1. Uncertainty and Framing in Medical Decision Making
KD Valentine, Victoria Shaffer, Laura Scherer, & Brian Zikmund-Fisher

2. Imagine the following is true: You recently went to the doctor as you have noticed that you have shortness of breath, frequently feel tired, and have been bruising very easily lately. Your doctor ordered a blood test and the results have come back. Your doctor informs you that you have Myelodysplastic Syndrome, or MDS. MDS is a syndrome that does not allow blood cells in your bone marrow to mature and become healthy cells. Because of this syndrome your body does not have enough red blood cells which is why you have been feeling tired. Your doctor tells you that you have two options: Receive a bone marrow transplant and maybe live the rest of your days, or do not receive the bone marrow transplant and only live 10 more years.
Scenario
Interesting because it is a real syndrome (Brian) with a real decision to be made that’s preference sensitive.

3. Correct decision vs. Good decision
What is a good decision?
Not really correct or incorrect decisions here, more nuanced. While you may be terrified of tx and say 10 yrs is good enough, I may say go for it.

4. Good outcome vs. Good decision
What is a good decision?
Talk about how when Brian talks about his experience with MDS people tell him he made a good decision and he says he had a good outcome

5. Decision Process Consistency of Preferences
What is a good decision?
The process should hopefully not be aversive if we can help it, while also being informative.
Discuss how preferences are thought to be somewhat stable. Here we will talk about preference for or against tx. If framing has no effect, we should find the same choices regardless of the frame it is presented in. switching from tx to no tx or visaversa would be considered
Can depend on the information given:
How do you hear about these options?

6. How is this survival information presented?
Physician tells patient information verbally
Decision aids
No DA for MDS so far
Left with physician giving info
And we know some pretty basic things can easily change the way we perceive this info such as the way the information is presented to us, as well as the uncertainty we are dealing with in the decision

7. Framing Effect s Valence Positive valence Negative valence
Of those who choose the transplant 70% will be cured for life
Negative valence
Of those who choose the transplant 30% will die within six months of the surgery
Framing Effect s

8. Valence Effects Choice differences Attitude differences
More likely to choose an option when framed in positive (survival) terms than is negative (loss) terms.
Attitude differences
Have more positive attitudes (e.g. more benefit and less risk) toward positive framing than negative framing.
Valence Effects
T&K = risky choice framing (# survive vs. # die)
Peters was all between
Tversky & Kahneman, 1981; Levin, Schneider, & Gaeth, 1998; Peters, Hart, & Fraenkel, 2011

9. Framing Effects Information Percentage information
Of those who choose the transplant 70% will be cured for life
Frequency information
Of those who choose the transplant 70 out of 100 will be cured for life
Framing Effects

10. Fagerlin, Zikmund-Fisher, & Ubel, 2011; Peters, Hart, & Fraenkel, 2011
Differences in Understanding
Overall information presented as a frequency creates equal or better understanding than percentage information.
Attitude differences
Some rate events as less risky when viewing percentages than they do when considering frequencies.
Information Effect s
Risk was done with numeracy. Those with lower num = less risky ratings (peters et al)
Pete’s note that we’re just discussing information that is given to us and that risk information is perceived differently if it must be learned?
Fagerlin, Zikmund-Fisher, & Ubel, 2011; Peters, Hart, & Fraenkel, 2011

11. Fully Crossed Framing Effects
Valence
Positive
Negative
Information
Percentage
Of those who choose the transplant, 70% will be cured for life.  
Of those who choose the transplant, 30% will die within six months of the surgery.  
Frequency
Of those who choose the transplant 70 out of 100 will be cured for life.
Of those who choose the transplant 30 out of 100 will die within six months of the surgery. 

12. Uncertainty Uncertainty Probability Ambiguity Complexity
Multiple systematic accounts, analyses, and taxonomies concerning uncertainty in medical decision making.
Han et al.’s is quite simple to understand and work with, and has features similar to many out there.
Lipshitz & Strauss, 1997; Babrow, Kasch, & Ford, 1998; Han, Klein, & Arora, 2011

13. Uncertainty Uncertainty Probability Ambiguity Complexity
Of those who choose the transplant, 70% will be cured for life.  
Lipshitz & Strauss, 1997; Babrow, Kasch, & Ford, 1998; Han, Klein, & Arora, 2011

14. Uncertainty Uncertainty Probability Ambiguity Complexity
Experts have studied this treatment but disagree about the specific benefits of the treatment. Of those who choose the transplant, about 70% will be cured for life.  However, you are unsure how this number applies to you.
Lipshitz & Strauss, 1997; Babrow, Kasch, & Ford, 1998; Han, Klein, & Arora, 2011

15. Uncertainty Uncertainty Probability Ambiguity Complexity
Of those who choose the transplant, 70% will be cured for life, given they have no symptoms of anemia, bleeding, or infection, have no abnormal changes in their chromosomes, and are at low risk of leukemia.
Lipshitz & Strauss, 1997; Babrow, Kasch, & Ford, 1998; Han, Klein, & Arora, 2011

16. Uncertainty + Frames = ?? Decisions
Judgment and decision making literature
Framing effects
“Good” decisions
Medical decision making literature
Uncertainty
Uncertainty + Frames = ?? Decisions
Bridging the Gap
Motivation for why we’re dong this. So from JDM we know framing effects, and JDM and MDM we know about decisions, and MDM knows about uncertainty, but what happens when we bring them all together?

17. How do frames and uncertainty interact?
How do different types of uncertainty effect choice and attitudes?
How does valence effect choice and attitudes?
How does information effect choice and attitudes?
Does the magnitude of a bias change under different types of uncertainty?
Are preferences sensitive to these frames and under different types of uncertainty?
How do frames and uncertainty interact?
Current research questions.

18. Present Study Participants Design
160 PSYC 1000 participants from Fall 2015
Design
3 (Group; between) X 2 (Valence; within) X 2 (Information; within)
Probability (N=55), Ambiguity (N=51), Complexity (N=54)
Present Study

19. Fully Crossed Framing Effects
Valence
Positive
Negative
Information
Percentage
Of those who choose the transplant, 70% will be cured for life.  
Of those who choose the transplant, 30% will die within six months of the surgery.  
Frequency
Of those who choose the transplant 70 out of 100 will be cured for life.
Of those who choose the transplant 30 out of 100 will die within six months of the surgery. 

20. Demographics Age Mean (SD) 18.5 (.793) Range 17-22 Sex Female
Ethnicity
Caucasian
83.75% (N = 134)

21. 1) Group Differences
Be sure to include that the y-axis is their ratings (strongly disagree = 1 to strongly agree = 7)
Benefit tx: P > C > A 2 = .034
Benefit no tx: P < A , C 2 = .041
Risk of no tx: P > A, C 2 = .040
Scared: P, C > A 2 = .010

22. 2) Valence Differences
Be sure to include that the y-axis is their ratings (strongly disagree = 1 to strongly agree = 7)
More likely to choose tx in 2 = .140
More benefit of tx, in + 2 = .115
less benefit of no tx in + 2 = .050
Less risk of tx in 2 = .139
more risk of no tx in + 2 = .027
More confidence in + 2 = .073
Less scared in + 2 = .010

23. 3) Information Differences and Other Effects
No information effects were found
No interactions were found
All λs > 0.98
3) Information Differences and Other Effects

24. 4) Group Differences in Magnitude of Effects
Is it possible that there are differences in the magnitude of these framing effects on the likelihood to receive the treatment?
Absolute difference scores were created for each framing effect:
Valence Difference = |positive – negative|
Information Difference=|percentage – frequency|
4) Group Differences in Magnitude of Effects

25. Absolute Valence Differences
Make sure to say these are dot plots, each dot = 1 person’s response
F(2, 157) = 0.019, p = .982, 2 < .001

26. Absolute Information Differences
F(2, 157) = 3.236, p = .042, 2 = Probability had less variability (M = 0.318, SD = 0.324; d = ) than both Ambiguity (M = 0.529, SD = 0.560; d = ) and Complexity (M = 0.546, SD = 0.631; d =) groups.
Greater variability in magnitude of the effect in the A and C than in P

27. 5) Uncertainty Preference Differences
To see if individuals were changing their preferences for the test, the choice ratings were compared between framing effects.
5) Uncertainty Preference Differences
Participant
Positive Frame
Negative Frame
Overall A
Treatment
No treatment
Switch B
No Switch

28. Did anyone actually switch?
Valence:
67 (41.88%) switched
Information
36 (29.03%) switched
Did anyone actually switch?

29. Direction of the switch
Positive Valence
Frequency
No Tx Tx
Percentage 5 14 9
142
McNemar’s χ2 = 1.23, p = .27
Direction of the switch
Negative Valence
Frequency
No Tx Tx
Percentage 45 11 13 91
Switch from wanting the treatment in the row condition to not wanting the treatment in the column condition
McNemar’s χ2 = 0.04, p = .84

30. Direction of the switch
Percentage Information
Negative
No Tx Tx
Positive 9 47
104
McNemar’s χ2 = 45.02, < .001
Direction of the switch
Frequency Information
Negative
No Tx Tx
Positive 10 4 48 98
Switch from wanting the treatment in the row condition to not wanting the condition in the column condition
McNemar’s χ2 = 35.56, p < .001

31. Can we predict who will switch with valence?
Variables
Estimate SE
z value
Pr(>|z|)
(Intercept)
1.98
4.35
0.46
0.65
Age
-0.15
0.22
-0.70
0.49
Ambiguity Aversion
0.43
0.33
1.30
0.20
Group Ambiguity
0.88
0.42
2.10
0.04
Group Complexity
0.68
0.41
1.66
0.10
Mastery
-0.28
0.30
-0.96
0.34
MMS
-0.11
0.28
-0.41
Risk Taking
0.14
0.27
0.52
0.61
SNS
0.19
-0.55
0.59
For valence switching, we see only group as being a predicting factor. Those in the ambiguity and complexity groups were more
likely to switch than those in the probability condition

32. Can we predict who will switch with valence?
Variables
Estimate SE
z value
Pr(>|z|)
(Intercept)
1.98
4.35
0.46
0.65
Age
-0.15
0.22
-0.70
0.49
Ambiguity Aversion
0.43
0.33
1.30
0.20
Group Ambiguity
0.88
0.42
2.10
0.04
Group Complexity
0.68
0.41
1.66
0.10
Mastery
-0.28
0.30
-0.96
0.34
MMS
-0.11
0.28
-0.41
Risk Taking
0.14
0.27
0.52
0.61
SNS
0.19
-0.55
0.59
For valence switching, we see only group as being a predicting factor. Those in the ambiguity and complexity groups were more
likely to switch than those in the probability condition

33. Switching for valence by groups
69%
51%
54%
31%
49%
46%

34. Can we predict who will switch with information?
Variables
Estimate SE
z value
Pr(>|z|)
(Intercept)
0.85
5.28
0.16
0.87
Age
-0.25
0.26
-0.95
0.34
Ambiguity Aversion
0.13
0.40
0.32
0.75
Group Ambiguity
1.46
0.59
2.46
0.01
Group Complexity
1.75
0.57
3.05
0.00
Mastery
-0.32
0.36
-0.90
0.37
MMS
0.48
1.41
Risk Taking
0.24
0.45
SNS
-0.09
0.23
-0.40
0.69
For information switching, we also see only group as being a predicting factor. Those in the ambiguity and complexity groups were more likely to
switch than those in the probability condition

35. Can we predict who will switch with information?
Variables
Estimate SE
z value
Pr(>|z|)
(Intercept)
0.85
5.28
0.16
0.87
Age
-0.25
0.26
-0.95
0.34
Ambiguity Aversion
0.13
0.40
0.32
0.75
Group Ambiguity
1.46
0.59
2.46
0.01
Group Complexity
1.75
0.57
3.05
0.00
Mastery
-0.32
0.36
-0.90
0.37
MMS
0.48
1.41
Risk Taking
0.24
0.45
SNS
-0.09
0.23
-0.40
0.69
For information switching, we also see only group as being a predicting factor. Those in the ambiguity and complexity groups were more likely to
switch than those in the probability condition

36. Switching for information by groups
91%
75%
67% 9%
25%
33%

37. Framing effects can make a large difference in both choice of and attitudes toward treatments.
Additional layers of uncertainty may magnify some of these, and may encourage more preference switching in certain frames.
General Conclusions

38. Could emotions mediate the relationship between uncertainty and switching?
Can including both positive and negative information together vary these effects?
Does the presentation of these (e.g. positive listed first vs. second) alter these effects?
What about printed information?
Does presenting both positive and negative information in pictographs (altering presentation of graphic to highlight either survival or death) change anything?
Many “best practices” exist in shared decision aids because of these factors. Are these best practices being used in current aids?
Exploration of the Ottawa Hospital’s A to Z Inventory of Decision Aids
Future Plans

39. Many Thanks! Victoria Shaffer Laura Scherer Brian Zikmund-Fisher
The Medical Decision Research Lab
Many Thanks!

40. Questions?