Evidence-based practice and Ax

Question 1

Evidence-based practice in SLT involves:

Answer 1

integrating the best research evidence with clinical expertise and patient values.

Question 2

3 pillars of EBP

Answer 2

scientific evidence, clinical expertise, and patient values.

Question 3

goal of EBP

Answer 3

to make informed clinical decisions and provide effective interventions.

Question 4

history of EBP

Answer 4

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.

Question 5

What does TEKA stand for?

Answer 5

The Total Evidence and Knowledge Approach

Question 6

What is TEKA?

Answer 6

An approach that emphasizes the use of a broad range of evidence and knowledge to support the evaluation of treatments and clinical decisions.
It encourages therapists to consider various forms of evidence, including research-based, patient-based, and practice-based evidence.

Question 7

What practices should you be aware of?

Answer 7

• eminence-based: 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
• convenience-based approaches

Question 8

What are levels of evidence?

Answer 8

provide a hierarchy for research designs based on their potential for bias, with randomized controlled trials (RCTs) often considered the gold standard.

Question 9

What are issues with levels of evidence?

Answer 9

limited availability of RCTs in many areas of speech and language therapy, generalizability concerns, and biases towards manualized interventions must be considered.

Question 10

Psychometric properties in research-based evidence

Answer 10

Reliability vs validity
Sensitivity vs specificity

Question 11

Reliability vs validity

Answer 11

1. Reliability refers to 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.
2. 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.

Question 12

Sensitivity vs specificity

Answer 12

These concepts help healthcare professionals understand how well a test can correctly identify individuals with a particular condition (sensitivity) and how well it can correctly identify individuals without the condition (specificity).

Question 13

Sensitivity

Answer 13

• Definition: 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: 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: 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).

Question 14

Specificity

Answer 14

• Definition: Specificity measures the ability of a diagnostic test to correctly identify individuals who do not have a specific condition or disease.
• Importance: 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: 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).