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Whether one is reading a research article to translate findings into evidence-based practice (EBP) or as a building block for a proposed study, the process often begins with appraising a single research article. Advanced practice nurses frequently read evidence (research, guidelines, reviews) to answer questions related to diagnosis, therapeutic interventions, and prognosis of individual patients (Dale et al., 2019). One of the barriers to translating research findings (and therefore providing evidence-based care or guideline-directed therapy) into practice is a lack of confidence in one’s ability to read and interpret research findings (Gray et al., 2017). The critical thinking skills nurses use in practice every day provide a foundation for developing the skill of reading and evaluating research.

Reading and evaluating literature is a critical skill in translating research into clinical practice. Previous chapters have addressed how to locate and retrieve evidence; chapters that follow detail the various elements and designs of collecting evidence and the reporting of results through publications. The purpose of this chapter is to review the sections of a single research article and to provide an organized approach to reading and interpreting the strength and relevance of the information presented in a data-based article.

The critical appraisal of the evidence determines the strengths, weaknesses, and usefulness of the findings for practice and future research. Using a published critical appraisal tool to evaluate the evidence guides the clinician through a comprehensive critique (Moralejo et al., 2017; Zuzelo, 2019). Clinicians must weigh the limitations and feasibility of the evidence with its strengths to evaluate if the evidence is usefulness to practice. One type of evidence clinicians appraise is a clinical research study. As a result, understanding the components of an article based on data and the important questions to consider while reading each section is needed.

All research articles are written with a standardized format. Components of an article based on data include the title, abstract, background or introduction and significance of the study, methods, data analysis, findings and results, discussion, limitations, and implications for practice. Minor variations in the formatting may be required by a journal for publication, for example, limitations may be included in the discussion. Even so, the logic of the researcher’s thinking should be clear enough so that the reader has few questions about how and why the study was conducted. By the end of the article, the reader should be able to determine how the research results fit into current knowledge and how (or whether) the findings translate to the practice environment for implementation or necessitate further testing and validation. As the reader progresses through the article, each section builds on the previous information. Exhibit 6.1 summarizes key elements 108to consider when appraising a data-based article and may serve as a general guide or checklist in reading the literature. This exhibit is one example of an appraisal tool; several other guides and tools are available including online software to assist in critically appraising the data-based literature.

The title describes and explains what the article is about. The title may include information about the focus or outcome of the research, the population studied, and the study design (Polit & Beck, 2020).

■ ABSTRACT

The first part of a research article is the abstract. The abstract is a brief, targeted summary of the full article that follows. Therefore a quality abstract presents a clear synopsis of the purpose, results, and research implications of the research manuscript. The abstract provides the reader with a succinct overview of the study and can be used to evaluate whether the study is of interest or applies to the reader’s practice setting or population (Alspach, 2017). Most readers use the abstract as a screen to determine whether or not to read the entire research article.

■ BACKGROUND (INTRODUCTION) AND SIGNIFICANCE

The background or introduction of a data-based article provides an overview of the current status of a specific field and a context for the research. The first few paragraphs provide the reader with an understanding of the background of the study, why the study was conducted, and why the study was important or significant. The reader should be able to identify gaps in current knowledge and how the proposed study specifically fills the gaps. Near the end of the section (or set apart), the purpose (also referred to as the aim) or problem statement of the study is presented. The purpose or problem statement is closely related. Both or only one may be included in an article. The purpose or problem statement should be clearly stated and provide the independent and 110dependent variables examined. The author may also include research questions, hypotheses tested in the study, or both. In any case, the reader will know the population (who) and the phenomenon (what) of interest. The reader uses this information to assess the remainder of the article.

■ LITERATURE REVIEW

In some cases, the background section includes a review of the literature. In other articles, the literature review is set apart as a separate section. The review of the literature should be appraised for both content and relevance. The literature presented should be relevant to the current study, relate to the variables that were studied, and be up to date. The literature review often includes reviews, theoretical and data-based sources. The previous research studies included in the background section should at the minimum address the purpose, sample, design, findings, and a brief critique of the study’s strengths and weaknesses (Gray et al., 2017). Another approach in reporting the research literature is to review and synthesize numerous studies and evaluate the body of knowledge. Whichever approach is used, the reader should understand the existing knowledge and how the study may address gaps in knowledge or expand current knowledge. The research literature included in the review may be directly or indirectly related to the purpose of the study. Indirectly related studies should be linked for relevance.

The reader should check the publication dates of the literature cited and of the reference list to judge whether the references are (at least reasonably) current. Although some studies are considered classics, much of the cited literature should be recent and reflect up-to-date thinking and understanding of the study’s focus. This is especially important in practice areas undergoing rapid change (e.g., genetics and genomics) and in areas that are time sensitive (e.g., attitudes and opinions). The reader’s personal knowledge and level of expertise in the content area are valuable in determining the currency and strength of the literature review included in the research article.

■ METHODS

A large section of the research article is the methods section, which describes how the study was conducted. The methods section includes design, sampling, instruments, and specific procedures for data collection (Polit & Beck, 2020). The methods section is a critical part of a research article and deserves careful attention. While reading the methods section, the reader should be alert for any problems in the way the study protocol was implemented, such as sample bias, inconsistencies in data collection among participants, loss of participants or attrition, and weaknesses of the instruments or tools used to collect the data. The strength of the methods section helps the reader determine the overall usefulness and generalizability of the results that will follow.

Design

The study design is identified early in the methods section if it has not already been implied in the purpose or problem statement. The author should identify whether the study used a quantitative, qualitative, or mixed methods design. Quantitative studies use designs that result in numerical data that can be used in statistical (mathematical) analyses and assess the size of relationships among variables (Al-Jundi & Sakka, 2017). Variables in quantitative designs may be measured using physiologic instruments (e.g., blood pressure and weight), questionnaires with fixed responses (e.g., scale of 1 to 5), or variables that can be assigned a number (e.g., age). Quantitative 111research designs may be further identified as experimental, quasi-experimental, or nonexperimental (descriptive or correlational), depending on how participants were chosen, whether and how study variables were manipulated, and how the data to measure the variables were collected (Gray et al., 2017).

Qualitative studies use a nonnumerical study approach to collect data, often to describe a phenomenon (Melnyk & Fineout-Overholt, 2019). The most common qualitative designs are ethnographic, phenomenological, historical, and grounded theory approaches. Just as in quantitative designs, there are specific and distinguishing elements among the qualitative designs. The goal of studies that use qualitative designs is to explore or explain the phenomenon of interest from the perspective of individuals experiencing the phenomenon. As a result, qualitative designs yield descriptions that can then be analyzed and coded for themes, common elements, and shared meaning among participants (Lewis, 2019). The end result of a qualitative design may be new knowledge or the beginning of a theory, whereas the end result of a quantitative study is often acceptance or rejection of current knowledge or theory.

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