Which of the following are examples of evidence-based research in nursing?

Choice A rationale

Teams that provide experimental treatments are typically clinical trial units or specialized medical teams. While IRBs review these trials, the board itself does not provide the treatment. The IRBs role is purely administrative and ethical oversight. They ensure that the risks to the patients receiving these experimental treatments are minimized and that the potential benefits justify those risks. They do not act as the healthcare providers or the direct facilitators of the medical intervention.

Choice B rationale

The generation of knowledge for a discipline is the primary goal of researchers and scientists conducting the studies. While the IRB facilitates this by approving ethical research, the board itself is not responsible for generating the data or the findings. IRBs are reactive bodies that review proposals created by others. Their focus is on the protection of the participants involved in the knowledge-generation process, ensuring that the pursuit of science does not violate fundamental human rights.

Choice C rationale

Institutional Review Boards are formally designated groups that review and monitor biomedical and behavioral research involving human subjects. Their primary purpose is to ensure that all research is conducted ethically and in accordance with federal regulations. They review study protocols to protect the rights, safety, and well-being of participants. This includes evaluating informed consent processes, assessing the balance of risks and benefits, and ensuring that participant selection is fair and equitable before any research begins.

Choice D rationale

Committees that oversee the distribution and safety of foods and drugs are typically government agencies like the Food and Drug Administration (FDA) in the United States. While the FDA sets the regulations that IRBs must follow for clinical trials, the IRB is usually an institution-level committee, such as at a university or hospital. The IRB focuses on the ethical conduct of specific research studies, whereas agencies like the FDA focus on broader public safety and the commercial approval of products.

Choice A rationale

Identifying the independent variable is a fundamental step in any experimental or quasi-experimental study, but it does not dictate the temporal dimension of the design. Independent variables represent the interventions or conditions being manipulated to observe an effect. Both cross-sectional and longitudinal designs can accommodate independent variables. Therefore, asking about the variable's presence does not clarify whether the researcher needs to collect data at one point or over an extended period of time.

Choice B rationale

The nature of the research problem dictates whether the study requires a snapshot of a population or an observation of change over time. If the problem involves understanding developmental trends, recovery processes, or the long-term effects of an intervention, a longitudinal design is mandatory. Conversely, if the problem concerns the prevalence of a condition or current attitudes at a specific moment, a cross-sectional approach is sufficient. The core problem determines the necessary timing of data.

Choice C rationale

The need for a measurement tool or instrument is a logistical requirement common to nearly all quantitative research. Whether the study uses a survey, a physiological sensor, or a standardized psychological scale, the choice of tool is independent of the timing of data collection. Researchers utilize instruments in both single-event cross-sectional studies and repeated-measure longitudinal studies. Consequently, this question does not help the researcher decide which specific quantitative temporal design is most appropriate.

Choice D rationale

Statistical analysis is a universal requirement for quantitative research and does not distinguish between design types. Both cross-sectional and longitudinal data are subjected to rigorous mathematical testing, such as t-tests, ANOVA, or regression analysis, to determine significance. Since the ability to apply statistics is a prerequisite for the entire quantitative paradigm, it does not provide guidance on whether a study should capture data once or track subjects over multiple points in time.