How Are Empirical Journal Articles Different From Review Journal Articles?
three.ane Reading an empirical journal commodity
Learning Objectives
- Place the key components of empirical journal manufactures
- Ascertain the basic elements of the results section in a journal article
- Depict statistical significance and confidence intervals
Reading scholarly articles tin can be a more challenging than reading a book, mag, news article—or even some textbooks. Theoretical and practical manufactures are, generally speaking, easier to understand. Empirical articles, considering they add together new knowledge, must get through corking detail to demonstrate that the information they offering is based on solid science. Empirical manufactures tin exist challenging to read, and this section is designed to brand that process easier for you lot.
Nearly all articles will take an abstract, the short paragraph at the kickoff of an commodity that summarizes the author'south enquiry question, methods used to answer the question, and primal findings. The abstract may also give you some thought virtually the theoretical perspective of the author. In effect, the abstract provides y'all with a framework to empathise the residuum of the article and the article'southward punch line: what the author(southward) found, and whether the commodity is relevant to your area of inquiry. For this reason, I suggest skimming abstracts as part of the literature search procedure.
Every bit yous will recall from Chapter 2, theoretical articles have no set structure and will await similar to reading a chapter of a book. Empirical articles contain the following sections (although exact section names vary): introduction, methods, results, and word. The introduction contains the literature review for the article and is an fantabulous source of information as you build your own literature review. The methods section reviews how the author gathered their sample, how they measured their variables, and how the data were analyzed. The results department provides an in-depth discussion of the findings of the study. The discussion section reviews the main findings and addresses how those findings fit in with the existing literature. At the terminate, in that location volition be a list of references (which you should read!) and in that location may exist a few tables, figures, or appendices if applicative.
While you should get into the habit of familiarizing yourself with each role of the articles you wish to cite, there are strategic ways to read journal articles that tin make them a little easier to digest. One time y'all have read the abstruse for an article and adamant it is 1 you'd like to read in total, read through the introduction and discussion sections adjacent. The introduction section will showcase other manufactures and findings that are significant in your topic area, so reading through it will be beneficial for your own information-gathering process for your literature review. Reading an article's discussion section helps you sympathize what the author views every bit their study's major findings and how the writer perceives those findings to relate to other enquiry.
As you progress through your research methods course, you lot will pick up additional research elements that are important to empathize. Yous volition larn how to identify qualitative and quantitative methods, as well every bit exploratory, explanatory, and descriptive research methods. You lot will besides learn the criteria for establishing causality and the different types of causality. Subsequent capacity of this textbook will address other elements of periodical articles, including choices about measurement, sampling, and design. Equally you larn near these additional items, you volition find that the methods and results sections begin to brand more sense and you will understand how the authors reached their conclusions.
Every bit you read a research study, there are several questions you can inquire yourself about each section, from abstract to conclusion. Those questions are summarized in Table iii.one. Keep in mind that the questions covered here are designed to assistance yous, the reader, to retrieve critically nearly the inquiry y'all see and to get a general understanding of the strengths, weaknesses, and key takeaways from a given study. I hope that by considering how you might respond to the following questions while reading research reports, yous'll proceeds conviction in describing the report to others and discussing its pregnant and touch on with them.
| Report section | Questions worth asking |
| Abstract | What are the key findings? How were those findings reached? What framework does the researcher employ? |
| Acknowledgments | Who are this study's major stakeholders? Who provided feedback? Who provided support in the form of funding or other resources? |
| Problem statement (introduction) | How does the author frame their research focus? What other possible ways of framing the trouble exist? Why might the author accept chosen this particular fashion of framing the problem? |
| Literature review (introduction) | How selective does the researcher appear to accept been in identifying relevant literature to discuss? Does the review of literature appear appropriately extensive? Does the researcher provide a critical review? |
| Sample (methods) | Where was the data nerveless? Did the researcher collect their own data or use someone else's information? What population is the study trying to brand claims nearly, and does the sample represent that population well? What are the sample'due south major strengths and major weaknesses? |
| Data collection (methods) | How were the information collected? What do you lot know about the relative strengths and weaknesses of the method employed? What other methods of data collection might accept been employed, and why was this particular method employed? What practice y'all know almost the data drove strategy and instruments (e.1000., questions asked, locations observed)? What don't you know about the data drove strategy and instruments? |
| Information assay (methods) | How were the data analyzed? Is in that location plenty data provided for you to feel confident that the proper analytic procedures were employed accurately? |
| Results | What are the study'southward major findings? Are findings linked back to previously described research questions, objectives, hypotheses, and literature? Are sufficient amounts of information (e.grand., quotes and observations in qualitative work, statistics in quantitative work) provided in social club to support conclusions fatigued? Are tables readable? |
| Discussion/conclusion | Does the author generalize to some population across her/his/their sample? How are these claims presented? Are claims made supported by data provided in the results section (e.g., supporting quotes, statistical significance)? Have limitations of the study been fully disclosed and adequately addressed? Are implications sufficiently explored? |
Understanding the results section
As mentioned previously in this chapter, reading the abstract that appears in most reports of scholarly enquiry will provide you with an excellent, hands digestible review of a written report's major findings and of the framework the author is using to position their findings. Abstracts typically comprise only a few hundred words, and so reading them is a nice way to quickly familiarize yourself with a study. If the study seems relevant to your newspaper, it'south probably worth reading more. If it's not, and then you have only spent a minute or so reading the abstract. Another way to become a snapshot of the article is to scan the headings, tables, and figures throughout the written report (Green & Simon, 2012).[i]
At this betoken, I have read hundreds of literature reviews written by students. 1 of the challenges I accept noted is that students will report the summarized results from the abstruse, rather than the detailed findings in the results department of the article. This is a problem when you are writing a literature review because yous need to provide specific and clear facts that support your reading of the literature. The abstract may say something like: "we found that poverty is associated with mental health status." For your literature review, you lot desire the details, not the summary. In the results section of the article, you may find a judgement that states: "for households in poverty, children are 3 times more likely to have a mental health diagnosis." This more detailed data provides a stronger basis on which to build a literature review.
Using the summarized results in an abstract is an understandable error to make. The results department often contains terminology, diagrams, and symbols that may be difficult to understand without having completed advanced coursework on statistical or qualitative assay. To that end, the purpose of this department is to amend reading comprehension by providing an introduction to the basic components of a results section.
Journal articles often comprise tables, and scanning them is a practiced way to begin reading an article. A table provides a quick, condensed summary of the report's key findings. The use of tables is not limited to one form or type of data, though they are used almost commonly in quantitative research. Tables are a concise fashion to written report big amounts of data. Some tables present descriptive information about a researcher'south sample, which is often the first table in a results section. These tables will probable contain frequencies (N) and percentages (%). For example, if gender happened to be an important variable for the researcher's analysis, a descriptive table would show how many and what percent of all written report participants are women, men, or other genders. Frequencies or counts will probably be listed as N, while the percent symbol (%) might be used to indicate percentages.
In a tabular array presenting a causal relationship, two sets of variables are represented. The contained variable, or cause, and the dependent variable, the effect. We'll go into more particular on variables in Chapter 6. The independent variable attributes are typically presented in the table'due south columns, while dependent variable attributes are presented in rows. This allows the reader to scan across a table's rows to meet how values on the dependent variable attributes modify as the contained variable aspect values alter. Tables displaying results of quantitative analysis volition also likely include some information nearly the strength and statistical significance of the relationships presented in the table. These details tell the reader how likely it is that the relationships presented will accept occurred simply past hazard.
Let'southward expect at a specific example. Table 3.2 shows information from a report of older adults that was conducted by Dr. Blackstone, an original author of this textbook. It presents the causal relationship between gender and the experience of harassing behaviors in the workplace. In this example, gender is the independent variable (the cause) and the harassing behaviors listed are the dependent variables (the effects). [two] Therefore, nosotros place gender in the table's columns and harassing behaviors in the table'due south rows.
Reading across the table's top row, we run across that 2.9% of women in the sample reported experiencing subtle or obvious threats to their condom at work, while 4.7% of men in the sample reported the aforementioned. We can read across each of the rows of the table in this way. Reading across the bottom row, we meet that 9.4% of women in the sample reported experiencing staring or invasion of their personal space at piece of work while simply 2.iii% of men in the sample reported having the same experience. We'll discuss p value later in this section.
| Behavior Experienced at work | Wome n | Men | p valu e |
| Subtle or obvious threats to your safety | two.9% | 4.vii% | 0.623 |
| Existence hit, pushed, or grabbed | two.2% | 4.vii% | 0.480 |
| Comments or behaviors that demean your gender | 6.v% | 2.3% | 0.184 |
| Comments or behaviors that demean your historic period | 13.viii% | 9.three% | 0.407 |
| Staring or invasion of your personal infinite | 9.4% | 2.3% | 0.039 |
| Note: Sample size was 138 for women and 43 for men. | |||
These statistics represent what the researchers found in their sample, and they are using their sample to make conclusions about the truthful population of all employees in the real globe. Because the methods nosotros use in social science are never perfect, there is some amount of mistake in that value. The researchers in this study estimated the true value we would go if nosotros asked every employee in the globe the same questions on our survey. Researchers will often provide a confidence interval, or a range of values in which the truthful value is likely to be, to provide a more than accurate clarification of their data. For example, at the time I'thou writing this, my married woman and I are expecting our first kid next month. The md told us our due date was August 15th. But the doctor besides told us that August 15th was merely their all-time estimate. They were actually 95% sure our baby might be born any time between August 1st and September 1st. Confidence intervals are often listed with a percentage, similar xc% or 95%, and a range of values, such as betwixt August 1st and September 1st. Y'all can read that every bit: we are 95% certain your baby will be born between August 1st and September 1st. So, while we get a due appointment of August 15th, the doubtfulness well-nigh the exact appointment is reflected in the confidence interval provided by our doctor.
Of course, we cannot assume that these patterns didn't but occur by take chances. How confident can nosotros be that the findings presented in the tabular array did not occur by chance? This is where tests of statistical significance come in handy. Statistical significance tells us the likelihood that the relationships we find could exist caused by something other than chance. While your statistics class volition give you more specific details on tests of statistical significance and reading quantitative tables, the important thing to exist aware of as a not-expert reader of tables is that some of the relationships presented volition be statistically significant and others may not exist. Tables should provide information nigh the statistical significance of the relationships presented. When reading a researcher's conclusions, pay attention to which relationships are statistically significant and which are not.
In Tabular array three.two, you may have noticed that a p value is noted in the very final column of the table. A p value is a statistical measure of the probability that at that place is no human relationship betwixt the variables nether written report. Some other fashion of putting this is that the p value provides guidance on whether or not we should reject the cipher hypothesis. The null hypothesis is simply the assumption that no human relationship exists between the variables in question. In Tabular array 3.2, nosotros encounter that for the offset behavior listed, the p value is 0.623. This means that there is a 62.3% chance that the zippo hypothesis is right in this instance. In other words, it seems likely that any relationship between observed gender and experiencing threats to safety at work in this sample is simply due to hazard.
In the final row of the table, however, we see that the p value is 0.039. In other words, there is a 3.9% take chances that the null hypothesis is right. Thus, nosotros can be somewhat more confident than in the preceding case that there may exist some relationship between a person'due south gender and their experiencing the behavior noted in this row. Statistical significance is reported in reference to a value, unremarkably 0.05 in the social science. This means that the probability that the relationship between gender and experiencing staring or invasion of personal space at work is due to random gamble is less than five in 100. Social scientific discipline oftentimes uses 0.05, just other values are used. Studies using 0.ane are using a more forgiving standard of significance, and therefore, have a higher likelihood of error (10%). Studies using 0.01 are using a more stringent standard of significance, and therefore, accept a lower likelihood of mistake (1%).
Discover that I'm hedging my bets here by using words like somewhat and may exist. When testing hypotheses, social scientists generally phrase their findings in terms of rejecting the null hypothesis rather than making bold statements about the relationships observed in their tables. You can learn more about creating tables, reading tables, and tests of statistical significance in a course focused exclusively on statistical assay. For now, I promise this brief introduction to reading tables volition improve your confidence in reading and agreement the quantitative tables y'all encounter while reading reports of social science inquiry.
A final caveat is worth noting hither. The previous discussion of tables and reading the results section is applicable to quantitative articles. Quantitative articles will comprise a lot of numbers and the results of statistical tests demonstrating association between those numbers. Qualitative articles, on the other hand, will consist mostly of quotations from participants. For nigh qualitative manufactures, the authors desire to put their results in the words of their participants, as they are the experts. The results department may exist organized by theme, with each paragraph or subsection illustrating through quotes how the authors interpret what people in their study said.
Key Takeaways
- Reading a research article requires reading beyond the abstract.
- In tables presenting causal relationships, the independent variable is typically presented in the table's columns while the dependent variables are presented in the table's rows.
- When reading a enquiry report, in that location are several key questions you should ask yourself for each section of the report.
Glossary
Abstract– the brusk paragraph at the starting time of an article that summarizes its master indicate
Confidence interval– a range of values in which the true value is probable to exist
Null hypothesis– the assumption that no relationship exists betwixt the variables in question
p-value– a statistical measure of the probability that in that location is no relationship between the variables nether study
Statistical significance– the likelihood that the relationships that are observed could be caused by something other than chance
Table– a quick, condensed summary of the report's central findings
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Source: https://scientificinquiryinsocialwork.pressbooks.com/chapter/3-1-reading-an-empirical-journal-article/
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