Published Sep 17, 2005
ccusherry
42 Posts
Hi all,
I'm presently taking my nursing research class for my bsn. My question is what are the criteria to differentiate between a empirical/research article and a conceptual/theoretical article? Any help would be appreciated!!!!
VickyRN, MSN, DNP, RN
49 Articles; 5,349 Posts
Hi all, I'm presently taking my nursing research class for my bsn. My question is what are the criteria to differentiate between a empirical/research article and a conceptual/theoretical article? Any help would be appreciated!!!!
These are some notes from my research class. Basically, the former involves quantitative research, and the latter research based on theory and concepts.
Theoretical / conceptual framework (theory, model): Abstract, theoretical basis for the study. Allows the researcher to link the findings from the study to a larger body of nursing knowledge. Framework is a testable theory, developed in nursing or another related discipline. The research tests the relational statements of the theory, not the theory as a whole. Frameworks can be expressed as a map or diagram of the relationships, or as a narrative describing the theorized relationships. The theoretical framework is distinguished from the conceptual framework, which is the overall guide to nursing practice (examples of conceptual frameworks: grand theories of nursing, general systems theory).
Theoretical literature: literature that contains information about the concepts, models, theories and conceptual framework(s) that one is using in the research. Example: Benner's novice-to-expert theory to guide research related to favorable patient care outcomes secondary to nurse practitioner competency.
Empiricism: Quantitative data are said to be "objective"--the behaviors are easily classified, sorted, or measured by the researcher. It involves analytical empiricism (feedback received through the five senses from the real world) and deductive reasoning. Empirical literature: literature that includes relevant research studies in journals, books, internet sources, as well as unpublished studies related to the problem/ purpose of the study.
Deductive research begins with known theory and tests it, usually by attempting to provide evidence for or against a pre-specified hypothesis. The hypothesis is tested (usually through an experiment) by the use of objective instruments and appropriate statistical analyses. Quantitative research is used to search for cause and effect (causality), predictive capability, or relationships.
Quantitative research calls for procedures that use precise definitions, that use objectivity-seeking methods for data collection and analysis, that are replicable, and that are systematic and cumulative. Replicable data means they can be re-collected by someone else, somewhere else, and be expected to measure or identify the same thing, and thus be directly comparable. The knowledge that results is useful for explaining and predicting.
Examples of quantitative data are either census (containing measures for the total or whole population) or sample (relating only to the sub-set of the population actually asked, surveyed, observed). The data are usually gathered with some sort of instrument (test, questionnaire) that can be scored reliably with relatively little training.
Quantitative designs usually deal with large numbers. Common quantitative designs are: experimental (randomized, controlled trial); quasi-experimental (pretest/ post-test control group with no randomization); and nonexperimental (descriptive, correlational). An experimental design is used to find effects of an intervention. The term quasi-experimental indicates a study with an intervention, but one in which it is difficult to manipulate or control the setting, subjects, or variables as need for a true experimental study. Descriptive studies describe new situations, events, or concepts, and correlational studies often search for associations among concepts or ideas.
Strengths of quantitative research include: prediction of outcomes, after the introduction of some kind of intervention; statistical analysis strategies.
Weakness of quantitative research: overly reductionistic (which means that quantitative researchers may miss the real meaning when they reduce everything to numbers).