experimental and nonexperimental - Nursing
1.
Provide examples of experimental and nonexperimental research design. Contrast the levels of control applied to each.
2.
Describe sampling theory and provide examples to illustrate your definition. Discuss generalizability as it applies to nursing research.
Pamela McNiff and Melissa Petrick
The heart of the discerning acquires knowledge, for the ears of the wise seek it out. —Proverbs 18:15 (New International Version)
Essential Questions
· What is one difference between qualitative and quantitative research design?
· What are two ethical considerations when looking at quantitative studies?
· What is one critical component of quantitative research methods?
· What are the main components of a published quantitative study?
· What is the main difference in the levels of control between experimental and non-experimental research design?
Introduction
Unlike qualitative research that uses subjective, nonquantifiable information, quantitative research uses a systematic approach in an orderly fashion to define a problem and a subsequent solution to the problem. This chapter will focus on quantitative research. Nursing research ethics and protecting the human rights of research subjects in quantitative research will be discussed. Understanding the role of registered nurses (RN) prepared with a Bachelor of Science in Nursing (BSN) as it relates to nursing research will be explored. Understanding how to take the knowledge gained from reading and processing research and applying it to clinical practice is pivotal not only to the BSN-prepared RN, but also to nursing practice as a whole.
The process of research-problem identification and understanding the purpose of quantitative study design will be outlined. Researchers have a choice on what they want to study, why the study is relevant, and which type of research design would be appropriate for the study. Understanding the key components to quantitative research is important to have as a solid foundation. There are four main quantitative research designs
descriptive
,
correlational
,
quasi-experimental
, and
experimental
. These designs relate to the degree the researcher controls the
variables
in the experiment. A researcher takes into consideration
control
,
manipulation
, and
bias
when designing a high-integrity research study. These topics, along with different variables seen in quantitative research, will be explored.
After understanding the key components of quantitative research, critically appraising a quantitative research study is the next step in order to determine the overall applicability of the research. Topics such as the goals of the study, implications for practice, and feasibility of the practice problem will be addressed. Hypotheses will be examined as well. Finally, the chapter will conclude by looking at nursing leadership and the current direction of research. As the profession of nursing evolves, so do the aims of research within the field.
Ethical Considerations in Quantitative Research
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The importance of ethics and informed consent when conducting a research study cannot be understated. As past human rights violations emerged, a code of ethics for research was developed to ensure that ethical standards are upheld. Ethical principles, established through government regulations around the world, are put in place to protect participants in research studies. Commissions, such as the Belmont Report, have been established to provide “a model for many disciplinary guidelines” (Polit & Beck, 2012). While many regulations are in place to protect the individual, ethical dilemmas can occur that are in direct conflict with an individual’s rights. For example, a newly developed medication for a specific type of cancer is being tested using a
randomized controlled trial (RCT)
. While this type of quantitative research reduces bias and is considered the gold standard for research, certain participants will receive a placebo versus the actual medication being tested. The dilemma that occurs in this situation, is the potential for cancer progression in individuals receiving the placebo.
Risk-Benefit Ratio
The risk-benefit ratio is a key component of safety when looking at a research study. Before the process of informed consent, the research investigator considers the sample that is intended to be studied in order to identify the possible positive and negative ramifications within the study design. The researcher must confirm that the risk of the study does not outweigh the benefits to the participant. After minimizing all foreseeable risks, the investigator needs to ensure that these identified risks are outlined in the informed consent, and communicated by the consent administrator (U.S. Food and Drug Administration [USDA], 2017). If the risks are not effectively communicated, they could negatively impact the overall ethical approach to the consent process (Nusbaum, Douglas, Damus, Paasche-Orlow, & Estrella-Luna, 2017).
Informed Consent
Frequently, an RN will serve as a witness between patients and physicians prior to a procedure that requires written documentation of informed consent. In regard to research, informed consent needs to be obtained from potential research subjects before conducting any research as dictated per the institutional review board (IRB). The idea of informed consent was a result of ethical principles being upheld from the Belmont Report that protects research subjects and their rights to decide whether to participate in a research study.
There are three main features of informed consent:
1. Disclosure of pertinent information needed for the potential subject to make educated consent,
2. Assistance in ensuring the information disclosed to the potential subject was understood, and
3. Encouraging the idea that the potential research subject is volunteering to participate (U.S. Department of Health & Human Services, 2018a).
A procedure that requires informed consent would not take place until the proper consent has been obtained; therefore, informed consent must to be obtained prior to the potential research subject participating in research. Obtaining informed consent for research is slightly different from how it is obtained in most preprocedure clinical scenarios. In the hospital setting, while the RN might discuss the procedure with the patient and serve as a witness, it is ultimately the responsibility of the licensed provider, such as a nurse practitioner or physician, who is going to perform the procedure to communicate potential risks and benefits to the patient; however, within nursing research, including quantitative research, informed consent is usually obtained by the research nurse. That RN is often in the role of the consent administrator. Thus, it is imperative that the risks and benefits are clearly explained at both a language and literacy level that will leave the prospective research subject able to make an educated decision on whether he or she will participate. It is important for the consent administrator to communicate whether the prospective research subject is choosing to participate out of free will (USDA, 2017).
The specific details included in one study’s informed consent will vary depending on the specific study design. For example, a quantitative study that is using an experimental research design for a treatment group and a
control group
will include discussion on risks and benefits for receiving the medication or medical treatment as well as those associated with receiving a placebo. If a study is designed to look at pain control relative to a particular pain medication regimen, before obtaining consent for the study, potential subjects need to be made aware of the possibility of an increased risk of pain if they are placed in the control group.
In addition, within quantitative research studies in which a medical treatment is being studied and compared to a placebo, there could be an additional caveat placed within the informed consent. To further protect the participant, the researcher might include an anticipated scenario in which the research study’s investigator has the ability to withdraw the subject from the study regardless of the participant’s personal desire to be in the study (USDA, 2017). For example, if a study participant becomes acutely ill and needs hospitalization for medical
intervention
, the researcher could determine that there is an increased risk for the participant to participate in the study and withdraw the participant. While gathering data is important in research, the safety of the research subject will always take priority over the study.
Inclusion/Exclusion Criteria
The role of inclusion and exclusion criteria are how the researcher defines the targeted subjects for the study. Inclusion criteria are the characteristics researchers want included in the subjects. Exclusion criteria are those characteristics researchers want to avoid in the subjects studied. Thus, when potential research subjects are screened, they must have the inclusion criteria characteristics and not have those characteristics predefined to be excluded.
A researcher wants to study the risk of developing pressure ulcers in patients in the intensive care unit who are intubated, sedated, and have a history of diabetes. The inclusion criteria include criteria such as intensive care unit patient, sedation, and diagnosis of diabetes. The researcher specifically wants to study patients who have been diagnosed with diabetes for more than 10 years. An exclusion criterion is now introduced, and no patients with a diagnosis of diabetes for fewer than 10 years qualify for the study. The potential research subject could meet every single inclusion criterion, but if they have even one exclusion criteria, they would then be excluded.
Specific criteria will help to increase the
internal
and
external validity
of the research study. Creating a sound research study is important. If the data that is produced is the result of an unethical, biased, or potentially false premise, then it would harm the integrity of the study and be of no value to health care providers in trying to apply it to future practice.
Voluntary Withdrawal
Voluntary withdrawal is an important aspect of the ethical considerations of a research study. At any point in the study, the patient can withdraw from the study. Patients may decide to withdraw because of reasons such as personal, financial, religious, or health. It must be made very clear to research participants that they may withdraw from the study at any point in time for any reason. Potential risks to withdrawing from a study could include, but are not limited to, decreased financial gain if they were receiving any compensation for the study and changes in their overall health if they were receiving medical treatment that made their health condition better.
Safety and Quality
·
Because of unethical research practices many years ago, standards for conducting research with human subjects were put into practice. For nurses, this is often a seamless thought process from clinical practice. A nurse can often think of nursing ethics, such as
beneficence
and
nonmaleficence
, and apply them within the context of protecting a research subject. For example, in the clinical setting, an RN would not allow a cognitively impaired patient to sign a consent form without following protocol to ensure the patient is protected. If there is a patient who is cognitively impaired, the consent administrator cannot ethically obtain consent because there is no way to determine if the patient understands the potential risks and benefits of the study. Consequently, the cognitive impairment would potentially exclude the patient, as that potential subject is no longer an appropriate research candidate; however, if the cognitive impairment would not affect his or her ability to participate, then the consent administrator would need to follow the proper steps to ensure the safety of that potential research subject.
Human Rights and Protection of the Study Participant
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·
Protections of human rights is another important element of the research process. It is the duty of everyone involved in the research process to protect these rights. These include self-determination, privacy, anonymity and confidentiality, fair selection and treatment, and protection from discomfort and harm. The foundation of
self-determination
is respect for persons and understanding that each person is in control of his or her body and the decision to enroll, stay, or withdraw from a study. Researchers respect this human right by ensuring that they disclose information prior to potential enrollment in a study and respect the person’s decision to pass or participate, complete, and/or withdraw from the study (Judkins-Cohn, Kielwasser-Withrow, Owen, & Ward, 2014). It is important to understand that for participants to have self-determination protected, they must not have their decision-making ability compromised. Certain groups of people need additional protection for self-determination when research is being conducted because of diminished autonomy. Persons with diminished autonomy include those with mental impairments, minor children, and persons confined to institutions.
Anonymity and confidentiality, both extensions of privacy, are two important human rights protected in research. Though it will be important for the researcher to share information about the research studies when publishing the findings, the researchers must ensure that the specific identity of the research subjects are not disclosed with the information obtained in the study. Complete anonymity normally does not occur in research. With complete anonymity, the research subject’s identity is concealed through anonymous coding, and the researcher does not know who the data correlates to within the study; however, the researcher must ensure that the research data is kept confidential and anonymous from other research subjects. Much like in the hospital setting, RNs ensure that patient information of one patient is not evident in the presence of another patient. For example, to maintain anonymity, the researcher would not bring data with personal information when meeting with another research subject. It is also important to note that, within these protections, the research participant has the right to disclose personal information to the extent they feel comfortable and may choose to keep information to themselves. They are not required to disclose all personal information (Bowrey & Thompson, 2014). Thus, if the potential research subject chooses not to share personal information that is needed in the study, it could potentially prevent the subject from participating.
Fair Selection and Treatment in Research
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Fair selection and treatment is another protected right that is integral to the ethical treatment of research subjects. Research subjects should not be chosen because of race, socioeconomic status, or any specific vulnerable trait. The researcher needs to be careful not to choose a subject because of personal relations or scenarios in which bias could influence the decision to have the subject as part of the study. Often, research subjects receive some form of compensation, such as free medication or financial compensation, and choosing subjects with bias would be unfair and compromises the integrity of the study’s data. For example, if a study design is presented in which the subjects are paid for their participation, a researcher may compromise the study by choosing participants strictly from lower socioeconomic groups. In this instance, patients may be enticed by the financial compensation, and dismiss or not fully consider the potential harms associated with the study. Consequently, the internal validity of the study, as well as the generalizability, are compromised.
There will be certain criteria that potential subjects need to meet depending on the study’s primary endpoints and desired sample. For example, the inclusion criteria for a study on a new drug being tested for asthma would include participants with a current diagnosis of asthma. In the same study, a change in protocol could occur if, for example, the age of the participant with asthma changes because of the small sample size. Consequently, modifying a current study in this manner requires many steps and approvals from an IRB; therefore the modification should clearly support the reason for the change.
Protection from discomfort and harm is imperative within research and is extended to research participants. The researcher must look at the intervention they are studying and the risks/benefits to the potential subject. Although a negative outcome may occur because of an intervention introduced in the study, a researcher should not knowingly apply an intervention with intent to harm; therefore, any potential risks should always be defined in the informed consent, so a potential subject can be fully aware before making a decision to participate in the study. The American Psychological Association (2017) reinforces that a researcher must actively work to prevent harm and use research to promote good in the world. For example, if a researcher wants to determine whether turning patients every three hours versus every two hours will minimize skin breakdown, the researcher should look to see if research already exists looking at this intervention. Once a literature review has been conducted, the research can determine whether the findings of existing studies leaves the researcher confident that this intervention will not intentionally create further skin breakdown? In this example, it is the due diligence of the researcher to prevent intentional physical harm.
While this example discussed potential physical harm, it is important to understand that harm can be found in other forms, such as emotional or social well-being. The researcher must also understand that
duty of care
is a legal obligation. Research and interventions are done as an act to protect the individual, are in the individual’s best interest, and cause no harm.
Specific to the RN, the American Nurses Association has a position statement on the topic of human rights in research; nurses who are researchers must work to ensure the research subject’s rights are protected with ongoing informed consent, judicious monitoring of the risk versus benefit for the subjects, and the protection of the subjects from harm (American Nurses Association, 2016).
Check for Understanding
1. What kind of ethical dilemma could be in direct conflict with an individual’s rights when signing a consent form for a study?
2. In experimental research, what specific details regarding the control group must potential research subjects clearly understand prior to giving consent?
Quantitative Research in Nursing
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Quantitative research has its own unique process in nursing research. Figure 3.1 illustrates the process involved with quantitative research. Quantitative research studies move in a linear or sequential format. The sequence or flow is typically the same from study to study. A question is posed at the beginning of the study with the question being answered at the end of the study, with the research outcomes generating further discussion.
Figure 3.1
Steps in Quantitative Research
The Quantitative Nursing Research Process Explained
The following is a discussion of each step of the quantitative research process used for nursing research.
1. Research Problem/Purpose: What is the problem to be studied?
2. Review of Relevant Literature: Does literature already exist on this topic? If so, are there any gaps. Does this gap make sense to be studied via quantitative research with close-ended questions, or does qualitative research seem to be a better fit for the problem?
3. Study Framework: What is the theory or conceptual framework that would best serve the variables of the study? Examples of theory branches include grand nursing theory and middle-range theory. There are subcategories within these theory branches. Theories are more abstract than frameworks. Frameworks are used as methods to map out how concepts or variables relate to each other.
4. Research Questions or Hypotheses: What needs to be clearly defined? What bridges the abstract framework and tests one or two variables? Hypotheses are essential in quasi-experimental and experimental studies, as these are the two study designs that have researcher manipulation and an element of control.
5. Study Variables: It is important to think through the idea of conceptual versus operational definitions of variables. How would a researcher describe an idea he or she wants to study to a fellow researcher? That description of the variable is referred to as the conceptual definition; however, the operational definition of a variable is how it will be measured in that particular research study.
6. Study Design: The design of the study is chosen to meet the needs of what is being studied. For example, if something is being tested and the outcomes of the application of that intervention is in need of discovery (i.e. a new piece of equipment, a new protocol in the hospital), then the design needs to be quasi-experimental or experimental; however, if the researchers are seeking to understand a new idea or general relationships between variables, then descriptive or correlational could be appropriate.
7. Population and Sample: Who are the appropriate research subjects to study ethically and appropriately in the desired research problem? What are the inclusion and exclusion criteria for the sample?
8. Measurement Methods: Measurement of data includes the predetermined assignment of value to different data sets. Researchers need to determine what method of measurement is the most appropriate for the desired variables to be studied in their research design and framework.
9. Data Collection: With the given design and environment chosen to conduct the research study, what is the most appropriate means to collect data? A few examples of data collection methods include surveys, interviews, observation, or a mixture of one or more methods.
10. Data Analysis: This is the section in quantitative research in which the information such as statistical or clinical significance, causation, and/or correlation will be discussed. Words such as significant or insignificant impact will appear here. Did the numbers support what the researcher thought was going to happen? The discussion of the results will occur in the final section.
11. Discussion of Research Outcomes: What do the results mean to a study? For example, what do the results mean to this particular disease state/patient population that has been studied? What does it mean to the profession of nursing? What should be done with this research? Is the data so strong that the researcher feels a call to action? If so, what are the next steps? If there are limitations in the study, what are they? What should be studied next? While this study filled a research gap determined in the literature review, is there now another area where this data can be extrapolated and/or further researched? Does a new gap now exist? The study’s validity will be important in understanding how the results can be applied to the general population. Internal validity should be at the forefront of all research to protect the integrity of the results of the study. In essence, within the confines of the study design and execution, is there any influence on the study that could have altered the validity of the results? External validity refers to the ability of the researcher to apply the results from their study at large. Sample size, research environment, and random selection are three key elements that can greatly impact the generalizability of the study.
Lastly,
intervention fidelity
is a concept in nursing research that speaks to the consistency of the research. This refers to the degree that the intervention was intended. Fidelity checklists should be utilized to ensure that the intervention implemented in a research design remains consistent with no variations in order to reduce possible bias or manipulation into the study.
For example, participants in a new clinical trial for a diabetes medication to reduce blood glucose levels were asked to self-report their exercise regime. In this case, it would be difficult to obtain fidelity in the study because variables exist that cannot be ruled out that can affect the glucose levels with the medication introduced in the study. Some participants may have been exercising for many years, some participants may have recently begun exercising as part of the study; therefore, it is important for researchers to be trained in fidelity efforts to reduce variables as much as possible in a research study.
The Need for Quantitative Research
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The difference between qualitative research and quantitative research is that qualitative research is a means to study and assign meaning to subjective life experiences, whereas quantitative research is a means of mathematically proving relationships exist between variables (Conner, 2014). Choosing to use quantitative research intentionally looks at the relationship between variables. Depending on the specific research design, the degree of the relationship being studied will change. For example, a study on diabetic medication cannot yield accurate data if the participants do not take their diabetes medication as directed.
In nursing, ideas are formed from research studies through the use of
evidence-based practice (EBP)
. EBP takes into account the evidence, the patients being served, and the organization as a whole. In addition, EBP values clinical expertise (Conner, 2014). The link between EBP and nursing research cannot be understated. EBP also is important in that key stakeholders, such as clinicians, patients, researchers, policy makers and others who are involved and support the research study, are more likely to use and disseminate the information they help to produce (Agency for Healthcare Research and Quality, 2018). The stronger the evidence presented, the more likely stakeholders will set priorities to invest in the research being proposed.
Quantitative research is an ongoing process. Once the end of one study has occurred, it becomes the springboard for another. There is strength in having similar results in multiple studies on similar topics. Thus, over time, multiple studies yield information for EBP. The studies will show either continued maintenance of a nursing practice, changes that need to be made because of new evidence and/or stronger evidence, or reveal previous gaps.
Four Main Categories of Quantitative Research
The four main categories of quantitative research—descriptive, correlational, quasi-experimental, and experimental research— are differentiated by
intent
,
environment
, manipulation/control, and bias (see Table 3.1). Quantitative research aims to study relationships between variables with numerical outcomes, descriptive and correlational designs are less concerned with cause-and-effect relationships than are quasi-experimental and experimental studies. Quasi-experimental and experimental studies exert more control over variables than descriptive and correlational studies. Thus, if a researcher is intending to make a claim that there is a definitive, direct, cause-and-effect relationship between variables, then experimental studies are more fitting than descriptive or correlational designs.
In research designs, specifically with experimental research, manipulation is used to purposefully change a variable within the study. This is done to see if the
independent variable
changes. While researchers can unethically manipulate factors, and create unreliable and untrustworthy research, variables are manipulated or controlled to see the impact of a variable with an intentional intervention. The specific quantitative research design used by the researcher will depend on the specific intent of the study. The further down the design is on the spectrum of the four categories, the tighter the control of the study.
Descriptive → Correlational → Quasi-Experimental → Experimental
Table 3.1
Four Categories of Quantitative Research
Category
Intent
Environment
Manipulation/Control
Bias
Descriptive Studies
To describe a situation, subject, behavior, or phenomenon
Observation of actual events/phenomena as they occur in various settings
None
More chance of bias
Correlational Studies
Type of nonexperimental research; measures the statistical relationship between two or more variables and the degree of the relationship (cause/effect)
Various settings
None
More chance of bias
Quasi-Experimental Studies
Determine the degree of relationship between variables in which an intervention is conducted on a target population without random assignment
Semicontrolled environment
Less control than experimental studies; intervention introduced; independent variables are manipulated
Less chance of bias
Experimental Studies
Highly controlled research; true experiment in which researcher manipulates one or more variables to determine effect on other variables; random assignment is used.
Highly controlled environment
Highly controlled; independent variable(s) manipulated
Less chance of bias
Note. Adapted from “Quantitative Approaches,” by the Center for Intervention and Research and Teaching, n.d.a.
Descriptive research design is the least controlled of all quantitative designs. With descriptive research, there is little known about the topic, leaving the researcher to observe the topic and describe it. From descriptive research, data is achieved that helps in the creation of hypotheses for future research.
With correlational research design, researchers are trying to understand relationships. While more information is understood on the topic than in studies utilizing the descriptive research design, studies suited for the correlational research design take what was learned in descriptive research studies and try to draw an idea of how the variables might interact. From the data collected in previous studies, it is known there is a relationship between variables. In correlational research studies, the researcher is trying to understand how the variables affect each other in the same way, or influence opposing directional outcomes. From here, the hypotheses for quasi-experimental and experimental research is often created.
In quasi-experimental research design, there is well understood directional relationships and the way in which cause and effect is being determined. The prefix quasi means nearly but not completely, so quasi-experimental means that it is nearly experimental. The greatest difference between quasi-experimental and experimental research designs is that the independent variable is not controlled in quasi-experimental research.
Experimental research design is the most highly controlled quantitative design. Experimental research is where the most manipulation occurs to have the most
reliable
outcomes and the most definitive answers on what factors truly influence others and how. The highest degree of control would occur in a randomized, double-blind, placebo-controlled study. This type of study would result in the least amount of bias because the participants are randomly selected for the treatment/intervention, and neither the patients nor the researcher would know if they were receiving the treatment/intervention or placebo. There would be specific coding of the patient to maintain the integrity of the
blinding
.
Variables in Quantitative Research
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Three main variables exist in quantitative research: independent, dependent, and extraneous. These variables are important for the researcher to consider in the quantitative study. The independent variable is the variable the researcher manipulates, and the
dependent variable
is the outcome being assessed (Center for Intervention and Research and Teaching [CIRT], n.d.c). For example, a researcher might look at using a new catheter kit (independent variable) to numerically quantify where urinary tract infection rates decrease (dependent variable).
Extraneous variables can be a multitude of factors. It is impossible for the researcher to control every potential extraneous variable, but the researcher needs to look at factors that could affect the outcomes of the independent and dependent variables to minimize outside influence of the outcome being studied (CIRT, n.d.c). Controlling extraneous factors are important because it minimizes doubt in the validity of the mechanism of the outcome.
Just as it is nearly impossible to remove every extraneous variable, the same is true of bias. Bias exists when there is influence of the study that change the results. Many factors can result in bias, including unintentional or intentional subjectivism with the researchers performing the study, inadequate study design and data collection methods, lack of honesty from study participants regarding behaviors, or sample imbalances, such as choosing one specific patient population over another. While bias is nearly unavoidable even in the best designed studies, steps should always be taken to reduce bias. Because of the level of control in the methodology, quasi-experimental and experimental quantitative studies have decreased risk of bias. In addition, the researcher should acknowledge any extraneous variables they think affected the dependent variable in the study. Any potential bias should be discussed as well. When looking at sources of bias, they could be as concrete as topics, such as the process of data collection or statistical analysis regarding vague topics, such as the belief systems of patients or researchers; financial topics, such as who’s funding the research; or any incentive the researcher has in creating certain outcomes from the research.
Critical Components of Quantitative Research Methods
·
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When reviewing quantitative research, it is important for the nurse to approach the study and data systematically. There can be differences within quantitative studies that make some studies stronger than others in support of EBP changes. One of the most critical components of research is finding the overall purpose of the study, commonly called objectives of the study, study goals, and aims of the study, which can be found in the abstract of the study.
Within the abstract, a reader should be able to understand quickly what type of nursing research was conducted and the overall goals of the study. In quantitative data, the independent and dependent variable will be discussed. In addition, there should be at least one numerical data outcome highlighted in the abstract. If the study uses
mixed methods research design
, it might be difficult to exclude that any qualitative data was used; however, it should be evident that quantitative methods were used by looking for variables and numerically driven outcomes.
The problem statement discusses the gap in knowledge that served as the catalyst for conducting the research in the first place. It should be evident what was missing on the particular subject being studied and why researching it will positively impact patient outcomes and/or improve health care delivery in general. The research objectives should align to what will be studied in order to give more insight into the problem statement.
In addition, the why of the study should be apparent. For example, a previous study investigated different urinary catheter materials, and there appeared to be a relationship between the two variables, but the results were not clearly supported numerically to deliver a quantifiable impact on the relationship. Based on this previous research, the research problem may conclude that a gap in knowledge exists in understanding the impact a particular catheter brand has on infection and catheters. Objectives should then clearly delineate how that impact is going to be studied by looking at the rate of infection using a specific urinary catheter.
As previously discussed, variables are a key part of quantitative research. In the critical appraisal of research, it is important to find the independent and dependent variables and understand what they are and how they were specifically defined for that study. It is also important to consider the population studied and to determine the inclusion/exclusion criteria so the characteristics of the sample is understood.
After reading what the study is, how it was performed, and what was gained in the study, the implications for practice indicate where the data can be applied. As an example, a study found that using a particular urinary catheter reduced catheter associated urinary tract infections by 30%. Such findings warrant a hospital taking the next steps in obtaining this catheter. On the other hand, if the study’s data show that there was a 30% decrease in infection with only this particular urinary catheter in conjunction with better hand hygiene, other interventions, in addition to obtaining this type of catheter, may need to be instituted. Numerical data can be very useful in understanding the impact of a particular nursing intervention.
Feasibility of a Research Study
·
·
The researcher will include the feasibility of studying the problem and study’s purpose. The feasibility discussion may be direct, inferred, or both. For example, if the issue is a large problem in health care that can be studied in multiple sites throughout the world, the feasibility of studying the topic would be increased; however, if the topic is very narrow, the feasibility of conducting the research is decreased.
Additionally, the researchers’ background will also be included in the research study. Do they have extensive knowledge on the topic? Are they new researchers, or have they been doing research in this field for many years? Questions should also be addressed regarding the breadth and depth of the researcher’s background. As with nursing, experience is very valuable when conducting research. Understanding the study in context to the experience of the researchers can be helpful in critically appraising the study.
Funding can affect a study in a number of ways, including bias from conflicts of interest, the duration of the study, the number of study sites, sample size, and statistical analysis. The funding sources can often be found toward the end of the study and are listed by the researcher. This helps the reader identify potential conflicts of interest between the study and those funding the research. For example, if a nursing researcher works for the company that makes the particular urinary catheter that’s been discussed hypothetically in this section, then the reader needs to keep this potential area of bias in mind as they continue to appraise the value of the data achieved. Besides potential bias, the funding for the study can dictate the study itself. If funding was limited, it can impact the overall study.
Information on adequacy of subjects, settings, and equipment can be found within the limitations of the study section. Here, the researcher will discuss whether there were any issues that impacted the ability of the research to be conducted, such as the study being performed in a center with a small population size, a large drop-out rate of subjects that impacted the integrity of the data obtained, or malfunctions with the equipment used in the study. All of these are examples of how to critically assess the adequacy of subjects, settings, and equipment when reading a research article. All topics should be assessed to help understand the value of the data when choosing to study a specific topic in the nursing profession.
Hypotheses in Quantitative Research Studies
·
Hypotheses
are always used in quantitative research; however, the way in which the hypothesis is written determines the degree of prediction between variables within each research design type. Quasi-experimental and experimental studies will include a strong predictive hypothesis as they predict cause and effect between independent and dependent variables. In addition, with quasi-experimental and experimental studies, there has already been previous data conducted that shows a relationship exists, but the exact degree of relationship may not be understood or measured mathematically (CIRT, n.d.b). Hypotheses for quasi-experimental and experimental research designs will be specific and testable. Correlational study designs will have hypotheses that predict the relationship between the independent and dependent variables; however, because of the lack of control in the study design, any change in the dependent variable cannot be determined to be a result of the independent variable. Finally, descriptive study designs will have hypotheses that merely state that one variable is related another. Descriptive designs are often used to create hypotheses for later research (Cantrell, 2011).
When critically appraising a research study, the variables should be outlined and discussed as they relate to the quantitative research design. Remember, with descriptive designs, there will be discussion about the existence of a relationship, whereas experimental designs will define the extent of the causal relationship. In addition to the independent and dependent variables, outside influences should be discussed as well, such as whether an extraneous variable had an effect or whether there were confounding variables in the study. Sometimes an extraneous variable can become a confounding variable. In order to have confounding variables, there must be at least three variables, and there has to be a systematic change that occurs in at least one of the measured variables. Often, it behaves similarly to the independent variable. Thus, if an extraneous variable is behaving similarly to the variable being studied, it is difficult to declare confidently that the resulting dependent variable changes because of the independent variable because the change could have been caused by the confounding variable instead. For example, if a researcher is studying whether individuals who run at least 6 miles per day (the dependent variable) have lower heart rates than individuals who do not run at all (the independent variable).
Types of Hypotheses
There are four main types of hypotheses: associative versus causal, simple versus complex, nondirectional versus directional, and statistical (null) versus research (see Figure 3.2). Associative hypotheses propose that there is a definite relationship that exists between two variables; if one variable changes, then the other changes as well; however, one variable does not directly cause the change in the other variable. In a causalhypothesis, there is a direct cause and effect relationship. This is aligned with independent and dependent variables and the relationship that exists between these two factors.
Simple versus complex differs because of the number of variables discussed. With a simple hypothesis, the relationship between two variables is discussed. In a complex hypothesis, three or more variables are analyzed. The relationship can be either associative or causal. A nondirectional hypothesis does not state the direction of the proposed relationship between two variables. Conversely, a directional hypothesis does speculate how the variables will impact each other, which more easily clarifies the studies outcome. Lastly, statistical, or null, hypotheses imply that no relationship exists between two variables. These hypotheses can be either simple/complex or associative/causal. Research hypotheses are the opposite of statistical hypotheses, as they propose that a relationship exists between variables. These hypotheses can be simple/complex, nondirectional/directional, or associative/causal (Rockinson-Szapkiw, 2017).
Figure 3.2
Directional vs. Nondirectional Hypotheses
Examples of Hypotheses Relationships
A researcher is studying whether individuals who run at least 6 miles per day (the dependent variable) have lower heart rates than individuals who do not run at all (the independent variable), the following hypotheses and relationships may develop.
Associative
· Relationship: Individuals who run and swim have lower heart rates than individuals who only run.
· Hypothesis: Can running and swimming both be associated to lower heart rates?
Causal
· Relationship: Individuals who run have lower heart rates.
· Hypothesis: Is the cause of lower heart rates due to running?
Simple
· Relationship: Individuals who run at least 6 miles per day have lower heart rates than individuals who do not run at all (one dependent variable and one independent variable).
Complex
· Relationship: Individuals who run at least 6 miles per day and swim at least twice a week have lower heart rates than individuals who do not run or swim at all (one dependent variable, two independent variables).
Directional
· Relationship: People who run have lower heart rates.
Nondirectional
· Relationship: People who run and swim have lower heart rates than people who only run.
Null
· Relationship: Individuals who do not run have the same heart rates as those individuals who run daily.
Check for Understanding
Why does evidence and support within a study need to be strong enough for key stakeholders to support and invest in the proposed research?
Critically Appraising the Literature Review
·
·
·
The literature review is an extremely important part of the research process. Being aware of this process can help to recognize appropriate data sources, as well as how to categorize this information for efficiency and use in a systematic way. Literature cited should be from credible, current sources that were written within the past 5 years. A reputable source would be an article found in PubMed written by an author within the National Institute of Health (NIH). When looking at multiple studies, it is important to pull out key themes and takeaways, such as anything that is repeated consistently within the research, including terms and noted gaps in the literature.
Conducting a literature review is necessary to support and fund a research study. It is imperative to critique the strength and weaknesses of a study before including it in one’s own study, as the value of the studies’ presented evidence can support or weaken a study. This is why it is imperative to evaluate all the evidence closely so that informed decisions can be made on choosing the correct literature to support the study.
Systematic Review of the Literature
Systematic reviews use methodical procedures to reproduce and verify research evidence. The primary focus of the review is to determine data and literature associated with a study for a proposal of a new study to help develop and test research evidence. A variety of databases are used to perform a search for the appropriate literature. Some of the more common research databases for nurse researchers include Beyond Cumulative Index of Nursing and Allied Health Literature (CINAHL), PubMed, and government databases. When approaching critical appraisal of a quantitative research article, it is often best to use a step-by-step process in order to synthesize the strengths and weaknesses of the article. Identifying specific elements and providing answers to the following questions will help to create a solid foundation of critical analysis of the research article.
Background of Study
1. Identify the clinical problem and research problem that led to the study. What was not known about the clinical problem that, if understood, could be used to improve health care delivery or patient outcomes? This gap in knowledge is the research problem.
2. How did the author establish the significance of the study? In other words, why should the reader care about this study? Look for statements about human suffering, costs of treatment, or the number of people affected by the clinical problem.
3. Identify the purpose of the study. An author may clearly state the purpose of the study or describe the purpose as the study goals, objectives, or aims.
4. List research questions that the study was designed to answer. If the author does not explicitly provide the questions, attempt to infer the questions from the answers.
5. Were the purpose and research questions related to the problem?
Methods of Study
1. Identify the benefits and risks of participation addressed by the authors. Were there benefits or risks the authors do not identify?
2. Was informed consent obtained from the subjects or participants?
3. Did it seem that the subjects participated voluntarily in the study?
4. Was an IRB approval obtained from the agency in which the study was conducted?
5. Are the independent and dependent variables identified and defined? What were these variables?
6. How were data collected in this study?
7. What rationale did the author provide for using this data collection method?
8. What was the time period for data collection of the study?
9. What was the sequence of data collection events for a participant?
10. What were the data management and analysis methods used in the study?
11. Did the author discuss how the rigor of the process was assured? For example, does the author describe maintaining a paper trail of critical decisions that were made during the analysis of the data? Was statistical software used to ensure accuracy of the analysis?
12. What measures were used to minimize the effects of researcher bias? For example, did two researchers independently analyze the data and compare their analyses?
Results of Study
1. What is the researcher's interpretation of findings?
2. Are the findings valid or an accurate reflection of reality?
3. What limitations of the study were identified by researchers?
4. Was there a coherent logic to the presentation of findings?
5. What implications do the findings have for nursing practice? For example, can the findings of the study be applied to general nursing practice, to a specific population, or to a specific area of nursing?
6. What suggestions are made for further studies?
Ethical Considerations
1. Was the study approved by an IRB?
2. Was patient privacy protected?
3. Were there ethical considerations regarding the treatment or lack of treatment?
Conclusion
1. Emphasize the importance and congruity of the thesis statement.
2. Provide a logical wrap-up to bring the appraisal to completion and to leave a lasting impression and takeaway points useful in nursing practice.
3. Incorporate a critical appraisal and a brief analysis of the utility and applicability of the findings to nursing practice.
4. Integrate a summary of the knowledge learned.
Mixed Design Research Methods
·
Mixed methods research design is becoming increasingly popular, particularly in the nursing profession. Utilizing a study that looks at a research question using both quantitative and qualitative design adds a depth and breadth of understanding to a topic that could not otherwise be obtained. In addition, having both quantitative and qualitative study designs occurring simultaneously leads to team research amongst those with quantitative expertise and those with qualitative expertise; however, conducting research in this manner comes with challenges.
With mixed method research design, there is often equal weight to each type of data used, meaning there is more data to analyze requiring more manpower to assess both types of data, which results in taking more time and money needed to conduct the research. In addition, with both types of studies occurring simultaneously, there might be a blend of the two data collections and potential inconsistencies within each objective collection. This might lead to delays in recollecting data, or potential issues with internal validity within the study. Overall, it is important to understand that this type of design is possible and preferred in research problems that need both designs to understand the problem more comprehensively (Doorenbos, 2014).
The Role of the BSN-Prepared Nurse in Research and Nursing Leadership
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The BSN-prepared RN has the ability to understand research, appraise the studies, and the importance of utilizing research to ensure EBP in the clinical setting. Additionally, BSN-prepared RNs are able to participate in research teams as a research nurse and be involved in the collection of data in clinical studies. RNs who have furthered their education and obtained their Master of Science in nursing (MSN) can conduct research studies and appraise and synthesize the data to affect the nursing practice. Protocol changes, editing, or creating new treatment algorithms are a few real-life applications of MSN-prepared RNs. RNs who have achieved a doctor of nurse practice (DNP) degree are able to impact national guidelines. Although DNPs are not PhDs who create new research, the DNP educated RN can take current data and apply it to nursing practice for the improvement of patient care. If gaps are seen, they can collaborate with nurse researchers to impact further research on the topic to advocate change (American Association of Colleges of Nursing, 2017).
Reflective Summary
Quantitative research is a very systematic approach to studying certain kinds of research problems. Understanding the four main types of quantitative design, what to expect, and when to use them are key to understanding quantitative research. Having a good working knowledge of independent, dependent, and extraneous variables are key elements in understanding the overall framework of the design and intervention. Above all, BSN-prepared RNs should have a good working knowledge of quantitative research as they learn to apply evidence-based interventions to their current practice as well as a means of ongoing quality improvement to practice in the nursing profession at large. Research will continue to challenge the status quo for the profession as well as those nurses who serve and protect patients.
Key Terms
Beneficence: Actively helping, doing kindness, performing quality conduct, and sharing goodness for the benefit of others.
Bias: External and internal influences within a study that can affect the validity and reliability of the outcomes.
Blinding: Not making the status of the treatment/intervention being tested known to the research subject or researcher; in double-blind studies, neither the researcher or research subject know the status of the treatment/intervention being tested.
Confidentiality: Keeping information secret from others; not disclosing private matters.
Control: The process of consistent management of influences on the dependent variable of the study.
Control Group: The group of subjects not receiving the treatment; the sample not receiving the intervention being studied; also known as comparison group.
Correlational Research Design: A type of quantitative research that is not controlled and aims to understand relationships between variables.
Dependent Variable: The outcome variable. It takes on different values in response to the independent variable.
Descriptive Research Design: The systematic collection of data to describe the variable, such as the characteristics of a population or current phenomena, being identified.
Duty of Care: A legal obligation on the part of an individual to adhere to standards of reasonable care while performing acts that could harm others.
Environment: The setting in which the research takes place.
Evidence-Based Practice (EBP): The integration of clinical expertise, the most up-to-date research, and patient’s preferences to formulate and implement best practices for patient care.
Experimental Research Design: A type of quantitative research design that is highly controlled and to study cause and effect with independent and dependent variables.
External Validity: The ability of the research study to be generalized to the population at large.
Independent Variable: The experimental or predictor variable. It is manipulated in the research to observe the effect on the dependent variable.
Intent: The purpose of the study.
Internal Validity: The ability of the researcher to minimize external influence on the data achieved in the study.
Intervention: What the researcher is assessing and looking for outcomes of in the study. For example, a new medication, procedure, protocol, or medical supply.
Intervention Fidelity: The process in which a researcher records and monitors the exact steps that are taken with each subject to ensure consistency in delivering the intervention in the study.
Manipulation: A means to control variables in quasi-experimental and experimental research studies in order to see the effect of an intervention on outcomes; what was introduced into the study that could change the outcome of the study; also referred to as the control.
Mixed Methods Research Design: A type of research design that includes both quantitative and qualitative design methods.
Nonmaleficence: Committing no harm or evil; based on Hippocrates' admonishment to first do no harm.
Quasi-Experimental Research Design: A type of quantitative research design that is partially controlled that studies cause and effect of variables.
Randomized Controlled Trials (RCT): Research studies in which patients are chosen at random to receive the treatment/intervention being tested; considered the gold standard of research design.
Reliability: The extent to which an experiment, test, or measuring procedure yields the same results on repeated trials.
Self-Determination: The right to make decisions for one’s self.
Variables: A data item such as characteristics, numbers, properties, or quantities that can be measured or counted. The value of the data item can vary or be manipulated from one entity to another. There are three different types of variables—dependent, independent, and extraneous.
Pamela McNiff and Melissa Petrick
The heart of the discerning acquires knowledge, for the ears of the wise seek it out. —Proverbs 18:15 (New International Version)
Essential Questions
· What is one difference between qualitative and quantitative research design?
· What are two ethical considerations when looking at quantitative studies?
· What is one critical component of quantitative research methods?
· What are the main components of a published quantitative study?
· What is the main difference in the levels of control between experimental and non-experimental research design?
Introduction
Unlike qualitative research that uses subjective, nonquantifiable information, quantitative research uses a systematic approach in an orderly fashion to define a problem and a subsequent solution to the problem. This chapter will focus on quantitative research. Nursing research ethics and protecting the human rights of research subjects in quantitative research will be discussed. Understanding the role of registered nurses (RN) prepared with a Bachelor of Science in Nursing (BSN) as it relates to nursing research will be explored. Understanding how to take the knowledge gained from reading and processing research and applying it to clinical practice is pivotal not only to the BSN-prepared RN, but also to nursing practice as a whole.
The process of research-problem identification and understanding the purpose of quantitative study design will be outlined. Researchers have a choice on what they want to study, why the study is relevant, and which type of research design would be appropriate for the study. Understanding the key components to quantitative research is important to have as a solid foundation. There are four main quantitative research designs
descriptive
,
correlational
,
quasi-experimental
, and
experimental
. These designs relate to the degree the researcher controls the
variables
in the experiment. A researcher takes into consideration
control
,
manipulation
, and
bias
when designing a high-integrity research study. These topics, along with different variables seen in quantitative research, will be explored.
After understanding the key components of quantitative research, critically appraising a quantitative research study is the next step in order to determine the overall applicability of the research. Topics such as the goals of the study, implications for practice, and feasibility of the practice problem will be addressed. Hypotheses will be examined as well. Finally, the chapter will conclude by looking at nursing leadership and the current direction of research. As the profession of nursing evolves, so do the aims of research within the field.
Ethical Considerations in Quantitative Research
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The importance of ethics and informed consent when conducting a research study cannot be understated. As past human rights violations emerged, a code of ethics for research was developed to ensure that ethical standards are upheld. Ethical principles, established through government regulations around the world, are put in place to protect participants in research studies. Commissions, such as the Belmont Report, have been established to provide “a model for many disciplinary guidelines” (Polit & Beck, 2012). While many regulations are in place to protect the individual, ethical dilemmas can occur that are in direct conflict with an individual’s rights. For example, a newly developed medication for a specific type of cancer is being tested using a
randomized controlled trial (RCT)
. While this type of quantitative research reduces bias and is considered the gold standard for research, certain participants will receive a placebo versus the actual medication being tested. The dilemma that occurs in this situation, is the potential for cancer progression in individuals receiving the placebo.
Risk-Benefit Ratio
The risk-benefit ratio is a key component of safety when looking at a research study. Before the process of informed consent, the research investigator considers the sample that is intended to be studied in order to identify the possible positive and negative ramifications within the study design. The researcher must confirm that the risk of the study does not outweigh the benefits to the participant. After minimizing all foreseeable risks, the investigator needs to ensure that these identified risks are outlined in the informed consent, and communicated by the consent administrator (U.S. Food and Drug Administration [USDA], 2017). If the risks are not effectively communicated, they could negatively impact the overall ethical approach to the consent process (Nusbaum, Douglas, Damus, Paasche-Orlow, & Estrella-Luna, 2017).
Informed Consent
Frequently, an RN will serve as a witness between patients and physicians prior to a procedure that requires written documentation of informed consent. In regard to research, informed consent needs to be obtained from potential research subjects before conducting any research as dictated per the institutional review board (IRB). The idea of informed consent was a result of ethical principles being upheld from the Belmont Report that protects research subjects and their rights to decide whether to participate in a research study.
There are three main features of informed consent:
1. Disclosure of pertinent information needed for the potential subject to make educated consent,
2. Assistance in ensuring the information disclosed to the potential subject was understood, and
3. Encouraging the idea that the potential research subject is volunteering to participate (U.S. Department of Health & Human Services, 2018a).
A procedure that requires informed consent would not take place until the proper consent has been obtained; therefore, informed consent must to be obtained prior to the potential research subject participating in research. Obtaining informed consent for research is slightly different from how it is obtained in most preprocedure clinical scenarios. In the hospital setting, while the RN might discuss the procedure with the patient and serve as a witness, it is ultimately the responsibility of the licensed provider, such as a nurse practitioner or physician, who is going to perform the procedure to communicate potential risks and benefits to the patient; however, within nursing research, including quantitative research, informed consent is usually obtained by the research nurse. That RN is often in the role of the consent administrator. Thus, it is imperative that the risks and benefits are clearly explained at both a language and literacy level that will leave the prospective research subject able to make an educated decision on whether he or she will participate. It is important for the consent administrator to communicate whether the prospective research subject is choosing to participate out of free will (USDA, 2017).
The specific details included in one study’s informed consent will vary depending on the specific study design. For example, a quantitative study that is using an experimental research design for a treatment group and a
control group
will include discussion on risks and benefits for receiving the medication or medical treatment as well as those associated with receiving a placebo. If a study is designed to look at pain control relative to a particular pain medication regimen, before obtaining consent for the study, potential subjects need to be made aware of the possibility of an increased risk of pain if they are placed in the control group.
In addition, within quantitative research studies in which a medical treatment is being studied and compared to a placebo, there could be an additional caveat placed within the informed consent. To further protect the participant, the researcher might include an anticipated scenario in which the research study’s investigator has the ability to withdraw the subject from the study regardless of the participant’s personal desire to be in the study (USDA, 2017). For example, if a study participant becomes acutely ill and needs hospitalization for medical
intervention
, the researcher could determine that there is an increased risk for the participant to participate in the study and withdraw the participant. While gathering data is important in research, the safety of the research subject will always take priority over the study.
Inclusion/Exclusion Criteria
The role of inclusion and exclusion criteria are how the researcher defines the targeted subjects for the study. Inclusion criteria are the characteristics researchers want included in the subjects. Exclusion criteria are those characteristics researchers want to avoid in the subjects studied. Thus, when potential research subjects are screened, they must have the inclusion criteria characteristics and not have those characteristics predefined to be excluded.
A researcher wants to study the risk of developing pressure ulcers in patients in the intensive care unit who are intubated, sedated, and have a history of diabetes. The inclusion criteria include criteria such as intensive care unit patient, sedation, and diagnosis of diabetes. The researcher specifically wants to study patients who have been diagnosed with diabetes for more than 10 years. An exclusion criterion is now introduced, and no patients with a diagnosis of diabetes for fewer than 10 years qualify for the study. The potential research subject could meet every single inclusion criterion, but if they have even one exclusion criteria, they would then be excluded.
Specific criteria will help to increase the
internal
and
external validity
of the research study. Creating a sound research study is important. If the data that is produced is the result of an unethical, biased, or potentially false premise, then it would harm the integrity of the study and be of no value to health care providers in trying to apply it to future practice.
Voluntary Withdrawal
Voluntary withdrawal is an important aspect of the ethical considerations of a research study. At any point in the study, the patient can withdraw from the study. Patients may decide to withdraw because of reasons such as personal, financial, religious, or health. It must be made very clear to research participants that they may withdraw from the study at any point in time for any reason. Potential risks to withdrawing from a study could include, but are not limited to, decreased financial gain if they were receiving any compensation for the study and changes in their overall health if they were receiving medical treatment that made their health condition better.
Safety and Quality
·
Because of unethical research practices many years ago, standards for conducting research with human subjects were put into practice. For nurses, this is often a seamless thought process from clinical practice. A nurse can often think of nursing ethics, such as
beneficence
and
nonmaleficence
, and apply them within the context of protecting a research subject. For example, in the clinical setting, an RN would not allow a cognitively impaired patient to sign a consent form without following protocol to ensure the patient is protected. If there is a patient who is cognitively impaired, the consent administrator cannot ethically obtain consent because there is no way to determine if the patient understands the potential risks and benefits of the study. Consequently, the cognitive impairment would potentially exclude the patient, as that potential subject is no longer an appropriate research candidate; however, if the cognitive impairment would not affect his or her ability to participate, then the consent administrator would need to follow the proper steps to ensure the safety of that potential research subject.
Human Rights and Protection of the Study Participant
·
·
Protections of human rights is another important element of the research process. It is the duty of everyone involved in the research process to protect these rights. These include self-determination, privacy, anonymity and confidentiality, fair selection and treatment, and protection from discomfort and harm. The foundation of
self-determination
is respect for persons and understanding that each person is in control of his or her body and the decision to enroll, stay, or withdraw from a study. Researchers respect this human right by ensuring that they disclose information prior to potential enrollment in a study and respect the person’s decision to pass or participate, complete, and/or withdraw from the study (Judkins-Cohn, Kielwasser-Withrow, Owen, & Ward, 2014). It is important to understand that for participants to have self-determination protected, they must not have their decision-making ability compromised. Certain groups of people need additional protection for self-determination when research is being conducted because of diminished autonomy. Persons with diminished autonomy include those with mental impairments, minor children, and persons confined to institutions.
Anonymity and confidentiality, both extensions of privacy, are two important human rights protected in research. Though it will be important for the researcher to share information about the research studies when publishing the findings, the researchers must ensure that the specific identity of the research subjects are not disclosed with the information obtained in the study. Complete anonymity normally does not occur in research. With complete anonymity, the research subject’s identity is concealed through anonymous coding, and the researcher does not know who the data correlates to within the study; however, the researcher must ensure that the research data is kept confidential and anonymous from other research subjects. Much like in the hospital setting, RNs ensure that patient information of one patient is not evident in the presence of another patient. For example, to maintain anonymity, the researcher would not bring data with personal information when meeting with another research subject. It is also important to note that, within these protections, the research participant has the right to disclose personal information to the extent they feel comfortable and may choose to keep information to themselves. They are not required to disclose all personal information (Bowrey & Thompson, 2014). Thus, if the potential research subject chooses not to share personal information that is needed in the study, it could potentially prevent the subject from participating.
Fair Selection and Treatment in Research
·
·
Fair selection and treatment is another protected right that is integral to the ethical treatment of research subjects. Research subjects should not be chosen because of race, socioeconomic status, or any specific vulnerable trait. The researcher needs to be careful not to choose a subject because of personal relations or scenarios in which bias could influence the decision to have the subject as part of the study. Often, research subjects receive some form of compensation, such as free medication or financial compensation, and choosing subjects with bias would be unfair and compromises the integrity of the study’s data. For example, if a study design is presented in which the subjects are paid for their participation, a researcher may compromise the study by choosing participants strictly from lower socioeconomic groups. In this instance, patients may be enticed by the financial compensation, and dismiss or not fully consider the potential harms associated with the study. Consequently, the internal validity of the study, as well as the generalizability, are compromised.
There will be certain criteria that potential subjects need to meet depending on the study’s primary endpoints and desired sample. For example, the inclusion criteria for a study on a new drug being tested for asthma would include participants with a current diagnosis of asthma. In the same study, a change in protocol could occur if, for example, the age of the participant with asthma changes because of the small sample size. Consequently, modifying a current study in this manner requires many steps and approvals from an IRB; therefore the modification should clearly support the reason for the change.
Protection from discomfort and harm is imperative within research and is extended to research participants. The researcher must look at the intervention they are studying and the risks/benefits to the potential subject. Although a negative outcome may occur because of an intervention introduced in the study, a researcher should not knowingly apply an intervention with intent to harm; therefore, any potential risks should always be defined in the informed consent, so a potential subject can be fully aware before making a decision to participate in the study. The American Psychological Association (2017) reinforces that a researcher must actively work to prevent harm and use research to promote good in the world. For example, if a researcher wants to determine whether turning patients every three hours versus every two hours will minimize skin breakdown, the researcher should look to see if research already exists looking at this intervention. Once a literature review has been conducted, the research can determine whether the findings of existing studies leaves the researcher confident that this intervention will not intentionally create further skin breakdown? In this example, it is the due diligence of the researcher to prevent intentional physical harm.
While this example discussed potential physical harm, it is important to understand that harm can be found in other forms, such as emotional or social well-being. The researcher must also understand that
duty of care
is a legal obligation. Research and interventions are done as an act to protect the individual, are in the individual’s best interest, and cause no harm.
Specific to the RN, the American Nurses Association has a position statement on the topic of human rights in research; nurses who are researchers must work to ensure the research subject’s rights are protected with ongoing informed consent, judicious monitoring of the risk versus benefit for the subjects, and the protection of the subjects from harm (American Nurses Association, 2016).
Check for Understanding
1. What kind of ethical dilemma could be in direct conflict with an individual’s rights when signing a consent form for a study?
2. In experimental research, what specific details regarding the control group must potential research subjects clearly understand prior to giving consent?
Quantitative Research in Nursing
·
·
Quantitative research has its own unique process in nursing research. Figure 3.1 illustrates the process involved with quantitative research. Quantitative research studies move in a linear or sequential format. The sequence or flow is typically the same from study to study. A question is posed at the beginning of the study with the question being answered at the end of the study, with the research outcomes generating further discussion.
Figure 3.1
Steps in Quantitative Research
The Quantitative Nursing Research Process Explained
The following is a discussion of each step of the quantitative research process used for nursing research.
1. Research Problem/Purpose: What is the problem to be studied?
2. Review of Relevant Literature: Does literature already exist on this topic? If so, are there any gaps. Does this gap make sense to be studied via quantitative research with close-ended questions, or does qualitative research seem to be a better fit for the problem?
3. Study Framework: What is the theory or conceptual framework that would best serve the variables of the study? Examples of theory branches include grand nursing theory and middle-range theory. There are subcategories within these theory branches. Theories are more abstract than frameworks. Frameworks are used as methods to map out how concepts or variables relate to each other.
4. Research Questions or Hypotheses: What needs to be clearly defined? What bridges the abstract framework and tests one or two variables? Hypotheses are essential in quasi-experimental and experimental studies, as these are the two study designs that have researcher manipulation and an element of control.
5. Study Variables: It is important to think through the idea of conceptual versus operational definitions of variables. How would a researcher describe an idea he or she wants to study to a fellow researcher? That description of the variable is referred to as the conceptual definition; however, the operational definition of a variable is how it will be measured in that particular research study.
6. Study Design: The design of the study is chosen to meet the needs of what is being studied. For example, if something is being tested and the outcomes of the application of that intervention is in need of discovery (i.e. a new piece of equipment, a new protocol in the hospital), then the design needs to be quasi-experimental or experimental; however, if the researchers are seeking to understand a new idea or general relationships between variables, then descriptive or correlational could be appropriate.
7. Population and Sample: Who are the appropriate research subjects to study ethically and appropriately in the desired research problem? What are the inclusion and exclusion criteria for the sample?
8. Measurement Methods: Measurement of data includes the predetermined assignment of value to different data sets. Researchers need to determine what method of measurement is the most appropriate for the desired variables to be studied in their research design and framework.
9. Data Collection: With the given design and environment chosen to conduct the research study, what is the most appropriate means to collect data? A few examples of data collection methods include surveys, interviews, observation, or a mixture of one or more methods.
10. Data Analysis: This is the section in quantitative research in which the information such as statistical or clinical significance, causation, and/or correlation will be discussed. Words such as significant or insignificant impact will appear here. Did the numbers support what the researcher thought was going to happen? The discussion of the results will occur in the final section.
11. Discussion of Research Outcomes: What do the results mean to a study? For example, what do the results mean to this particular disease state/patient population that has been studied? What does it mean to the profession of nursing? What should be done with this research? Is the data so strong that the researcher feels a call to action? If so, what are the next steps? If there are limitations in the study, what are they? What should be studied next? While this study filled a research gap determined in the literature review, is there now another area where this data can be extrapolated and/or further researched? Does a new gap now exist? The study’s validity will be important in understanding how the results can be applied to the general population. Internal validity should be at the forefront of all research to protect the integrity of the results of the study. In essence, within the confines of the study design and execution, is there any influence on the study that could have altered the validity of the results? External validity refers to the ability of the researcher to apply the results from their study at large. Sample size, research environment, and random selection are three key elements that can greatly impact the generalizability of the study.
Lastly,
intervention fidelity
is a concept in nursing research that speaks to the consistency of the research. This refers to the degree that the intervention was intended. Fidelity checklists should be utilized to ensure that the intervention implemented in a research design remains consistent with no variations in order to reduce possible bias or manipulation into the study.
For example, participants in a new clinical trial for a diabetes medication to reduce blood glucose levels were asked to self-report their exercise regime. In this case, it would be difficult to obtain fidelity in the study because variables exist that cannot be ruled out that can affect the glucose levels with the medication introduced in the study. Some participants may have been exercising for many years, some participants may have recently begun exercising as part of the study; therefore, it is important for researchers to be trained in fidelity efforts to reduce variables as much as possible in a research study.
The Need for Quantitative Research
·
·
The difference between qualitative research and quantitative research is that qualitative research is a means to study and assign meaning to subjective life experiences, whereas quantitative research is a means of mathematically proving relationships exist between variables (Conner, 2014). Choosing to use quantitative research intentionally looks at the relationship between variables. Depending on the specific research design, the degree of the relationship being studied will change. For example, a study on diabetic medication cannot yield accurate data if the participants do not take their diabetes medication as directed.
In nursing, ideas are formed from research studies through the use of
evidence-based practice (EBP)
. EBP takes into account the evidence, the patients being served, and the organization as a whole. In addition, EBP values clinical expertise (Conner, 2014). The link between EBP and nursing research cannot be understated. EBP also is important in that key stakeholders, such as clinicians, patients, researchers, policy makers and others who are involved and support the research study, are more likely to use and disseminate the information they help to produce (Agency for Healthcare Research and Quality, 2018). The stronger the evidence presented, the more likely stakeholders will set priorities to invest in the research being proposed.
Quantitative research is an ongoing process. Once the end of one study has occurred, it becomes the springboard for another. There is strength in having similar results in multiple studies on similar topics. Thus, over time, multiple studies yield information for EBP. The studies will show either continued maintenance of a nursing practice, changes that need to be made because of new evidence and/or stronger evidence, or reveal previous gaps.
Four Main Categories of Quantitative Research
The four main categories of quantitative research—descriptive, correlational, quasi-experimental, and experimental research— are differentiated by
intent
,
environment
, manipulation/control, and bias (see Table 3.1). Quantitative research aims to study relationships between variables with numerical outcomes, descriptive and correlational designs are less concerned with cause-and-effect relationships than are quasi-experimental and experimental studies. Quasi-experimental and experimental studies exert more control over variables than descriptive and correlational studies. Thus, if a researcher is intending to make a claim that there is a definitive, direct, cause-and-effect relationship between variables, then experimental studies are more fitting than descriptive or correlational designs.
In research designs, specifically with experimental research, manipulation is used to purposefully change a variable within the study. This is done to see if the
independent variable
changes. While researchers can unethically manipulate factors, and create unreliable and untrustworthy research, variables are manipulated or controlled to see the impact of a variable with an intentional intervention. The specific quantitative research design used by the researcher will depend on the specific intent of the study. The further down the design is on the spectrum of the four categories, the tighter the control of the study.
Descriptive → Correlational → Quasi-Experimental → Experimental
Table 3.1
Four Categories of Quantitative Research
Category
Intent
Environment
Manipulation/Control
Bias
Descriptive Studies
To describe a situation, subject, behavior, or phenomenon
Observation of actual events/phenomena as they occur in various settings
None
More chance of bias
Correlational Studies
Type of nonexperimental research; measures the statistical relationship between two or more variables and the degree of the relationship (cause/effect)
Various settings
None
More chance of bias
Quasi-Experimental Studies
Determine the degree of relationship between variables in which an intervention is conducted on a target population without random assignment
Semicontrolled environment
Less control than experimental studies; intervention introduced; independent variables are manipulated
Less chance of bias
Experimental Studies
Highly controlled research; true experiment in which researcher manipulates one or more variables to determine effect on other variables; random assignment is used.
Highly controlled environment
Highly controlled; independent variable(s) manipulated
Less chance of bias
Note. Adapted from “Quantitative Approaches,” by the Center for Intervention and Research and Teaching, n.d.a.
Descriptive research design is the least controlled of all quantitative designs. With descriptive research, there is little known about the topic, leaving the researcher to observe the topic and describe it. From descriptive research, data is achieved that helps in the creation of hypotheses for future research.
With correlational research design, researchers are trying to understand relationships. While more information is understood on the topic than in studies utilizing the descriptive research design, studies suited for the correlational research design take what was learned in descriptive research studies and try to draw an idea of how the variables might interact. From the data collected in previous studies, it is known there is a relationship between variables. In correlational research studies, the researcher is trying to understand how the variables affect each other in the same way, or influence opposing directional outcomes. From here, the hypotheses for quasi-experimental and experimental research is often created.
In quasi-experimental research design, there is well understood directional relationships and the way in which cause and effect is being determined. The prefix quasi means nearly but not completely, so quasi-experimental means that it is nearly experimental. The greatest difference between quasi-experimental and experimental research designs is that the independent variable is not controlled in quasi-experimental research.
Experimental research design is the most highly controlled quantitative design. Experimental research is where the most manipulation occurs to have the most
reliable
outcomes and the most definitive answers on what factors truly influence others and how. The highest degree of control would occur in a randomized, double-blind, placebo-controlled study. This type of study would result in the least amount of bias because the participants are randomly selected for the treatment/intervention, and neither the patients nor the researcher would know if they were receiving the treatment/intervention or placebo. There would be specific coding of the patient to maintain the integrity of the
blinding
.
Variables in Quantitative Research
·
·
Three main variables exist in quantitative research: independent, dependent, and extraneous. These variables are important for the researcher to consider in the quantitative study. The independent variable is the variable the researcher manipulates, and the
dependent variable
is the outcome being assessed (Center for Intervention and Research and Teaching [CIRT], n.d.c). For example, a researcher might look at using a new catheter kit (independent variable) to numerically quantify where urinary tract infection rates decrease (dependent variable).
Extraneous variables can be a multitude of factors. It is impossible for the researcher to control every potential extraneous variable, but the researcher needs to look at factors that could affect the outcomes of the independent and dependent variables to minimize outside influence of the outcome being studied (CIRT, n.d.c). Controlling extraneous factors are important because it minimizes doubt in the validity of the mechanism of the outcome.
Just as it is nearly impossible to remove every extraneous variable, the same is true of bias. Bias exists when there is influence of the study that change the results. Many factors can result in bias, including unintentional or intentional subjectivism with the researchers performing the study, inadequate study design and data collection methods, lack of honesty from study participants regarding behaviors, or sample imbalances, such as choosing one specific patient population over another. While bias is nearly unavoidable even in the best designed studies, steps should always be taken to reduce bias. Because of the level of control in the methodology, quasi-experimental and experimental quantitative studies have decreased risk of bias. In addition, the researcher should acknowledge any extraneous variables they think affected the dependent variable in the study. Any potential bias should be discussed as well. When looking at sources of bias, they could be as concrete as topics, such as the process of data collection or statistical analysis regarding vague topics, such as the belief systems of patients or researchers; financial topics, such as who’s funding the research; or any incentive the researcher has in creating certain outcomes from the research.
Critical Components of Quantitative Research Methods
·
·
When reviewing quantitative research, it is important for the nurse to approach the study and data systematically. There can be differences within quantitative studies that make some studies stronger than others in support of EBP changes. One of the most critical components of research is finding the overall purpose of the study, commonly called objectives of the study, study goals, and aims of the study, which can be found in the abstract of the study.
Within the abstract, a reader should be able to understand quickly what type of nursing research was conducted and the overall goals of the study. In quantitative data, the independent and dependent variable will be discussed. In addition, there should be at least one numerical data outcome highlighted in the abstract. If the study uses
mixed methods research design
, it might be difficult to exclude that any qualitative data was used; however, it should be evident that quantitative methods were used by looking for variables and numerically driven outcomes.
The problem statement discusses the gap in knowledge that served as the catalyst for conducting the research in the first place. It should be evident what was missing on the particular subject being studied and why researching it will positively impact patient outcomes and/or improve health care delivery in general. The research objectives should align to what will be studied in order to give more insight into the problem statement.
In addition, the why of the study should be apparent. For example, a previous study investigated different urinary catheter materials, and there appeared to be a relationship between the two variables, but the results were not clearly supported numerically to deliver a quantifiable impact on the relationship. Based on this previous research, the research problem may conclude that a gap in knowledge exists in understanding the impact a particular catheter brand has on infection and catheters. Objectives should then clearly delineate how that impact is going to be studied by looking at the rate of infection using a specific urinary catheter.
As previously discussed, variables are a key part of quantitative research. In the critical appraisal of research, it is important to find the independent and dependent variables and understand what they are and how they were specifically defined for that study. It is also important to consider the population studied and to determine the inclusion/exclusion criteria so the characteristics of the sample is understood.
After reading what the study is, how it was performed, and what was gained in the study, the implications for practice indicate where the data can be applied. As an example, a study found that using a particular urinary catheter reduced catheter associated urinary tract infections by 30%. Such findings warrant a hospital taking the next steps in obtaining this catheter. On the other hand, if the study’s data show that there was a 30% decrease in infection with only this particular urinary catheter in conjunction with better hand hygiene, other interventions, in addition to obtaining this type of catheter, may need to be instituted. Numerical data can be very useful in understanding the impact of a particular nursing intervention.
Feasibility of a Research Study
·
·
The researcher will include the feasibility of studying the problem and study’s purpose. The feasibility discussion may be direct, inferred, or both. For example, if the issue is a large problem in health care that can be studied in multiple sites throughout the world, the feasibility of studying the topic would be increased; however, if the topic is very narrow, the feasibility of conducting the research is decreased.
Additionally, the researchers’ background will also be included in the research study. Do they have extensive knowledge on the topic? Are they new researchers, or have they been doing research in this field for many years? Questions should also be addressed regarding the breadth and depth of the researcher’s background. As with nursing, experience is very valuable when conducting research. Understanding the study in context to the experience of the researchers can be helpful in critically appraising the study.
Funding can affect a study in a number of ways, including bias from conflicts of interest, the duration of the study, the number of study sites, sample size, and statistical analysis. The funding sources can often be found toward the end of the study and are listed by the researcher. This helps the reader identify potential conflicts of interest between the study and those funding the research. For example, if a nursing researcher works for the company that makes the particular urinary catheter that’s been discussed hypothetically in this section, then the reader needs to keep this potential area of bias in mind as they continue to appraise the value of the data achieved. Besides potential bias, the funding for the study can dictate the study itself. If funding was limited, it can impact the overall study.
Information on adequacy of subjects, settings, and equipment can be found within the limitations of the study section. Here, the researcher will discuss whether there were any issues that impacted the ability of the research to be conducted, such as the study being performed in a center with a small population size, a large drop-out rate of subjects that impacted the integrity of the data obtained, or malfunctions with the equipment used in the study. All of these are examples of how to critically assess the adequacy of subjects, settings, and equipment when reading a research article. All topics should be assessed to help understand the value of the data when choosing to study a specific topic in the nursing profession.
Hypotheses in Quantitative Research Studies
·
Hypotheses
are always used in quantitative research; however, the way in which the hypothesis is written determines the degree of prediction between variables within each research design type. Quasi-experimental and experimental studies will include a strong predictive hypothesis as they predict cause and effect between independent and dependent variables. In addition, with quasi-experimental and experimental studies, there has already been previous data conducted that shows a relationship exists, but the exact degree of relationship may not be understood or measured mathematically (CIRT, n.d.b). Hypotheses for quasi-experimental and experimental research designs will be specific and testable. Correlational study designs will have hypotheses that predict the relationship between the independent and dependent variables; however, because of the lack of control in the study design, any change in the dependent variable cannot be determined to be a result of the independent variable. Finally, descriptive study designs will have hypotheses that merely state that one variable is related another. Descriptive designs are often used to create hypotheses for later research (Cantrell, 2011).
When critically appraising a research study, the variables should be outlined and discussed as they relate to the quantitative research design. Remember, with descriptive designs, there will be discussion about the existence of a relationship, whereas experimental designs will define the extent of the causal relationship. In addition to the independent and dependent variables, outside influences should be discussed as well, such as whether an extraneous variable had an effect or whether there were confounding variables in the study. Sometimes an extraneous variable can become a confounding variable. In order to have confounding variables, there must be at least three variables, and there has to be a systematic change that occurs in at least one of the measured variables. Often, it behaves similarly to the independent variable. Thus, if an extraneous variable is behaving similarly to the variable being studied, it is difficult to declare confidently that the resulting dependent variable changes because of the independent variable because the change could have been caused by the confounding variable instead. For example, if a researcher is studying whether individuals who run at least 6 miles per day (the dependent variable) have lower heart rates than individuals who do not run at all (the independent variable).
Types of Hypotheses
There are four main types of hypotheses: associative versus causal, simple versus complex, nondirectional versus directional, and statistical (null) versus research (see Figure 3.2). Associative hypotheses propose that there is a definite relationship that exists between two variables; if one variable changes, then the other changes as well; however, one variable does not directly cause the change in the other variable. In a causalhypothesis, there is a direct cause and effect relationship. This is aligned with independent and dependent variables and the relationship that exists between these two factors.
Simple versus complex differs because of the number of variables discussed. With a simple hypothesis, the relationship between two variables is discussed. In a complex hypothesis, three or more variables are analyzed. The relationship can be either associative or causal. A nondirectional hypothesis does not state the direction of the proposed relationship between two variables. Conversely, a directional hypothesis does speculate how the variables will impact each other, which more easily clarifies the studies outcome. Lastly, statistical, or null, hypotheses imply that no relationship exists between two variables. These hypotheses can be either simple/complex or associative/causal. Research hypotheses are the opposite of statistical hypotheses, as they propose that a relationship exists between variables. These hypotheses can be simple/complex, nondirectional/directional, or associative/causal (Rockinson-Szapkiw, 2017).
Figure 3.2
Directional vs. Nondirectional Hypotheses
Examples of Hypotheses Relationships
A researcher is studying whether individuals who run at least 6 miles per day (the dependent variable) have lower heart rates than individuals who do not run at all (the independent variable), the following hypotheses and relationships may develop.
Associative
· Relationship: Individuals who run and swim have lower heart rates than individuals who only run.
· Hypothesis: Can running and swimming both be associated to lower heart rates?
Causal
· Relationship: Individuals who run have lower heart rates.
· Hypothesis: Is the cause of lower heart rates due to running?
Simple
· Relationship: Individuals who run at least 6 miles per day have lower heart rates than individuals who do not run at all (one dependent variable and one independent variable).
Complex
· Relationship: Individuals who run at least 6 miles per day and swim at least twice a week have lower heart rates than individuals who do not run or swim at all (one dependent variable, two independent variables).
Directional
· Relationship: People who run have lower heart rates.
Nondirectional
· Relationship: People who run and swim have lower heart rates than people who only run.
Null
· Relationship: Individuals who do not run have the same heart rates as those individuals who run daily.
Check for Understanding
Why does evidence and support within a study need to be strong enough for key stakeholders to support and invest in the proposed research?
Critically Appraising the Literature Review
·
·
·
The literature review is an extremely important part of the research process. Being aware of this process can help to recognize appropriate data sources, as well as how to categorize this information for efficiency and use in a systematic way. Literature cited should be from credible, current sources that were written within the past 5 years. A reputable source would be an article found in PubMed written by an author within the National Institute of Health (NIH). When looking at multiple studies, it is important to pull out key themes and takeaways, such as anything that is repeated consistently within the research, including terms and noted gaps in the literature.
Conducting a literature review is necessary to support and fund a research study. It is imperative to critique the strength and weaknesses of a study before including it in one’s own study, as the value of the studies’ presented evidence can support or weaken a study. This is why it is imperative to evaluate all the evidence closely so that informed decisions can be made on choosing the correct literature to support the study.
Systematic Review of the Literature
Systematic reviews use methodical procedures to reproduce and verify research evidence. The primary focus of the review is to determine data and literature associated with a study for a proposal of a new study to help develop and test research evidence. A variety of databases are used to perform a search for the appropriate literature. Some of the more common research databases for nurse researchers include Beyond Cumulative Index of Nursing and Allied Health Literature (CINAHL), PubMed, and government databases. When approaching critical appraisal of a quantitative research article, it is often best to use a step-by-step process in order to synthesize the strengths and weaknesses of the article. Identifying specific elements and providing answers to the following questions will help to create a solid foundation of critical analysis of the research article.
Background of Study
1. Identify the clinical problem and research problem that led to the study. What was not known about the clinical problem that, if understood, could be used to improve health care delivery or patient outcomes? This gap in knowledge is the research problem.
2. How did the author establish the significance of the study? In other words, why should the reader care about this study? Look for statements about human suffering, costs of treatment, or the number of people affected by the clinical problem.
3. Identify the purpose of the study. An author may clearly state the purpose of the study or describe the purpose as the study goals, objectives, or aims.
4. List research questions that the study was designed to answer. If the author does not explicitly provide the questions, attempt to infer the questions from the answers.
5. Were the purpose and research questions related to the problem?
Methods of Study
1. Identify the benefits and risks of participation addressed by the authors. Were there benefits or risks the authors do not identify?
2. Was informed consent obtained from the subjects or participants?
3. Did it seem that the subjects participated voluntarily in the study?
4. Was an IRB approval obtained from the agency in which the study was conducted?
5. Are the independent and dependent variables identified and defined? What were these variables?
6. How were data collected in this study?
7. What rationale did the author provide for using this data collection method?
8. What was the time period for data collection of the study?
9. What was the sequence of data collection events for a participant?
10. What were the data management and analysis methods used in the study?
11. Did the author discuss how the rigor of the process was assured? For example, does the author describe maintaining a paper trail of critical decisions that were made during the analysis of the data? Was statistical software used to ensure accuracy of the analysis?
12. What measures were used to minimize the effects of researcher bias? For example, did two researchers independently analyze the data and compare their analyses?
Results of Study
1. What is the researcher's interpretation of findings?
2. Are the findings valid or an accurate reflection of reality?
3. What limitations of the study were identified by researchers?
4. Was there a coherent logic to the presentation of findings?
5. What implications do the findings have for nursing practice? For example, can the findings of the study be applied to general nursing practice, to a specific population, or to a specific area of nursing?
6. What suggestions are made for further studies?
Ethical Considerations
1. Was the study approved by an IRB?
2. Was patient privacy protected?
3. Were there ethical considerations regarding the treatment or lack of treatment?
Conclusion
1. Emphasize the importance and congruity of the thesis statement.
2. Provide a logical wrap-up to bring the appraisal to completion and to leave a lasting impression and takeaway points useful in nursing practice.
3. Incorporate a critical appraisal and a brief analysis of the utility and applicability of the findings to nursing practice.
4. Integrate a summary of the knowledge learned.
Mixed Design Research Methods
·
Mixed methods research design is becoming increasingly popular, particularly in the nursing profession. Utilizing a study that looks at a research question using both quantitative and qualitative design adds a depth and breadth of understanding to a topic that could not otherwise be obtained. In addition, having both quantitative and qualitative study designs occurring simultaneously leads to team research amongst those with quantitative expertise and those with qualitative expertise; however, conducting research in this manner comes with challenges.
With mixed method research design, there is often equal weight to each type of data used, meaning there is more data to analyze requiring more manpower to assess both types of data, which results in taking more time and money needed to conduct the research. In addition, with both types of studies occurring simultaneously, there might be a blend of the two data collections and potential inconsistencies within each objective collection. This might lead to delays in recollecting data, or potential issues with internal validity within the study. Overall, it is important to understand that this type of design is possible and preferred in research problems that need both designs to understand the problem more comprehensively (Doorenbos, 2014).
The Role of the BSN-Prepared Nurse in Research and Nursing Leadership
·
·
The BSN-prepared RN has the ability to understand research, appraise the studies, and the importance of utilizing research to ensure EBP in the clinical setting. Additionally, BSN-prepared RNs are able to participate in research teams as a research nurse and be involved in the collection of data in clinical studies. RNs who have furthered their education and obtained their Master of Science in nursing (MSN) can conduct research studies and appraise and synthesize the data to affect the nursing practice. Protocol changes, editing, or creating new treatment algorithms are a few real-life applications of MSN-prepared RNs. RNs who have achieved a doctor of nurse practice (DNP) degree are able to impact national guidelines. Although DNPs are not PhDs who create new research, the DNP educated RN can take current data and apply it to nursing practice for the improvement of patient care. If gaps are seen, they can collaborate with nurse researchers to impact further research on the topic to advocate change (American Association of Colleges of Nursing, 2017).
Reflective Summary
Quantitative research is a very systematic approach to studying certain kinds of research problems. Understanding the four main types of quantitative design, what to expect, and when to use them are key to understanding quantitative research. Having a good working knowledge of independent, dependent, and extraneous variables are key elements in understanding the overall framework of the design and intervention. Above all, BSN-prepared RNs should have a good working knowledge of quantitative research as they learn to apply evidence-based interventions to their current practice as well as a means of ongoing quality improvement to practice in the nursing profession at large. Research will continue to challenge the status quo for the profession as well as those nurses who serve and protect patients.
Key Terms
Beneficence: Actively helping, doing kindness, performing quality conduct, and sharing goodness for the benefit of others.
Bias: External and internal influences within a study that can affect the validity and reliability of the outcomes.
Blinding: Not making the status of the treatment/intervention being tested known to the research subject or researcher; in double-blind studies, neither the researcher or research subject know the status of the treatment/intervention being tested.
Confidentiality: Keeping information secret from others; not disclosing private matters.
Control: The process of consistent management of influences on the dependent variable of the study.
Control Group: The group of subjects not receiving the treatment; the sample not receiving the intervention being studied; also known as comparison group.
Correlational Research Design: A type of quantitative research that is not controlled and aims to understand relationships between variables.
Dependent Variable: The outcome variable. It takes on different values in response to the independent variable.
Descriptive Research Design: The systematic collection of data to describe the variable, such as the characteristics of a population or current phenomena, being identified.
Duty of Care: A legal obligation on the part of an individual to adhere to standards of reasonable care while performing acts that could harm others.
Environment: The setting in which the research takes place.
Evidence-Based Practice (EBP): The integration of clinical expertise, the most up-to-date research, and patient’s preferences to formulate and implement best practices for patient care.
Experimental Research Design: A type of quantitative research design that is highly controlled and to study cause and effect with independent and dependent variables.
External Validity: The ability of the research study to be generalized to the population at large.
Independent Variable: The experimental or predictor variable. It is manipulated in the research to observe the effect on the dependent variable.
Intent: The purpose of the study.
Internal Validity: The ability of the researcher to minimize external influence on the data achieved in the study.
Intervention: What the researcher is assessing and looking for outcomes of in the study. For example, a new medication, procedure, protocol, or medical supply.
Intervention Fidelity: The process in which a researcher records and monitors the exact steps that are taken with each subject to ensure consistency in delivering the intervention in the study.
Manipulation: A means to control variables in quasi-experimental and experimental research studies in order to see the effect of an intervention on outcomes; what was introduced into the study that could change the outcome of the study; also referred to as the control.
Mixed Methods Research Design: A type of research design that includes both quantitative and qualitative design methods.
Nonmaleficence: Committing no harm or evil; based on Hippocrates' admonishment to first do no harm.
Quasi-Experimental Research Design: A type of quantitative research design that is partially controlled that studies cause and effect of variables.
Randomized Controlled Trials (RCT): Research studies in which patients are chosen at random to receive the treatment/intervention being tested; considered the gold standard of research design.
Reliability: The extent to which an experiment, test, or measuring procedure yields the same results on repeated trials.
Self-Determination: The right to make decisions for one’s self.
Variables: A data item such as characteristics, numbers, properties, or quantities that can be measured or counted. The value of the data item can vary or be manipulated from one entity to another. There are three different types of variables—dependent, independent, and extraneous.
Sampling methods in Clinical Research; an Educational Review
Mohamed Elfil
1 and
Ahmed Negida
2
Author information Article notes Copyright and License information
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cited by
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Abstract
Clinical research usually involves patients with a certain disease or a condition. The generalizability of clinical research findings is based on multiple factors related to the internal and external validity of the research methods. The main methodological issue that influences the generalizability of clinical research findings is the sampling method. In this educational article, we are explaining the different sampling methods in clinical research.
Key Words: Research design, sampling studies, evidence-based medicine, population surveillance, education
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Introduction
In clinical research, we define the population as a group of people who share a common character or a condition, usually the disease. If we are conducting a study on patients with ischemic stroke, it will be difficult to include the whole population of ischemic stroke all over the world. It is difficult to locate the whole population everywhere and to have access to all the population. Therefore, the practical approach in clinical research is to include a part of this population, called “sample population”. The whole population is sometimes called “target population” while the sample population is called “study population. When doing a research study, we should consider the sample to be representative to the target population, as much as possible, with the least possible error and without substitution or incompleteness. The process of selecting a sample population from the target population is called the “sampling method”.
Sampling types
There are two major categories of sampling methods (
figure 1
): 1; probability sampling methods where all subjects in the target population have equal chances to be selected in the sample [
1
,
2
] and 2; non-probability sampling methods where the sample population is selected in a non-systematic process that does not guarantee equal chances for each subject in the target population [
2
,
3
]. Samples which were selected using probability sampling methods are more representatives of the target population.
Open in a separate window
Figure 1
Sampling methods.
Probability sampling method
Simple random sampling
This method is used when the whole population is accessible and the investigators have a list of all subjects in this target population. The list of all subjects in this population is called the “sampling frame”. From this list, we draw a random sample using lottery method or using a computer generated random list [
4
].
Stratified random sampling
This method is a modification of the simple random sampling therefore, it requires the condition of sampling frame being available, as well. However, in this method, the whole population is divided into homogeneous strata or subgroups according a demographic factor (e.g. gender, age, religion, socio-economic level, education, or diagnosis etc.). Then, the researchers select draw a random sample from the different strata [
3
,
4
]. The advantages of this method are: (1) it allows researchers to obtain an effect size from each strata separately, as if it was a different study. Therefore, the between group differences become apparent, and (2) it allows obtaining samples from minority/under-represented populations. If the researchers used the simple random sampling, the minority population will remain underrepresented in the sample, as well. Simply, because the simple random method usually represents the whole target population. In such case, investigators can better use the stratified random sample to obtain adequate samples from all strata in the population.
Systematic random sampling (Interval sampling)
In this method, the investigators select subjects to be included in the sample based on a systematic rule, using a fixed interval. For example: If the rule is to include the last patient from every 5 patients. We will include patients with these numbers (5, 10, 15, 20, 25, ...etc.). In some situations, it is not necessary to have the sampling frame if there is a specific hospital or center which the patients are visiting regularly. In this case, the researcher can start randomly and then systemically chooses next patients using a fixed interval [
4
].
Cluster sampling (Multistage sampling)
It is used when creating a sampling frame is nearly impossible due to the large size of the population. In this method, the population is divided by geographic location into clusters. A list of all clusters is made and investigators draw a random number of clusters to be included. Then, they list all individuals within these clusters, and run another turn of random selection to get a final random sample exactly as simple random sampling. This method is called multistage because the selection passed with two stages: firstly, the selection of eligible clusters, then, the selection of sample from individuals of these clusters. An example for this, if we are conducting a research project on primary school students from Iran. It will be very difficult to get a list of all primary school students all over the country. In this case, a list of primary schools is made and the researcher randomly picks up a number of schools, then pick a random sample from the eligible schools [
3
].
Non-probability sampling method
Convenience sampling
Although it is a non-probability sampling method, it is the most applicable and widely used method in clinical research. In this method, the investigators enroll subjects according to their availability and accessibility. Therefore, this method is quick, inexpensive, and convenient. It is called convenient sampling as the researcher selects the sample elements according to their convenient accessibility and proximity [
3
,
6
]. For example: assume that we will perform a cohort study on Egyptian patients with Hepatitis C (HCV) virus. The convenience sample here will be confined to the accessible population for the research team. Accessible population are HCV patients attending in Zagazig University Hospital and Cairo University Hospitals. Therefore, within the study period, all patients attending these two hospitals and meet the eligibility criteria will be included in this study.
Judgmental sampling
In this method, the subjects are selected by the choice of the investigators. The researcher assumes specific characteristics for the sample (e.g. male/female ratio = 2/1) and therefore, they judge the sample to be suitable for representing the population. This method is widely criticized due to the likelihood of bias by investigator judgement [
5
].
Snow-ball sampling
This method is used when the population cannot be located in a specific place and therefore, it is different to access this population. In this method, the investigator asks each subject to give him access to his colleagues from the same population. This situation is common in social science research, for example, if we running a survey on street children, there will be no list with the homeless children and it will be difficult to locate this population in one place e.g. a school/hospital. Here, the investigators will deliver the survey to one child then, ask him to take them to his colleagues or deliver the surveys to them.
APA Formatting Tutorial
Introduction
Hello, and welcome to Grand Canyon University’s APA Formatting Tutorial. This tutorial will cover the basic format required for all papers submitted to GCU and will utilize Microsoft Word. Most of the features demonstrated in this tutorial are available in earlier versions of Microsoft Word but may be found in different locations. Keep in mind that different platforms and versions of Word may look different and have different features. Access to Microsoft Office is provided by GCU and can be installed from the GCU Technical Support website. A link is provided in the Additional Resources list below this video.
Using GCU Templates
Using GCU Templates. The easiest way to format your paper correctly is by beginning with the APA Template provided in the Student Success Center. To access the Student Success Center, first log into your course. Next, click on “Dashboard,” then “Student Resources” and then click on “Student Success Center.”
On the Student Success Center page, click on the Resources drop-down menu toward the top of the page. Under Tools, click on “The Writing Center” and then “Style Guides and Templates.”
Under “Style Guides and Templates,” you will see the APA 7th Edition Template listed. There are two versions, one with an abstract and one without. Click on the version that you want to use. Your assignment will say if an abstract is required or not.
Note that there are a number of different templates available in the Writing Center and that different level classes and disciplines have unique formatting requirements. You should select and use the correct template for your assignment. If you are unsure as to which template to use, consult your instructor.
When you click on the template, your computer will ask you to open or save the file. Choose “Save” and save it with your other Word documents, or somewhere that you will easily remember.
Once you save the template, double click on the file to open it. The file template may also open automatically depending on your computer’s settings.
If there is a yellow bar at the top of the page that says “Protected View,” you will need to click “Enable Editing” before you can make changes. This too may vary depending on the platform you are using.
Now that the template is open, you will be able to simply insert your information into the paper by highlighting the text you want to replace and typing over it.
Title Page
Title Page. First, add your title to the paper in place of the text “Typing Template for APA Papers: A Sample of Proper Formatting for the APA 7th Edition.” A title should be descriptive, focused, and it should include the key concepts of the paper.
After you have entered your title, add your Name where the Template says “Student A. Sample.” For group projects, add the names of the other students in your group on the same line.
Next, enter the name of your college at GCU, such as the College of Nursing & Health Care Professions, which is followed on all papers by "Grand Canyon University." Then enter the course prefix and number, and the course title. The next line is for your instructor or instructors. Finally, enter the date the assignment is due.
The template already includes the page numbers, so you will not need to add them.
There is more information about how to format your title page on the APA Style website and the GCU Library’s Citing Sources in APA guide. Links are provided in the additional resources section.
Abstract
Abstract. If you downloaded the template that included the abstract, your next page is the abstract. An abstract is just a brief summary of your paper. Abstracts should be no more than 250 words and include your key points, research question, and conclusions. For papers that include original research, include the design, method, and results of the research you did.
Your assignment will say if an abstract is required. Many assignments do not require an abstract, so use the Template Without Abstract if one is not required.
There is more information about how to create an abstract on the APA Style website and the GCU Library’s Citing Sources in APA guide. Links are provided in the additional resources section.
Main Body
Main Body. Once you are finished with your abstract (if you have one) scroll to the next page (page 3). If you do not have an abstract, this will be the second page right after the title page. This is where you will begin to write your paper.
NEW SECTION
On the first line on this page, type the full title of your paper, in bold. Once you have done this, you are ready to start typing your paper on the line below the title. Notice that the first line of the paragraph is indented. Each time you start a new paragraph, the first line will automatically be indented.
If you wish to divide your paper into sections, follow the format in the template. All headings are in bold and have the first word and all words over four letters capitalized. The main headings, called Level 1 headings, are centered. There is more information about how to use headings and the different levels on the APA Style website and the GCU Library’s Citing Sources in APA guide. Links to these resources are provided in the additional resources section.
In-Text Citations
In-Text Citations. As you type your paper, make sure that you cite any content that is from another person or another source, whether a direct quote or just an idea. Citations will go in two places. First, you will add an in-text citation directly after you reference another source in your paper. Secondly, you will add the full reference to your reference list at the end of your paper. Information about in-text and reference citations can be found in GCU Library’s Citing Sources in APA Guide, the APA Style website, and in the Publication Manual of the American Psychological Association.
In-text citations are much shorter than full citations. They generally include the author and date, and for quotations, they also include page number or other specific location. For example, if I am quoting from Eats, Shoots & Leaves: The Zero Tolerance Approach to Punctuation, by Lynne Truss in my paper, I would say: Truss (2003) says about commas, “when it comes to improving the clarity of a sentence, you can nearly always argue that one should go in; you can nearly always argue that one should come out” (p. 80). You will notice the year follows the author’s name. Since this is a direct quote, I include the page number at the end of the quote.
Sometimes sources, including some ebooks, do not have page numbers. If I want to quote Good Arguments: Making Your Case in Writing and Public Speaking by Richard Holland Jr. and Benjamin Forrest in my paper, I would say: As Holland and Forrest (2017) said, “No one knows everything...you included. It stands to reason, then, that if you want to make good arguments, you will need to rely on the arguments, ideas, and expertise of other authors” (Chapter 8). Since this ebook does not have page numbers, I include the chapter instead. If you are not naming the author in your sentence, then the in-text citation will follow the quote with author, year, and page number or location. For example, if you were to write, “the English language first picked up the apostrophe in the 16th century” you would then use author, year, and page number at the end of quote: (Truss, 2003, p. 37).
If your quote is 40 or more words, it will need to be placed into a block quotation. Quotation marks should not be used. The quote should begin on a new line and the entire quote should be indented .5 inches from the left margin. Once the entire quote is written, remember to include the in-text citation with a page number or other specific location in parentheses after the closing punctuation mark.
More examples and tips for in-text citations can be found at the GCU Library’s Citing Sources in APA Guide under ‘In-Text Citations’. For more information, please see the URLs listed below under Additional Resources.
References Page
References. At the end of your paper, you will have your reference list. This is formatted correctly in the APA 7th edition template in the Student Success Center that we have been using as an example.
Note how the second line and any following lines of each citation in the reference list are indented .5 inches. This is called a hanging indentation.
Let’s take a look at how the reference page is formatted. The first thing you should notice is that the references are listed in alphabetical order by the author’s last name. In some cases, when there is no personal author, the name of the organization responsible for the source is used as the author.
While all references include the same basic information, each type of source is formatted slightly differently. The last citation, Holland & Forrest, is for the book we quoted from earlier. The citation includes the authors’ last names, followed by their initials, the publication year in parentheses, the title of the book in sentence case and italics, and the name of the publisher. Even though this book came from the library’s ebook collection, because it does not have a DOI, or Digital Object Identifier, the reference is written the same as if it were a print book. The reference to the Publication Manual is also a book, but it does have a DOI, so the DOI is at the end.
Next, we’ll look at the fourth reference, which is for a journal article by Copeland and others. This article has four authors and all are listed. The publication year follows in parentheses, then the title of the article. Two items when referencing a journal article are always in italics, the journal title and the volume number. If there is an issue number, it will follow the journal volume in parenthesis. The page numbers come next. At the end of this particular reference is a DOI. Not all articles or books have DOIs, but if you use a source in your paper and it has a DOI, be sure to include this in your reference. It should be formatted just as shown in the example.
The final references we will look at are for a document or a webpage found on an organization website, the American Nurses Association and the Center for Substance Abuse Treatment examples. Notice that these references do not have a personal author. Instead, the department or organization that is responsible for the information is listed as the author. Following the author is the publication year in parentheses, and the title of the document found on the website in italics. The first example then ends with the direct link to the source, as the webpage author and the website’s owner are the same. The second example includes two additional pieces of information before the link, a publication number, and the name of the overall government agencies responsible for the document. Not all documents found online will include publication numbers, but if you use a source that includes this information, it should be included in the reference. These two pieces of information about this source can be clearly seen on the webpage for this source, so we know to include them.
There is more information about different source types and how to cite them on the APA Style website and the GCU Library’s Citing Sources in APA guide. Links are provided in the additional resources section.
Finding Citations
Finding Citations in the Library. Many of the databases in the library include citations that you can copy and paste into the References section of your paper. In general, once you locate an article in a database, look for a button or link that says “cite.” We will demonstrate how to locate citations in two of our general databases.
First, let’s look at the Academic Search Complete database. To get there from the library homepage, click “Find Journal Articles” in the middle of the page. Then scroll down to click on “Academic Search Complete” on the list. If you are prompted to login, enter your GCU login – the same one you use to log into the student portal. Let’s try a simple search to find scholarly articles. When you locate an article that you wish to use as a source for your paper, click on the title of that article to view the detailed record. On the right side of the screen, you will see a list of tools. Locate the “Cite” button and click on it. The center of the screen will now display citations formatted in different citation styles. Highlight the APA formatted citation with your mouse, then right click and select “Copy” from the menu that pops up. Next, go to your Word document, find the correct location in your “References” list for the reference, and right click in that location. From the menu that pops up, click on “Merge Formatting” – it’s the middle icon. If the reference is more than one line long, the second and any following lines should be indented. To set this in Microsoft Word, highlight the entire reference, go to the “Home” tab and click on the small arrow in the lower right corner of the “Paragraph” section. In the “Indentation” area of the window that opens, select “Hanging” from the menu below “Special,” and then click on OK.
It’s also important to check the capitalization of words in the titles of selected resources. In this example provided by the database, the first letter of each word in the title is capitalized.
Although the first letter of the first word needs to be uppercase, the remaining words in the article title may need to be changed to lowercase letters per APA guidelines.
Next, let’s locate a reference in the Credo Reference database. To get there, go back to the “Find Journal Articles” page. Since we know the name of the database, click on “C” and then click on “Credo Reference.” When you locate an entry that you wish to use as a source for your paper, click on the title of that article in your results list to open it. To the top of the article, click on the “Citation” button – a dialogue box will open. Next, make sure that “APA” is selected, then highlight, copy, and paste the citation into the appropriate place in the “References” section of your paper. You will then need to correct any extra information included.
The library databases automatically generate citations based on data that is included in the detailed bibliographic record. Sometimes, the citation may be missing some key information that you would need to complete your reference page, and some databases have not yet updated to the APA 7th Edition formatting. Many will also include the permalink, so you can find the article again. Though this link is helpful to you, it is not a part of an APA reference. Always proofread and double-check the citations from any library database.
Figuring out the correct way to cite sources can be challenging; however, there are many resources available to assist you in the process. For quick citation formatting help, you can also visit the GCU Library’s Citing Sources in APA guide or the APA Style website. Links to these resources are located at the bottom of the page under “Additional Resources.”
Inside the Writing Center, where you downloaded the template at the beginning of this tutorial, is a Style Guide for the APA 7th Edition that also includes examples of citations.
If you are in doubt about a citation format, please do not hesitate to contact a librarian by e-mail or by chat at http://library.gcu.edu or by phone at 1-800-800-9776, extension 639-6641. You can also consult with a LEAD at the ACE Centers. Make an appointment and find out more at the ACE Center website found with the links below.
This concludes the APA Formatting Tutorial. If you have further questions about APA style, please refer to these additional resources.
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