Quiz 1 Flashcards
Scientific Method
- Observations
- Question
- Hypothesis
- Experiment
- Analysis
- Conclusion
Control Group
Ensures that you’re actually looking at the variable you’re supposed to during the experiment
Negative Control
a group in an experiment that does not receive any type of treatment and, therefore, should not show any change during the experiment.
Positive Control
a group in an experiment that receives a treatment with a known result, and therefore should show a particular change during the experiment
Experimental Research
a scientific methodology of understanding relationships between two or more variables - includes using independent and dependent variables to deduce a correlation
Observational Research
a research technique where you observe participants and phenomena in their most natural settings.
Survey research
- the collection of information from a sample of individuals through their responses to questions
- could be used in psychology research, public health
- problems include that people could lie and not provide accurate information
Case Study Research
- an in-depth, detailed examination of a particular case (or cases) within a real-world context.
- Could be used in medical research, or clinical research
How do you build the case that supports or refutes two
opposing “hypotheses”
-absence of evidence doesn’t mean evidence of absence and you can use past experiences, knowledge
-always have a way to prove what you know
Bandwagon Fallacy
-Asserts a claim is true because many people believe it is
- e.g., “everyone was speeding, so i SHOULDN’T GET A TICKET.”
-A tip to remember is that many people can be and have been wrong
- this is a failure in logic/reasoning
Occams Razor
-Law of parsimony (simple)
-Law of economy
-heuristic meaning that this is considered a short cut
-usually the simplest explanation is the most likely and best solution/explanation
–can be used when looking at multiple explanations/competing hypotheses
-Not helpful sometimes in Biomedical sciences because it can be a short cut which is an issue since there’s complexity in many biological systems and the simplest explanation isn’t always right since it can exclude other pathways etc that could be contributing
Scientists often think
(& teach & learn) very
narrowly without
reference to the bigger
context (society)
-It’s important to recognize your own biases and reflect on them
-if you can’t do this as a scientist. then it can have consequences on your science (e.g., cause sexism or racism in the results that you conclude)
Methods
-details of exactly how we will collect data
Methodology
-How we should best collect data
Epistemology
-How we should investigate the world
-the theory of knowledge, especially with regard to its methods, validity, and scope.
- What is knowledge? And who
gets to decide?
How do you know what you
know? And why? - concerned with the nature of knowledge and different methods of gaining knowledge
- what do you know and how do you know it
Ontology
- how we view the world
- concerned with what is true or real, and the nature of reality
- What is existence and what is the nature of existence
Axiology
-Philosophical study of value
-it’s what we value; it’s also what is the ultimate worth of research
-It includes questions about the
nature and classification
of values and about what
kinds of things have value.
- What s good/right?
Teleology
- What is the goal?
Some steps to consider
- Formulate your question – know what you
are looking for - Gather your information (‘infodemic” - it’s
not a lack of information that is often the issue – it’s too much low quality information) - Apply the information (what am I assuming? Is it logical?)
- Consider the implications (slow down and think things through)
- Explore other points of view (take your time – weigh strengths & weaknesses)
- Consider the information and ask - what am I assuming?
What are my biases? Can I calibrate for them? Is my
analysis logical?
*Explore other points of view (take your time – weigh
strengths & weaknesses;. Be
prepared to change your mind on the weight of new evidence
or perspectives. It’s OK!
CARS-type Q
In biomedical research, the
pursuit of knowledge about diseases and their treatments is accompanied by ethical considerations and the need to define the boundaries of what is knowable.
Scientists often navigate the intersection of epistemology, axiology, and ontology when
conducting research on complex medical issues.
The ethical implications of research
Researchers must consider not only what can be known but also the ethical boundaries and values associated with their research.
Dual Process Theory of Cognition
-Suggests that there are two systems of thinking
-System 1 = intuitive, fast, almost unconscious thinking; engaging your amygdala
-System 2 = slower, analytical, effortful thinking; engaging the rest of your brain
Clinical decision making
-Involves two stages:
1. An early stage that involves generating one or more diagnostic hypotheses
2. A subsequent verification stage where the hypotheses are tested and the final diagnosis are confirmed
Reasoning vs Rationalizing
- Reasoning = Following evidence to a logical conclusion
(Body of evidence -> reasoning & logic -> conclusion) - Rationalizing = Selecting evidence to justify a conclusion
(Desired conclusion -> motivation reasoning & confirmation bias -> cherry picked & low quality evidence)
Critical Thinking
Critical = Conducting an analysis of the pros and faults of a piece of work
- Don’t think in terms of good or bad
-Think interns of more or less rigorous and more or less calibrated
- critical doesn’t equal negative
-critical = analytical
- analytical doesn’t equal unemotional
the formation of our unconscious biases
- The amygdala, the prefrontal cortex, the posterior cingulate and the
anterior temporal cortex are involved in the origin, development,
processing and application of biases. - Evolution has selected for
neurological wiring that
allows bias
-Effective critical thinking involves
using different parts of the brain
(know which parts are particularly important)
Orbitofrontal Cortex
-Decision making and emotional processing
- instead of proceeding to the thalamus like other sensory systems, scent signals first travel to brain regions that process emotions and memory
Frontal lobe
- problem solving
-emotional traits
-Reasoning (judgement)
-speaking
-voluntary motor activity
Parietal lobe
-knowing right from left
-sensation
-reading
-body orientation
Occipital Lobe
-Vision
-Color perception
Temporal lobe
-understanding language
-behavior
-memory
-hearing
Brain stem
-breathing
-body temperature
-digestion
-Alertness/sleep
-swallowing
Cerebellum
-Balance
-coordination and control of voluntary movement
-fine muscle control
Reflexivity vs Reflective
-Reflexivity is the ability to reflect on
your own assumptions, values, biases
& perspectives & how they influence
your research process and outcomes.
Reflexivity helps you to acknowledge & address your positionality, power
relations, ethical issues, & limitations in your research or thinking - Recognize your bias, calibrate
accordingly
-Reflective thinking turns experience into insight - most of your time spent in science will be reflecting on thinking about what people said, what you’ve read etc
Assumptions
-a belief or statement taken for granted without verification
-It is a starting point for reasoning or decision making, often based on incomplete information
-Assumptions can simplify complex situations but may also lead to inaccuracies if not validated
Example of Assumptions
-False Consensus bias = People often overestimate the extent to which their beliefs, values or opinions are shared by others; naive realism
-Gender bias = Individuals may make assumptions about someone’s abilities based solely on their gender, often favouring one gender over another
Availability Heuristic
The short cuts we take to come to a conclusion; we see lots of it around so it must be true
Representative Heuristic
a mental shortcut that we use when making judgments about probability.
Engrams
-The form that memory takes; set of neutrons that are linked and the network of neurons
- The more you return to that information, the stronger they get
- located around cortex
Ladder of inference
-A set of useful tools that can be helpful with learning how to recalibrate your thinking, avoiding jumping to conclusions and making decisions based on reality
-happens unconsciously and quickly
7 steps:
1. Available data (This is the reality that we are able to observe)
- Selected data (We select what we pay attention to based on our prior experiences and existing beliefs - we don’t have the mental capacity to take in every piece of data available, so we have to make this selection)
Question = What did I ignore or didn’t pay attention to? Are there other sources of data I didn’t consider? - Interpretations (we give facts meaning - we paraphrase what we see or hear to make sense of it)
Question = Am I looking at the data objectively? What other meanings could they have? - Assumptions (Based on our interpretation, we make our own personal assumptions)
Question = Are my assumptions valid? Why am I assuming this? - Conclusions (We draw conclusions from our analysis/data we derived)
Question = Why did I conclude this> What are my assumptions there? - Beliefs (Our beliefs are then developed from the conclusions we make; modify)
Question = What beliefs do I hold about this? What conclusions are they based on? - Actions (Finally, we take actions that are rooted in what we believe
Question = Why do I believe this to be the right action? What are some alternative options?
Ladder of Inference Example
You are a medical student working as part of a healthcare
team in a busy hospital. One day, you are assigned to a
patient with a complex medical history and multiple
symptoms. The patient, Mr. Smith, is in his 60s and has
been admitted with complaints of chest pain, shortness of
breath, and fatigue. He also has a history of high blood
pressure and diabetes. Blood pressure measurements, an
ECG, & blood tests are conducted showing abnormalities.
Observable Data (Rung 1):
1.Mr. Smith’s vital signs, including
elevated blood pressure and heart rate.
2.Results from an electrocardiogram
(ECG) showing abnormalities.
3.Lab results indicating elevated
cholesterol levels.
4.Mr. Smith’s medical history, including
hypertension and diabetes.
5.The patient’s description of chest pain
and shortness of breath.
Selecting Data (Rung 2):
You and your team focus on the
elevated blood pressure, abnormal
ECG, and high cholesterol levels as
the most relevant pieces of
information
Adding Meaning (Rung 3):
You interpret these findings as
potential signs of a heart problem,
possibly a myocardial infarction
(heart attack), given Mr. Smith’s risk
factors.
Making Assumptions (Rung 4):
Based on your interpretation, you
assume that Mr. Smith’s symptoms
and test results are indicative of a
cardiac issue, and you may suspect a
blocked coronary artery.
Drawing Conclusions (Rung 5):
You conclude that Mr. Smith is likely
experiencing a heart attack and
needs immediate intervention, such
as cardiac catheterization and
possible stent placement.
Developing Beliefs (Rung 6):
Your opinion is that cardiac issues
are the primary concern for Mr.
Smith, and the focus should be on
addressing this aspect of his health.
Taking Actions (Rung 7):
You communicate your conclusion
and belief to the attending physician,
recommending cardiac interventions
and immediate action - However, the attending physician
asks you to reconsider your
conclusion and take a step back.
After reviewing additional information
and running more tests, it becomes
clear that Mr. Smith’s symptoms are
due to a severe respiratory infection,
not a heart attack. The initial
assumption and conclusion based
solely on the observable data led to
an incorrect diagnosis.
-review what you know, able to recognize to know what you don’t know, able to find resources to close the gaps in your knowledge
-
Weighing Information/evidence from sources
Placing Trust Into where the information is from affects how much we weigh that info
Hierarchy of Scientific Evidence
weakest to strongest:
1. Case reports, opinion papers and letters
2. animal trials and in vitro studies
3. cross sectional studies
4. case control studies
5. cohort studies
6. randomized controlled trials (gold standard but doesn’t mean that all are done well)
7. meta analyses and systematic reviews
What factors do you consider in weighing up evidence?
- Who’s making the claim?
-> do you trust this source?
-Who is the cohort?
-> Was the study done on a diverse group?
-> who/what was the study done on?
-Citations
-> potential issues
-> biased (e.g., self-citation)
-Experimental design
-> appropriate controls?
->reproducibility?
-> proper technique?
-> routine methodology or new technique?
-How old the source is
-> newer or older could weigh more depending on the topic
-How well written is the article?
-> What journal is the article published in?
-> diff journals have diff criteria/standards
-> some may be more or less strict with the material allowed to be submitted
-Who’s involved with the journal
-> in house review or global review?
-> Who funds the journal?
-Journal impact factor
-> proxy metric for journal quality; measure created by university librarians (SUPPOSED TO TELL US how good the quality of journal is by checking to see how many times the journal has been taken out but this method may not actually reflect quality)
Critical Thinking, Logic and Reasoning
-Logical thinking = the ability to put together arguments so they
make sense and stand up to critical analyses by others skilled in critical thinking.
- Skills needed – Analytical, communication,
open-minded, self-awareness, broad thinking
- Critical thinking is the ability to judge arguments (weigh evidence, determine if the arguments, explanations, etc are logical. Critical thinking is the analysis (analytical approach) to testing arguments or explanations - put forward by you or others - to determine rigour, check for sound reasoning (deductive/inductive), identify flaws & weaknesses and make reasonable conclusions.
Inductive Reasoning
-used to formulate hypothesis and theories (logic & reason)
-involves moving from specific instances or observations to broader generalizations (e.g., the sun has risen every morning throughout history; therefore the sun will rise tomorrow.)
Deductive Reasoning
- used when applying them to specific situations (analysis of evidence & argument).
-the information is already available,you just have to work out the conclusion…(weigh the evidence).
Evaluating Evidence
- The evidence must be sufficient to establish the accuracy of a claim
–> the person making the claim bears the burden of proof
-> extraordinary claims require extraordinary evidence
-> claims based on authority are never sufficient
-> anecdotes are never sufficient - The evident must be relevant to the claim (irrelevant evidence can sound persuasive but needs to be relevant)
-> can include logical fallacies such as
-> appeals to emotion (strong emotions can be very convincing but it’s not evidence)
-> ad hominem attacks (shifts the focus away from the evidence and towards the person making the claim - your feelings towards the person is irrelevant to the accuracy of the claim)
-> appeal to the masses (suggests that since everyone believes something, it must be true) or appeal to tradition (a claim must be true since people have believed it for a long time)
-> red herring (when someone shifts the focus away from the topic being discussed) - the evidence must be comprehensive (does it build toward the claim?)
-> you need to look at all of the pieces of evidence, not cherry pick pieces, otherwise you could miss the bigger picture - The evidence must be reliable
-> How was the information gathered?
What is an Argument in terms of science?
-is an argument (building the case on the basis of evidence, logic, reasoning, weight of evidence) well-reasoned?
-Scientific arguments are logical descriptions of a scientific idea and the evidence for or against it
-think like a lawyer is the argument for or against the evidence/accept or refute the evidence)
- Sometimes a scientific idea precedes any evidence relevant to it, and other times the evidence helps inspire the idea
Infodemic
-An infodemic is too much information including false or misleading information in digital and physical environments during a disease outbreak
-It causes confusion and risk-taking behaviours that can harm health
It also leads to mistrust in health authorities and undermines the public health response
-An infodemic can intensify or lengthen outbreaks when people are unsure about what they need to do to protect their health and the health of people around them
-With growing digitization - an expansion of social media and internet use - information can spread more rapidly
-This can help to more quickly fill information voids but can also amplify harmful messages
Infodemic Management
-The systematic use of risk and evidence-based analysis and approaches to manage the infodemic and reduce its impact on health behaviours during health emergencies
-Infodemic management aims to enable good health practices through 4 types of activities:
1. Listening to community concerns and questions
2. Promoting understanding of risk and health expert advice
3. Building resilience to misinformation
4. Engaging and empowering communities to take positive action
The top conspiracy theories are often very difficult to dislodge. In part, that’s because they fulfill a psychological need
-That may be the social need to feel good about the group they belong to, the need to know the truth and have certainty, or the
existential need to feel safe or feel a sense of control over what happens to us
-And hardcore believers are adept at rationalizing away evidence that contradicts their beliefs.
-Eyewitnesses who dispute the conclusions of even the biggest conspiracy theories are mistaken, according to believers — or part
of the conspiracy.
Research tells us that people are drawn to conspiracy theories due to 3 key psychological motives
1.Epistemic motives: These stem from the desire for knowledge, certainty, and truth. When people feel uncertain, particularly in the face of major events, they seek explanations. Those with lower education levels may lack tools to assess credible sources and thus turn to conspiracy theories for answers.
- Existential motives: These refer to the need for safety, security, and control. When
people feel powerless or out of control, conspiracy theories provide a sense of
understanding or explain why they lack control, helping them cope with feelings of
disillusionment. - Social motives: These relate to the desire to feel good about oneself and one’s group.
Believing in conspiracy theories can give individuals a sense of superiority or uniqueness, as they feel they possess information others don’t. At the group level, conspiracy theories can reinforce group identity, portraying one’s group as good while others are seen as evil.
-These motives—epistemic, existential, and social—form the core psychological drivers
behind conspiracy theory beliefs.
science is about the general
relationships that we can deduce from facts.
-Biomedical science is not a collection of isolated facts.
-We were all forced to commit fragments of
knowledge to memory and to regurgitate it
all on our final exams.
-Most scientists come to realize that science is not about facts;
Need to apply critical thinking to biomedical science reported in literature
Definitions of deductive reasoning and inductive reasoning are similar but not the
same
-Deductive reasoning – proceeds from one
or more general axioms (premises) and
comes to a certain, specific conclusion
using logic
-Inductive (ampliative) reasoning –
extends what we know to new
areas (may require analogies and generalizations)
Inductive Reasoning vs Deductive Reasoning
- Scientists may use:
inductive reasoning to
formulate hypothesis and theories
(logic & reason) from observations & data
& use deductive reasoning when applying
them to specific situations (analysis of
evidence & argument). Requires premises
that must be true
- Scientists may use:
inductive reasoning to formulate (build) hypotheses, theories, arguments, case (logic & reason)
and use deductive reasoning when to analyse specific situations, arguments, evidence, etc. (logic & reason)
-Scientists may use:
inductive reasoning (“bottom-up”)
and use deductive reasoning
(“top down”)’
But often they use
Abductive reasoning – best educated
guess, building upon observed
phenomena and previous studies.”
-Scientists use:
inductive reasoning to formulate (build)
hypotheses, theories, arguments, case
(logic & reason)
and use deductive reasoning when to
analyse specific situations, arguments,
evidence, etc
*But what is an argument?
Argument
A reason or set of responses given with the aim of persuading others that an action or idea is right or wrong
-You are practicing doing this in the tutorials, in your assignments, etc. building the case, setting up the reasons, providing the evidence for a particular position or opinion, weighing the evidence, providing the reasons, persuading others, etc……. Being analytical while being self-aware
What is an argument in terms of science?
Is an argument well-reasoned?
- Scientific arguments are logical descriptions of a scientific idea and the evidence for or against it.
-Sometimes a scientific idea precedes any evidence relevant to it, and other times the evidence helps inspire the idea.
The Logic Of scientific arguments
-Taken together, the expectations generated by a scientific idea and the actual observations relevant to those expectations form what we’ll call a scientific argument
-This is a bit like an argument in a court case - a logical description of what we think and why we think it
- A scientific argument uses evidence (we need to be able to weigh the evidence) to make a case for whether a scientific idea is accurate or inaccurate
-For example, the idea that illness in new mothers can be caused by doctors’ dirty hands generates the expectation that illness rates should go down when doctors are required to wash their hand before attending births - when this test was actually performed in the 1800s, the results matched the expectations, forming a strong scientific argument in support of the idea, and hand washing
- you can make predictions based on observations/evidence and people can end up not accepting it even if it’s right
scientific idea + expectations + observations = scientific argument
- these elements are always related in the same logical way, but in the process of science these elements may be assembled in different orders
-sometimes the idea comes first and then scientists go looking for the observations that bear on it
-sometimes the idea and the observations are already out there, and someone comes along later and figures out that the two might be related to one another
Scientific Argument
- you need to be able to distinguishh between correction and causation because if it is mixed up, it weakens your argument
-A logical description of a scientific idea and the evidence for or against it
-In everyday language, an argument usually means a verbal disagreement but here we use another meaning of the term: a reasoned case for or against a particular viewpoint - scientific arguments generally have a few basic components: What is the idea? If this idea were true, what would we expect to observe in a given situation? Is this expectation borne out? How does that reflect on the likelihood that the idea is accurate or inaccurate?
Is an argument well-reasoned?
- A critical thinker will be able to deconstruct the argument, look at the evidence (convincing, compelling,
weak?), the premises, determine the strength of the basis that the argument built on, look at the reasoning is
being used, and ask is it valid, is it logical?
-you become self-aware on how you use information and evidence to make decisions even in simple decisions
- being able to see the thinking in your head and being aware as it happens
- advanced thinking = making a hypothesis and holding a scientific argument when conducting experiments and making predictions instead of just saying “I’m going to do an experiment and see what happens.”
Premises
-building blocks of previous work to support an argument
What part of a scientific paper constitutes “the argument” section?
Discussion
- abstract might briefly in discussion as well;
Logic & Reasoning & Critical
Thinking
- Logical thinking is putting together arguments so they make sense
(e.g. you are writing a paper in the biomedical sciences) - Logical thinking often used as a way to undermine people
- Critical thinking is the ability to judge those arguments to determine
rigour, sound thinking, reasoning, flaws, weaknesses and make reasonable conclusions (e.g. you critiquing something written or spoken about an issue in biomedical sciences).
–> Assessing the arguments and being analytical but not ignoring your emotions - How are the authors using the data in support of their conclusions?
Skills needed – self-awareness, analytical, communication, etc. (be a
lawyer)
Where should you start when analyzing scientific papers?
- abstract since it gives a short summary of the paper and states how the results support the paper, then look at the discussion and then see if the results support the claims
A better way to argue
- Everyday arguments
–> based on opinions, biases, feelings, emotions
–> illogical - commits fallacies
–> conflict is disrespectful and pesonal
–> used to “win” and be “right” - Critical thinking arguments
–> claim is supported by evidence
–> logical - based on reason (is there sound logic?)
–> Disagreements are respectful, not personal (you are aware of bias/be a lawyer and hold emotions consciously)
–> collaborative, to find greater understanding (science allows us to move towards ever decreasing uncertainty) - knowing how to form good arguments helps us to think better, and prevents us from falling for bad arguments
The slippery slope fallacy
- Should you five Dan some gum?
- slippery slope fallacy = once one event occurs, other events will follow until you reach unwanted consequence (a chain of events)
Key questions:
- Is the claimed affect that bad? (the bottom of the slope)
- are the claimed affects likely to follow? (how slippery is the slope really?)
- Do the costs outweigh the benefits? (are there other releveant facts to consider)
Hasty Generalization:
- This is a conclusion based on insufficient or biased evidence. In other words,
you are rushing to a conclusion before you have all the relevant facts
Example: Even though it’s only the first day, I can tell this is going to be a boring course.
In this example, the author is basing her evaluation of the entire course on only the first day, which is notoriously boring and full of housekeeping tasks for most courses. To make a fair and reasonable evaluation the author must attend not one but several classes, and possibly even examine the textbook, talk to the professor, or talk to others who have previously finished the course in order to
have sufficient evidence on which to base a conclusion
In biomedical sciences context
– a hasty generalization might result from conclusions derived from very small sample sizes or few
experiments. - The slippery slope fallacy – e.g. I don’t need to run a control for just this one experiment, set of experiments, subset of my thesis research/proposal, all of my dissertation, the whole research program. We never run controls in the lab
Valid versus invalid arguments as used in Logic and Philosophy (but possibly not science)
Be aware that there are various meanings of valid and invalid. Be aware that constructing and dissecting arguments
is highly developed aspect of disciplines such as math and is routinely used in professions such as law and politics. What are the implications here for biomedical sciences?
Fallacies to Know
Ad hominem
anecdotal
appeal to authority
appeal to emotions
appeal to nature
appeal to tradition
argument from ignorance
bandwagon
burden of proof
false cause
false equivalence
hasty generalizations
I’m entitled to my opinion
red herring
single cause
slippery slope
straw man
Thinking is Power video
-people with low education more drawn in with conspiracy theories
-should not be persuaded by someone overconfident (still use critical thinking to analyze what people say)
- your identity is separate from your argument
-step 2: are the premises true/accurate?
–> argument
