CDS 501 Final Exam

  1. Components of Informed Consent
    • 1. Purpose of the study
    • 2. Procedures
    • 3. Potential Benefits
    • 4. Potential Risks
    • 5. The fact that they may withdraw at any time without penalty
  2. Importance of Informed Consent
    the key to promoting ethical values in research 

    • ASHA Principle I of Ethics 
    • Rules of Ethics N: Individuals shall use persons in research or as subjects of teaching demonstrations only with their informed consent
  3. Institutional Review Boards (IRB)
    • independent bodies that review research for the protection of  human participants
    • approve plans that eliminate/reduce harm and offer some benefit to the participant 
    • evaluate risks to participants, assess safeguards, and recommend modifications when necessary
  4. Levels of Review for IRB
    • Full review: the standard
    • Expedited review: faster process
    • Exemption: the study doesn't require it because there are no subjects (ex. meta-analysis)
  5. The Belmont Report
    • developed framework for ethics code
    • institutions must be clear about routine and research services purposes 
    • vulnerable populations must be protected
    • research must demonstrate respect for persons, beneficence, and justice
  6. 3 Critical Elements of the Belmont Report
    Respect for persons: recognize people have value and choice (informed consent)

    Beneficence: do no harm, maximize benefits to the client, try to make benefits outweigh the risks 

    Justice: treat all people equally; subject selection formed to the study and fair
  7. Components of IRB Application
    Contact Dr. Adibi

    • approval form 
    • abstract 
    • informed consent agreement 
    • support letter(s)
    • survey instrument, treatment protocols, test instrument, test/treatment materials
  8. Abstract/Summary of IRB
    Intro (rationale, statement of purpose, hypothesis)

    Method (design, setting, participants, instruments, procedures for recruiting subjects, data collection procedures)
  9. Evidence Based Practice (EBP)
    • process that aims to provide clients and practitioners with info needed to choose the best procedure/treatment for the client
    • current high quality research, clinical experience, and client preference is used to make treatment and diagnostic decisions
  10. Components to Ensure EBP
    • clinical decisions based on most up to date scientific and clinical evidence 
    • clinician level of experience
    • involve the client in the decision making process
  11. Steps of EBP
    • 1. ID the clinical problem
    • 2. gather info about the problem from research studies 
    • 3. ensure adequate knowledge to read and analyze the studies 
    • 4. summarize info to use in your practice 
    • 5. define expected outcomes for clients and the families 
    • 6. provide EDU and training to implement the suggested change in practice 
    • 7. eval the practice; change/modify if necessary
  12. 2 Major Sources of Info for EBP
    • raw evidence 
    • pre-filtered evidence
  13. Raw Evidence
    info that has not been subjected to expert review
  14. Pre-filtered Evidence
    info that has been reviewed by experts
  15. History of EBP
    • governed by medical EBP
    • EBP began in audiology first (1995)
    • 2005 ASHA convention dedicated to formally make SLP EBP 
    • ASHA code of ethics for EBP made in 2003
  16. Ethics in EBP
    • must include client's best interests
    • must favor the proven intervention 
    • based on clinically relevant evidence in collaboration with the client 
    • considers costs, benefits, resources, and options
  17. Model For EBP
    • 1. Formulate answerable question about prevention, diagnosis, prognosis, or therapy 
    • 2. Locate best evidence to answer the question 
    • 3. Eval the evidence based on validity, impact, and utility 
    • 4. Combine eval with clinical experience and the client's unique circumstances
    • 5. implement and eval effectiveness and efficacy
  18. PICO Questions
    Patient/Population Intervention Comparison and Outcome questions 

    • population should include age, disorder, severity, time since onset
    • intervention of interest stated in a specific way 
    • comparison of other possible interventions for the population in question 
    • what are the expected outcomes?
  19. Things to Remember about EBP
    • Every case is different 
    • Not solely a matter of science and evidence; recognize specific client needs
    • reading textbooks/journals and attending conferences is not enough for EBP
    • EBP can be effective without randomized clinical trials
  20. Measurement
    systematically assign numbers to object, persons, or events according to rules determined by the research design to determine the degree of difference 

    • determine the extent of IV on DV
    • allows us to examine sim/diff between measured events
    • forms the basis of statistical analysis
  21. Data
    • form (usually numerical) in which measurements are collected and stored
    • dictate the types of statistical analyses that can be applied
  22. Parameter
    a number describing a population characteristic

    ex) average weight of women -- based on gen pop, not sample
  23. A Statistic
    number describing a sample characteristic
  24. Two Types of Statistics
    • Descriptive Statistics 
    • Inferential Statistics
  25. Descriptive Statistics
    • involves tabulating, depicting, and describing data
    • a specific feature or characteristic of a set of data is measured
    • data summary used to organize data (visual description of the results)
    • used in qualitative and quasi experimental studies 
    • may use simple count data
  26. Simple Count Data
    • number of occurrences of the behavior
    • used in small samples
  27. Inferential Statistics
    tests that allow us to estimate/predict characteristics of a pop from knowledge of characteristic from the sample 

    (make inferences to the gen pop)
  28. 4 Scales of Measurement (Stevens Taxonomy)
    applied to data dependent on its properties 

    • Level 1: Nominal Level 
    • Level 2: Ordinal Level 
    • Level 3: Interval Level
    • Level 4: Ratio Level
  29. Nominal Level
    • Level 1 of Stevens Taxonomy 
    • naming level 
    • has no quantitative properties 
    • allows us to classify groups, categories, behaviors, and events 
    • assumed that groups don't overlap 

    ex) male and female; may be numbered (male=1 and female=2) as a descriptor, but the number itself has no value
  30. Ordinal Level
    • Level 2 of Stevens Taxonomy
    • to rank/order the levels of the variable being studied 
    • imprecisely measured data 
    • ranked highest to lowest, greatest to least, etc.
    • not suitable for  statistical analysis 
    • ex) the likert scale
  31. Interval Level
    • Level 3 of Stevens Taxonomy 
    • used to analyze inferential statistics 
    • meaningful difference between the numbers on the scale 
    • intervals are equal in size 
    • distance between intervals is known and fairly consistent 
    • NO ABSOLUTE ZERO (zero does not mean the absence of something)
    • may have a relative zero 
    • ex) decibels -- zero decibels isn't the absence of sound, just the lowest sound a human can hear
  32. Ratio Level
    • Level 4 of Stevens Taxonomy 
    • highest level of measurement
    • used in inferential statistics  
    • same characteristics as interval level PLUS the presence of an absolute zero
    • can compare points along a scale in absolute terms 
    • continuous variables that have all the math properties
  33. Nominal Variables
    • used to name things 
    • no numerical value
  34. Numbers on an athlete's jersey represent what type of variable?
    Nominal Variable
  35. Measures of Central Tendency
    • mean (average)
    • median (middle)
    • mode (occurs most often)

    can always be applied to data
  36. What does a negative distribution do when compared to a normal distribution?
    underestimates performance of the participants
  37. What does a positive distribution do when compared to a normal distribution?
    overestimates performance of the participants
  38. When is the best time to use the mean when describing data?
    when the distribution is normal
  39. Non-parametric Statistical Analysis
    • does not need normal distribution
    • does not assume that data reps a normal distribution 
    • used on nominal and ordinal data
  40. Parametric Statistics
    • analyze groups with normal distribution
    • used for interval and ratio data
  41. Standard Scores
    • raw scores that are converted to standard deviation units 
    • also known s z-scores
  42. Raw Score
    • initial score on a test
    • has no real value 
    • must be changed to converted (standard) score
  43. Levels of Power Applied to Statistics
    • p = 0.05 (average; reject the null hypothesis)
    • p=0.01 (more statistically powerful)
    • p = 0.001 (most statistically significant)
  44. Student's t-test
    • most popular statistical procedure for testing the difference between two groups of subjects
    • applied to between-subjects designs
    • parametric test (assume normal distribution)
    • used if # of subjects is less than 30
  45. Z-test
    • parametric test (assumes normal distribution)
    • used when the # of subjects is greater than 30
  46. ANOVA
    • analysis of variance 
    • allows groups of different variables to be compared at the same time 
    • used at interval or ratio levels of measurement 
    • participants randomly samples
    • assume normal distribution (parametric)
    • populations have equal variance
  47. ANOVA Classification
    • one way (simple): one grouping factor; determine if the variance is because of sampling error or the treatment effect
    • multi-factor (complex): analyzing interaction of factors and separate effects of each factor
  48. Format for Final Paper
    • Table of Contents
    • Abstract
    • Chpt 1: Intro
    • Chpt 2: Research Methods
    • Chpt 3: Results/Data
    • Chpt 4: Discussion 
    • Chpt 5: References 
    • Chpt 6: Appendix
  49. Rating Scales vs Likert Scales
    Rating Scale: assign value to an object

    Likert Scale: 5 to 7 point rating scale that determines the extent to which someone agrees or disagrees with a statement
Card Set
CDS 501 Final Exam
CDS 501