EBP midterm

Evidence, clinical experience, patient preferences

three parts of the evidence-based practice triangle

Ask, find, appraise, incorporate, self-evaluation

5-step process of EBP

Incorporation

the _______ step of EBP involves evaluating clinical expertise, patient values, and circumstances

Background

Information on the diagnosis or medical management

Foreground

What is the best intervention for my patient

Patient, intervention, comparison, outcomes

PICO stands for

Type of question, type of study design

extensions for PICO

Blind comparison RCT

Best study design for diagnosis

RCT, cohort study

best study design for therapy, treatment options

Cohort study, case control study

best study design for prognosis

RCT, cohort study

best study design for harm/etiology

RTC, cohort study

best study design for prevention

Blind comparison RTC

best study design for clinical exam

Cohort study, case control study

best study design for cost benefit

Narrative review, case report, case control study, cohort study, randomized control trial, meta-analysis, clinical practice guideline

evidence hierarchy

Cohort study, case control study

two types of observational studies

Meta-analysis, clinical practice guideline

two types of pre-appraised/filtered studies

High-quality research

higher levels of the pyramid represent

Clinical practice guidelines

provide clinicians with direct recommendations to make decisions based on available evidence

T

T/F - clinical practice guidelines can make definitive statements

Systematic review

answers questions by systematically reviewing and describing all available evidence, synthesized al relevant available evidence and recommend future directions

Meta-analysis

synthesized findings from multiple studies to generate summary statistics, polls studies to create larger sample sizes

Forrest plot

graph used in systematic reviews and meta analyses, show effect estimate and confidence interval

Clinical practice guidelines

answers “what should clinicians do”

Systematic review/meta analysis

answers “what does the evidence say”

Cohort study

retrospective or prospective study of exposures and outcomes

Case-control study

observational study design where cases have a condition of interest

Observational studies

type of study that attempts to understand relationships

F

T/F - observational studies control for bias

Case study/case series

description of treatment of patients or participants

Standardized, sample free, equal distances between scores

3 parts of a perfect measurement tool

Measurement value

true value + random error + systematic error

Patient, examiner, environment, instrument

4 sources of error in measurement

Primary variance

consistent changes in the measured value related to the primary effect

Secondary variance

consistent changes in the measured value due to factors other than the primary effect

Error variance

inconsistent changes in the measured value to to measurement error or using the incorrect statistics

Standard error

how much error exists in an individual’s observed score

Measurement validity

test/instrument measures what it is supposed to measure

T

T/F - a measure cannot be valid if it is not reliable

Face validity

does the test/instrument a good tool to measure the construct of interest

Content validity

the instrument measures only the constructs of interest, and does not include irrelevant elements

Predictive, concurrent

two types of criterion validity

Criterion validity

the measurement is related to the outcome of interest

Predictive validity

the measurement predicts an outcome of interest

Concurrent validity

the measure of interest and a measure with established validity are administered at same time point and produce consistent results

Construct validity

Instrument measures what it claims to measure, Depends on operational definition of construct being measured

Reliability

Repeated measurements are consistent

Test-retest reliability

Measure is consistent when performed multiple times (2+) on same patient/participant and construct has not changed

Intra-rater reliability

measurements obtained by same assessor are consistent

Inter-rater reliability

measurements obtained by 2 or more assessors are consistent

Relationships

graphing data can give a better understanding of

Central tendency

used to describe measure that tell about the center of a distribution of data

Mean, median, mode

3 measures of central tendency

Mode

measures of central tendency for nominal data

Mode, median

measures of central tendency for ordinal data

Mean, median, mode

measures of central tendency for interval data

Mean, median, mode

measures of central tendency for ratio data

Histogram

graph that represents the frequency for each time a specific value occurs in a data set

Mean, median, mode

Central line in a normal distribution special

Mode, mean, median

order for right-skewed data

Mean, median, mode

order for left-skewed data

Variability

used to describe measures that tell about the spread of a distribution of data

Range, standard deviation

2 measures of variability

Standard deviation

describes the spread of data around the mean value

Coefficient of variation

a measure of relative variability, used to compare variability across groups or measures, expressed as a percentage of the mean

Coefficient of variation

used to compare variability between different measures of the same construct that do not share the same units

T

T/F - coefficient of variation can be used to compare the variability between 2 different samples of the same measure

Z-score

measure of relative standing, used to compare a score to a reference population via standard deviation

x-mean/SD

z-score =

0

a z-score of ____ means the value is exactly at the mean

95%

___% of z scores in a normally distributed variability are between -2 and +2

Standard error of the mean, confidence interval

indicators/measures of precision

Standard error of the mean

measure of ‘precision’ of the sample mean as an estimate of the population (true value)

Confidence intervals

Range of plausible values for the “true” population value, calculated from sample data.

Confidence intervals

If studies were repeated many times, approximately 95% of calculated ____________ would contain the true value.

Type 1 question

Does Intervention A improve an outcome measure more than Intervention B?

Type 2 question

Does Intervention A improve an outcome measure?

Type 3 question

Is Variable C associated with Variable D?

Type 4 question

Can the values of Variable C (and D, etc…) predict the value of Variable E?

Type 5 question

Is Population F different from Population G in terms of some characteristic or outcome measure?

Type 6 question

none of the above

Internal validity

the degree to which the results of the study can be attributed to the study intervention and not to extraneous factors

Selection bias

Process of selecting subjects leads to a sample that is not representative of the target population (ex: convenience sample)

Randomized subjects

solution to selection bias

Insufficient sample size

Sample size is determined by a calculation to detect an estimated effect (ex. change in a dependent variable) while balancing the risk of error.

Sample size justification

solution to insufficient sample size

Enroll additional subjects

solution to participant attrition

Random assignment

solution to history

History

Events that occur outside the study, but influence the results of the study

Random assignment, more baseline testing

solutions to maturation

Maturation

Changes over time that are internal to participants. Not related to study, but may impact results.

Regression to the mean

Participants with high or low scores at baseline testing will likely score closer to the mean at subsequent testing sessions (ex: post-test)

Multiple baseline assessments, remove outliers

solutions to regression to the mean

Practice sessions

solution to testing threat

Testing

Subjects become familiar with test (reason for observed changes in outcomes)

Blind assessor, third party tester

solution to assessor bias

Assessor bias

The person testing the participants has a particular bias or opinion about how the outcome of the study should look.

Declare

solution to conflicts of interest

Ground randomization, blind participants

solutions to placebo

Placebo

participants’ expectation influence outcome positively