A blueprint for conducting a study.

Increases the probability that the study findings are an accurate reflection of reality.

Examining variables as they naturally occur in environment and not on the implementation of a treatment by the researcher.

Examining a group of subjects in various stages of development, levels of education, severity of illness or stages of recovery to describe changes in a phenomenon across stages.

Collecting data from the same subject at different points in time and can be referred to as repeated measures.

Used to develop theories, identify problems with practice, make judgments about practice, or identify trends of illnesses, illness prevention, and health promotion in selected groups.

To examine variables in a single sample; identifying the variables within a phenomenon of interest, measuring these variables, and describing them.

To describe variables and examine differences in variables in two or more groups that occurs naturally in a setting.

To examine relationships between or among two or more variables in a single group in a study.

To describe variables and examine relationships among these variables.

To predict the value of one variable based on the values obtained for another variable(s).

Requires that all concepts relevant to the model be measured and the relationships among these concepts examined.

: Things have causes, and causes lead to effects.

Multiple causes for an effect.

Addresses a relative rather than absolute causality.

A slant or deviation from the true or expected; distorts the findings from what the results would have been without the bias.

Having power to direct or manipulate factors to achieve a desired outcome.

A form of control used in quasi-experimental and experimental studies.

A measure of the truth or accuracy of the findings obtained from a study.

Whether the conclusions about relationships or differences drawn from statistical analysis are an accurate reflection of the real world.

Increases the probability of concluding that there is no significant difference between samples when there is a difference (Type II error).

The extent to which the effects detected in the study are a true reflection of reality rather than the result of extraneous variables.

Examines the fit between the conceptual and operational definitions of variables.

Expected to result in differences in post-test measures between the treatment and control or comparison group.

A detailed description of the essential elements of the intervention and the consistent implementation of the intervention during the study.

The group of subjects who received the study intervention.

The group that is not exposed to the intervention.

Facilitates the search for knowledge and examination of causality in situations in which complete control is not possible.

Developed for studies focused on examining causality.

The strongest methodology for testing the effectiveness of a treatment because of the elements of the design that limit the potential for bias.

Withholding of study information from data collectors, participants and their HCP.

Offer investigators the ability to use the strengths of qualitative and quantitative research designs.

Evolved to include multiple data collection and analysis methods, multiple data sources, multiple analyses and multiple theories or perspectives.