Ethics and Quantitative Research

Views:
 
Category: Education
     
 

Presentation Description

Narrated Lecture

Comments

Presentation Transcript

Ethics in Research and Designing a Quantitative Project:

Ethics in Research and Designing a Quantitative Project Angela Orsky, DNP, LNHA, RN

Objectives:

Objectives Describe importance of Institutional Review Boards and implication to ethics in research. Define quantitative and qualitative research. Discuss methods involved in critiquing quantitative research problems /questions and qualitative studies. Discuss the importance of research utilization. Comparing Parametric Tests with Nonparametric Tests.

Ethics in Research:

Ethics in Research Henrietta Lacks… Discussion Questions Importance of Institutional Review Boards Formal designation to review and monitor biomedical research involving human subjects. Protects rights and welfare of human subjects in research. Can be internal or external (contracted). Informed Consent Written and Verbal. Full Disclosure. Any changes to the study must be reported to IRB before implemented (unless imminent harm). http://www.fda.gov/RegulatoryInformation/Guidances/ucm126420.htm

Quantitative Research:

Quantitative Research Nursing Role: development of evidence-based practice using the current and best research available to guide clinical decision making. Purpose of Quantitative An experiment to “prove” something. Quantitative collects data in numeric form and emphasizes measurement of variables. Often conducted using rigorous study designs . ( Melnyk , B. & Fine- Overholt , E. (2005). Evidence-Based Practice in Nursing and Healthcare. Lippincott, Williams & Wilkins)

PowerPoint Presentation:

Guide to Critiquing Quantitative Research (Polit and Beck, 2008) . Variables Measured: Independent Variable (variable that is believed to cause or influence the dependent variable). Dependent Variable (outcome variable of interest; caused or predicted by dependent variable). http://www.delmarlearning.com/companions/content/1401859186/About_Book/Sample%20Chapter/DeLaune_ch03.pdf

Quantitative Study Designs:

Quantitative Study Designs Randomized Controlled Trials Tx or control groups; evaluate if they experience an outcome of interest (e.g. reduced hospital stay, pain relief, etc.). Observational Commonly used when issues of harm are known. Case-control May include a look back in time to determine whether patients had exposure to a potentially harmful agent. Cohort Comparing a similar group of patients .

Qualitative Study Designs:

Qualitative Study Designs Most common in published health care research include: Case Studies. Ethnography Learning about a culture from the people who live in the culture. Grounded Theory Discover the meanings that humans assign to people and objects in which they interact. Phenomenology Gain deeper understanding of the nature or meaning of the everyday “lived” experience of people.

Critiquing Quantitative Designs:

Critiquing Quantitative Designs Descriptive statistics are useful for communicating information about the study sample. Inferences about external validity are dependent upon key characteristics and attributes. Important identifiers describing risks: Absolute Risk Reduction (ARR) which expressed the estimated proportion of people who would be spared from an adverse outcome through exposure to an intervention. Relative Risk (RR) is the estimated proportion of the original risk for an adverse outcome that persists among people exposed to the intervention. Relative Risk Reduction (RRR) is the estimated proportion of untreated risk that is reduced through exposure to the interventions. Odds Ratio (OR) is the ratio of the odds for the treated versus untreated group, with the odds reflecting the proportion of people with the adverse outcome relative to those without it. Number Needed to Treat (NNT) is an estimate of how many people would need to receive the intervention to prevent one adverse outcome.

Guidelines for Critiquing Research Problems, Questions and Hypotheses in Quantitative Studies:

Guidelines for Critiquing Research Problems, Questions and Hypotheses in Quantitative Studies What is the research problem? Problem statement easy to locate and clearly stated. Does the problem have significance for nursing? Is there a good fit between the research question and the use of a quantitative paradigm? Clear statement of purpose, research question, and/or hypothesis? Key concepts and variables identified and the population of interest specified? If no formal hypothesis, absence justified? Statistical test used in analyzing data despite absence of hypothesis? Hypothesis state a predicted relationship between two or more variables?

Critiquing Qualitative Analysis:

Critiquing Qualitative Analysis Evaluation is difficult due to readers not having access to determine if researchers exercised good judgment and critical insight. Primary task is to determine if researchers took sufficient steps to validate inferences and conclusions. Did researcher adequately document the analytic process, model, or theme.

Research Utilization:

Research Utilization Given today’s increasing emphasis on quality, evidence-based practice, accountability, and fiscal responsibility in health care, it is likely that research utilization will be a major focus of all health professionals in the future. Research Utilization Occurs at Three Levels: 1. Instrumental utilization is the direct, explicit application of knowledge gained from research to change practice. 2. Conceptual utilization refers to the use of findings to enhance one’s understanding of a problem or issue in nursing. 3. Symbolic utilization is the use of evidence to change minds of other people, usually decision makers.

Comparison of Parametric to Nonparametric Tests:

Comparison of Parametric to Nonparametric Tests Parametric Nonparametric Pearson coefficient r Kendall’s Tau t test correlated samples Sign test Wilcoxon matched-pairs signed-ranks test t test independent samples Median test Mann-Whitney U test One-way ANOVA Kruskal Wallis one-way ANOVA of ranks Median test One-way ANOVA with repeated measures Friedman two-way ANOVA or ranks None Chi-square Single-sample k independent samples

authorStream Live Help