative studies might use text analysis and coding for themes in order to interpret data. While you'll probably see more numbers, charts, and graphs in a quantitative study, be careful. Just because you see these doesn't automatically mean the study is quantitative. Qualitative studies might report basic demographic information numerically before diving into qualitative analysis, so it's always important to read the study for additional information. Let's take a look at some examples. Here are three studies about adolescent mental health. We'll focus on their goals, methods, data, and data analysis techniques to determine if they're quantitative or qualitative. Our first study is about depression in female adolescents. According to the article, the goal of this exploratory study was to gain an understanding of female adolescents' own experiences of depression and give voice to their experiences. The method for doing this was six open-ended interviews regarding participants' experiences of depression. The data consisted of interview transcripts, and the article includes quotes from the interviews. A data analysis technique was interpretive phenomenological analysis in which researchers distilled themes from the interview transcripts. This is an example of a qualitative study. Our second example is about sleep issues as a risk factor for suicidal behavior in depressed children and adolescents. According to the article, the goal of this study was to investigate the association between sleep complaints and suicidal behaviors. In this population, the method for doing this was through a structured interview about sleep. The same questions for every participant, plus two tests, the children's depression rating scale and the children's global assessment scale. The data consisted of frequency of sleep issues from the interviews, as well as a numerical score. For the two scales, the researchers used statistical analysis to analyze the data and present the information about the correlation between variables using tables. This is an example of a quantitative study. Our last example is about self-labeling among adolescents with mental disorders or the impact of mental illness labels on teen psychological well-being. According to the article, the goal of this study was to investigate associations between self-labeling and perceived negative treatment by other clinical and demographic factors. The researchers had the hypothesis that many teens wouldn't self-label, and those that did would have worse psychological well-being. The researchers combined the methods to test this hypothesis. They did semi-structured interviews with some open-ended questions where teens could express their thoughts and emotions. They also used rating scales to quantify teens' experiences, like the Rosenberg self-esteem scale and the clinical information about each patient, like their type of disorder and age of first treatment for mental health issues. The data in the study consisted of interview transcripts, scores from the scales, and clinical information. Because researchers combined two methods, they also needed to use several data analysis techniques. The researchers used textual analysis to find themes in the interview transcripts, and they ran statistical analyses for relationships between the variables on the scale and the clinical information. The articles included quotes from the teens, as well as statistical tables. That was a bit of a trick question because this study uses both qualitative and quantitative methods. We call this kind of study a mixed-method study. So, what makes a better empirical study? Quantitative studies aren't automatically better or worse than qualitative studies. These two approaches are just different. Sometimes researchers even combine approaches to present a fuller picture through a mixed-method study. When you're evaluating a study's approach, ask yourself, how well do the methods and analyses fit the research question? If you need help with quantitative, qualitative, and mixed-method studies, you can always ask a librarian or other member of the library staff.