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Clarifying Quantitative Research Designs

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Stories of 6 young people are described in the article. There was an extensive 4 year period of in depth fieldwork that included telephone and in person interviews and participant observation.

The stories powerfully illustrated how the culture in which the youths had to survive was so alienating that they deliberately sought exposure to HIV. The findings provide an important understanding for nurses working with adolescents in either preventive or acute care roles. The ethnographic approach was uniquely suited to bring attention to the important influence of the context of marginalisation, insensitive social policies, and demanding caretaking responsibilities, on the lives of these youths.

The purpose of a grounded theory approach to qualitative research is to discover social-psychological processes. Theoretical sampling refers to sampling decisions made throughout the entire research process in which participants are selected based on their knowledge of the topic and based on emerging study findings. In data analysis, the researcher constantly compares incidents, categories, and constructs to determine similarities and differences and to develop a theory that accounts for behavioural variation.

Both observation and interviewing are commonly used for data collection. Grounded theory was used to answer the research question what is the process of reimaging after an alteration in body appearance or function? The theoretical sample consisted of 28 participants who had experienced body image disruptions such as significant weight change; amputation or paralysis of body parts; and scars from burns, surgery, or trauma.

Participants were interviewed at 3, 6, 12, and 18 months after the physical alteration. The constant comparative method of concurrent data collection and analysis was used to develop a 3 phase theory of the process of reimaging: Nurses can use this vital understanding of the phases of reimaging to assist clients through the process by anticipating potential needs or problems, providing information and support, and exploring alternative problem solving strategies.

The grounded theory approach was ideally suited to discovering the social-psychological process of reimaging. The examples of nursing research studies using 3 different approaches exemplify the value of qualitative research in answering important nursing questions. All studies, however, resulted in important new information about the phenomena studied.

This new information facilitates a deeper understanding of participants' experiences by nurse readers and—as long as nurses remain aware of the theoretical rather than empirical basis for generalising from the qualitative findings—has the potential for influencing nursing practice in similar situations.

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Log in via OpenAthens. Log in using your username and password For personal accounts OR managers of institutional accounts. Forgot your log in details? Register a new account? Forgot your user name or password? Search for this keyword. Latest content Current issue Archive Authors About. Log in via Institution. Identifying the best research design to fit the question. Sampling, data collection, and data analysis Sampling refers to the process used to select a portion of the population for study.

Types of qualitative research There are many different types of qualitative research, such as ethnography, phenomenology, grounded theory, life history, and ethnomethodology. Phenomenology The aim of a phenomenological approach to qualitative research is to describe accurately the lived experiences of people, and not to generate theories or models of the phenomenon being studied.

Ethnography The goal of ethnography is to learn about a culture from the people who actually live in that culture.

Grounded theory The purpose of a grounded theory approach to qualitative research is to discover social-psychological processes. Conclusion The examples of nursing research studies using 3 different approaches exemplify the value of qualitative research in answering important nursing questions. National League for Nursing Press, Designing funded qualitative research.

Qualitative research methods for health professionals. Qualitative research in nursing: This chapter introduces you to selected experimental designs and provides examples of these designs from published nursing studies. The algorithm shown in Figure may be used to determine the type of design descriptive, correlational, quasi-experimental, and experimental used in a published study.

This algorithm includes a series of yes or no responses to specific questions about the design. Sometimes, researchers combine elements of different designs to accomplish their study purpose.

For example, researchers might conduct a cross-sectional, descriptive, correlational study to examine the relationship of body mass index BMI to blood lipid levels in early adolescence ages 13 to 16 years and late adolescence ages 17 to 19 years.

It is important that researchers clearly identify the specific design they are using in their research report. Descriptive studies are designed to gain more information about characteristics in a particular field of study. The purpose of these studies is to provide a picture of a situation as it naturally happens. A descriptive design may be used to develop theories, identify problems with current practice, make judgments about practice, or identify trends of illnesses, illness prevention, and health promotion in selected groups.

No manipulation of variables is involved in a descriptive design. Protection against bias in a descriptive design is achieved through 1 conceptual and operational definitions of variables, 2 sample selection and size, 3 valid and reliable instruments, and 4 data collection procedures that might partially control the environment. Descriptive studies differ in level of complexity.

Some contain only two variables; others may include multiple variables that are studied over time. You can use the algorithm shown in Figure to determine the type of descriptive design used in a published study. Typical descriptive and comparative descriptive designs are discussed in this chapter.

Grove and colleagues have provided details about additional descriptive designs. A typical descriptive design is used to examine variables in a single sample Figure This descriptive design includes identifying the variables within a phenomenon of interest, measuring these variables, and describing them.

The description of the variables leads to an interpretation of the theoretical meaning of the findings and the development of possible relationships or hypotheses that might guide future correlational or quasi-experimental studies. When critically appraising the designs of descriptive and correlational studies, you need to address the following questions:. Is the study design descriptive or correlational? Review the algorithm in Figure to determine the type of study design. If the study design is descriptive, use the algorithm in Figure to identify the specific type of descriptive design implemented in the study.

If the study design is correlational, use the algorithm in Figure to identify the specific type of correlational design implemented in the study. Were the study variables measured with quality measurement methods? Maloni, Przeworski, and Damato studied women with postpartum depression PPD after pregnancy complications for the purpose of describing their barriers to treatment for PPD, use of online resources for assistance with PPD, and preference for Internet treatment for PPD.

Inclusion criteria were women between 2 weeks and 6 months postpartum who had been hospitalized for pregnancy complications.

EPDS is a widely used screening instrument to detect postpartum depression…. Questions were developed from review of the literature. Maloni and associates clearly identified their study design as descriptive and indicated that the data were collected using an online survey. This type of design was appropriate to address the study purpose. The sample section was strengthened by using the EPDS to identify women with PPD and using the sample criteria to ensure that the women had been hospitalized for pregnancy complications.

However, the sample size of 53 was small for a descriptive study. The item questionnaire had content validity and was consistently implemented online using standard survey software. This typical descriptive design was implemented in a way to provide quality study findings. The common barriers that prevented them from getting treatment included time and the stigma of PPD diagnosis. A comparative descriptive design is used to describe variables and examine differences in variables in two or more groups that occur naturally in a setting.

A comparative descriptive design compares descriptive data obtained from different groups, which might have been formed using gender, age, educational level, medical diagnosis, or severity of illness. Buet and colleagues conducted a comparative descriptive study to describe and determine differences in the hand hygiene HH opportunities and adherence of clinical e.

The following study excerpt includes key elements of this comparative descriptive design:. Throughout the study, regular debriefings were also held to review and discuss data recording. During approximately hours of observation, HH opportunities were observed.

Buet and associates clearly described the aspects of their study design but did not identify the specific type of design used in their study. The design was comparative descriptive because the HH opportunities and adherence for clinical and nonclinical caregivers were described and compared.

The study included hours of observation 16 hours per child of HH opportunities in four different ECF settings. Thus the sampling process was strong and seemed focused on accomplishing the study purpose. The data collectors were well trained and monitored to ensure consistent observation and recording of data. Buet and co-workers found that the HH of the clinical caregivers was significantly higher than the nonclinical caregivers.

The low HH adherence suggested increased potential for transmission of infections among children in ECFs. Additional HH education is needed for clinical and nonclinical caregivers of these children to prevent future adverse events.

The purpose of a correlational design is to examine relationships between or among two or more variables in a single group in a study. This examination can occur at any of several levels— descriptive correlational, in which the researcher can seek to describe a relationship, predictive correlational, in which the researcher can predict relationships among variables, or the model testing design, in which all the relationships proposed by a theory are tested simultaneously.

In correlational designs, a large range in the variable scores is necessary to determine the existence of a relationship. Therefore the sample should reflect the full range of scores possible on the variables being measured.

Some subjects should have very high scores and others very low scores, and the scores of the rest should be distributed throughout the possible range. Because of the need for a wide variation on scores, correlational studies generally require large sample sizes.

Subjects are not divided into groups, because group differences are not examined. To determine the type of correlational design used in a published study, use the algorithm shown in Figure More details on correlational designs referred to in this algorithm are available from other sources Grove et al.

The purpose of a descriptive correlational design is to describe variables and examine relationships among these variables. Using this design facilitates the identification of many interrelationships in a situation Figure The study may examine variables in a situation that has already occurred or is currently occurring. Researchers make no attempt to control or manipulate the situation. As with descriptive studies, variables must be clearly identified and defined conceptually and operationally see Chapter 5.

Burns, Murrock, and Graor conducted a correlational study to examine the relationship between BMI and injury severity in adolescent males attending a National Boy Scout Jamboree. The key elements of this descriptive correlational design are presented in the following study excerpt. This study used a descriptive, correlational design to examine the relationship between obesity and injury severity. Exclusion criteria were adolescent males presenting with medical complaints unrelated to an injury e.

Each facility was equipped to manage both medical complaints and injuries. Past medical history, weight in pounds and height in inches were obtained from the HMR [health and medical record]. BMI [body mass index] and gender-specific BMI percentage were calculated electronically using online calculators from the Centers for Disease Control and Prevention and height and weight data.

BMI-P defines four weight status categories: Age was measured in years and was self-reported. This five-level triage rating scale was developed by the Agency for Healthcare Research and Quality and provides rapid, reproducible, clinically relevant stratification of patients into levels based on acuity and resource needs. When discrepancies were found, the primary researcher reviewed the treatment record to determine the most accurate score.

Burns and colleagues clearly identified their study design in their research report. The sampling method was a nonrandom sample of convenience that is commonly used in descriptive and correlational studies.

The exclusion sampling criteria ensured that the subjects selected were most appropriate to address the study purpose. The BMI-P and severity injury scores were obtained using reliable and valid measurement methods, and the data from the medical facilities were checked for accuracy.

The design of this study seemed strong and the knowledge generated provides a basis for future research. Burns and associates found a significant relationship between BMI-P and injury severity. Additional research is needed to examine the relationship of BMI to injury risk and to identify ways to prevent injuries in these adolescents.

The findings from this study also emphasize the importance of healthy weight in adolescents to prevent health problems. QSEN implications are that evidence-based knowledge about the relationship between obesity and severity of injury provides nurses and students with information for educating adolescents to promote their health. The purpose of a predictive correlational design is to predict the value of one variable based on the values obtained for another variable or variables.

Prediction is one approach to examining causal relationships between variables. Because causal phenomena are being examined, the terms dependent and independent are used to describe the variables. The variable to be predicted is classified as the dependent variable, and all other variables are independent or predictor variables. A predictive correlational design study attempts to predict the level of a dependent variable from the measured values of the independent variables.

For example, the dependent variable of medication adherence could be predicted using the independent variables of age, number of medications, and medication knowledge of patients with congestive heart failure. The independent variables that are most effective in prediction are highly correlated with the dependent variable but are not highly correlated with other independent variables used in the study.

The predictive correlational design structure is presented in Figure Predictive correlational designs require the development of a theory-based mathematical hypothesis proposing variables expected to predict the dependent variable effectively. Researchers then use regression analysis to test the hypothesis see Chapter Coyle used a predictive correlational design to determine if depressive symptoms were predictive of self-care behaviors in adults who had suffered a myocardial infarction MI.

The following study excerpt presents key elements of this design. A descriptive correlational design examined the relationship between the independent variable of depressive symptoms [agitation and loss of energy] and the dependent variable of self-care.

Data were collected from 62 patients in one hospital, who were recovering from an MI in the metropolitan Washington, areaA…. Self-care behaviors after an MI were measured by the Health Behavior Scale HBS , developed specifically for measuring the extent to which persons with cardiac disease perform prescribed self-care behaviors.

Coyle might have identified her study design more clearly as predictive correlational but did clearly identify the dependent variable as self-care and the independent variables as depressive symptoms. The design also included the longitudinal measurement of self-care with the HBS at 2 weeks and 30 days. The design was appropriate to accomplish the study purpose. The sample of 62 subjects was adequate because the study findings indicated significant results.

HBS had strong reliability in previous studies but the validity of the scale was not addressed. This study has a strong design with more strengths than weaknesses, and the findings are probably an accurate reflection of reality. The study needs to be replicated with stronger measurement methods and a larger sample.

Coyle found that depressive symptoms of agitation and loss of energy were significantly predictive of self-care performance in patients with an MI at 30 days post—hospital discharge. Coyle recommended screening post-MI patients for depressive symptoms so that their symptoms might be managed before they were discharged. Further research is recommended to examine depression and self-care behaviors after hospital discharge to identify and treat potential problems.

Some studies are designed specifically to test the accuracy of a hypothesized causal model see Chapter 7 for content on middle range theory. The model testing design requires that all concepts relevant to the model be measured and the relationships among these concepts examined. A large heterogeneous sample is required.

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An overview of research designs relevant to nursing: Part 1: Quantitative research designs. Valmi D. Sousa I; Martha Driessnack II; Isabel Amélia Costa Mendes III. I PhD, so it is important to have a broad preparation and understanding of the different types of research designs available.

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What are the main types of quantitative approaches to research? It is easier to understand the different types of quantitative research designs if you consider how the researcher designs for control of the variables in the investigation.. If the researcher views quantitative design as a continuum, one end of the range represents a design where the variables are not controlled at all and only. There are four main types of quantitative research designs: descriptive, correlational, quasi-experimental and experimental. The differences between the four types primarily relates to the degree the researcher designs for control of the variables in the experiment.

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A nurses’ guide to Quantitative Research AUTHOR Rebecca (Becky) Ingham‑Broomfield Designs Quantitative research falls into four main designs, namely, Descriptive, Correlational, Experimental and Quasi‑ measures (Polit and Hungler ). Commonly used methods in nursing research also include focus groups and interviews that are. AN OVERVIEW OF RESEARCH DESIGNS RELEVANT TO NURSING: PART 1: QUANTITATIVE RESEARCH DESIGNS Valmi D. Sousa1 Martha Driessnack2 and understanding of the different types of research designs available. Research designs are most often classified as either quantitative or qualitative. However.