Related to the research questions and limitations on implications or findings (causal vs. relational):
- What are the basic research designs?
- What are the corresponding or additional questions used?
- What analytical methods are used?
1. Basic Research Designs
There are three broad categories of research designs used in health sciences and other disciplines:
| Type of Design | Purpose | Causal or Relational? | Examples |
|---|---|---|---|
| Experimental (Quantitative) | Tests cause-and-effect relationships by manipulating one variable and observing its impact on another | Causal | Randomized Controlled Trial (RCT), Laboratory experiments |
| Quasi-Experimental (Quantitative) | Examines cause-and-effect relationships but lacks random assignment | Causal (weaker evidence) | Pretest-posttest design, Time-series design |
| Non-Experimental (Quantitative or Qualitative) | Observes variables without manipulation; explores relationships or descriptions | Relational or Descriptive | Correlational studies, Cross-sectional surveys, Case-control, Cohort studies |
| Qualitative Designs | Explores meaning, experiences, or perceptions rather than numerical data | Relational / Exploratory | Phenomenology, Grounded theory, Ethnography, Case study |
2. Corresponding or Additional Research Questions
Each research design type is associated with particular kinds of research questions.
| Design Type | Common Research Questions | Question Type Examples |
|---|---|---|
| Experimental | Determines the effect of an intervention or manipulation | “Does intervention X cause improvement in outcome Y?” “What is the effect of drug A on blood pressure?” |
| Quasi-Experimental | Explores possible causal effects when randomization isn’t feasible | “Does implementing a hand hygiene campaign reduce infection rates in hospitals?” |
| Non-Experimental / Correlational | Examines associations or relationships between variables | “What is the relationship between stress levels and blood pressure?” “Is there a link between nurse staffing levels and patient satisfaction?” |
| Descriptive | Describes characteristics or frequency of phenomena | “What are the common symptoms experienced by patients with long COVID?” |
| Qualitative | Explores lived experiences, meanings, or processes | “How do nurses perceive the challenges of telehealth delivery?” “What factors influence patient adherence to medication regimens?” |
3. Analytical Methods Used
The choice of analytical method depends on the research design and nature of the variables (quantitative vs qualitative).
| Design Type | Analytical Methods | Examples of Tests / Analyses |
|---|---|---|
| Experimental (Causal) | Statistical comparison between groups | t-tests, ANOVA, ANCOVA, regression, MANOVA |
| Quasi-Experimental | Statistical comparison with control of confounding factors | Regression analysis, difference-in-differences, propensity score matching |
| Correlational (Relational) | Measures strength and direction of relationships | Pearson’s or Spearman’s correlation, linear or logistic regression |
| Descriptive (Quantitative) | Summarizes and describes data | Frequencies, percentages, means, standard deviations |
| Qualitative | Thematic or content analysis to identify patterns, meanings, or themes | Thematic analysis, Grounded theory coding, Narrative analysis, Constant comparative method |
Summary Table
| Design | Question Focus | Causal or Relational | Analytical Method |
|---|---|---|---|
| Experimental | Does X cause Y? | Causal | t-test, ANOVA, Regression |
| Quasi-Experimental | Does X affect Y (without randomization)? | Causal (less control) | ANCOVA, Difference-in-differences |
| Correlational | Is X related to Y? | Relational | Correlation, Regression |
| Descriptive | What is happening? | Descriptive | Descriptive statistics |
| Qualitative | What does it mean / How is it experienced? | Relational / Exploratory | Thematic or Content Analysis |