Evidence-based practice Flashcards
Evidence-based practice in SLT involves
integrating the best research evidence with clinical expertise and patient values.
3 pillars
scientific evidence, clinical expertise, patient values
goal of EBP
to make informed clinical decisions and provide effective interventions
history of EBP
dates back to the mid-19th century, with its modern form emerging in the early 1990s in Canada, driven by demands for accountability in service provision.
Total Evidence and Knowledge Approach emphasises
the use of a broad range of evidence and knowledge to support the evaluation of speech-language pathology treatments and clinical decisions.
TEKA encourages
therapists to consider various forms of evidence, including research-based, patient-based, and practice-based evidence.
With TEKA, it’s important to be aware of:
- over-reliance on certain forms of evidence, such as research efficacy studies, while neglecting patient- and practice-based evidence.
- eminence-based practice: places a strong emphasis on the opinions and recommendations of experts or authorities in the field, often based on their reputation, status, or experience.
- habit-based practice
- convenience-based approaches
Levels of evidence provide
a hierarchy for research designs based on their potential for bias, with randomized controlled trials (RCTs) often considered the gold standard.
Issues with levels of evidence to consider
limited availability of RCTs in many areas of speech and language therapy, generalizability concerns, and biases towards manualized interventions must be considered.
Research evidence should be based on factors like
Reliability and validity
Reliability
the consistency and stability of measurements or assessments over time and across situations. It ensures that repeated measurements produce similar results and helps prevent random errors.
Validity
assesses the accuracy and truthfulness of measurements, ensuring that a measurement tool or instrument accurately measures what it is intended to measure. It is crucial for obtaining meaningful and relevant information in healthcare.
Sensitivity
Sensitivity, also known as the true positive rate or the recall rate, measures the ability of a diagnostic test to correctly identify individuals who have a specific condition or disease.
Importance of sensitivity
Sensitivity is crucial when the consequences of missing a true positive (i.e., failing to identify a person with the disease) are significant. In healthcare, a highly sensitive test is desirable when early detection and intervention are critical to improving patient outcomes.
Calculation of sensitivity
Sensitivity is calculated as the number of true positives (individuals correctly identified as having the condition) divided by the sum of true positives and false negatives (individuals with the condition incorrectly classified as not having it). Mathematically, it can be expressed as Sensitivity = True Positives / (True Positives + False Negatives).
Specificity
Specificity measures the ability of a diagnostic test to correctly identify individuals who do not have a specific condition or disease.
Importance of specificity
Specificity is important when a false positive result (i.e., identifying someone as having the condition when they do not) can lead to unnecessary medical procedures, costs, and anxiety. In some cases, specificity may be prioritized over sensitivity.
Calculation of specificity
Specificity is calculated as the number of true negatives (individuals correctly identified as not having the condition) divided by the sum of true negatives and false positives (individuals without the condition incorrectly classified as having it). Mathematically, it can be expressed as Specificity = True Negatives / (True Negatives + False Positives).
Psychometrics
the application of statistics to measure human behavior. Psychometricians use specialized statistical tools to create valid assessments, and speech-language pathologists use these for language-related assessments.
Standardized assessments
- have structured administration and scoring procedures, ensuring consistency. - They involve interpreting scores based on a representative sample of similar individuals.
are important for consistent, unbiased assessments, supporting clinical judgment, and guiding treatment. They also help in measuring treatment outcomes and forming best practice recommendations. - Standardized assessments provide various scores, such as standard scores, T-scores, and percentile ranks, making interpretation and comparison easier.
- Converting raw scores to standard scores allows comparing a client’s performance to the normative sample, ensuring accurate assessment and interpretation.
Standardised scores and the normal curve
Standard scores are based on normative data and transformed to create a normal curve with a specific mean and standard deviation.
Mean is the 50th percentile, representing the average score.
Standard deviations above the mean correspond to higher percentiles, while those below indicate lower percentiles.
For normally distributed constructs, one standard deviation below the mean corresponds to the 16th percentile.
Basal and ceiling rules
Basal rules determine where to start a test, typically at a point where 95% of children of that age respond correctly.
Ceiling rules indicate when to stop testing, preventing administering items that exceed the client’s ability to respond
Confidence Intervals:
Confidence intervals account for measurement error inherent in clinical tests.
They provide a range of scores that likely include the client’s true score with 90% or 95% likelihood.
A narrower confidence interval indicates a more precise score.
Standard Error of Measurement
The standard error of measurement (SEM) estimates measurement error in a test.
SEM is inversely related to reliability; higher reliability results in a smaller SEM.
It’s used to create confidence intervals and interpret test scores accurately
Quality Norms:
Normative samples should be large enough for stable estimates of the mean and standard deviation.
The sample should be representative of the population for which the test is intended.
Factors known to influence test scores should be adequately represented.
Norms should be current, as norms may shift over time due to societal changes.
Not All Assessments Require Norms:
Criterion-referenced tests are keyed to external standards or criteria, such as curriculum standards, and do not rely on norms.
Reliability:
Reliability assesses the dependability of a test.
Internal consistency reliability measures the correlation between items to determine if they measure the same construct.
Test-retest reliability estimates stability by comparing scores from two test administrations to the same examinee.
Reliability is important to ensure that a test consistently measures what it’s supposed to measure
Validity
Validity assesses whether a test measures what it is intended to measure.
Evidence of validity can be provided through various approaches.
Concurrent validity involves comparing a new test with established tests to demonstrate correlations.
Convergent validity shows high correlation with other tests measuring the same construct.
Divergent validity demonstrates lower correlation with tests measuring different constructs.
Validity is not a single number but a collection of evidence supporting the test’s intended use
