Term
|
Definition
- dissemination of scientific knowledge
- critique of studies
- synthesis of research findings |
|
|
Term
|
Definition
Level I: BEST; systematic review or META analysis of all RCTs
Level II: one well-designed RTC
Level III: controlled trials W/O randomization
Level IV: Nonexperimental studies (case control, cohort, etc.)
Level V: Systematic reviews of descriptive and qualitative studies
Level VI: from single descriptive or qualitative study (longitudinal descriptive, case study)
Level VII: from opinion/observation of authorities and/or reports of expert opinions |
|
|
Term
| True experiment (3 items) |
|
Definition
1. Randomization
2. Control/Experiment
3. Manipulation/Intervention |
|
|
Term
|
Definition
| - understanding a description of human experience |
|
|
Term
|
Definition
| - from something small to something big |
|
|
Term
|
Definition
| - from something big to something small |
|
|
Term
|
Definition
- also like retrospective studies
- lung cancer example, they look back at their lives |
|
|
Term
|
Definition
- prospective
- twins, which one is gonna have cancer
- 2 groups of girls, one with fh of cancer other without...look into the future to see who gets cancer |
|
|
Term
| critiquing a research article |
|
Definition
1. critique the question
2. critique the hypothesis
3. critique the literature review
4. critique the theoretical framework
p. 7 in winter research guide |
|
|
Term
|
Definition
| Def: The systematic scientific process of generating new evidence. |
|
|
Term
|
Definition
1. validity
2. Reliability
3. Applicability |
|
|
Term
|
Definition
- population
- intervention
- comparison
- outcome
- time |
|
|
Term
|
Definition
o Quality aspects: policy (Administration)
o Model for evidence based practice to promote quality care
1. Triggers stimulate practitioners to question practice
• Problem focused triggers (i.e. risk management data, financial data, clinical problem)
• Knowledge based triggers (i.e. new research, national guidelines, philosophies of care)
2. Decision to make: What is the priority problem?
• ID and form a team
• Assemble research
• Critique and synthesize
3. Is there enough evidence to support the change?
• If there is enough, pilot the change in practice
• ID outcomes
• Collect data
• Design guidelines and implement
• Evaluate and modify
4. If there is not enough evidence?
• Conduct new research
• Base change on other types of evidence (case reports, expert opinion, theory)
5. Decision making regarding adoption in practice
• Will not adopt
• Continue to evaluate quality of care and new knowledge
• Will adopt
• Monitor and analyze structure, process and outcome data
• Monitor environment, staff, cost, patient and family Disseminate the results |
|
|
Term
|
Definition
• Implication: procedural
• Establishes a framework w/ specific criteria to help practitioners make decisions about the applicability of research findings to clinical practice
• Phases
o Preparation
• ID a need for knowledge r/t specific nursing practice situation
• ID purpose
• Conduct a review of published research r/t topic of concern
o Validation
• Synthesis of knowledge
• Do research critique (TOE)
• Evaluate scientific merit and applicability of findings → what is significant
• Is it relevant with pt population
• What are sources of bias/error? Valid sample, design, instrumentation?
o Comparative Evaluation/Decision Making
• Substantiating the evidence (synthesize cumulative findings from research)
• Fit of the setting with your clinical setting
• How feasible is the innovation to implement (resources, readiness of organization or individuals)
• What is the current practice on the unit and how does it compare to innovation?
• Decision
• Use the findings, consider using the findings, delay the use of findings, to not use the findigns
o Translation/Application
• The plan to use the innovation is carefully worked out
• Steps of the plan → develop protocol and implement the plan
• Types of change:
• Cognitive
o Improve understanding of a situation
o Analyze practice dynamics
o Expand problem solving skills for clinical problems
o Validate current practice
• Instrumental
o Change individual behavior
o Develop a protocol, guideline or algorithm based on research
o Document steps for changing practice
• Symbolic
o Revise a policy
o Develop a new role
o Legitimize a position
o Implement a new health delivery system
o Develop position paper or proposal for change
o Evaluation
• Formal evaluation (i.e. case studies, audits, surveys, quality assurance projects)
• Informal evaluation (i.e. self-monitoring, discussions with patients, families, peers and other professionals) |
|
|
Term
|
Definition
Nominal: Categories that are not more or less, but are different from one another in some way; NAMED
ex. Colors, jersey numbers etc.
Ordinal: Categories are orderable (by size, cost, height, importance, or complexity)
UNEQUAL INTERVALS; assigning numbers to categories
Ex. 1= tallest, 2= next tallest, etc.; rank in class, team standings
Interval: categories are orderable and distance btwn intervals ARE EQUAL, no zero, all manmade scales
Ex. Temperature and dress size
Ratio: HIGHEST FORM, numbers are in order, distances btwn numbers are equal, HAS AN ABSOLUTE ZERO
Ex. Number of patients seen, distance to class, number of sales made |
|
|
Term
|
Definition
- in a survey... ask the same thing different times...make sure they are consistent
- how many hours of sleep a night? how many hours a day are u awake?
- want it to be greater than 0.8 |
|
|
Term
|
Definition
- p want it to be less than or equal to .05...so 0.025 on either side of bell curve
- means alpha
- 95% accuracy
- significance level |
|
|
Term
|
Definition
- measure of variability
- average deviation of scores from the mean |
|
|
Term
|
Definition
- tests difference between means for 2 variables for 2 or more groups
- analysis of variance |
|
|
Term
|
Definition
- multiple analysis of variance
- used to determine differences in group means, but used when there is more than one dependent variable (consequence or the presumed effect that varies w/ a change in the independent variable |
|
|
Term
|
Definition
- Analysis of covariance
- designed to reduce the error term (variance within groups) by partialing out the variance resulting from a confounding variable by performing regression analysis before performing analysis of variance |
|
|
Term
|
Definition
| performed AFTER ANOVA – used to indicate whether the groups are significantly different |
|
|
Term
|
Definition
- external: generalizability of the findings to other settings or samples
- Internal: accuracy in which causal relationships can be made btwn variables/behaviors in study
- Measurement: do our variables/data accurately represent the behaviors we intended to study?
- Statistical conclusion: have we reached the correct conclusion about whether or not there is a relationship btwn variables/behaviors we are studying? |
|
|
Term
|
Definition
| an extraneous variable that is allowed to change systematically along with the two variables being studied |
|
|
Term
| Levels of measurement (4) |
|
Definition
1. Nominal: Categories that are not more or less, but are different from one another in some way; NAMED
ex. Colors, jersey numbers etc.
2. Ordinal: Categories are orderable (by size, cost, height, importance, or complexity)
UNEQUAL INTERVALS; assigning numbers to categories
Ex. 1= tallest, 2= next tallest, etc.; rank in class, team standings
3. Interval: categories are orderable and distance btwn intervals ARE EQUAL, no zero, all manmade scales
Ex. Temperature and dress size
4. Ratio: HIGHEST FORM, numbers are in order, distances btwn numbers are equal, HAS AN ABSOLUTE ZERO
Ex. Number of patients seen, distance to class, number of sales made |
|
|
Term
| parametric vs nonparametric |
|
Definition
PARAMETRIC = interval and ratio
- perfect bell curve
NONPARAMETRIC = nominal and ordinal
- non perfect bell curve |
|
|
Term
|
Definition
The consistency and stability of measurements
- test-retest: Consistency of repeated measures of same attribute with use of same scale/instrument over time (stability over time)
- internal consistency: Expresses the degree of consistency in the measurement of test scores (across items within a test)
CRONBACH’S ALPHA: want it to be AT LEAST 0.8
- Interrater reliability: assess degree to which different raters/observers give consistent estimates of same phenomenon
- Parallel reliability: assess consistency of results of 2 tests constructed in same way from the same content domain |
|
|
Term
|
Definition
RELATIONSHIP btwn variables (-1 to +1)
- interval or ratio
- strong = (-0.76 to +0.76) |
|
|
Term
|
Definition
-simple random: Every subset of a specified size n from the population has an equal chance of being selected
- systematic: Every kth member ( for example: every 10th person) is selected from a list of all population members.
- stratified: The population is divided into two or more groups called strata, according to some criterion, such as geographic location, grade level, age, or income, and subsamples are randomly selected from each strata.
- cluster: The population is divided into subgroups (clusters) like families. A simple random sample is taken of the subgroups and then all members of the cluster selected are surveyed. |
|
|
Term
|
Definition
- convenience sampling: attempts to obtain a sample of convenient elements. Often, respondents are selected because they happen to be in the right place at the right time.
- Quota sampling: Convenience sampling with set proportions from certain groups (just like stratified random sampling, but NOT random)
- Purposive sampling: Certain elements purposefully selected; Conscious selection of the persons most likely to provide useful information
- Networking (snowball) sampling: Takes advantage of social networks; Used to obtain subjects difficult to identify or connect with in other ways |
|
|
Term
|
Definition
|
|
Term
| Controlling extraneous variables |
|
Definition
- To CONTROL extraneous variables
o Random sampling
o Random assignment to groups
o Selecting subjects that are homogeneous in terms of a particular extraneous variable
o Selecting a heterogeneous sample
o Blocking
• The researcher includes subjects with various levels of an extraneous variable in the sample but controls the numbers of subjects at each level of the variable and their random assignment to groups within the study
•
o Stratification
• Blocking but without talking about extraneous variables in the analysis of the data
o Matching subjects – pick a variable and make sure both groups have even amounts
o Statistical control – ignore extraneous variable |
|
|
Term
|
Definition
Associative v. Causal – Associative hypotheses identify relationships among variables in a study but do not indicate that one variable causes an effect on another variable. Associative hypotheses are developed to examine relationships among variables in the study; Causal relationships identify a cause-and-effect interaction between two or more variables, dependent or independent variables.
Simple v. Complex – Simple hypotheses predicts the relationship (associative or causal) between two variables. Complex hypotheses predicts the relationship (associative or causal) among three or more variables
Nondirectional v. Directional – Nondirectional states that a relationship exists but does not predict the nature of the relationship. Directional states the nature or direction of the relationship between two or more variables
Null v. Research – Null (statistical) is used for statistical testing and interpretation of these results. Research hypothesis is the alternative hypothesis to the null. It states that there is a relationship between two or more variable and it can be simple or complex, nondirectional or directional, and associative or causal.
Null = NO RELATIONSHIP
- If you accept the null hypothesis, you have found no statistically significant difference in your variable
- If you reject the null hypothesis, you ACCEPT the research hypothesis |
|
|
Term
|
Definition
Level I - exploratory or descriptive research questions
Level II - Explanatory research questions
Level III - Predictive research questions |
|
|
Term
| 3 characteristics of a true experiment |
|
Definition
1. one experimental and one control group
2. manipulation of the independent variable
3. random assignment |
|
|
