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Critical Inquiry > flashcard data - final > Flashcards

flashcard data - final

1
Q

Evidence based practice (EBP)

A

Fundamental principle that the quality of care will depend on our ability to make choices that have been confirmed by sound scientific data and are based on the BEST evidence currently available

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2
Q

Basic experimental research

A

In a lab; used to further our knowledge not necessarily applicable to our everyday lives

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3
Q

Applied Research

A

Doing something to someone else

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4
Q

Case report

A

NAME?

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5
Q

Case series

A

Several case reports put together to illustrate a single point

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6
Q

Case Control Studies

A

Medical history of persons with a rare disease are compared to history of similar (matched) person without the disease

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7
Q

Cohort studies

A

One group of people

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8
Q

Randomized control study (RCT)

A

Gold standard for experimental

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9
Q

Systematic Review

A

combine many studies into one large study

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10
Q

Meta-analysis within systematic review

A

when data of the studies is complied and analyzed as one

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11
Q

Qualitative Research

A

Generally applied to descriptive or exploratory

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12
Q

Quantitative Research

A

Descriptive exploratory (correlative), experimental

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13
Q

Evidence based pyramid

A

Top:

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14
Q

Primary source

A

Authors are reporting the original report of research they have conducted (ie: applied or basic, descriptive, experimental or correlational)

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15
Q

Secondary source

A

A summary of primary work (ie: book chapters, literature review)

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16
Q

Experimental Research

A

Attempts to define a cause and effect difference through group comparisons: controlled manipulation of independent variable

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17
Q

Types of Experimental Research

A

RCT

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18
Q

Quasi-experimental

A

lacks control and or/randomization

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19
Q

Repeated measures

A

Same participant are measured under all levels of the IV

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20
Q

Single Subject design

A

Analysis of a single subject across time

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21
Q

Difference between case study and single subject design

A

Case study-description of individual response to treatment–non-experimental

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22
Q

Confounding variable

A

Variable that contaminates data

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23
Q

Examples of confounding variables

A

Assignment to group (randomized??)

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24
Q

What is a subject

A

One who has provided consent to be involved in research, not synonymous to a patient

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25
Q

Sampling bias

A

individuals selected over represent or under represent certain population attributes

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26
Q

Validity

A

The degree to which a useful (meaningful) interpretation can be inferred from a measurement

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27
Q

External vs Internal Validity

A

EV:To whom the results are applied to

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28
Q

Types of validity

A

Content (of what you want to evaluate)-accurate representation

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29
Q

Threats to internal validity

A

Subject selection

30
Q

Reliability

A

The extent to which a measurement is free from error

31
Q

Types of reliability

A

Inter-rater, Intra-rater, test-retest

32
Q

Sources of error in reliability

A

Rater

33
Q

Threats to reliability

A

Repeated errors of measurement

34
Q

Independent vs Dependent variables

A

IV: presumed to be the cause of the dependent variable; the variable that is manipulated or controlled by the researcher

35
Q

Descriptive statistics

A

(ie: mean median mode) formulate a description of reported data, (sample characteristics, results of the study)

36
Q

Inferential statistics

A

Modulating numbers, Used to make comparisons, determine the effect of different factors on an outcome

37
Q

Clinically relevant statistics

A

Evaluate the importance of outcomes for patient care

38
Q

Nominal data

A

categories where the order does not matter (ie: colors)

39
Q

Ordinal data

A

categories where the order matters (high, med, low)

40
Q

Continuous data

A

Specifically ratio data (data that is measured by consecutive numbers that represent, infinity of options)

41
Q

Criteria for correlation coefficient

A

.75 to 1.0=good to excellent

42
Q

Correlation interpretation to be careful of

A

Correlation not that same as causal

43
Q

Type I vs Type II error

A

Type I: rejection of the null hypothesis when it was actually true (usually because of biases)

44
Q

Power

A

The probability that a study will detects a statistically significant difference between groups…if it exists

45
Q

Parametric data vs. non-parametric data

A

parametric: refers to assumption about the population from which that data was obtained (bell-shaped curve)

46
Q

P-value

A

the percent chance that the results were due to chance

47
Q

Alpha value

A

The level that the significant difference will occur due to chance alone

48
Q

Null hypothesis

A

any observed difference between populations means are due to chance

49
Q

Alternative hypothesis

A

Observed differences between two populations means are not due to chance

50
Q

ANOVA

A

comparing 3 or more independent variables (one-way, two-way, repeated measures)

51
Q

one-way anova

A

comparing two or more independent variables on one dependent variable; hypothesis test that considers population means based on one characteristic

52
Q

post-hoc testing

A

after rejecting the null hypothesis it tell us where the differences are….perform after the null hypothesis is rejected

53
Q

two-way anova

A

used when two independent variables are examined in a single experiement; a hypothesis test that considders comparisons between populations based on multiple characteristics

54
Q

interaction effect

A

one variable is dependent on the level of the second variable

55
Q

MDC

A

minimal detectable change (represents the smallest change in score that likely reflects true change rather than measurement change alone (only shows that minimal change that is detectable by the instrument and not necessarily theamong of change that could be considered clinically meaningful to the patient)

56
Q

MCID

A

smallest treatment effect that a clinician seems to make a change in a patient/ clients function or quality of life in response to an intervention (how much change is required for a patient to experience a meaningful change?)

57
Q

NNT

A

number needed to treat: modest effects that occur frequently

58
Q

Confidence interval

A

range of scores with specific boundaries that should contain the population mean

59
Q

Diagnostic accuracy

A

ability of an exam or diagnostic test to accurately identify or rule out a condition

60
Q

Diagnostic test

A

determines the presence of absence of a disease or abnormal condition

61
Q

Reference standard

A

A method that will identify if a person has a condition (gold standard)

62
Q

Contingency table

A

Top: Gold standard

63
Q

sensitivity

A

ability to obtain a positive test when the testing condition is truly positive (true positive/(false negative+true positive))

64
Q

specificity

A

ability to obtain a negative test when the testing condition is truly negative (true negative/(false positive+ false negative))

65
Q

positive predictive value

A

proportion of those with a positive test that have the disease

66
Q

negative predictive value

A

proportion of those with a negative test that do not have the disease

67
Q

Positive likelihood ratio

A

the probability that a person with a positive diagnostic test result has the suspected problem; greater than 10 is a conclusive test

68
Q

Negative likelihood ratio

A

the probability that a person with a negative diagnostic test result does not have the suspected problem; less than .1 is a good conclusive test

69
Q

acceptable value for ICC

A

.8 or greater

70
Q

acceptable value for likelihood ratio

A

positive- greater than 10

71
Q

acceptable value for correlation value

A

greater than .75

Critical Inquiry (4 decks)

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