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Ohoho HD right Flashcards

1
Q

Hierarchy of evidence

A

a tool that can be used to quickly grade research studies according to their quality

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2
Q

What are other factors to consider about hierarchy of evidence?

A

they do not assess actual quality of studies themselves.
do not consider generalisability
benefits: the effect of the result and whether its clinically worthwhile
harms: adverse affects and costs

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3
Q

Evidence Based Practice

A

making decisions about how to promote health or provide care by integrating the best available evidence

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4
Q

5 step approach

A

Ask: define problem as a searchable question (PICO)
Acquire: search and acquire relevant info
Appraise: appraise the information you acquired
apply: using the evidence and applying into practice
assess: assess the results of how you went in the 5 step approach

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5
Q

PICO, what does it stand for?

A

P- patient
I- intervention
C- comparison
O- outcome

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6
Q

Quantitative data

A

research focuses on the use of numbers and testing hypotheses

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7
Q

Qualitative data

A

research focuses on words and analysis of themes, ideas and beliefs

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8
Q

Continuous data

A

can be given any value (temperature, height etc)

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9
Q

Discontinuous (discrete) data

A

Data that fits into one of two or more discrete categories

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10
Q

Nominal scale (categorical)

A

data obtained fits into one f two or more groups. NO RANKING OR ORDER ASSOCIATED WITH THE GROUPS.

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11
Q

Ordinal scale

A

Data obtained fits into one of two or more groups. THERE IS A RANKING OR ORDER ASSOCIATED WITH THE GROUPS.

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12
Q

Interval scale

A

There is no true zero point (temperature)

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13
Q

Ratio scale

A

There is a true zero point

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14
Q

What are the 4 key things you are trying to learn about from PICO?

A

Prevalence, Diagnosis, Prognosis and treatment

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15
Q

Measures of central tendency and dispersion

A

Centre of the distribution - median, mean

Variability/dispersion of the data - interquartile range/range, standard deviation

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16
Q

Nominal data presentation

A

Usually presented in contingency tables

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17
Q

Ordinal data presentation

A

Median, Range, IQR

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18
Q

Interval/ratio data presentation

A

mean, SD

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19
Q

Inferential statistics

A

statistics that enable generalisation (inferences) to the wider population

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20
Q

Internal validity

A

the truthfulness of the findings of a study based on the methods used in that study

conclusions about causal relationships can be made (cause and effect), based on measures used, the research setting and the whole research design. independent and dependent variables would be made if it has good internal validity.

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21
Q

External validity

A

the extent to which findings from a study relate to patients or clients in the real world. (generalisability of the study)

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22
Q

Construct validity

A

to what extent does research actually measure what the theory says they do?

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23
Q

Chi^2 tests

A

used to compare frequencies of an event occurring in two groups

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24
Q

T-test

A

used to compare the mean values of two groups that have received different interventions for a particular condition

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25
P value
used to determine the probability of an event occurring.
26
Point estimate
used as an estimate of the effect of an intervention. tells us how big the effect was in the sample studied.
27
Confidence Intervals
indicates how precise the point estimate is and how well the sample represents a wider population
28
Bias
prejudice for or against a group
29
Intention to treat analysis
used in RCTs where outcome measures are obtained regardless o compliance with the trial protocol and where data from all participants are analysed according to the allocation
30
Sample size
should be large enough to detect if the intervention is being evaluated leads to a clinically worthwhile effect
31
outcome measures
used to measure the effect of an intervention. that should be both valid and reliable.
32
patient-reported outcome
an outcome where the patient, rather than the clinician, reports on the impact of a disease or intervention on the status of their health
33
confounder
an extraneous factor that distorts the true effect of an intervention
34
selection bias
investigators systematically manipulate enrolment
35
allocation bias
process of allocation participants to groups leads to differences in baseline characteristics of those groups
36
assessment bias
assessment of participants lacks objectivity. subjective outcome measures are prone to exaggerate the effect of the intervention
37
ascertainment bias
results or conclusions are distorted by knowing which interventions each participant is receiving
38
stopping rule bias
the trial is stopped inappropriately
39
maturation bias
the effect might be due to changes that have occurred naturally over time, not because of any intervention
40
attrition bias
participants who withdraw from studies may differ systematically from those who remain. other there may be more participants lost from one group than the other one
41
measurement bias
errors in measuring exposure or outcome can lead to differential accuracy of information between groups.
42
placebo effect
an improvement in the participants condition may occur because they expect or believe that the intervention that they are receiving will cause an improvement
43
hawthorne effect
Alteration of behaviour by the subjects due to awareness of being observed
44
explanatory trial
a trial that is highly controlled and hence reduces the number of variables that can affect the final outcome
45
pragmatic trial
one in which the investigators attempt to mimic common practice, thereby endeavouring as much as possible to make the results generalisable to everyday practice
46
publication bias
occurs when a trial is published or not published because of the direction of its findings. studies that have a positive results are more likely to be published.
47
citation bias
occurs where articles that have more statistically significant findings are cited more often than others.
48
the CONSORT statement
(consolidated standards of reporting trials) aims to ensure accurate and complete reporting f the design, conduct, analysis and generalisability of the trials, thus ensuring the highest posisble standards are met when clinical trials are published
49
Type I statistical errors
occur when researchers mistakenly conclude that a finding was statistically significant when it may be a result of chance rather than being a real difference
50
Type II statistical errors
there may have been a worthwhile clinical effect, however the trial did not have a large enough SAMPLE SIZE to detect it statistically
51
Quality assessment
evaluation of the methodological quality of a particular study.
52
Homogeneity
level of similarity of findings between different studies
53
Heterogeneity
level of dissimilarity of findings between different studies (due to variables, biases, methods of obtaining results)
54
Natural progression
succession fo quantities in which there is a constant relation between each member and the one succeeding it
55
Regression to the mean
if the variable is extreme upon first measurement, it is closer to average on the second measurement
56
Rosenthal effect
the greater the expectation placed on people, the better they perform
57
Resentful demoralisation
those in the control group are resentful for not receiving the experimental treatment. could lead to non-compliancy and un-cooperativeness. can lead to significant systematic differences in the outcome of the control group
58
APPLY - 1 strength
level and quality of the evidence | statistical vs. clinical significance
59
APPLY - 1 Completeness
study findings are explicit and complete | comparison to other studies and similarities
60
APPLY - 1 relevance
appropriate for your patient?
61
APPLY - 2 Risks and benefits
clinically worthwhile? any side effects?
62
APPLY - 2 costs
direct vs indirect costs
63
APPLY - 3 influencing factors
``` individual practicality local context ethical economical social political ```
64
Risk ratio - use? (discontinuous data)
Compare the rate (chance) of an event in one group against the rate of an event in another group
65
Risk ratio
the chance of risk
66
0.00 to 0.25
little/no relationship
67
0.25 to 0.50
fair relationship
68
0.50 to 0.75
moderate to good relationship
69
0.75 to 1.00
good to excellent relationship
70
correlations - what variables can they be?
ordinal, interval or ratio
71
What does the black diamond show in a systematic review forest plot?
Pooled results from the included studies and treatment led to a non-statistically significant increase in the risk of side effects
72
Negatively skewed data means (in regards to statistical mean/median etc)
median is greater than the mean | mode is greater than the mean
73
Standardised mean difference
effect size calculated for the difference between the two treatment groups 0.5 large effect
74
statistical tests to calculate effect size for continuous data
standarised mean difference
75
alternative hypothesis
a real difference between the groups/observations due to a systematic cause
76
null hypotheses
no real difference between groups/observations
77
Heterogenous on a forest plot would indicate that
P value for Chi^2 test is less than 0.1 | I^2 test is greater than 50%

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