Intro to Quanitative Research II

Meta-analysis

A quantitative technique that combines the results of several independent studies using statistical methods

Meta-synthesis

A qualitative or mixed -methods technique that synthesizes the findings of multiple studies using thematic or narrative methods

Internal validity

The extent to which a study can support that a casual relationship exists between the independent and dependent variables, and that the observed effect on the dependent variable is not caused by other variables

-Asks whether the IV really made the difference or change in the DV

Bias

A systematic influence that moves a study’s findings away from the truth

-Any tendency which prevents unprejudiced consideration of a question (many types)

Threats to internal validity

History, maturation, testing, instrumentation, mortality, selection bias

External validity

Generalizability of one study to additional populations or other environmental conditions

-Ex: COVID caused recruitment barriers

Reactive effects

Subject’s response to being studied (Hawthorne Effect)

-Effects are from the realization of the subjects they are being studied, not from the intervention

Measurement effects

Pre testing can affect the post-test responses within a study and affects the generalizability

Quantitative Research Process

Nursing intervention effectiveness is tested by using experimental and quasi-experimental designs

-Researcher actively intervenes by manipulating study variables to bring about a desired effect

-By manipulating an IV, the researcher can measure a change in behaviors or actions which is the DV

Experimental and quasi-experimental studies provide the two highest levels of evidence

Level II and III for a single study

-A framework for measuring the effectiveness of nursing interventions through controlled conditions, allowing the researcher to draw causal inferences

Randomized controlled trial (RCT)

Study using an experimental design

-Gold standard for providing information about the cause-and-effect relationships

-Generates level II evidence

Experimental design types

-Randomization (mentioned previously)

-Control and comparison: Conditions are held constant to limit bias that could influence the dependent variables , comparison = treatment as usual, placebo, EB intervention

-Manipulation: Changing the independent variables (such as txt) for at least some of the involved subjects

Strengths and weaknesses of the experimental design

-Strengths: Most powerful fo testing cause-and-effect relationships to the use of control, manipulation, and randomization

-Weaknesses: Complicated to design and can be costly to implement

No experimental designs

Used when the researcher wishes to explore events, people, or situations as they naturally occur

-Test relationships and differences among variables

Inferential statistics

Allow the testing of hypotheses using data obtained from probability and nonprobability samples to make inferences about a population

Null hypothesis (H0)

There’s no effect in the population

-States no relationship exists between the two variables being studied (one variable doesn’t affect the other)

Alternative hypothesis (Ha or H1)

There’s an effect in the population

-Independent variable affected the dependent variable, and the results are significant in supporting the theory being investigated

Type I vs II errors

Type I error occurs when the null hypothesis is rejected when it is actually true, while Type II error occurs when the null hypothesis is not rejected when it is false

P value of > 0.05 in nursing statistics

This means that the result is NOT significant

P value of < 0.05

The result IS statistically significant

Clinically vs Statistically significant

A p value only measures statistical probability, not practical value, meaning that something cannot be clinically probable if math is involved

Quantitative

research that involves the systematic empirical investigation of observable phenomena through statistical, mathematical, or computational techniques

Qualitative

research that explores subjective experiences and interpretations, often utilizing interviews or focus groups

Mixed methods

A research approach that combines both quantitative and qualitative methods to provide a more comprehensive understanding of a research question

Experimental

research methodology that tests hypotheses through controlled experimentation, allowing for the establishment of cause-and-effect relationships