Nursing Research Flashcards
Sources of Data: Primary Sources
Preferred
- research from which the data originated
- these sources are factual and not subject to interpretation by others
Sources of Data: Secondary Sources
- created when the original data (primary data) are interpreted or analyzed by another person (not the original researcher)
- “second-hand” accounts
Ethical Issues in nursing Research: Institutional Review Boards (IRBs) + Committee Members
- an important duty of institutional review boards (IRBs) is to ensure the rights, safety, and welfare of human research subjects who are participating in research studies in their institutions
Committee Members:
- members designated to review and monitor research that involves human subjects at their institution
- physicians, clinicians, or retail pharmacists are not affiliated w/ the institution are generally not included in an IRB committee (unless they are hired as consultants)
- experienced staff members, not recent graduates, are preferred
- size of the IRB and the # of members depend on the type of institution
Vulnerable Populations
Almost all types of biomedical and behavioral research in the US required informed consent
“Vulnerable populations” require special protections and consent requirements:
- infants and children <18 years
- Pregnant women, fetuses
- Prisoners
- Refugees, ethnic minorities
- Persons /w mental or physical disabilities, visual, or hearing impairment
- Persons who are economically disadvantaged
Belmont Report
- a report that outlines the important ethical principles that should be followed when performing research that involves human subjects
- issued by the National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research (1979)
Tuskegee Syphilis Experiment
- an infamous study of 600 African American sharecroppers (1932-1972) in Alabama
- men were all tested for syphilis infection, and those who had positive results were never informed or treated
- because of this study, laws were passed that protect human subjects’ rights and mandate informed consent
Informed Consent of Human Subjects
Research subjects must be informed that they have the right to withdraw from the research study at any time w/out adverse consequences or penalty
- there are additional requirements for minors and vulnerable subjects
Components:
- Describe the study; informs he subject of what they are expected to do (e.g., questionnaires, labs)
- describe the risk or the discomforts of participating in the study in the presentation and the future (if applicable)
- Describe the benefits of participating in the study in the present and the future (if applicable)
- Discuss the alternatives to the study; allow enough time for the subject to ask questions
- discuss whether there is any compensation or reward for participation
- discuss how confidentiality and data will be secured to protect the subject’s identity
- give the number and/or email address of the contact for the study so that the subject can contact that person if they have any concerns/problems w/ the study
Minors
Any persons who are <18 years of age
Emancipated Minor Criteria
- legal court document declaring that the minor is an “emancipated minor”
- active duty in the US military
- legally binding marriage 9or divorced from a legally binding marriage)
Consent vs Assent
- consent may be given only be individual who are 18+ years
- a minor (who is not emancipated) as young as the age 7-17 years can give assent to participate in a research study but cannot give consent legally
- child should be assured that they can withdraw from the study after discussing it w/ their parents
- parent or legal guardian must first consent to the minor’s participation in the study
- the researcher needs parental permission to speak w/ the minor in order to obtain assent (the child signs a separate assent form)
- Assent refers to minors because they legally cannot give consent (unless an emancipated minor)
Research Terms: Variables (Independent variable + Dependent variable)
- any attribute or characteristic that varies and is measurable
Independent variable —> variable that is being manipulated and is used to influence the dependent variable
- in experimental studies, the research has control over the independent variable
Dependent variable —> result of the manipulation of the independent variable
- Ex: Manipulation by researcher (independent variable) allows a response to manipulation that can be observed and measured (dependent variable)
Research Terms: Hypothesis
- an idea (or supposition) that can be tested and refuted
- when conducting research, an examiner tests a hypothesis (or several hypotheses) and can either accept or refute the hypothesis
Research Terms: Null Hypothesis (H0)
- opposite of the hypothesis being studied
Ex: If the hypothesis is “corn plans grow faster when exposed to sunlight,” the null hypothesis is “corn plants will not grow faster when exposed to sunlight”
If the research data meets the p-value (p<.01), the results are considered significant (not due to random chance), and the null hypothesis can be rejected. If the null hypothesis cannot be rejected, it means that there is no relationship b/w the variables, and the results are d/t chance
Research Terms: Normal curve
A bell-shaped curve
Measures of Distribution: Mean
AKA the average
- calculated by adding all of the scores together and dividing it by the total #
Ex: 5, 5, 5, 10, 10 (35/5=7, average is 7)
Measures of Distribution: Median
The number that is in the middle when values are arranged from lowest to highest (chronological order)
Ex: 1, 3, 4, 5, 7, 10, 14 (mean is 5)
Measures of Distribution: Mode
The roost common value or frequently occurring value in a set of scores
Ex: 3, 5, 7, 7, 7, 8, 9, 10, 10 (mode is 7)
Research-related Terms: Statistical Significance (a, control group, N, n, significance level definitions)
a —> aka “significance level” or “p-value”
- usually set as either p<.05 or p<.01
* a significance level of p<.05 means there is a 5% probability that the study results are due to chance
* a significance level of p<.01 means there is only a 1% probability that the study results are due to chance
- therefore, a of p<.01 is “better” than a of p<.05
Control group —> subjects in an experiment who do not receive treatment
N —> indicates total size of sample
n —> # of subjects in the group
Significance level —> AKA a or p-value; either set as p<.05 or p<.01
Measures of Distribution: Range
The difference b/w the largest and smallest values in a distribution
Ex: 2, 3, 5, 7, 10, 15 (15-2, range is 13)
Research Designs - Types of Studies: Prospective
Studies done in the present (to the future)
- longitudinal studies are a type of prospective study
- data are obtained in the present and then periodically measured in the future
Research Designs - Types of Studies: Retrospective
AKA ex post facto
- studies done on events that have already occurred
Ex:
- chart reviews
- recall of events
Research Designs - Types of Studies: Longitudinal
- long-term studies that follow the same group of subjects (or cohort) over many years to observe, measure, and compare the same variables over time
- These are observational studies (there is no manipulation or intervention)
Ex:
- The Framingham Heart Study has tracked the same research subjects (N=5,029) from the town of Framingham, Mass.
Goal: to study the development and identify the risk factors that are associated w/ the development of cerebrovascular disease
Research Designs - Types of Studies: Cohort
- groups of individuals that share some common characteristics (e.g., gender, age, job, ethnicity)
- useful for studying the causative factors/risk factors of a disease(s)
Ex:
- Nurses’ Health Study is a longitudinal cohort study that examined the effects of oral contraceptive use in nurses over the long term
- has been expanded to study the effect of lifestyle choices on health
Research Designs - Types of Studies: Cross-Sectional
- compares differences and similarities b/w ≥2 groups of people or phenomena and collects data at one pint in time
Research Designs - Types of Studies: Case Study
- an in-depth investigation of a single person, group, or phenomenon
Research Designs - Types of Studies: Descriptive
- researchers observe and collect pertinent information but do not manipulate or change the environment
- AKA observational studies
Research Designs - Types of Studies: Correlational
- type of observational study in which relationship (interrelationships) b/w at least 2 variables is evaluated
3 types:
- positive correlation: 2 variables change together int he same direction
- Ex: when variable A increase, then variable B also increases
- Negative correlation: an increase in one variable results in a decrease in the other
- Ex: when variable A increase, this causes variable B to decrease
- No correlation: the variables are not related
- Ex: a change in variable A does not affect variable B
- study search for relationships b/w a minimum of 2 variables
Research Designs - Types of Studies: Experimental
- an important criterion is the use of random sampling and random assignment or research subjects
- at least one control group and one (or more) intervention or treatment group (manipulation)
- causality can be determined (if A + B occur, this will cause C)
Research Designs - Types of Studies: Quasi-Experimental
- similar to an experiemental study, except there is no randomization of the research subjects
- instead, recruitment of subjects is convenience sample
Deductive Reasoning
- involves going from more general to more specific findings
- AKA “top-down” logic
- in research, this means starting with a theory (generalization) and then narrowing it down buy formulating specific hypotheses (deduction)
- Quantitative studies uses deductive reasoning
Ex:
- Data —> numerical and measurable data
- # of subjects —> May involve large # of individuals, databases
- Subject recruitment —> Randomization possible if experimental design
- Data gathering —> questionnaires, instruments, measurements, surveys
- Logic —> Deductive reasoning
- Design —> systematic, design is known before research starts
- Statistical testing —> Pearson correlation, paired t-test, simple/multiple regression, analysis of variance (ANOVA), etc
- Notes: researcher is an objective observer, declares bias (funding sources)
Inductive Reasoning
- opposite of deductive reasoning
- AKA “bottom-up” logic
- involves going from specific findings to generalizations
- ones tarts w/ specific observations, and from these, one may detect a pattern that helps to formulate tentative hypothesis, which may help to generate new theory
- Qualitative studies
Ex:
- Data —> involves words, narratives, subjective opinions
- # of subjects —> few individuals
- Subject recruitment —> Small # of subjects, not randomized
- Data gathering —> in-depth interviews, focus groups, observations; audio or video is recorded, data are transcribed
- Logic —> inductive reasoning, specific data can be generalized
- Design —> may change and evolve to adapt to situation or subjects
- Statistical testing —> interpretation of common themes and patterns; uses limited statistic such as chi-square
- Notes: research is a participant and also an observer (degree of participation varies)
Research Process/Phases
Phase 1–Conception
- formulate research problem/question
- review literature
- develop hypothesis(es)
Phase 2-Design and Planning
- select research design
- identify population/sample
- determine protocols, methods, resources required, and ethical considerations
- prepare proposal
- submit to IRB for approval
Phase 3-Implementation
- Recruit participants (obtain consent)
- implement research design
- collect data
Phase 4-Analysis
- organize, analyze, and interpret data
Phase 5-Dissemination
- Prepare final report
- publish and disseminate findings (e.g., journal articles, poster presentations, lectures)
