Objectives, Questions, Hypotheses, and Study Variables



Objectives, Questions, Hypotheses, and Study Variables


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Researchers formulate objectives, questions, and hypotheses to bridge the gap between the more abstractly stated research purpose and the detailed plan for data collection and analysis. Objectives, questions, and hypotheses delineate the study variables, the relationships among the variables, and, often, the population to be studied.


Study variables are concepts at various levels of abstraction that are measured, manipulated, or controlled in a study. Concrete concepts, such as temperature, weight, and blood pressure, are referred to as variables in a study; abstract concepts, such as creativity, empathy, and social support, are sometimes referred to as research concepts. Research variables and concepts are conceptually defined, on the basis of the study framework, and are operationally defined to direct their measurement, manipulation, or control in a study.


In this chapter, you will explore when objectives, questions, or hypotheses might be developed to direct the conduct of a study. You will also learn how to formulate research objectives, questions, and hypotheses, especially how to test different types of hypotheses through research. This chapter concludes with a discussion of different types of variables and direction for conceptually and operationally defining variables for a study.



Formulating Research Objectives or Aims


Research objectives or aims are clear, concise, declarative statements expressed in the present tense that usually are presented following the study purpose to specify the study focus. For clarity, an objective usually focuses on one or two variables (or concepts) and indicates whether the variables are to be identified or described. Objectives can also identify relationships or associations among variables, determine differences between groups or compare groups on selected variables, and predict a dependent variable on the basis of selected independent variables.


A combination of the following formats might be used in developing objectives to guide a study. The focus of each objective is identified in the parentheses at the end of each statement. The objectives are placed in order from the least complex to the most complex in generating research evidence. Thus, the objectives or aims of studies might be to:





Research Problem


“A major component of nursing care after coronary artery bypass surgery (CABS) is focused on educating patients to recognize and manage postoperative symptoms [problem significance]. The symptoms commonly experienced have been well documented in the literature and include sleep disturbances (Tranmer & Parry, 2004; Zimmerman, Barnason, Nieveen, & Schmaderer, 2004), fatigue (Tranmer & Parry, 2004; Zimmerman et al., 2004), swelling (Tranmer & Parry, 2004; Zimmerman et al., 2004), shortness of breath (SOB), appetite problems, and chest and leg incision pain (Zimmerman et al., 2004) [problem background]. Although much has been done to document postoperative symptoms, very little has been done to describe the strategies that patients use to manage these symptoms [problem statement].” (Schulz et al., 2011, pp. 65-66)



In this example, the problem provides a basis for the purpose, and the aims evolve from the purpose to clearly focus the conduct of the study. The first aim was focused on identification of the categories of symptom management strategies (variable) used by older adults (population) 3 and 6 weeks after CABS (hospital and home settings). The study participants were recruited from four Midwestern hospitals, but the majority of data collection took place in the participants’ homes. The second aim was focused on description of the older adults’ symptom management strategies (variable) used. The third objective was focused on comparison of or differences in patients’ reported symptom management strategies and current evidence-based guidelines developed by the American Heart Association. Schulz et al. (2011, p. 65) found, “Three weeks after surgery, the most frequently used strategies were rest to manage shortness of breath (53%) and fatigue (53%), medications for incision pain (24%), and repositioning for swelling (35%) and sleep disturbance (18%). Overall, fewer patients experiencing sleep disturbances (39%), incision pain (39%), swelling (46%), and appetite problems (17%) reported using a strategy to manage their symptoms.” Thus, the researchers stressed the importance of nurses’ education of patients about symptom identification and effective management strategies to improve recovery following CABS.



Formulating Objectives or Aims in Qualitative Studies


Many qualitative studies are guided by the study purpose and do not include research objectives or questions. However, some qualitative researchers do develop objectives to guide selected studies. The objectives in qualitative studies usually have a broader focus and include more abstract and complex variables or concepts than those in quantitative studies (Munhall, 2012). An ethnographic study by Happ, Swigart, Tate, Hoffman, and Arnold (2007) included objectives to direct their investigation of patients’ involvement in health-related decisions during prolonged critical illness, as shown by the following excerpts.



In this ethnographic study, the problem statement indicated that inadequate research had been conducted on patient involvement in health-related decisions during critical illness, which provided a basis for the study purpose. All four objectives focused on detailed descriptions of the study variables: (1) characteristics of patients undergoing PMV, (2) health-related decision making of these patients, (3) how patient involvement in decision making occurred, and (4) extent of patient decision making. The findings from this study indicated that families, advanced practice nurses, and physicians were engaging critically ill patients in decision making whenever possible. However, most of the time the patients could not make independent decisions but were able to share decision making with their families and clinicians. These findings emphasize how important it is for families and clinicians to include critically ill patients in health-related decisions at whatever level possible (Happ et al., 2007).



Formulating Research Questions


A research question is a concise, interrogative statement that is worded in the present tense and includes one or more variables (or concepts). The research questions focus on the following: (1) the identification and/or description of the variable(s), (2) a determination of differences between two or more groups regarding selected variables, (3) an examination of relationships among variables (relational), and (4) the use of independent variables to predict a dependent variable.


You might use the following formats in developing research questions for a study (the focus for each question is shown in parentheses). The levels of evidence to be generated by the following research questions progress from simple (identification) to complex (prediction).




Formulating Questions in Quantitative Studies


Delaney, Apostolidis, Lachapelle, and Fortinsky (2011, p. 285) conducted a comparative descriptive study to examine “home care nurses’ knowledge of evidence-based education topics for management of heart failure.” The following excerpts from this study demonstrate the flow from research problem and purpose to research questions.




Research Problem


“Heart failure (HF), a chronic and disabling syndrome affecting adults of all ages and particularly older adults, is a major public health problem. An estimated 5.7 million Americans are currently affected by HF, and this figure is expected to double over the next 25 years, primarily because of the aging of the population and decreased mortality from other cardiovascular conditions (Hodges, 2009). … HF is characterized by poor posthospital discharge outcomes [problem significance]. … Home care agencies are currently being challenged by Centers for Medicare and Medicaid Services (CMS) to improve outcomes in HF management. … Home care nurses play key roles in the delivery of education to patients and their families [problem background]. However, home care nurses face unique challenges compared with nurses at other sites of care in providing comprehensive education on managing HF. These challenges include a lack of access to detailed patient information (Bowles, Pham, O’Connor, & Horowitz, 2010), a focus on generalist rather than specialist practice, and few opportunities for continuing education in specialized knowledge such as managing HF [problem statement].” (Delaney et al., 2011, p. 286)




Question 1 focused on description of the home care nurses’ (population) knowledge about HF (variable). Question 2 focused on determining differences in the nurses’ knowledge on the basis of educational level and years of work experience (demographic variables). Question 3 focused on description of the nurses’ self-reported knowledge needs (variable) in managing patients with HF. Delaney et al. (2011) found that home care nurses were limited in their evidence-based knowledge for managing HF. There were no significance differences in the nurses’ knowledge and their educational level and years of experience. The researchers concluded that the home care nurses needed educational programs focused on HF patient management to improve the quality of patient education they could provide.



Formulating Questions in Qualitative Studies


The questions in qualitative studies are often limited in number, have a broad focus, and include variables or concepts that are more complex and abstract than those in quantitative studies. Marshall and Rossman (2011) noted that the questions in qualitative research either might be theoretical ones, which can be studied with different populations or in a variety of sites, or could be focused on a particular population or setting. Hudson et al. (2010) conducted an exploratory-descriptive qualitative study to examine the health-seeking challenges perceived by homeless young adults. The problem, purpose, and research questions used to direct this study are presented in the following excerpts.




Research Problem


“Adolescent homelessness is a distressing social problem. Approximately 1.5 to 2 million homeless adolescent persons live on the streets in the United States (Bucher, 2008); homelessness among young persons is more common than homelessness among older adults. … Homeless young adults are highly vulnerable to negative health consequences because of the realities of street life [problem significance]. … Homeless young persons are at risk for sexual and physical abuse. … Other negative health consequences experienced by homeless young adults include sexually transmitted infections, poorly controlled chronic mental illness, and lack of immunization for conditions, such as hepatitis A and hepatitis B (Hudson, Nyamathi, & Sweat, 2008). … Homeless persons are more likely to be admitted to the hospital and have increased durations of hospitalization than those of nonhomeless persons due to negative health consequences associated with street living. … Nearly half of all homeless young persons have no regular source of health care (Sneller et al., 2008) [problem background]. … The perceptions of how homeless persons view the health care system have not been well studied. … There is a growing assertion that improvements should be made with respect to the provision of quality care for the homeless young adults living in the United States. … One way to achieve high-quality programs designed to improve health care for homeless adults is to solicit these adults’ input in program development [problem statement].” (Hudson et al., 2010, pp. 212-213)




The first study question focused on developing a description of the homeless young adults’ (population) perspectives on facilitators and barriers to receiving health care (research variables). The second question focused on identifying and describing how young-adult-centered healthcare programs can be improved (research variable). The study’s “identified themes were failing access to care based on perceived structural barriers (limited clinic sites, limited hours of operation, priority health conditions, and long wait times) and social barriers (perception of discrimination by uncaring professionals, law enforcement, and society in general…)” (Hudson et al., 2010, p. 212). The researchers also gained insights into the programmatic and agency resources that are needed to promote health-seeking behaviors by homeless young adults.



Formulating Hypotheses


A hypothesis is the formal statement of the expected relationship or relationships between two or more variables in a selected population. The hypothesis translates the problem and purpose into a clear explanation or prediction of the expected results or outcomes of the study (Shadish, Cook, & Campbell, 2002). This section describes the purpose, sources, and types of hypotheses that are commonly developed by researchers. In addition, the process for developing and testing hypotheses in nursing studies is described.



Purpose of Hypotheses


The purpose of a hypothesis is similar to that of research objectives and questions. A hypothesis (1) specifies the variables you will manipulate or measure, (2) identifies the population you will examine, (3) indicates the type of research, and (4) directs the conduct of your study. Hypotheses direct the conduct of a study by influencing the study design, sampling technique, data collection and analysis methods, and interpretation of findings. Hypotheses differ from objectives and questions by predicting the outcomes of a study. Study hypotheses are used to organize the results section of a study, and the results indicate support or nonsupport of each hypothesis. Hypothesis testing allows us to generate knowledge by testing theoretical statements or relationships that were identified in previous research, proposed by theorists, or observed in practice (Chinn & Kramer, 2008; Fawcett & Garity, 2009



Sources of Hypotheses


Research hypotheses can be generated by observing phenomena or problems in nursing practice, analyzing theory, and reviewing the research literature. Many hypotheses originate from real-life experiences. Clinicians and researchers observe events in practice and identify relationships among these events (theorizing), which are the bases for formulating hypotheses. For example, you may notice that the hospitalized patient who complains the most about pain receives the most pain medicine and other pain management strategies. The relationship identified is a prediction about events in clinical practice that has potential for empirical testing, because certain patients might not be receiving adequate pain management.


You could conduct a literature review to identify a theory that supports this relationship. For example, Fagerhaugh and Strauss (1977) developed a theory of pain management and identified the following relationship or proposition: As expressions of pain increase, pain management increases. The researchers developed this proposition through the use of grounded theory research. Additional testing is necessary to determine its usefulness in describing how patients express pain and how that pain is managed in a variety of practice situations. On the basis of theory and clinical observation, the following hypothesis might be formulated: The more frequently a hospitalized patient verbalizes perceptions of pain, the greater the administration of analgesic medications by healthcare providers.


Some hypotheses are initially generated from relationships expressed in a theory, when the intent of the researcher is to test a theory. Usually, middle-range theories are tested in research, and a proposition or relationship from the theory provides the basis for the generation of one or more study hypotheses (Fawcett & Garity, 2009; Smith & Liehr, 2008). For example, Rungruangsiripan, Sitthimongkol, Maneesriwongul, Talley, and Vorapongsathorn (2011) tested the relationships in the Common-Sense Model of Illness Representation (Diefenbach & Leventhal, 1996) to examine the factors affecting medication adherence in individuals with schizophrenia. Figure 8-1 contains the framework model for this study based on the Common-Sense Model of Illness Representation, which has three stages: sources of information, illness representation, and coping. “Sources of information included social support variable, therapeutic alliance variable, and experience of medication side effects variable. Coping consisted of intention to change adherence behavior and adherence behavior” (Runguangsiripan et al., 2011, p. 272). This model shows the direct and indirect relationships among the concepts that provide a basis for the study hypotheses. A direct relationship is when one concept links to another concept without an intervening concept. For example, the concept of social support is linked directly to illness representation. In an indirect relationship, one concept is linked to another concept through an intervening third concept. For example, the concept experience with medication side effects is indirectly linked to the concept intention to change adherence behavior through the concept of illness representation (see Figure 8-1). The Rungruangsiripan et al. (2011) study set the following hypotheses:




These hypotheses were formulated to test the propositions or relationships from the Common-Sense Model of Illness Representation (see Figure 8-1). The researchers found that “therapeutic alliance and the experience of medication side-effects enhanced illness representation, which in turn led to an intention to change adherence behavior. Social support did not alter illness representation or adherence behavior” (Rungruangsiripan et al., 2011, p. 269). Illness representation is the patients’ perception of their schizophrenia and their ability to cope with the illness. Patients with a clear perception of their schizophrenia have strong intentions to change their adherence behaviors. Thus, mental health nurses need to promote the patients’ understanding of their schizophrenia illness to enhance their adherence to their medications.


Reviewing the research literature and synthesizing findings from different studies can also be used to generate hypotheses. For example, Ross, Sawatphanit, Mizuno, and Takeo (2011) synthesized the findings from studies to identify the factors that predict depressive symptoms in postpartum women who are HIV-positive. They developed a conceptual framework for their study that is presented in Figure 8-2. The researchers “hypothesized that depressive symptoms are negatively related to self-esteem, emotional support, and infant health status but positively associated with physical symptoms” (Ross et al., 2011, p. 37).



Ross et al. (2011) found that self-esteem and infant health status were significant predictors of postpartum women’s depressive symptoms but physical symptoms and emotional support were not. The study results indicated that 74.1% of the HIV-positive postpartum women had symptoms of depression, and the researchers encouraged nurses to examine the self-esteem and infant health status of such women to increase identification of episodes of depression. The researchers also recommended further research to identify additional factors that might be predictive of depression in HIV-positive postpartum women. Thus, two relationships, those of self-esteem and infant health status to depressive symptoms, were supported in the framework model (see Figure 8-2). However, the other relationships, those of emotional support and physical symptoms to depressive symptoms, were not supported in this study. Additional research is needed to increase understanding of the factors that might be predictive of depression in postpartum women who are HIV-positive.



Types of Hypotheses


Hypotheses identify different types of relationships and include different numbers of variables. Studies might have one, three, or more hypotheses, depending on the complexity and scope of the study. The type of hypothesis developed is based on the problem and purpose of a study. The following four categories are used to describe types of hypotheses: (1) associative versus causal, (2) simple versus complex, (3) directional versus nondirectional, and (4) null versus research.



Associative versus Causal Hypotheses


The relationships in hypotheses are identified as associative or causal. An associative relationship identifies variables that occur or exist together in practice, and as one variable changes so does the other. For example, research indicates there is an associative relationship between anxiety and depression, and as a person’s depression changes so does the anxiety level. Thus, associative hypotheses are developed to examine relationships among variables in a study. The formats used for expressing associative hypotheses follow:



1. Variable X is related to or associated with variable Y in a selected population. (Predicts a relationship between two variables but does not indicate the type of relationship.)


2. An increase in variable X is related to an increase in variable Y, or variable X is positively related to variable Y in a selected population. (Predicts a positive relationship.)


3. A decrease in variable X is related to a decrease in variable Y in a selected population. (Predicts a positive relationship.)


4. An increase in variable X is related to a decrease in variable Y, or variable X is negatively related to variable Y in a selected population. (Predicts a negative or inverse relationship.)


5. Variables X and Y are predictive of variable Z in a study. (The independent variables X and Y are used to predict the dependent variable Z in a predictive correlational study.)


Associative hypotheses identify relationships among variables in a study but do not indicate that one variable causes an effect on another variable. Researchers state associative hypotheses when the focus of their study is to examine relationships and not to determine cause and effect. For example, Reishtein (2005) conducted a predictive correlational study to examine the relationships between symptoms and functional performance in patients with chronic obstructed pulmonary disease (COPD). Reishtein developed the following associative hypotheses to guide the study:



Hypothesis 1 predicts positive relationships or associations among the variables of dyspnea, fatigue, and sleep difficulty for patients with COPD. A positive relationship means that the variables change together; thus, they will all increase together in value or all decrease together. These relationships are depicted in the following diagram:


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Hypothesis 2 predicts relationships between three variables—dyspnea, fatigue, and sleep difficulty—and the variable functional performance, but it does not identify the type of relationship. These relationships are shown in the following diagram:


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Hypothesis 3 uses the independent variables dyspnea, fatigue, and sleep difficulty to predict the dependent or outcome variable functional performance in COPD patients. The predictive relationship is shown in the following diagram:


Dyspnea+Fatigue+Sleep DifficultyFunctional Performance


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Feb 17, 2017 | Posted by in NURSING | Comments Off on Objectives, Questions, Hypotheses, and Study Variables

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