Ch 8. Personal observations, Surveys/questionnaires, Scientific research/method, and Analogies Flashcards
(11 cards)
Personal Observations
Using what we see as evidence (eye-witness testimony)
Issues:
Not “pure” observations, filtered through set of expectations, values, beliefs and attitudes
Confirmation bias
Selective attention, inattentional blindness
Memory and stress may distort observations
Factors that improve quality:
Recency
Made by several people who are unbiased under optimal conditions with no apparent or strong expectations or biases
Supporting data aside from observations
Is personal observations a good source of evidence for HP?:
Essential but limits
Can be improved by: Accurate knowledge base and appropriate skills and expertise
Appropriate administration of objective assessments
Independent confirmation by other helping professionals
Personal experience is not the same as personal observations
Surveys and questionnaires
Usually used to measure people’s behaviors, attitudes and beliefs
Are surveys/questionnaires valid for HP?:
Can provide useful information about:
Frequency of use of diagnostic or treatment approaches
Attitudes and beliefs about communication disorders
Concerns/issues faced by HP or people with communication disorders or their significant others
3 factors that influence quality of evidence from surveys:
Honesty: Are the subjects giving honest answers?
Ambiguity: Questions may be subject to multiple interpretations
Biased wording: Way a question is asked has major effect on how it’s answered
Scientific research studies/methods
Systematically collected observations by people trained to do scientific research
Obtaining publicly verifiable data
Is scientific research valid for HP?
Best available support for HP
Consider the 8 characteristics
3 characteristics of scientific method that improves quality:
Replication/repeatability:
Publicly verifiable data
Used to minimize wishful thinking
Data obtained by optimal conditions where others can make similar research and get similar results
More replicable, more reliable
Control:
Using special procedures to reduce error in observations and interpretation of research findings
Ways of reducing bias and minimizing extraneous factors
Precision in language:
Precise and consistent terminology used to reduce confusion and ambiguity
Concepts redefined to be observable and measurable, not abstract
8 considerations with scientific research (issues)
- Quality
- Singularity
Single studies presented out of context of other studies often provide misleading information/conclusion - Prove rather than support
Studies never prove a conclusion, only confirms
Scientists make interpretations of findings and those interpretations are NOT truths - Bias
- Distorting conclusions
Usually when evidence is presented by someone else (media) - Out-dated
- Artificiality
Makes it difficult to generalize - COI
Publish or perish
Issues with rejecting scientific evidence too early
Impossible certainty fallacy:
Assuming research study should be rejected if not absolutely certain (searching for perfect solutions fallacy)
Certain is usually impossible, some uncertainty is to be expected
3 factors for generalizing research study
- Number of sample
- Breadth (diversity) of sample
- Randomness of sample
When can you trust expert opinions?
- You have avoided system 1 thinking
- Expert opinions supported by evidence
- No COI
- Includes qualifying statements
- Not universal and recognizes limits of applications
- Studies of many experts overtime
- Holds up to scrutiny of other experts
- Sought out sources that discuss in-depth analysis of research claims
- Sufficient quality of evidence
Analogies
Comparison between 2 things, typically for purpose of explanation/clarification
Factors to consider:
In how many ways are the two things similar/different?
Are they actually similar?
Are analogies useful in HP?
Understanding and explaining complex information in simpler language for patients and clients
Breaking through mental block impeding understanding
Analogy studies consists of research that includes participants that are similar but not identical to target population
Uncertainty
Low tolerance of uncertainty:
Professional anxiety
More diagnostic errors
Less searching for errors
Ignoring conflicting information (resolves via wishful thinking)
High tolerance of uncertainty:
Better cooperation with other specialists
Better management of uncertainty especially when backed by clinical experience