Key Concepts and Steps in Qualitative and Quantitative Research

Key Concepts and Steps in Qualitative and Quantitative Research

Ch. 3: Key Concepts and Steps in Qualitative and Quantitative Research


3: Key Concepts and Steps in Qualitative and Quantitative Research

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This chapter covers a lot of ground—but, for many of you, it is familiar ground. For those who have taken an earlier research course, this chapter provides a review of key terms and steps in the research process. For those without previous exposure to research methods, this chapter offers basic grounding in research terminology.

Research, like any discipline, has its own language—its own jargon. Some terms are used by both qualitative and quantitative researchers, but others are used mainly by one or the other group. To make matters more complex, some nursing research jargon has its roots in the social sciences, but sometimes different terms for the same concepts are used in medical research; we cover both.


When researchers address a problem—regardless of the underlying paradigm—they undertake a study(or an investigation). Studies involve people working together in different roles.

The Faces and Places of Research

Studies with humans involve two sets of people: those who do the research and those who provide the information. In a quantitative study, the people being studied are called subjects or study participants( Table 3.1 ). In a qualitative study, those cooperating in the study are called study participants,  informants , or key informants. Collectively, study participants comprise the  sample .

TABLE 3.1: Key Terms in Quantitative and Qualitative Research

Person contributing information Subject

Study participant

Study participant

Informant, key informant

Person undertaking the study Researcher




That which is being investigated






System of organizing concepts Theory, theoretical framework

Conceptual framework, conceptual model


Conceptual framework, sensitizing framework

Information gathered Data (numerical values) Data (narrative descriptions)
Connections between concepts Relationships (cause-and-effect, associative) Patterns of association
Logical reasoning processes Deductive reasoning Inductive reasoning

The person who conducts a study is the researcher or investigator. When a study is done by a team, the person directing the study is the  principal investigator (PI) . In large-scale projects, dozens of individuals may be involved in planning, managing, and conducting the study. The following examples of staffing configurations span the continuum from an extremely large project to a more modest one.

Examples of Staffing on a Quantitative Study: The first author of this book was involved in a multicomponent, interdisciplinary study of poor women living in four major U.S. cities. As part of the study, she and two colleagues prepared a report documenting the health problems of 4,000 welfare mothers who were interviewed twice over a 3-year period (Polit et al., 2001). The project was staffed by over 100 people, including lead investigators of six project components (Polit was one), over 50 interviewers, and dozens of research assistants, computer programmers, and other support staff. Several health consultants, including a prominent nurse researcher (Linda Aiken), served as reviewers.

Examples of Staffing on a Qualitative Study: Beck (2009) conducted a qualitative study focusing on the experiences of mothers caring for their children with a brachial plexus injury. The team consisted Beck as the PI (who gathered and analyzed all the data), members of the United Brachial Plexus Executive Board (who helped to recruit mothers for the study), a transcriber (who listened to the tape-recorded interviews and typed them up verbatim), and an undergraduate nursing student (who checked the accuracy of the interview transcripts against the tape-recorded interviews).

Research can be undertaken in a variety of settings (the specific places where information is gathered) and in one or more sites. Some studies take place in  naturalistic settings  in the field, such as in people’s homes, but some studies are done in controlled laboratory or clinical settings. Qualitative researchers are especially likely to engage in  fieldwork  in natural settings because they are interested in the contexts of people’s experiences. The site is the overall location for the research—it could be an entire community (e.g., a Haitian neighborhood in Miami) or an institution (e.g., a hospital in Toronto). Researchers sometimes engage in multisite studies because the use of multiple sites offers a larger or more diverse sample of participants.

The Building Blocks of Research

Phenomena, Concepts, and Constructs

Research involves abstractions. For example, painquality of life, and resilience are abstractions of particular aspects of human behavior and characteristics. These abstractions are called  concepts  or, in qualitative studies, phenomena.

Researchers also use the term  construct . Like a concept, a construct is an abstraction inferred from situations or behaviors. Kerlinger and Lee (2000) distinguish concepts from constructs by noting that constructs are abstractions that are deliberately invented (constructed) by researchers. For example, self-care in Orem’s model of health maintenance is a construct. The terms construct and concept are sometimes used interchangeably but, by convention, a construct typically refers to a more complex abstraction than a concept.

Theories and Conceptual Models

 theory  is a systematic, abstract explanation of some aspect of reality. Theories, which knit concepts together into a coherent system, play a role in both qualitative and quantitative research.

Quantitative researchers may start with a theory, framework, or conceptual model (distinctions are discussed in  Chapter 6 ). Based on theory, researchers predict how phenomena will behave in the real world if the theory is true—researchers use deductive reasoning to go from a theory to specific hypotheses. Predictions deduced from theory are tested through research, and results are used to support, reject, or modify the theory.

In qualitative research, theories may be used in various ways. Sometimes conceptual or sensitizing frameworks, derived from qualitative research traditions we describe later in this chapter, offer an orienting worldview. In such studies, the framework helps to guide the inquiry and to interpret research evidence. In other qualitative studies, theory is the product of the research: The investigators use information from participants inductively to develop a theory rooted in the participants’ experiences.

Deductive and inductive logical reasoning processes are described more fully on the Supplement to this chapter on .


In quantitative studies, concepts often are called variables. A variable, as the name implies, is something that varies. Weight, fatigue, and anxiety are variables—each varies from one person to another. In fact, most aspects of humans are variables. If everyone weighed 150 pounds, weight would not be a variable, it would be a constant. It is precisely because people and conditions do vary that most research is conducted. Quantitative researchers seek to understand how or why things vary and to learn if differences in one variable are related to differences in another. For example, lung cancer research is concerned with the variable of lung cancer, which is a variable because not everyone has this disease. Researchers have studied factors that might be linked to lung cancer, such as cigarette smoking. Smoking is also a variable because not everyone smokes. A variable, then, is any quality of a person, group, or situation that varies or takes on different values. Variables are the building blocks of quantitative studies.

When an attribute is highly varied in the group under study, the group is heterogeneous with respect to that variable. If the amount of variability is limited, the group is homogeneous. For example, for the variable height, a sample of 2-year-old children would be more homogeneous than a sample of 21-year-olds.

Variables may be inherent characteristics of people, such as their age, blood type, or weight. Sometimes, however, researchers create a variable. For example, if a researcher tests the effectiveness of patient-controlled analgesia as opposed to intramuscular analgesia in relieving pain after surgery, some patients would be given patient-controlled analgesia and others would receive intramuscular analgesia. In the context of this study, method of pain management is a variable because different patients get different analgesic methods.

Continuous, Discrete, and Categorical Variables.

Some variables take on a wide range of values. A person’s age, for instance, can take on values from zero to more than 100, and the values are not restricted to whole numbers.  Continuous variables  have values along a continuum and, in theory, can assume an infinite number of values between two points. Consider the continuous variable weight: between 1 and 2 pounds, the number of values is limitless: 1.05, 1.8, 1.333, and so on.

By contrast, a  discrete variable  has a finite number of values between any two points, representing discrete quantities. For example, if people were asked how many children they had, they might answer 0, 1, 2, 3, or more. The value for number of children is discrete, because a number such as 1.5 is not meaningful. Between 1 and 3, the only possible value is 2.

Other variables take on a small range of values that do not represent a quantity. Blood type, for example, has four values—A, B, AB, and O. Variables that take on a handful of discrete nonquantitative values are  categorical variables . When categorical variables take on only two values, they are  dichotomous variables . Gender, for example, is dichotomous: male and female.

Dependent and Independent Variables.

Many studies seek to unravel and understand causes of phenomena. Does a nursing intervention causeimprovements in patient outcomes? Does smoking cause lung cancer? The presumed cause is the  independent variable , and the presumed effect is the  dependent variable  (or, the  outcome variable ). In terms of the PICO scheme discussed in  Chapter 2 , the dependent variable corresponds to the “O” (outcome). The independent variable corresponds to the “I” (the intervention, influence, or exposure) plusthe “C” (the comparison). In searching for existing evidence, you might want to learn about the effects of an intervention or influence (I), compared to any alternative, on an outcome (O) of interest. In a study, however, researchers must always specify the comparator (the “C”).

Variation in the dependent variable is presumed to depend on variation in the independent variable. For example, researchers study the extent to which lung cancer (the dependent variable) depends on smoking (the independent variable). Or, investigators might study the extent to which patients’ pain (the dependent variable) depends on different nursing actions (the independent variable). The dependent variable is the outcome that researchers want to understand, explain, or predict.

The terms independent variable and dependent variable can also be used to indicate direction of influence rather than a cause and effect. For example, suppose a researcher studied the mental health of the spousal caregivers of patients with Alzheimer’s disease and found lower depression for wives than for husbands. We could not conclude that depression was caused by gender. Yet the direction of influence clearly runs from gender to depression: A patient’s level of depression does not influence their gender. Although it may not make sense to infer a cause-and-effect connection, it is appropriate to consider depression as the outcome variable and gender as an independent variable.

Most outcomes have multiple causes or influences. If we were studying factors that influence people’s body mass index (the dependent variable), we might consider height, physical activity, and diet as independent variables. Two or more dependent variables also may be of interest. For example, a researcher may compare the effects of two methods of nursing care for children with cystic fibrosis. Several dependent variables could be used to assess treatment effectiveness, such as length of hospital stay, number of recurrent respiratory infections, and so on. It is common to design studies with multiple independent and dependent variables.

Variables are not inherently dependent or independent. A dependent variable in one study could be an independent variable in another. For example, a study might examine the effect of an exercise intervention (the independent variable) on osteoporosis (the dependent variable) to answer a Therapy question. Another study might investigate the effect of osteoporosis (the independent variable) on bone fracture incidence (the dependent variable) to address a Prognosis question. In short, whether a variable is independent or dependent is a function of the role that it plays in a particular study.

Example of Independent and Dependent Variables: Research question (Etiology/Harm question): Are interruptions during patient medication rounds in a mental health hospital associated with higher rates of nurses’ medication-administration errors? (Cottney & Innes, 2015)

Independent variable: Interruptions during medication rounds

Dependent variable: Medication administration errors

Conceptual and Operational Definitions

Concepts are abstractions of observable phenomena, and researchers’ worldviews shape how those concepts are defined. A  conceptual definition  presents the abstract or theoretical meaning of concepts under study. Even seemingly straightforward terms need to be conceptually defined. The classic example is the concept of caring. Morse and colleagues (1990) examined how researchers and theorists defined caring and identified five classes of conceptual definition: as a human trait, a moral imperative, an affect, an interpersonal relationship, and a therapeutic intervention. Researchers undertaking studies of caring need to clarify which conceptual definition they have adopted.

In qualitative studies, conceptual definitions of key phenomena may be a major end product, reflecting an intent to have the meaning of concepts defined by those being studied. In quantitative studies, however, researchers must define concepts at the outset because they must decide how the variables will be observed and measured. An  operational definition  of a concept specifies what the researchers must do to measure the concept and collect needed information.

Variables differ in the ease with which they can be operationalized. The variable weight, for example, is easy to define and measure. We might operationally define weight as the amount that an object weighs, to the nearest half pound. This definition designates that weight will be measured using one system (pounds) rather than another (grams). We could also specify that weight will be measured using a digital scale with participants fully undressed after 10 hours of fasting. This operational definition clarifies what we mean by the variable weight.

Few variables are operationalized as easily as weight. Most variables can be measured in different ways, and researchers must choose the one that best captures the variables as they conceptualize them. Take, for example, anxiety, which can be defined in terms of both physiologic and psychological functioning. For researchers choosing to emphasize physiologic aspects, the operational definition might involve a measure such as pulse rate. If researchers conceptualize anxiety as a psychological state, the operational definition might be scores on a paper-and-pencil test such as the State Anxiety Scale. Readers of research articles may not agree with how variables were conceptualized and measured, but definitional precision is important for communicating exactly what concepts mean within the study.

TIP: Operationalizing a concept is often a two-part process that involves deciding (1) how to accurately measure the variable and (2) how to represent it in an analysis. For example, a person’s age might be obtained by asking them to report their birthdate but operationalized in an analysis in relation to a threshold (e.g., under 65 versus 65 or older).

Example of Conceptual and Operational Definitions: Fogg and colleagues (2011) developed a scale to measure people’s beliefs and intentions about HIV screening. The scale relied on constructs from a theory called the Theory of Planned Behavior (see  Chapter 6 ). The researchers provided examples of both conceptual and operational definitions of key constructs. For example, “subjective norm” was conceptually defined as “the overall perception of social pressure to perform or not perform the behavior” and a scale item used to measure this construct in the context of HIV screening was “The people in my life whose opinions I value are regularly tested for HIV” (p. 76).


Research  data  (singular, datum) are the pieces of information obtained in a study. In quantitative studies, researchers identify and define their variables and then collect relevant data from study participants. Quantitative researchers collect primarily  quantitative data —data in numeric form. For example, suppose we conducted a quantitative study in which a key variable was depression. We might ask, “Thinking about the past week, how depressed would you say you have been on a scale from 0 to 10, where 0 means ‘not at all’ and 10 means ‘the most possible’?”  Box 3.1  presents quantitative data for three fictitious people. Subjects provided a number along the 0 to 10 continuum representing their degree of depression—9 for subject 1 (a high level of depression), 0 for subject 2 (no depression), and 4 for subject 3 (little depression). The numeric values for all people, collectively, would comprise the data on depression.

BOX 3.1: Example of Quantitative Data

Question: Thinking about the past week, how depressed would you say you have been on a scale from 0 to 10, where 0 means “not at all” and 10 means “the most possible”?
Data: 9 (Subject 1)

0 (Subject 2)

4 (Subject 3)

In qualitative studies, researchers collect  qualitative data , that is, narrative descriptions. Narrative information can be obtained by having conversations with participants, by making detailed notes about how people behave in naturalistic settings, or by obtaining narrative records, such as diaries. Suppose we were studying depression qualitatively.  Box 3.2  presents qualitative data for three people responding conversationally to the question, “Tell me about how you’ve been feeling lately—have you felt sad or depressed at all, or have you generally been in good spirits?” The data consist of rich narrative descriptions of participant’s emotional state.

BOX 3.2: Example of Qualitative Data

Question: Tell me about how you’ve been feeling lately—have you felt sad or depressed at all, or have you generally been in good spirits?
Data: “Well, actually, I’ve been pretty depressed lately, to tell you the truth. I wake up each morning and I can’t seem to think of anything to look forward to. I mope around the house all day, kind of in despair. I just can’t seem to shake the blues, and I’ve begun to think I need to go see a shrink.” (Participant 1)

“I can’t remember ever feeling better in my life. I just got promoted to a new job that makes me feel like I can really get ahead in my company. And I’ve just gotten engaged to a really great guy who is very special.” (Participant 2)

“I’ve had a few ups and downs the past week, but basically things are on a pretty even keel. I don’t have too many complaints.” (Participant 3)


Researchers are rarely interested in isolated concepts, except in descriptive studies. For example, a researcher might describe the percentage of patients receiving intravenous (IV) therapy who experience IV infiltration. In this example, the variable is IV infiltration versus no infiltration. Usually, however, researchers study phenomena in relation to other phenomena—that is, they focus on relationships. A  relationship  is a bond or a connection between phenomena. For example, researchers repeatedly have found a relationship between cigarette smoking and lung cancer. Both qualitative and quantitative studies examine relationships but in different ways.

In quantitative studies, researchers examine the relationship between the independent and dependent variables. Researchers ask whether variation in the dependent variable (the outcome) is systematically related to variation in the independent variable. Relationships are usually expressed in quantitative terms, such as more thanless than, and so on. For example, let us consider a person’s weight as our dependent variable. What variables are related to (associated with) body weight? Some possibilities are height, caloric intake, and exercise. For each independent variable, we can make a prediction about its relationship to the outcome variable:

· Height: Taller people will weigh more than shorter people.

· Caloric intake: People with higher caloric intake will be heavier than those with lower caloric intake.

· Exercise: The lower the amount of exercise, the greater will be the person’s weight.

Each statement expresses a predicted relationship between weight (the dependent variable) and a measurable independent variable. Terms such as more than and heavier than imply that as we observe a change in one variable, we are likely to observe a change in weight. If Alex is taller than Tom, we would predict (in the absence of any other information) that Alex is heavier than Tom.

Quantitative studies can address one or more of the following questions about relationships:

·  Does a relationship between variables exist? (e.g., Is cigarette smoking related to lung cancer?)

·  What is the direction of the relationship between variables? (e.g., Are people who smoke more likely or less likely to get lung cancer than those who do not?)

·  How strong is the relationship between the variables? (e.g., How much higher is the risk that smokers will develop lung cancer?)

·  What is the nature of the relationship between variables? (e.g., Does smoking cause lung cancer? Does some other factor cause both smoking and lung cancer?)

As the last question suggests, variables can be related to one another in different ways. One type of relationship is called a cause-and-effect (or causal relationship . Within the positivist paradigm, natural phenomena are assumed not to be haphazard; they have antecedent causes that are presumably discoverable. In our example about a person’s weight, we might speculate that there is a causal relationship between caloric intake and weight: Consuming more calories causes weight gain. As noted in  Chapter 1 , many quantitative studies are cause-probing—they seek to illuminate the causes of phenomena.

Example of a Study of Causal Relationships: Townsend-Gervis and colleagues (2014) studied whether interdisciplinary rounds and a structured communication protocol had an impact on patient satisfaction, patient readmission, and Foley catheter removal compliance.

As noted earlier, not all relationships between variables can be interpreted as causal ones. There is a relationship, for example, between a person’s pulmonary artery and tympanic temperatures: People with high readings on one tend to have high readings on the other. We cannot say, however, that pulmonary artery temperature caused tympanic temperature nor that tympanic temperature caused pulmonary artery temperature. This type of relationship is called a functional (or an associative relationship  rather than as a causal relationship.

Example of a Study of Associative Relationships: Hsieh and colleagues (2014) examined the relationship between physical activity, body mass index, and cardiorespiratory fitness among Taiwanese school children.

Qualitative researchers are not concerned with quantifying relationships nor in testing causal relationships. Qualitative researchers seek patterns of association as a way to illuminate the underlying meaning and dimensionality of phenomena. Patterns of interconnected themes and processes are identified as a means of understanding the whole.

Example of a Qualitative Study of Patterns: Martsolf and colleagues (2012) investigated patterns of dating violence in 88 young adults aged 18 to 21 who had experienced violent dating relationships as teenagers. Analysis of the in-depth interviews revealed four patterns of adolescent dating violence based on the number of violent relationships in which each teen had been involved.


Researchers usually work within a paradigm that is consistent with their worldview and that gives rise to questions that excite their curiosity. The maturity of the focal concept also may lead to one or the other paradigm: When little is known about a topic, a qualitative approach is often more fruitful than a quantitative one. In this section, we briefly describe broad categories of quantitative and qualitative research.

Quantitative Research: Experimental and Nonexperimental Studies

A basic distinction in quantitative studies is between experimental and nonexperimental research. In  experimental research , researchers actively introduce an intervention or treatment—most often, to address Therapy questions. In  nonexperimental research , researchers are bystanders—they collect data without intervening (most often, to address Etiology, Prognosis, or Diagnosis questions). For example, if a researcher gave bran flakes to one group of people and prune juice to another to evaluate which method facilitated elimination more effectively, the study would be experimental because the researcher intervened in the normal course of things. If, on the other hand, a researcher compared elimination patterns of two groups whose regular eating patterns differed, the study would be nonexperimental because there is no intervention. In medical research, an experimental study usually is called a  clinical trial , and a nonexperimental inquiry is called an observational study. As we discuss in  Chapter 9 , a randomized controlled trial or RCT is a particular type of clinical trial.

TIP: On the evidence hierarchy shown in  Figure 2.1 , the two rungs below systematic reviews (RCTs and quasi-experiments) involve interventions and are experimental. The four rungs below that are nonexperimental.

Experimental studies are explicitly cause-probing—they test whether an intervention caused changes in the dependent variable. Sometimes nonexperimental studies also explore causal relationships, but the resulting evidence is usually less conclusive. Experimental studies offer the possibility of greater control over confounding influences than nonexperimental studies, and so causal inferences are more plausible.

Example of Experimental Research: Williams and colleagues (2014) tested the effect of an intervention called Reasoning Exercises in Assisted Living on residents’ problem solving and reasoning. Some study participants received the cognitive training intervention, and others did not.

In this example, the researchers intervened by giving some patients the special intervention but not giving it to others. In other words, the researcher controlled the independent variable, which in this case was receipt or nonreceipt of the cognitive training intervention.

Example of Nonexperimental Research: Huang and colleagues (2014) studied factors that predicted fatigue severity in Taiwanese women with breast cancer 1 year after surgery. They found, for example, that women who were married and who had poorer functional performance at diagnosis had higher levels of fatigue.

In this nonexperimental study to address a Prognosis question, the researchers did not intervene in any way. Their intent was to explore existing relationships rather than to test a potential solution to a problem.

Qualitative Research: Disciplinary Traditions

The majority of qualitative studies can best be described as qualitative descriptive research. Many qualitative studies, however, are rooted in research traditions that originated in anthropology, sociology, and psychology. Three such traditions that are prominent in qualitative nursing research are briefly described here.  Chapter 21  provides a fuller discussion of these traditions and the methods associated with them.

Grounded theory  research, with roots in sociology, seeks to describe and understand the key social psychological processes that occur in social settings. Most grounded theory studies focus on a developing social experience—the social and psychological processes that characterize an event or episode. A major component of grounded theory is the discovery of not only the basic social psychological problem but also a core variable that is central in explaining what is going on in that social scene. Grounded theory researchers strive to generate explanations of phenomena that are grounded in reality. Grounded theory was developed in the 1960s by two sociologists, Glaser and Strauss (1967).

Example of a Grounded Theory Study: Ramirez and Badger (2014) conducted a grounded theory study to explore the social psychological processes of men who suffer from depression. They uncovered six stages through which men navigated in their experiences with depression.

Phenomenology , rooted in a philosophical tradition developed by Husserl and Heidegger, is concerned with the lived experiences of humans. Phenomenology is an approach to thinking about what life experiences of people are like and what they mean. The phenomenologic researcher asks the questions: What is the essence of this phenomenon as experienced by these people? Or, What is the meaning of the phenomenon to those who experience it?

Example of a Phenomenologic Study: Ekwall and co-researchers (2014) conducted in-depth interviews to explore the lived experience of having recurring ovarian cancer.

Ethnography , the primary research tradition in anthropology, provides a framework for studying the patterns, lifeways, and experiences of a defined cultural group in a holistic manner. Ethnographers typically engage in extensive fieldwork, often participating in the life of the culture under study. Ethnographic research can be concerned with broadly defined cultures (e.g., Hmong refugee communities) but sometimes focuses on more narrowly defined cultures (e.g., the culture of an intensive care unit). Ethnographers strive to learn from members of a cultural group, to understand their worldview, and to describe their customs and norms.

Example of an Ethnographic Study: Broadbent and colleagues (2014) conducted ethnographic fieldwork to investigate the emergency department triage environment and its effect on triage practices for clients with a mental illness.


In quantitative studies, researchers move from the beginning of a study (posing a question) to the end point (obtaining an answer) in a reasonably linear sequence of steps that is broadly similar across studies. In some studies, the steps overlap; in others, some steps are unnecessary. Still, a general flow of activities is typical in a quantitative study (see  Figure 3.1 ). This section describes that flow, and the next section describes how qualitative studies differ.



Phase 1: The Conceptual Phase

Early steps in a quantitative study typically have a strong conceptual element. These activities include reading, conceptualizing, theorizing, and reviewing ideas with colleagues or advisers. During this phase, researchers call on such skills as creativity, deductive reasoning, and a firm grounding in previous research on a topic of interest.

Step 1: Formulating and Delimiting the Problem

Quantitative researchers begin by identifying an interesting, significant research problem and formulating research questions. Good research requires starting with good questions. In developing research questions, nurse researchers must attend to substantive issues (What kind of new evidence is needed?), theoretical issues (Is there a conceptual context for understanding this problem?), clinical issues (How could evidence from this study be used in clinical practice?), methodologic issues (How can this question best be studied to yield high-quality evidence?), and ethical issues (Can this question be rigorously addressed in an ethical manner?)

TIP: A critical ingredient in developing good research questions is personal interest. Begin with topics that fascinate you or about which you have a passionate interest or curiosity.

Step 2: Reviewing the Related Literature

Quantitative research is conducted in a context of previous knowledge. Quantitative researchers typically strive to understand what is already known about a topic by undertaking a literature review. A thorough  literature review  provides a foundation on which to base new evidence and usually is conducted before data are collected. For clinical problems, it may also be necessary to learn the “status quo” of current procedures and to review existing practice guidelines.

Step 3: Undertaking Clinical Fieldwork

Unless the research problem originated in a clinical setting, researchers embarking on a clinical nursing study benefit from spending time in relevant clinical settings, discussing the problem with clinicians and administrators, and observing current practices. Clinical fieldwork can provide perspectives on recent clinical trends, current diagnostic procedures, and relevant health care delivery models; it can also help researchers better understand clients and the settings in which care is provided. Such fieldwork can also be valuable in gaining access to an appropriate site or in developing research strategies. For example, in the course of clinical fieldwork, researchers might discover the need for research assistants who are bilingual.

Step 4: Defining the Framework and Developing Conceptual Definitions

Theory is the ultimate aim of science: It transcends the specifics of a particular time, place, and group and aims to identify regularities in the relationships among variables. When quantitative research is performed within the context of a theoretical framework, the findings often have broader significance and utility. Even when the research question is not embedded in a theory, researchers should have a conceptual rationale and a clear vision of the concepts under study.

Step 5: Formulating Hypotheses

Hypotheses state researcher’s expectations (predictions) about relationships between study variables. The research question identifies the study concepts and asks how the concepts might be related; a hypothesis is the predicted answer. For example, the research question might be: Is preeclamptic toxemia related to stress during pregnancy? This might be translated into the following hypothesis: Women with high levels of stress during pregnancy will be more likely than women with lower stress to experience preeclamptic toxemia. Most quantitative studies involve testing hypotheses through statistical analysis.

Phase 2: The Design and Planning Phase

In the second major phase of a quantitative study, researchers decide on the methods they will use to address the research question. Researchers usually have flexibility in designing a study and make many decisions. These methodologic decisions have crucial implications for the integrity and generalizability of the resulting evidence.

Step 6: Selecting a Research Design

The  research design  is the overall plan for obtaining answers to the research questions. Many experimental and nonexperimental research designs are available. In designing the study, researchers select a specific design and identify strategies to minimize bias. Research designs indicate how often data will be collected, what types of comparisons will be made, and where the study will take place. The research design is the architectural backbone of the study.

Step 7: Developing Protocols for the Intervention

In experimental research, researchers create an intervention (the independent variable), and so they need to develop its specifications. For example, if we were interested in testing the effect of biofeedback on hypertension, the independent variable would be exposure to biofeedback compared with either an alternative treatment (e.g., relaxation) or no treatment. An  intervention protocol  for the study must be developed, specifying exactly what the biofeedback treatment would entail (e.g., what type of feedback, who would administer it, how frequently and over how long a period the treatment would last, and so on) and what the alternative condition would be. The goal of well-articulated protocols is to have all people in each group treated in the same way. (In nonexperimental research, this step is not necessary.)

Step 8: Identifying the Population

Quantitative researchers need to clarify the group to whom study results can be generalized—that is, they must identify the population to be studied. A  population  is all the individuals or objects with common, defining characteristics (the “P” component in PICO questions). For example, the population of interest might be all patients undergoing chemotherapy in Dallas.

Step 9: Designing the Sampling Plan

Researchers collect data from a sample, which is a subset of the population. Using samples is more feasible than collecting data from an entire population, but the risk is that the sample might not reflect the population’s traits. In a quantitative study, a sample’s adequacy is assessed by its size and representativeness. The quality of the sample depends on how typical, or representative, the sample is of the population. The  sampling plan  specifies how the sample will be selected and recruited and how many subjects there will be.

Step 10: Specifying Methods to Measure Research Variables

Quantitative researchers must develop or borrow methods to measure their research variables. The primary methods of data collection are self-reports (e.g., interviews), observations (e.g., observing the sleep–wake state of infants), and biophysiologic measurements. Self-reported data from patients is the largest class of data collection methods and is often referred to as patient-reported outcomes (PROs). The task of measuring research variables and developing a data collection plan is complex and challenging.

Step 11: Developing Methods to Safeguard Human/Animal Rights

Most nursing research involves humans, and so procedures need to be developed to ensure that the   study adheres to ethical principles. A formal review by an ethics committee is usually required.

Step 12: Reviewing and Finalizing the Research Plan

Before collecting their data, researchers often take steps to ensure that plans will work smoothly. For example, they may evaluate the readability of written materials to assess if participants with low reading skills can comprehend them, or they may pretest their measuring instruments to see if they work well. Normally, researchers also have their research plans critiqued by peers, consultants, or other reviewers before implementing it. Researchers seeking financial support submit a  proposal  to a funding source, and reviewers usually suggest improvements.

TIP: For major studies, researchers often undertake a small-scale  pilot study  to test their research plans. Strategies for designing effective pilot studies are described in  Chapter 28 .

Phase 3: The Empirical Phase

The empirical phase of quantitative studies involves collecting data and preparing the data for analysis. Often, the empirical phase is the most time-consuming part of the investigation. Data collection typically requires months of work.

Step 13: Collecting the Data

The actual collection of data in quantitative studies often proceeds according to a preestablished plan. The plan typically spells out procedures for training data collection staff, for actually collecting data (e.g., where and when the data will be gathered), and for recording information.

Technologic advances have expanded possibilities for automating data collection.

Step 14: Preparing the Data for Analysis

Data collected in a quantitative study must be prepared for analysis. One preliminary step is coding, which involves translating verbal data into numeric form (e.g., coding gender information as “1” for females and “2” for males). Another step may involve transferring the data from written documents onto computer files for analysis.

Phase 4: The Analytic Phase

Quantitative data must be subjected to analysis and interpretation, which occur in the fourth major phase of a project.

Step 15: Analyzing the Data

Quantitative researchers analyze their data through statistical analyses, which include simple procedures (e.g., computing an average) as well as ones that are complex. Some analytic methods are computationally formidable, but the underlying logic of statistical tests is fairly easy to grasp. Computers have eliminated the need to get bogged down with mathematic operations.

Step 16: Interpreting the Results

Interpretation  involves making sense of study results and examining their implications. Researchers attempt to explain the findings in light of prior evidence, theory, and their own clinical experience—and in light of the adequacy of the methods they used in the study. Interpretation also involves drawing conclusions about the clinical significance of the results, envisioning how the new evidence can be used in nursing practice, and clarifying what further research is needed.

Phase 5: The Dissemination Phase

In the analytic phase, the researcher comes full circle: Questions posed at the outset are answered. Researchers’ responsibilities are not completed, however, until study results are disseminated.

Step 17: Communicating the Findings

A study cannot contribute evidence to nursing practice if the results are not shared. Another—and often final—task of a study is the preparation of a  research report  that summarizes the study. Research reports can take various forms: dissertations, journal articles, conference presentations, and so on. Journal articles—reports appearing in professional journals such as Nursing Research—usually are the most useful because they are available to a broad, international audience. We discuss journal articles later in this chapter.

Step 18: Utilizing the Findings in Practice

Ideally, the concluding step of a high-quality study is to plan for the use of the evidence in practice settings. Although nurse researchers may not themselves be able to implement a plan for using research findings, they can contribute to the process by making recommendations for utilizing the evidence, by ensuring that adequate information has been provided for a systematic review, and by pursuing opportunities to disseminate the findings to clinicians.


Quantitative research involves a fairly linear progression of tasks—researchers plan the steps to be taken to maximize study integrity and then follow those steps as faithfully as possible. In qualitative studies, by contrast, the progression is closer to a circle than to a straight line—qualitative researchers continually examine and interpret data and make decisions about how to proceed based on what has already been discovered ( Figure 3.2 ).



Because qualitative researchers have a flexible approach, we cannot show the flow of activities precisely—the flow varies from one study to another, and researchers themselves do not know ahead of time exactly how the study will unfold. We provide a sense of how qualitative studies are conducted, however, by describing some major activities and indicating when they might be performed.

Conceptualizing and Planning a Qualitative Study

Identifying the Research Problem

Qualitative researchers usually begin with a broad topic area, focusing on an aspect of a topic that is poorly understood and about which little is known. Qualitative researchers often proceed with a fairly broad initial question, which may be narrowed and clarified on the basis of self-reflection and discussion with others. The specific focus and questions are usually delineated more clearly once the study is underway.

Doing a Literature Review

Qualitative researchers do not all agree about the value of doing an up-front literature review. Some believe that researchers should not consult the literature before collecting data because prior studies could influence conceptualization of the focal phenomenon. In this view, the phenomena should be explicated based on participants’ viewpoints rather than on prior knowledge. Those sharing this opinion often do a literature review at the end of the study. Other researchers conduct a brief preliminary review to get a general grounding. Still others believe that a full early literature review is appropriate. In any case, qualitative researchers typically find a fairly small body of relevant previous work because of the types of question they ask.

Selecting and Gaining Entrée into Research Sites

Before going into the field, qualitative researchers must identify an appropriate site. For example, if the topic is the health beliefs of the urban poor, an inner-city neighborhood with low-income residents must be identified. Researchers may need to engage in anticipatory fieldwork to identify a suitable and information-rich environment for the study. In some cases, researchers have ready access to the study site, but in others, they need to gain entrée. A site may be well suited to the needs of the research, but if researchers cannot “get in,” the study cannot proceed. Gaining entrée typically involves negotiations with gatekeepers who have the authority to permit entry into their world.

TIP: The process of gaining entrée is usually associated with doing fieldwork in qualitative studies, but quantitative researchers often need to gain entrée into sites for collecting data as well.

Developing an Overall Approach in Qualitative Studies

Quantitative researchers do not collect data before finalizing their research design. Qualitative researchers, by contrast, use an  emergent design  that materializes during the course of data collection. Certain design features may be guided by the qualitative research tradition within which the researcher is working, but nevertheless, few qualitative studies adopt rigidly structured designs that prohibit changes while in the field.

Although qualitative researchers do not always know in advance exactly how the study will progress, they nevertheless must have some sense of how much time is available for fieldwork and must also arrange for and test needed equipment, such as recording equipment or laptop computers. Other planning activities include such tasks as hiring and training interviewers to assist in the collection of data; securing interpreters if the informants speak a different language; and hiring appropriate consultants, transcribers, and support staff.

Addressing Ethical Issues

Qualitative researchers, like quantitative researchers, must also develop plans for addressing ethical issues—and, indeed, there are special concerns in qualitative studies because of the more intimate nature of the relationship that typically develops between researchers and study participants.  Chapter 7 describes these concerns.

Conducting a Qualitative Study

In qualitative studies, the tasks of sampling, data collection, data analysis, and interpretation typically take place iteratively. Qualitative researchers begin by talking with or observing a few people who have first-hand experience with the phenomenon under study. The discussions and observations are loosely structured, allowing for the expression of a full range of beliefs, feelings, and behaviors. Analysis and interpretation are ongoing, concurrent activities that guide choices about the kinds of people to sample next and the types of questions to ask or observations to make.

The process of data analysis involves clustering together related types of narrative information into a coherent scheme. As analysis and interpretation progress, researchers begin to identify themes and categories, which are used to build a rich description or theory of the phenomenon. The kinds of data obtained and the people selected as participants tend to become increasingly purposeful as the conceptualization is developed and refined. Concept development and verification shape the sampling process—as a conceptualization or theory develops, the researcher seeks participants who can confirm and enrich the theoretical understandings as well as participants who can potentially challenge them and lead to further theoretical development.

Quantitative researchers decide up-front how many people to include in a study, but qualitative researchers’ sampling decisions are guided by the data. Qualitative researchers use the principle of  data saturation , which occurs when themes and categories in the data become repetitive and redundant, such that no new information can be gleaned by further data collection.

Quantitative researchers seek to collect high-quality data by measuring their variables with instruments that have been demonstrated to be reliable and valid. Qualitative researchers, by contrast, are the main data collection instrument and must take steps to demonstrate the trustworthiness of the data. The central feature of these efforts is to confirm that the findings accurately reflect the experiences and viewpoints of participants rather than the researcher’s perceptions. One confirmatory activity, for example, involves going back to participants and sharing interpretations with them so that they can evaluate whether the researcher’s thematic analysis is consistent with their experiences.

Disseminating Qualitative Findings

Qualitative nurse researchers also share their findings with others at conferences and in journal articles. Regardless of researchers’ positions about when a literature review should be conducted, a summary of prior research is usually offered in qualitative reports as a means of providing context for the study.

Quantitative reports almost never contain  raw data —that is, data in the form they were collected, which are numeric values. Qualitative reports, by contrast, are usually filled with rich verbatim passages directly from participants. The excerpts are used in an evidentiary fashion to support or illustrate researchers’ interpretations and thematic construction.

Example of Raw Data in a Qualitative Report: Gitsels-van der Wal and colleagues (2015) did an in-depth study of how pregnant Muslim women living in the Netherlands make decisions about antenatal anomaly screening. The researchers found that the women were hesitant about the test uptake. Here is an illustrative quote:

· I thought, “What if there is something wrong?” It would have to be something really major before you’d want a termination, but I think it would be a desperately difficult choice…. It seems like a very awkward choice, because you got pregnant in the first place because you wanted a baby, and then it doesn’t matter whether it’s disabled or not. (p. e45)

Like quantitative researchers, qualitative nurse researchers want their findings used by others. Qualitative findings often are the basis for formulating hypotheses that are tested by quantitative researchers, for developing measuring instruments for both research and clinical purposes, and for designing effective nursing interventions. Qualitative studies help to shape nurses’ perceptions of a problem or situation, their conceptualizations of potential solutions, and their understanding of patients’ concerns and experiences.



Research journal articles, which summarize the context, design, and results of a study, are the primary method of disseminating research evidence. This section reviews the content and style of research journal articles to ensure that you will be equipped to delve into the research literature. A more detailed discussion of the structure of journal articles is presented in  Chapter 30 , which provides guidance on writing research reports.

Content of Journal Articles

Many quantitative and qualitative journal articles follow a conventional organization called the  IMRAD format . This format, which loosely follows the steps of quantitative studies, involves organizing material into four main sections—Introduction, Methods,  R esults, and  D iscussion. The text of the report is usually preceded by an abstract and followed by cited references.

The Abstract

The  abstract  is a brief description of the study placed at the beginning of the article. The abstract answers, in about 250 words, the following: What were the research questions? What methods did the researcher use to address the questions? What did the researcher find? What are the implications for practice? Readers review abstracts to assess whether the entire report is of interest. Some journals have moved from traditional abstracts—single paragraphs summarizing the study’s main features—to longer, structured abstracts with specific headings. For example, in Nursing Research, the abstracts are organized under the following headings: Background, Objectives, Method, Results, and Conclusions.

The Introduction

The introduction communicates the research problem and its context. The introduction, which often is not be specifically labeled “Introduction,” follows immediately after the abstract. This section typically describes (1) the central phenomena, concepts, or variables under study; (2) the population of interest; (3) the current state of evidence, based on a literature review; (4) the theoretical framework; (5) the study purpose, research questions, or hypotheses to be tested; and (6) the study’s significance. Thus, the introduction sets the stage for a description of what the researcher did and what was learned. The introduction corresponds roughly to the conceptual phase (Phase 1) of a study.

The Method Section

The method section describes the methods used to answer the research questions. This section lays out methodologic decisions made in the design and planning phase (Phase 2) and may offer rationales for those decisions. In a quantitative study, the method section usually describes (1) the research design, (2) the sampling plan for selecting participants from the population of interest, (3) methods of data collection and specific instruments used, (4) study procedures (including ethical safeguards), and (5) analytic procedures and methods.

Qualitative researchers discuss many of the same issues but with different emphases. For example, a qualitative study often provides more information about the research setting and the study context and less information on sampling. Also, because formal instruments are not used to collect qualitative data, there is less discussion about data collection methods, but there may be more information on data collection procedures. Increasingly, reports of qualitative studies are including descriptions of the researchers’ efforts to enhance the trustworthiness of the study.

The Results Section

The results section presents the  findings  (results) from the data analyses. The text summarizes key findings, and (in quantitative reports) tables provide greater detail. Virtually all results sections contain a description of the participants (e.g., their average age, percent male/female).

In quantitative studies, the results section provides information about statistical tests, which are used to test hypotheses and evaluate the believability of the findings. For example, if the percentage of smokers who smoke two packs or more daily is computed to be 40%, how probable is it that the percentage is accurate? If the researcher finds that the average number of cigarettes smoked weekly is lower for those in an intervention group than for those not getting the intervention, how probable is it that the intervention effect is real? Is the effect of the intervention on smoking likely to be replicated with a new sample of smokers—or does the result reflect a peculiarity of the sample? Statistical tests help to answer such questions. Researchers typically report:

·  The names of statistical tests used. Different tests are appropriate for different situations but are based on common principles. You do not have to know the names of all statistical tests—there are dozens of them—to comprehend the findings.

·  The value of the calculated statistic. Computers are used to calculate a numeric value for the particular statistical test used. The value allows researchers to draw conclusions about the meaning of the results. The actual numeric value of the statistic, however, is not inherently meaningful and need not concern you.

·  The significance. A critical piece of information is whether the value of the statistic was significant (not to be confused with important or clinically relevant). When researchers say that results are statistically significant, it means the findings are probably reliable and replicable with a new sample. Research reports indicate the  level of significance , which is an index of how probable it is that the findings are reliable. For example, if a report says that a finding was significant at the .05 level, this means that only 5 times out of 100 (5 ÷ 100 = .05) would the result be spurious. In other words, 95 times out of 100, similar results would be obtained with a new sample. Readers can have a high degree of confidence—but not total assurance—that the evidence is reliable.

Example from the Results Section of a Quantitative Study: Edwards and colleagues (2014) evaluated whether the introduction of an aquarium into dementia units would result in improved resident behavior and increased staff satisfaction. Here is what they reported: “Residents’ behavior improved along four domains: uncooperative, irrational, sleep, and inappropriate behaviors. The overall residents’ behavior score was significantly improved after an aquarium was introduced, F = 15.60, p < .001″ (p. 1309).

In this study, Edwards et al. found improvement over time (from an initial measurement to a second measurement after aquariums were introduced) in various realms of behavior among dementia unit residents. This finding is highly reliable: Less than one time in 1,000 (p < .001) would changes as great as those observed have occurred as a fluke. To understand this finding, you do not have to understand what an F statistic is nor do you need to worry about the actual value of the statistic, 15.60.

Results sections of qualitative reports often have several subsections, the headings of which correspond to the themes, processes, or categories identified in the data. Excerpts from the raw data are presented to support and provide a rich description of the thematic analysis. The results section of qualitative studies may also present the researcher’s emerging theory about the phenomenon under study.

The Discussion Section

In the discussion section, researchers draw conclusions about what the results mean and how the evidence can be used in practice. The discussion in both qualitative and quantitative reports may include the following elements: (1) an interpretation of the results and their clinical significance, (2) implications for clinical practice and for future and research, and (3) study limitations and ramifications for the integrity of the results. Researchers are in the best position to point out sample deficiencies, design problems, weaknesses in data collection, and so forth. A discussion section that presents these limitations demonstrates to readers that the author was aware of these limitations and probably took them into account in interpreting the findings.

The Style of Research Journal Articles

Research reports tell a story. However, the style in which many research journal articles are written—especially reports of quantitative studies—makes it difficult for many readers to figure out the story or become intrigued by it. To unaccustomed audiences, research reports may seem stuffy, pedantic, and bewildering. Four factors contribute to this impression:

· 1. Compactness. Journal space is limited, so authors compress a lot of information into a short space. Interesting, personalized aspects of the study are not reported. In qualitative studies, only a handful of supporting quotes can be included.

· 2. Jargon. The authors of research reports use terms that may seem esoteric.

· 3. Objectivity. Quantitative researchers tell their stories objectively, often in a way that makes them sound impersonal. For example, most quantitative reports are written in the passive voice (i.e., personal pronouns are avoided), which tends to make a report less inviting and lively than use of the active voice. Qualitative reports, by contrast, are more subjective and personal and written in a more conversational style.

· 4. Statistical information. Quantitative reports summarize the results of statistical analyses. Numbers and statistical symbols can intimidate readers who do not have statistical training.


In this textbook, we try to assist you in dealing with these issues and also strive to encourage you to tell your research stories in a manner that makes them accessible to practicing nurses.

Tips on Reading Research Reports

As you progress through this textbook, you will acquire skills for evaluating various aspects of research reports critically. Some preliminary hints on digesting research reports follow.

·  Grow accustomed to the style of research articles by reading them frequently, even though you may not yet understand all the technical points.

·  Read from an article that has been copied (or downloaded and printed) so that you can highlight portions and write marginal notes.

·  Read articles slowly. Skim the article first to get major points and then read it more carefully a second time.

·  On the second reading of a journal article, train yourself to be an active reader. Reading actively means that you constantly monitor yourself to assess your understanding of what you are reading. If you have problems, go back and reread difficult passages or make notes so that you can ask someone for clarification. In most cases, that “someone” will be your research instructor but also consider contacting researchers themselves via e-mail.

·  Keep this textbook with you as a reference while you are reading articles, so that you can look up unfamiliar terms in the glossary or index.

·  Try not to get scared away by statistical information. Try to grasp the gist of the story without letting numbers frustrate you.

·  Until you become accustomed to research journal articles, you may want to “translate” them by expanding compact paragraphs into looser constructions, by translating jargon into familiar terms, by recasting the report into an active voice, and by summarizing findings with words rather than numbers. ( Chapter 3  in the accompanying Resource Manual has an example of such a translation.)


Most chapters of this book contain guidelines to help you evaluate different aspects of a research report critically, focusing primarily on the researchers’ methodologic decisions.  Box 3.3   presents some further suggestions for performing a preliminary overview of a research report, drawing on concepts explained in this chapter. These guidelines supplement those presented in  Box 1.1  Chapter 1 .

BOX 3.3: Additional Questions for a Preliminary Review of a Study

· 1. What is the study all about? What are the main phenomena, concepts, or constructs under investigation?

· 2. If the study is quantitative, what are the independent and dependent variables?

· 3. Do the researchers examine relationships or patterns of association among variables or concepts? Does the report imply the possibility of a causal relationship?

· 4. Are key concepts clearly defined, both conceptually and operationally?

· 5. What type of study does it appear to be, in terms of types described in this chapter: Quantitative—experimental? nonexperimental? Qualitative—descriptive? grounded theory? phenomenologic? ethnographic?

· 6. Does the report provide any information to suggest how long the study took to complete?

· 7. Does the format of the report conform to the traditional IMRAD format? If not, in what ways does it differ?


In this section, we illustrate the progression of activities and discuss the time schedule of two studies (one quantitative and the other qualitative) conducted by the second author of this book.

Project Schedule for a Quantitative Study

·  Study: Postpartum depressive symptomatology: Results from a 2-stage U.S. national survey (Beck et al., 2011)

·  Study Purpose: Beck and colleagues undertook a study to estimate the prevalence of mothers with elevated postpartum depressive symptom levels in the United States and the factors that contributed to variability in symptom levels.

·  Study Methods: This study required a little less than 3 years to complete. Key activities and methodologic decisions included the following:

Phase 1. Conceptual Phase: 1 Month

Beck had been a member of the Listening to Mothers II National Advisory Council. The data for their national survey (the Childbirth Connection: Listening to Mothers II U.S. National Survey) had already been collected when Beck was approached to analyze the variables in the survey relating to postpartum depressive (PPD) symptoms. The first phase took only 1 month because data collection was already completed and Beck, a world expert on PPD, just needed to update a review of the literature.

Phase 2. Design and Planning Phase: 3 Months

The design phase entailed identifying which of the hundreds of variables on the national survey the researchers would focus on in their analysis. Also, their research questions were formalized during this phase. Approval from a human subjects committee also was obtained during this phase.

Phase 3. Empirical Phase: 0 Month

In this study, the data from nearly 1,000 postpartum women had already been collected.

Phase 4. Analytic Phase: 12 Months

Statistical analyses were performed to (1) estimate the percentage of new mothers experiencing elevated postpartum depressive symptom levels and (2) to identify which demographic, antepartum, intrapartum, and postpartum variables were significantly related to these elevated symptom levels.

Phase 5. Dissemination Phase: 18 Months

The researchers prepared and submitted their report to the Journal of Midwifery & Women’s Health for possible publication. It was accepted within 5 months and was “in press” (awaiting publication) another 4 months before being published. The article received the Journal of Midwifery & Women’s Health 2012 Best Research Article Award.

Project Schedule for a Qualitative Study

·  Study: Subsequent childbirth after a previous traumatic birth (Beck & Watson, 2010)

·  Study Purpose: The purpose of this study was to describe the meaning of women’s experiences of a subsequent childbirth after a previous traumatic birth.

·  Study Methods: The total time required to complete this study was a little more than 4 years. Beck and Watson’s key activities included the following:

Phase 1. Conceptual Phase: 2 Months

Beck had previously studied traumatic childbirth, and one of the mothers in the initial study inspired an interest in what happened to these mothers in a subsequent pregnancy and childbirth. During this phase, Beck reviewed the literature on subsequent childbirth following birth trauma.

Phase 2. Design and Planning Phase: 5 Months

Beck and Watson chose a descriptive phenomenologic design for this study. Once their proposal was finalized, it was submitted to the university’s committee for reviewing ethical research conduct for approval.

Phase 3. Empirical/Analytic Phases: 26 Months

A recruitment notice was placed on the website of Trauma and Birth Stress, a charitable Trust located in New Zealand. Thirty-five women sent their stories of their subsequent childbirth after a previous traumatic birth to Beck via the Internet. Analysis of the mothers’ stories took an additional 5 months. Four themes emerged from the data analysis: (1) riding the turbulent wave of panic during pregnancy, (2) strategizing: attempts to reclaim their body and complete the journey to motherhood, (3) bringing reverence to the birthing process and empowering women, and (4) still elusive: the longed-for healing birth experience.

Phase 4: Dissemination Phase: 17 Months

It took 6 months to prepare the manuscript for this study. It was submitted to the journal Nursing Research on August 17, 2009. On October 13, 2009, Beck and Watson received a letter from the journal’s editor indicating that the reviewers recommended they revise and resubmit the paper. On December 18, 2009, Beck and Watson submitted a revised manuscript that incorporated the reviewers’ recommendations. On January 27, 2010, Beck and Watson were notified that their manuscript had been accepted for publication and the article was published in the July/August 2010 issue. Beck has also presented the findings at national conferences.


·  The people who provide information to the researchers (investigators) in a study are called subjectsor study participants (in quantitative research) or study participants or informants in qualitative research; collectively, the participants comprise the sample.

·  The site is the overall location for the research; researchers sometimes engage in multisite studiesSettings are the more specific places where data collection occurs. Settings can range from totally naturalistic environments to formal laboratories.

·  Researchers investigate concepts (or constructs) and phenomena, which are abstractions or mental representations inferred from behavior or characteristics.

·  Concepts are the building blocks of theories, which are systematic explanations of some aspect of the real world.

·  In quantitative studies, concepts are called variables. A variable is a characteristic or quality that takes on different values (i.e., varies from one person to another). Groups that are varied with respect to an attribute are heterogeneous; groups with limited variability are homogeneous.

·  Continuous variables can take on an infinite range of values along a continuum (e.g., weight). Discrete variables have a finite number of values between two points (e.g., number of children). Categorical variables have distinct categories that do not represent a quantity (e.g., blood type).

·  The dependent (or outcomevariable is the behavior or characteristic the researcher is interested in explaining, predicting, or affecting (the “O” in the PICO scheme). The independent variable is the presumed cause of, antecedent to, or influence on the dependent variable. The independent variable corresponds to the “I” and the “C” components in the PICO scheme.

·  A conceptual definition describes the abstract or theoretical meaning of a concept being studied. An operational definition specifies how the variable will be measured.

·  Data—information collected during a study—may take the form of narrative information (qualitative data) or numeric values (quantitative data).

·  A relationship is a bond or connection between two variables. Quantitative researchers examine the relationship between the independent variable and dependent variable.

·  When the independent variable causes the dependent variable, the relationship is a cause-and-effect(or causalrelationship. In an associative (functionalrelationship, variables are related in a noncausal way.

·  A key distinction in quantitative studies is between experimental research, in which researchers intervene, and nonexperimental (or observational) research, in which researchers make observations of existing phenomena without intervening.

·  Qualitative research sometimes is rooted in research traditions that originate in other disciplines. Three such traditions are grounded theory, phenomenology, and ethnography.

·  Grounded theory seeks to describe and understand key social psychological processes that occur in social settings.

·  Phenomenology focuses on the lived experiences of humans and is an approach to learning what the life experiences of people are like and what they mean.

·  Ethnography provides a framework for studying the meanings, patterns, and lifeways of a culture in a holistic fashion.

·  Quantitative researchers usually progress in a fairly linear fashion from asking research questions to answering them. The main phases in a quantitative study are the conceptual, planning, empirical, analytic, and dissemination phases.

·  The conceptual phase involves (1) defining the problem to be studied, (2) doing a literature review, (3) engaging in clinical fieldwork for clinical studies, (4) developing a framework and conceptual definitions, and (5) formulating hypotheses to be tested.

·  The planning phase entails (6) selecting a research design, (7) developing intervention protocols if the study is experimental, (8) specifying the population, (9) developing a sampling plan, (10) specifying methods to measure research variables, (11) developing strategies to safeguard the rights of participants, and (12) finalizing the research plan (e.g., pretesting instruments).

·  The empirical phase involves (13) collecting data and (14) preparing data for analysis.

·  The analytic phase involves (15) analyzing data through statistical analysis and (16) interpreting the results.

·  The dissemination phase entails (17) communicating the findings in a research report and (18) promoting the use of the study evidence in nursing practice.

·  The flow of activities in a qualitative study is more flexible and less linear. Qualitative studies typically involve an emergent design that evolves during data collection.

·  Qualitative researchers begin with a broad question regarding a phenomenon, often focusing on a little-studied aspect. In the early phase of a qualitative study, researchers select a site and seek to gain entrée into it, which typically involves enlisting the cooperation of gatekeepers.

·  Once in the field, researchers select informants, collect data, and then analyze and interpret them in an iterative fashion. Knowledge gained during data collection helps in to shape the design of the study.

·  Early analysis in qualitative research leads to refinements in sampling and data collection, until saturation (redundancy of information) is achieved.

·  Both qualitative and quantitative researchers disseminate their findings, often in journal articles that concisely communicate what the researchers did and what they found.

·  Journal articles typically consist of an abstract (a brief synopsis) and four major sections in an IMRAD format: an Introduction (explanation of the study problem and its context), Method section (the strategies used to address the problem), Results section (study findings), and Discussion (interpretation of the findings).

·  Research reports can be difficult to read because they are dense and contain a lot of jargon. Quantitative research reports may be intimidating at first because, compared to qualitative reports, they are more impersonal and include statistical information.

·  Statistical tests are procedures for testing research hypotheses and evaluating the believability of the findings. Findings that are statistically significant are ones that have a high probability of being “real.”




Beck, C. T. (2009). The arm: There is no escaping the reality for mothers of children with obstetric brachial plexus injuries. Nursing Research58, 237–245.

Beck, C. T., Gable, R. K., Sakala, C., & Declercq, E. R. (2011). Postpartum depressive symptomatology: Results from a two-stage U.S. national survey. Journal of Midwifery & Women’s Health56, 427–435.

Beck, C. T., & Watson, S. (2010). Subsequent childbirth after a previous traumatic birth. Nursing Research59, 241–249.

Broadbent, M., Moxham, L., & Dwyer, T. (2014). Implications of the emergency department triage environment on triage practice for clients with a mental illness at triage in an Australian context. Australasian Emergency Nursing Journal17, 23–29.

Cottney, A., & Innes, J. (2015). Medication-administration errors in an urban mental health hospital: A direct observation study. International Journal of Mental Health Nursing24, 65–74.

Edwards, N. E., Beck, A., & Lim, E. (2014). Influence of aquariums on resident behavior and staff satisfaction in dementia units. Western Journal of Nursing Research36, 1309–1322.

Ekwall, E., Ternestedt, B., Sorbe, B., & Sunvisson, H. (2014). Lived experiences of women with recurring ovarian cancer. European Journal of Oncology Nursing18, 104–109.

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