Research FINAL EXAM Flashcards
Examples of quantitative and qualitative data
Definitions of important concepts: e.g., research, primary source, generalization, transferability,
Agencies in the USA that support nursing research.
Types of study: prospective, retrospective, cross-sectional, experimental, empirical literature, EBP importance, systematic reviews, survey,
A priori, sample size, primary investigator, independent variable, dependent variable, difference between uni/bi/multivariate variables extraneous, null hypothesis, alpha level, different types of triangulation e.g. data, theory.
Grounded theory ethnography, phenomenological, quasi-experimental, case study
How is Cohen’s kappa related to inter-rater and inter-coder reliability?
Bracketing, maturation, history, Power, immersion/crystallization, integrative reviews
Practice guidelines, translating research to practice – using models.
Difference between research, EBP and quality improvement/process improvement
Standard normal deviation, bell curve, mode/median/mean
p-value significance
Indicates that the probability the results were due to chance is also very small —> test is said to have a statistical significance
Cohen’s Kappa r/t dependability of analysis in QUANTitative analysis
A measure of inter-rater or inter-coder reliability between two raters or coders. The test yields the percentage of agreement and the probability of error
— Generates a p-value for probability that random error was responsible for the agreement
— Agreement of at least 80% = acceptable for qualitative coding, with an associated p-value <5% that the agreement was due to chance
Quantitative study
A traditional approach to research where variables are identified and measured in a reliable and valid way
—Generalized and determines whether an outcome is caused by chance; is the result clinically significant?
— Based on reliability and validity = consistency
— Validity = instrument you are using in quantitative study tests what it was designed to test
— SPSS = program to analyze data using #s
Qualitative study
A natural approach to research where the focus is understanding the meaning of an experience from the individual’s perspective
— Transferability; provide holistic view; uses words, languages, concepts rather than #s to produce evidence; NO hypothesis, objectives, aims
— ID meaning of a phenomenon, event, or experience for an individual
— NVIVO = program to analyze data using words, themes, codes
— e.g. What are your thoughts of the shooting at Ariana Grande concert? Will you ever attend a concert again?
The strongest evidence is
Well-designed clinical trials
Randomized experimental designs
Multiple studies reporting replicable findings
Meta-analysis or meta-synthesis
Power r/t sample size in QUANTitative studies
An analysis that indicates how large a sample is needed to adequately detect a difference in the outcome variable
— There are enough subjects to detect a difference in the outcome variable
— Mathematical process done either prospectively (to determine how many subjects are needed) OR retrospectively (to determine how much power a sample possessed)
— 3 factors for ultimate sample size: significance level needed, power, magnitude of any differences found (e.g. effect size)
Sample size in QUANTitative studies
– Need it to be large so that study is more credible and detect difference in outcome variable
– Power analysis = G-Power (80% = safe); make sure to mention in paper (“We used G-power”)
– Choose methodology/design
– Go to previous studies/authors to determine the sample size + document
(E.g. Hypothesis: Smoking will increase lung cancer (directional hypothesis b/c placing a key word))
QUALitative studies
— think: redundancy + saturation
— When is the point at which no new information is being generated?
NOTE: When you’ve hit redundancy, you can stop interviewing people because you’ve hit data saturation
Define research
— A systematic process of inquiry that uses rigorous guidelines to produce unbiased, trustworthy answers to questions about nursing practice.
New information gathered, more information to validate, must be original (for PhD students)*
Define evidence-based practice
— The use of the best scientific evidence, integrated with clinical experience and incorporating patient values and preferences in the practice of professional nursing care
— Translating research to implement
Define quality improvement
Process improvement
— The systematic, databased monitoring and evaluation of organizational processes with the end goal of continuous improvement. The goal of data collection is internal application rather than external generalization
— Intent is to improve processes for the benefit of patients/customers w/in an organizational context
— Studies often undertaken to determine if appropriate and existing standards of care are practiced in a specific clinical setting
— Management tool to ensure continuous improvement and a focus on quality
What is a sample?
Selection of objects/observations taken from a population of interest
— e.g. All apples at an orchard at a given time; wish to know how big all apples at the orchard are, but cannot measure all of them, so we take some from the population
What are we looking for in a QUALitative analysis?
– Trends and themes
– Saturation of information/data
– Trustworthiness
– Transferability to a similar situation/population
Goals of Qualitative analysis
– Used to organize, provide structure, and draw meaning from the data
– The data collection an analysis must be trustworthy
Challenges of QUALitative analysis
– No single standard or any stipulated guidelines for the analytical process
– Looking for keywords when it comes to your themes and codes
Qualitative research analysis
Collecting data and analyzing is done simultaneously and continuous comparison is done when going from the 1st participant to the 10th
What are the common QUALitative analytic styles?
has either a structure or lack of structure
– Template analysis
– Editing analysis
– Immersion/crystallization
Qualitative researcher
QUAL – heavily imbedded and involved (listening, observing, etc) into the data; really depends on their intuition (what they’re thinking, how they’re thinking, etc)
QUAN – not as involved; very objective
Phases of QUALitative analysis
– Comprehending
– Synthesizing (find meanings; interpreting)
– Theorizing (researcher looks at data, believes/doesn’t believe in the data); e.g. “Ooh, I hit the nail on the head;” “This is not working”
– Recontextualizing (applying findings you obtained from your analysis different groups/setting); finding meaning that can lead to theory.
Possible Types of Codes for QUALitative results
– Setting + context codes
– Perspective codes (viewpoints of…
– Subjects way of thinking
– Process codes
– Activity codes
– Strategy codes
– Relationship codes
– Social structure codes
Techniques to support credibility in QUALitative trustworthiness
– Prolonged engagement
– Triangulation
– External checks
QUALitative trustworthiness
– Credibility
– Dependability
– Confirmability
– Transferability
Techniques to support dependability in QUALitative trustworthiness
– Inter-rater and inter-coder reliability
– Inquiry audit: review relevant data and documents, procedures, and results of an external reviewer
Instrument reliability
Internal reliability: Stability within the instrument
Item-total correlation: Stability among individuals
Inter-rater reliability: Stability between raters
Test-retest: Stability over time
Techniques to support confirmability in QUALitative trustworthiness
– Inquiry audit
– Audit trail
– Decision trail
Techniques to support transferability in QUALitative trustworthiness
– Thick description
– Context of the data
– Deep level of detail
Specific processes of phenomenology
– Reflection on the data
– Explication of themes
– Discernment of patterns that form the ‘essence of the experience’
Specific processes of ethnography
– Triangulation of multiple sources of information
– Use of thick description to draw conclusions to make sure that its correct
Specific processes of grounded theory
● Generate categories of meaning from the ground up (why you’re accepting vs. not accepting)
● Position each category in a theoretical model
demonstrating relationships
● Create a story from the interconnectedness of the
categories
● Add informants as the theory unfolds to illuminate
and/or refute specific conclusions
Examples of QUANTitative research
QUANTitative research: A traditional approach to research in which variables are identified and measured in a reliable and valid way
— To use measurement to determine the effectiveness of interventions.
— Involves measuring objective characteristics or responses of subjects, and is reported using numbers
Examples of QUALitative research
A naturalistic approach to research in which the focus is on understanding the meaning of an experience from the individual’s perspective
Definition of nursing research
Is a systematic process of inquiry that uses rigorous guidelines to produce unbiased, trustworthy answers to questions about nursing practice
Definition of Primary vs. Secondary data + examples
Primary: original data derived from your research endeavors
— e.g. taking surveys about hospital food
2ndary: data derived/obtained from your primary data
– e.g. reviewing surveys from former patients about hospital food
Generalization vs. Transferability
Generalizability = QUANTitative
Transferability = QUALitative
Agencies in the USA that support nursing research
— National Research Act —> enacted by Congress, signed into law to protect human subjects
— The Belmont Report —> deals with beneficence, justice, respect
— National Institute for Nursing (NINI) —> establish national research agenda
Retrospective study
A study that compares two groups of people: those with the disease or condition under study (cases) and a very similar group of people who do not have the disease or condition (controls).
— use 2ndary data that have already been collected about events that have already happened
– e.g. a group of 100 people with AIDS might be asked about their lifestyle choices and medical history in order to study the origins of the disease.
Retrospective = taking data from something that already happened (the data was there)
– e.g. were the patient in the last 3 months satisfied with their meals?
Prospective study
—Collecting data now to use in the future (don’t know when/how/where); followed over time as characteristics/circumstances change
— uses primary data to be implemented in the future
– e.g. birth cohort studies
Cross-sectional
— Can evaluate people of different ages, ethnicity, geographical locations, social backgrounds
— Studies conducted by looking at a single phenomenon across multiple populations at a single point in time
Standard normal deviation
Standard normal distribution: mean = 0 and std. deviation = 1
Standard score — Describe the relative position of an observation within a distribution
– z-score depicts the number of standard deviations above or below the mean an observation falls
–Positive z-score: Above the mean
–Negative z-score: Below the mean
Nominal & Ordinal data vs. Internal & Ratio data
N-O Data
Frequency table
Bar graph
Pie chart
Relative frequency
I-R Data
Measures of Central Tendency
Histograms
Variability
Position
