Introduction to Quantitative Research Methods

Introduction to Quantitative Research Methods

• Quantitative research methods are used to study topics in nursing.
• Required readings include chapters 9, 10, and 15 of Polit & Beck's Canadian Essentials of Nursing Research (4th Edition).

Key Research Design Features

• Intervention: actions taken to impact the study's subjects.
• Comparisons: comparing outcomes between intervention and control groups.
• Control over confounding variables: limiting the impact of unrelated factors.
• Blinding: preventing bias by concealing treatment assignments.
• Time frames: the duration of the study.
• Relative timing: the sequence of events in the study.
• Location: where the study was conducted.

Broad Design Options

• Experimental (RCT): randomized control trials
• Quasi-experimental: controlled trials without randomization
• Nonexperimental (observational): studies observing existing phenomena without intervention.

Hierarchy of Designs for Different Cause-Probing Questions

• Different types of questions (e.g., therapy, prognosis, etiology/harm) require different hierarchical levels of research designs.
• This hierarchy typically begins with experimental trials progressing to quasi-experimental trials, cohort studies, case-control studies, and lastly, descriptive correlation studies.
• The specific study design depends on the type of question being asked.

Therapy & Etiology/Harm (Prevention) Questions

• RCTs (Randomized Controlled Trials) are at the top of the hierarchy for these questions.
• Quasi-experimental designs are used for those questions as well.
• Followed by Cohort studies, case-control studies and eventually descriptive correlational studies.

Prognosis Questions

• Cohort studies usually come first for prognosis questions.
• Followed by case-control studies and descriptive correlational studies.

Experimental Designs

• Offer strong evidence for cause and effect relationship.
• A researcher manipulates an intervention for some subjects, while the control group receives no intervention.
• Participants are assigned randomly to the intervention or control group.

Variations in Experimental Design

• Posttest-only: outcome data gathered after the intervention only.
• Pretest-posttest: outcome data collected before and after intervention.
• Crossover: subjects exposed to two or more conditions in random order.

Intervention vs. Control Conditions

• Intervention (treatment): described in formal protocols.
• Intervention fidelity: treatment is delivered as planned.
• Control: no treatment is given.
• Usual care: standard procedures or treatment used in the study.
• Placebo: a treatment known to have no therapeutic effect.

Quasi-Experimental Designs

• Involve intervention but lack randomization or control.
• Nonequivalent control group designs: compare different groups without randomization.
• Within-subject designs: examine changes in one group over time.

Nonexperimental (Observational) Designs

• Also known as non-experimental designs.
• Some variables (e.g., gender, smoking) can not be manipulated.
• Often useful for large-scale data collection when intervention is not possible.
• Does not yield strong evidence for causal inferences.

Correlational Studies

• Examine associations between variables without establishing cause-and-effect relationships.
• Weaker than RCTs in proving causality.

Prospective Studies (Cohort Design)

• Look forward from cause to effect.
• Study a group over a period to examine if cause influences effect.
• Stronger than retrospective designs in supporting inferences, but less strong than experimental designs.

Retrospective Studies

• Examine effects in the present that may be linked to causes in the past.
• Often involves comparing "cases" (e.g., those with a condition) to "controls" (those without) to identify possible past causes.

Descriptive Studies

• Descriptive: aim to describe a situation or set of circumstances. Examples include determining the prevalence of a disease.
• Descriptive correlational: look for relationships between variables, but do not establish causality.

Time Dimension in Research Design

• Cross-sectional: data from a single point in time.
• Longitudinal: data collected over an extended time.

Techniques of Research Control

• Controling the study context.
• Controlling participant factors.
• Randomization.
• Statistical control.
• Matching.
• Homogeneity.

Statistical Validity

• Statistical validity: the ability to detect true relationships statistically.
• Low statistical power (e.g., small sample size).
• Unreliable implementation of intervention.

Threats to Validity

• Selection bias: differences between groups from the start.
• History threats: events occurring during the study affecting the outcome.
• Maturation: changes in subjects over time.
• Mortality/attrition: subjects dropping out of the study.

Sampling Concepts

• Population: entire group of interest.
• Sample: a subgroup from the population.
• Eligibility criteria: characteristics defining who is included/excluded in the sample.
• Sampling bias: under- or over-representing key characteristics in the sample.
• Accessible population: those from whom the sample is drawn.
• Representative sample: closely represents the population in terms of key characteristics.

Probability Sampling

• Simple random: selects members from a list randomly.
• Stratified random: dividing the population into strata then selecting randomly from each.
• Systematic: selecting every "nth" member from a list.

Nonprobability Sampling

• Convenience: selection of readily available subjects.
• Quota: ensuring the sample reflects proportions of the population in specified groups .
• Purposive: selecting subjects based on specific characteristics for the research.

Sample Size

• Key determinant for sample quality.
• Should be estimated using power analysis to determine the appropriate sample size.
• Small sample sizes increase risk of inaccurate conclusions.

Data Collection Methods

• Structured self-reports: using questionnaires or interviews with pre-specified questions.
• Psychosocial Scales: measuring psychological or social well-being using scales (e.g., Likert scales).
• Biophysiologic Measures: measuring physical aspects of an organism (e.g., lab values).
• Observational Methods: carefully structured observations on behaviours or characteristics.

Response Set Bias

• Social desirability bias: tendency to answer questions in socially desirable ways.
• Extreme response set: always picking the very ends of scales.
• Acquiescence response set: responding "yes" or "agree" to most questions.

Interpreting Quantitative Results

• Statistical significance.
• Precision of estimates. (Confidence intervals)
• Magnitude of effects (effect sizes).

Clinical Significance

• Practical importance: effect on daily patient life.
• Effect on care decisions made concerning a patient.

CONSORT Guidelines

• Consolidated Standards of Reporting Trials (CONSORT) guidelines help readers evaluate methodological decisions and outcomes.
• Flow charts help document the study's participant flow.

This quiz focuses on key aspects of quantitative research methods as applied in nursing. It covers essential features such as intervention, comparisons, and control of confounding variables referenced from chapters 9, 10, and 15 of Polit & Beck's Canadian Essentials of Nursing Research. Test your understanding of research designs and their implications for nursing studies.