Data Collection and Quantitative Research Methodology
Quantitative Research
Quantitative research consists of the collection, tabulation, summarization, and analysis of numerical data for the purpose of answering research questions or hypotheses.
The term quantitative research is of recent
origin and is distinguished from qualitative research in design, process, and
the use of quantification techniques to measure and analyze the data. The vast
majority of all nursing studies can be classified as quantitative.
Use of Statistical Methods in Quantitative Research
Quantitative research uses statistical methodology at every stage in the research process. At the inception of a research project, when the research questions are formulated, thought must be given to how the research variables are to be quantified, defined, measured, and analyzed.
Study subjects are often selected for a research project through the statistical method of random sampling, which promotes an unbiased representation of the target population among the sample from whom generalizations will be made.
Statistical methods are used to summarize study data, to determine sampling error, and in studies in which hypotheses are tested, to analyze whether results obtained exceed those that could be attributed to sampling error (chance) alone.
The important role of statistical methodology in quantitative research should not obscure the fact that other methodologies and scientific disciplines play important roles in nursing research.
These methods are used in the delineation of research questions and hypotheses, exposure of conceptual frameworks and hypotheses, design of data collection instruments and tools, and interpretation of study data, particularly determination of the clinical significance of the data and dissemination of findings.
Much of the history of nursing research involves quantitative research. Florence Nightingale, who was a skilled statistician, used quantitative measures to describe and evaluate hospital performance (Nightingale, 1858). Studies of nursing in the United States, beginning in the 1940s, used quantitative techniques to survey and analyze nursing education and supply and distribution of nurses.
In the 1960s, with
support from the federal government, research in nursing began to use advanced
research designs, such as controlled experiments, which made extensive use of
quantitative tools, techniques, and processes ( Hasselmeyer , 1961).
Quantitative Data Collection
Quantitative data collected in quantitative research are obtained by the use of measurement scales. There are three distinct types of scales: nominal, ordinal, and continuous. Nominal scales consist of two or more ungraded or unranked categories of variables, such as eye color (green, blue, brown) or political affiliation (Republican, Democrat).
Ordinal scales possess categories that are ranked or graded, from high to low, small to large, near too far. Graded scales, such as the Likert and Guttman scales, are commonly used in nursing research to measure intensity of opinions, attitudes, and other psychological variables.
When nominal and ordinal scales are used, quantitative
summaries of the data collected consist of aggregating the number of responses
in each scale category, converting them to relative frequencies such as
percentages, and if hypotheses are being tested in the research, applying one
of many nonparametric techniques available to test the statistical significance
of the data.
Continuous scales have continuous quantitative values rather than verbal categories, as in nominal and ordinal scales. These include the scientific measuring instruments widely used in nursing to measure variables such as temperature, weight, height, blood pressure.
Continuous measurement scales have certain advantages over other scales because they yield more precise and sensitive data. Also, the statistical significance of continuous data can be analyzed by the more powerful parametric techniques.
Quantitative Research Generalization
Quantitative research is concerned with making generalizations from a study sample to a target population, a process called statistical inference. There are two categories of generalizations in quantitative research:
(a) estimates of the quantitative value of selected characteristics of a target population
(b) results of tests of statistical hypotheses concerning relationships among variables in the target population. Studies in the first category are called descriptive studies; those in the second category are called analytical or explanatory studies.
The focus of many early nursing studies was to describe
nurses and nursing practice using questionnaire or interview techniques to
collect data from large samples of respondents. Recent studies using conceptual
frameworks from emerging nursing theories and models have tested hypotheses in
controlled or semi-controlled settings.
Statistical Tests in Quantitative Research
Statistical techniques are used extensively in descriptive studies to compute summary measures, such as means, standard deviations, and coefficients of correlation, and to determine the sampling error of the measures.
In explanatory studies, statistical techniques are used to test whether there are significant relationships among study variables that are delineated in the hypotheses, meaning relationships that cannot be explained by random sampling error (chance).
Widely used statistical techniques to test
hypotheses include parametric tests such as the t test and analysis of variance
and non parametric tests such as chi square and rank-order correlation.
Quantitative Research In Nursing
Quantification in nursing research has helped advance nursing as a scientific discipline. Quantification offers many advantages to nursing research. There is a rich set of statistical tools available for data analysis that can be applied to practically every research question to assist in summarizing the data and evaluating their statistical significance.
The internal and external validity of the data of quantitative research can be readily verified by other researchers. Results of similar quantitative studies can be synthesized and analyzed by the meta-analysis technique to shed new light on the research questions.
Dissemination of the results of quantitative research is facilitated by the clarity and objectivity possessed by quantitative data. Some studies in nursing tend to overquantify.
Reports of these studies are dominated by statistical data and tests, with a minimum of narrative discussion, providing little interpretation of the clinical significance of results. Sometimes too little time is spent on evaluating the quality of data used or on the appropriateness of the statistical tests.
Qualitative research,
with its focus on meaning and interpretation of data, can help to enrich the
results of quantitative studies in nursing. The approach called triangulation,
which utilizes and integrates methodology from quantitative and qualitative
research in a single study, can help achieve the best of both worlds of
research methodology.
Nature and Characteristics of Quantitative Research
The history of nursing research reveals a trend from purely descriptive studies of nurses and nursing to the evaluation of the effects of nursing care. Properly applied quantitative research can advance the scientific basis of nursing as well as provide a potent tool for defining and evaluating the outcomes of nursing care.
In the future, quantitative research will play an increasingly valuable role in nursing effectiveness studies. The randomized clinical trial (RCT) method, perhaps the most quantitative of all research methods, will find increasing application in nursing as attempts are made to determine the efficacy of nursing interventions.
Clinically oriented research using methods such as randomized clinical trials require development of quantitative outcome measures of variables such as quality of care and quality of life. This will stimulate quantitative research to provide the needed measures and indicators.
As more replications of quantitative nursing research
become available, the research synthesis techniques of meta-analysis will be
increasingly applied to expand nursing's knowledge base.Read More
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