Conceptual Model Training...Savings/ credit Condition of old car Commuting New baby Buy car Income...
Transcript of Conceptual Model Training...Savings/ credit Condition of old car Commuting New baby Buy car Income...
Conceptual Model Training
“Buying a car” example
Facilitation Questions to Create
Conceptual Model
1. What are some important reasons someone
might buy a car?
2. What are some important reasons someone
might NOT buy a car?
3. What else influences whether or not someone
will buy a car?
4. Why might someone choose to buy a car?
5. Who might be in the market to buy a new car?
Savings/ credit
Condition of old car
Commuting
New baby Buy car
Income
Age
Urban/suburban/ rural
Garden
Sample Conceptual Model
Discussion Questions
1. What do you think makes this model useful?
2. If you were selling cars, how would this
model affect who you will try to sell a car to?
How about where you build a car
dealership?
3. If you were selling cars, would this model
help you? Why?
4. If you were buying a car, would this model
help you? Why or why not?
“Flu Vaccination”
example
Facilitation Questions to Create
Conceptual Model
1. What influences whether or not someone
will get a flu vaccine? Why might someone
choose to get a vaccine or not?
a. What influences these factors?
2. How are all these factors related to each
other? What relationships exist between
these factors?
Decision to
get a flu
vaccine (or
not get it)
Cost
Belief of vaccine’s
effectiveness
Belief about severity of flu
Belief that getting
vaccine is painful
Availability of vaccine
(shortages)
Convenience
(time/location)
Belief that vaccine causes
flu/other issues
Prior experience getting/not
getting flu vaccine
Friends/family get/don’t
get flu vaccine
Exposure to education/
awareness campaigns
Doctor
recommends it
Have PCP/See a
doctor
Health Insurance
Income
Geographic
location (Rural/Urban)
Cultural Norms
Sample Conceptual Model
Discussion Questions
1. What do you think makes this model useful?
2. If you were a public health official trying to
encourage more people to get the flu
vaccine, would this model help you? How
so?
Facilitated Activity #1
Building Conceptual Models
Introduction
• Purpose of activity
• Ground rules
• Meeting logistics
Part I: Identifying factors affecting
[the health outcome]
Step 1: Brainstorm
– On your own, list 5-10 factors that
contribute to or worsen [health outcome]
(Part 1 of worksheet)
Domains/Categories
1. Health
2. Social
3. Behavior
4. Environment
5. Health care
Step 2: Domains and factors
Organize your list into these domains using worksheet
6. Family/community
7. Demographic
8. Attitudes/beliefs
9. Genetic
Part I: Identifying factors affecting
[the health outcome]
Step 3: Adding factors
• We will choose additional factors from
each domain and add to Part 3 of
worksheet
Additional factors by Domain/Category
Health
• Physical health
• Mental health
• Dental health
• Stress/Trauma
• Weight
• Fitness
• Memory
• ADL/Self-care
• Pain
• Mobility
• Pregnancy
• Addictions
• IQ
• Sight/hearing ability
• Communication ability
Social
• Education
• Income/poverty
• Support from friends/family
• Sense of community
• Employment status
• Racism/discrimination
• Marital status
• Religion
• SNAP/income support
• Literacy
• Language(s) spoken
• Immigration status
• Culture/Religious Practices
• Social outcast
Additional factors by Domain/Category
Behavior
• Exercise
• Smoking
• Drinking alcohol
• Taking drugs
• Sexual behavior
• Sleep
• Use of health care services
• Risk taking
• Leisure time/activities/
• hobbies
• Sources of information
• Getting information
• Internet/media usage
• Social skills
Environment
• Occupational health/work
conditions
• Industry
• Access to food
• Food quality
• Housing quality
• Transportation
• Weather
• Violence
• Green space/Parks
• Good schools
• Climate change
Additional factors by Domain/Category
Health care
• Insurance status
• Affordability of health care
• Availability of health care
• Quality of care
• Regular doctor
• Availability of medications
• Follow up care
• Coordination of care
• Alternative Health care
• Health education
Family/community
• Family type
• Family size
• Community involvement
• Social values
• Social policies
• Social programs
• Laws
Additional factors by Domain/Category
Demographic
• Male/Female
• Race/ethnicity
• Urban/rural
• Age
• Place
Attitudes/beliefs
• Health related beliefs
• Sense of control
• Hope
• Hostility/anger
Genetics
• Inherited conditions
• Risk factors
Part I: Identifying factors affecting
[the health outcome]
Step 4: Fill in domain charts
• We will take turns reading out factors from Part 3 of the worksheet
• Provide your reasoning/example
• Discussion
• Group decision about keeping factor
• Write on sticky note and place on Domain flipchart
**Only factors that are discussed during this step will be included in the path diagram!!**
Part II: Modeling [the health
outcome]
• Introduction: Recap of last meeting of
Conceptual model training and “buying a
car” example
Savings/ credit
Condition of old car
Commuting
New baby Buy car
Income
Age
Urban/suburban/ rural
Garden
Sample Conceptual Model
Part II: Modeling [the health
outcome]• Step 1: Take turns selecting factors
– Place [health outcome] on far right
– One person selects a factor to add to the model• Where does it belong on model?
• Does the factor go all the way on the left, or does something else affect it?
• Does the factor go all the way on the right, or does it affect something else?
• Does this factor affect something else?
• Group discussion
– Next person selects a factors to add to the model– Continue until all factors have been moved from
‘Domain’ flip charts to model
Part II: Modeling [the health
outcome]
• Step 2: Building the paths
– We will decide on how all the factors fit
together in the model
– Start with left most factor:
• What factor does this directly affect?
– Place arrows between factors on model
– Continue until all factors have connecting
arrows
Part II: Modeling [the health
outcome]
• Step 3: Reviewing the path diagram
– Does anything look like it doesn’t belong?
– Have all arrows been added? (Look at each
factor)
– Group reviews models and makes additions
and changes
Facilitated Activity #2
Developing Research Questions
Introduction
• Recap of last meeting: Building conceptual
models
• Today’s agenda
Part I: Review of models
• Topic Group reviews their own conceptual
model, discusses, and makes
additions/changes
• Topic Group reviews models from other
groups and discusses
• Topic Group reviews Conceptual Model
Factor Summary sheet
[Insert Topic Group
conceptual model]
[Insert Topic Group
conceptual model]
[Insert Topic Group
conceptual model]
Conceptual Model Factor Summary
[Insert Summary of Conceptual model factors –unique and similar factors across all Topic Groups]
Part II: Training on Creating
Research Questions
**Use optional training powerpoint included
in materials**
Part III: Question development
• Go through each Question prompt and
write down 2-3 questions on Worksheet
Time to develop
your own research
questions!
Step 1 (Prompt #1): Causes
In order to improve [health topic], we need to better understand the relationship between ____ and ____
X Y
Example: “Are people more likely to buy a car after having a first child or after a third child?
Step 2 (Prompt #2): Impact
If we could change one of the factors in the model, would it likely have a strong effect (BIG IMPACT) on [health topic]?
X Y[health topic]
A
J
Example: “If we could help people have better credit scores, would that impact their ability to buy a car?”
Step 3 (Prompt #3): Patient-Centeredness
• What questions (if answered) would help patients with [health condition] make more informed decisions?
• If we could answer this questions, patients with [health condition] would have better information for choosing treatments or making other types of decisions
Example: “If we provided fuel efficiencies across cars, would that help people make better decisions about which car to buy?”
Step 4 (Prompt #4): Verification
• Are there relationships in the model that we need to know more about?
• Is there something that needs to be proven as fact?
• Do we need more evidence to show that a particular cause is important or that a promising treatment is effective?
Example: “Are people who just moved to a new neighborhood more likely to be shopping for a car compared to people who have lived in a neighborhood longer?”
Step 5 (Prompt #5): New Directions
• Looking at the models, what is a new way of thinking about [health topic]?
• Is there something important as a ‘cause’ or ‘solution’ that is missing or misunderstood in these models?
• Is there something in the models that we know very little about right now?
Example: “What are the factors impacting future sales of self-driving cars?”
Part III: Question development
• Step 6: Review all questions on worksheet
and highlight the ones you feel are most
important
Part IV: Listing questions
• Step 1: Listing Questions
– Each person to read one of their questions off
their list and provide explanation of why they
feel it’s important
– Continue through group as time allows
• Step 2: Wrap-up
– Plan for next meeting
Creating Research Questions
SEED Method Training
Step 1. Identify a focus area
We already have a research area:
All of the questions we create today will fit into this focus
area. Everyone here today was invited to participate
because they already have some experience in this area.
Lung Cancer Outcomes
Step 2. Identify a topic
Using conceptual models and highlighted factors to come up with potential topics.
• The other two groups also developed their conceptual models.
• We reviewed all of the factors and relationships in those models.
• Then, you had the opportunity to highlight the factors or relationships in those models that you think we need to know more about.
• That process helped us identify some potential topics within our focus area to ask questions about.
Step 3. Begin to ask questions about a topic
How we ask a question can lead to different types of answers and research
• It might lead to research that aims to explore a topic (to gain new insights we didn’t have before. )
• Or, it might aim to explain a topic, so that we understand it in more detail.
For example….
Let’s assume our research area was something like factors that affect whether someone gets a flu shot.
• Let’s say that some topics identified were
– Fear of negative side effects
– Perceptions of how effective the shot is at preventing the flu
Some questions are framed that lead to open-ended,
exploratory types of inquiry that focuses on how and why
things happen.
WHY: Why do people feel the flu shot is ineffective?
• Asking this type of question leads to exploring the
relationship between perceived effectiveness and action.
• If we ask this question in an open-ended way, we can listen
to the stories people tell, record the words that they use, and
try to understand the issue from their point of view.
Open ended, exploratory questions
Perceived effectiveness of flu shot
Getting a flu shot (ACTION)
WHAT: What are the negative side effects of the flu vaccine
that people fear?
• Asking this question also seeks exploratory information from
the point of view of respondents.
Open ended, exploratory questions
Some questions seek to narrow something down and
understand the specifics in greater detail. These questions
may come after we have explored a topic and want to know
more about it.
HOW: How does previous experience with the flu affect intention to get the flu vaccine next year?
• With How questions, we can look specifically at how two factors are related.
Open ended, exploratory questions
When we research these “how” questions, we may wish to find a specific relationship between factors. We refer to this as testing a hypothesis.
Hypothesis: People who have had the flu are more likely to want a flu shot in the future.
• Having a hypothesis like this allows us to make predictions and test them with data.
Hypothesis
When we talk about factors being related, that might mean that as one occurs, the other is also MORE LIKELY to occur.
Here are some examples:
– As it gets hotter, ice cream sales go up.
– As adults age, the likelihood of falling is greater.
– As driving speed goes up, the likelihood of fatal car crashes increases.
Other examples?
Related factors
On the other hand, when two factors are related it can
mean that as one occurs, the other is LESS LIKELY to occur.
• As seatbelt use goes up, the likelihood of fatal injuries
in car accidents goes down.
• The more cigarettes a person smokes in a day, the
lower the likelihood of healthy lung functioning.
• As the price of an item rises, the number of potential
customers decreases.
Other examples?
Related factors
We can ask people whether they had the flu and also ask them
about their intentions to get a flu shot.
• When we test a hypothesis using data, we may or may not
find that it is supported.
Testing a Hypothesis
If our hypothesis is supported, we may then wish to be able to
create a better prediction.
For example, when we analyze the data we may be able to say
something like:
People who had the flu this year are 3 times as likely to
say they intend to get a flu shot next year compared to
people who did not get the flu this year.
You may have noticed that a question like this one compares
two groups. Who are we comparing here?
Testing a Hypothesis
When, Where, and Who can help us create better questions
Before: What are the negative side effects of the flu vaccine that people fear?
After: What are the negative side effects of the flu vaccine that African American seniors in the East End fear before getting the flu shot?
Before: Why do people feel the flu shot is ineffective?
After: Prior to the 2015 flu season, why did uninsured young adults in Virginia feel the flu shot is ineffective?
Before: How does previous experience with the flu affect intention to get the flu vaccine next year?
After: Among adults age 18-64 in Virginia in 2015, how much more likely were those who had the flu the previous year to state that they intended to get the vaccine this year, compared to adults who did not have the flu last year?
When asking these questions, we consider:
• Who is the population of interest?
– Can they be defined by age, sex, race, place, condition, or some other characteristic?
• What is being compared?
– Two different interventions or treatments? Two populations? Two behaviors or social conditions?
• Is the outcome clearly defined?
Another set of framing of research questions includes
SHOULD?
That is, does the evidence support a specific set of
actions?
Step 4. Creating research questions
• Be specific when using terms.
For example, when a flu vaccine is mentioned, does that mean only injectable flu shots, or does it include nasal sprays?
• Avoid questions that are too narrow
-- Such as questions that require only a YES/NO answer or are answered with a simple fact.
• Avoid questions that are too broad – narrow down to something that can be answered in one study.
• Look at topics that are measurable and researchable.
Some questions are not researchable because we can’t observe and collect data on them.
For example, we can’t use research to answer a question like ‘Is vanilla ice cream better than chocolate ice cream?’
We can, however, answer a question such as, ‘Do more people buy vanilla ice cream or chocolate ice cream?’
Importance
There are an infinite number of research questions we
can ask. However, there is limited time and resources so
we must ultimately choose questions that are important.
Adds to current knowledge
Knowledge is always evolving and growing. We want to
answer NEW questions rather than questions that have
already been answered.
**Sometimes things that YOU know are not always things
people in the scientific world know – this is why we are
here! We are helping to grow the current knowledge by
including more perspectives!**
Research questions are ones that we can use evidence to support or
discredit!
Facilitated Activity #3
Prioritizing Research Questions
Introduction
• Recap from last meeting
• Plan for today’s meeting
Part I: Prioritization
• Step 1: Listing questions
– Review and discuss group’s research questions from last meeting
• Step 2: Multi-voting
– Vote on most important questions using ballots
Topic Group #1: Research Questions
[Insert Topic Group #1’s research questions from last meeting]
Topic Group #2: Research Questions
[Insert Topic Group #2’s research questions from last meeting]
Topic Group #3: Research Questions
[Insert Topic Group #3’s research questions from last meeting]
Part II: Making research questions
patient-centered
Population
• Who should be included as research
participants?
• Are there people you think should be a
part of a study? Not part of the study?
Meaningful Outcomes
• What outcomes would be most
meaningful/important/helpful to patients?
• What should researchers measure?
[Optional prompts]
Treatment
• What should we compare the treatment
to?
Timeframe
• What timeframe would be best for patients
to look at outcomes?
• What about follow-up?
Setting
• What settings should this research take
place in? Hospitals? Clinics? Community
Centers? Home?
Wrap-up
• Project conclusions
• Next steps