Nursing Research is similar to other fields of research; it is scientific, empirical, and a problem-solving approach used in health-care. Overall, it is a tool to enhance client care. This process is step-by-step, and can be classified as:
flowchart TD
0(Research)
0-->1(Based on Purpose)
0-->2(Time Dimension)
0-->3(Research Design)
1-->1.1(Basic/Pure)
1-->1.2(Applied)
2-->2.1(Cross-sectional)
2-->2.2(Longitudinal)
3-->3.1(Quantitative)
3.1-->3.1.1(Experimental)
3.1-->3.1.2(Non-experimental)
3-->3.2(Qualitative)
3-->3.3(Quantitative)
- Basic/Pure: a research done on a singular variable.
- Applied: research involving various variables applied to practical uses.
- Cross-sectional: research data collected in one time frame only.
- Longitudinal: research data collected in a time series, to determine changes over time.
- Quantitative: research involving statistical analysis and numerical data as the core of the study. This may be divided further between experimental and non-experimental types:
- True Experimental Study: a study that fulfills all three requisites for an experiment— randomization, control, and manipulation.
- Quasi-Experimental Study: if randomization or control is missing (but not manipulation), the study becomes quasi-experimental.
- Comparative Study: a study determining the difference between variables.
- Co-relational Study: a study determining the strength of relationships between variables.
- Qualitative: research involving thematic analysis of collected data, often in the form of interviews and explanations.
- Phenomenology Study: a study focusing on the lived experiences of respondents.
- Historical Study: a study focusing on historical events and records.
- Ethnography Study: a study wherein the researcher immerses themself in the community under observation, for at least six months.
- Delphi Study: a study of particular use to assessing textbooks, flowcharts, procedures, etc. This involves the use of expert consultants to evaluate the material under study.
- Photovoice: the use of imagery to produce a representation of experiences.
- Grounded Theory: a study used for the production of theoretical models and frameworks.
- Mixed Method: a combination of both qualitative and quantitative methods.
Variables
Variables are the elements under observation within a particular study— the object of the study. In a quantitative setting, variables must be measurable, and take the form of the following basic types:
- Independent Variables: the presumed cause of the phenomenon
- Dependent Variables: the variable changing in response to changes in the independent variable.
- Intervening Variables: variables that are not the primary independent variable, but is nonetheless involved in the changes in the dependent variable.
Studies may also be classified according to:
- According to Number of Variables: one variable (univariate) or two and more (bivariate)
- According to Kinds of Data: quantitative (height, weight, distance, etc.) or qualitative (color, smell) data. Both of these are used for quantitative studies, first by using quantitative data as-is, and secondly by encoding qualitative data using a codal system, such as assigning varying odors to a numerical scale.
- Additionally, quantitative studies may also be classified according to the nature of data: (a) Discrete data that uses distinct, exact intervals between each value such as
members in a family, and (b) Continuous data that plots values on a continuum, such asweight. Often, the distinction lies in that discrete data is exact while continuous data is approximately. - Furthermore, the method by which data is arranged or plotted also varies. There are four categories: (a) Interval, a scale where zero has meaning i.e. weight, height, and temperature, (b) Ratio, where zero simply dictates the absence of the variable, e.g., a score of zero on an exam denotes there were no correct answers, (c) Nominal where data points are categorized by characteristics or qualities, and (d) Ordinal where data points are ordered in a ranking/hierarchy system. The Likert scale is a type of ordinal data. In general, intervals and ratios are considered a higher form of data, known as parametric statistics. Nominal and ordinal data are non-parametric.
- Additionally, quantitative studies may also be classified according to the nature of data: (a) Discrete data that uses distinct, exact intervals between each value such as
Statistical Analysis
For parametric data dealing with interval and ratio data,
- T-tests are statistical analyses are used for sets of data with 1 or 2 groups.
- For sets of data with more groups, the Analysis of Variance (ANOVA) methodology is often used.
- For determining correlation, the Pearson-R analysis is used.
For non-parametric data dealing with nominal and ordinal data,
Spearman-Rho is used to determine correlations.
Types of Correlational Findings direct relationship between the variables.
If one value rises when the other depresses, the relationship is known as inverse or indirect.
Hypotheses
A hypothesis is an educated statement about the phenomenon made by the researchers. This may take the form of hypotheses that affirm a relationship or deny a relationship. Based on the nature of the hypothesis, this may be:
- Alternative Hypothesis (Ha or H1): an affirmative hypothesis; this states that the researchers believe that the object of the study is present, e.g.,
There is a significant difference between the experimental and control groups. - Null Hypothesis (H0): a negativistic hypothesis, simply the inversion of Ha, i.e.
There is no significant difference between the experimental and control groups.