1. Explaining Contraceptive Risk to Patients
Sponsored by
Association of Reproductive Health Professionals
Planned Parenthood® Federation of America
This slide should be shown at each presentation.
FACULTY ANNOUNCEMENTS
[Note: Please follow ARHP guidelines for CME presentations by including all required information in your introduction. This information is in your teaching packet. As a faculty representative, you are requested to do the following:]
Announce program sponsors: Association of Reproductive Health Professionals (ARHP) and Planned Parenthood Federation of America (PPFA).
Announce unrestricted educational grant from Ortho Women’s Health and Urology.
Announce that the presentation may include information that is not on FDA-required product labels.
Disclose any financial relationship(s) you have with industry.
A component of You Decide: Making Informed Health Decisions about Hormonal Contraception
Supported by an independent educational grant from Ortho Women’s Health and Urology

2. Expert Medical Advisory Committee
James R. Allen, MD, MPH Medical Advisor American Social Health Association Washington, DC
Vanessa Cullins, MD, MPH, MBA (co-chair) Vice President for Medical Affairs Planned Parenthood Federation of America New York, NY
Linda Dominguez, RN-C, NP Assistant Medical Director Planned Parenthood of New Mexico Albuquerque, NM
Julie Downs, PhD Research Faculty Carnegie Mellon University Department of Social and Decision Sciences Pittsburgh, PA
Martin Fishbein, PhD Professor, Annenberg Public Policy Center University of Pennsylvania Philadelphia, PA
Kamini Geer, MD Fellow, Family Planning Montefiore Medical Center Department of Social and Family Medicine Bronx, NY
David Grimes, MD (co-chair) Vice President Biomedical Affairs Family Health International Durham, NC
Joel Shuster, PharmD, BCPP Professor of Clinical Pharmacy Temple University School of Pharmacy Clinical Pharmacy Consultant Episcopal Hospital Temple University School of Pharmacy Philadelphia, PA
Eshauna Smith, MPA Program Manager Pro-Choice Public Education Project (PEP) New York, NY
Scott Spear, MD Director of Clinical Services University Health Services Associate Professor of Pediatrics (CHS) University of Wisconsin-Madison Madison, WI
James Trussell, BPhil, PhD Director Office of Population Research Princeton University Princeton, NJ
Sandy Worthington, MSN, RNC, CNM Program Director Planned Parenthood Federation of America Philadelphia, PA

3. Learning Objectives
Define relative risk, attributable risk and absolute risk
List three different means of presenting risk and describe the advantages of each
Identify at least three patient characteristics to consider when counseling about risks and benefits
Describe at least one patient education tool that can be used to effectively communicate the risks and benefits of hormonal contraceptives
This slide should be shown at each presentation.

4. Case Study: Alyssa Smith
25 year old nonsmoker, 3 children
Satisfied user of DMPA for 3 years
Past contraceptive history
Patch caused nausea
Difficulty remembering to take oral contraceptives (OCs)
Not interested in IUD
Not interested in vaginal insertion methods
Talking Points
DMPA = depot medroxyprogesterone acetate (Depo-Provera)
Name changed but is an actual case

5. Case Study, Alyssa Smith (cont’d)
Primary care clinic stopped prescribing DMPA
Ms. Smith left without a plan for an effective contraceptive method
Early medication abortion
Physician said, “It’s bad for bones” but provided no specifics
Pregnancy within 3 months
Talking Points
Key point is that general information about risk doesn’t allow an individual to make an informed decision
Important to weigh risks of adverse events associated with contraceptive method with the risks associated with unintended pregnancy

6. Case Study (cont.)
Specific risks were explained and placed in context by another provider
Ms. Smith was comfortable with risks and benefits of DMPA
She decided to resume DMPA
Talking Points
When specific risks and benefits are reviewed and placed in context, a person can make a more informed decision.

7. Risk Misperception & the Provider
Talking Points
Misperception of risk by the provider may cause him or her to limit a woman’s contraceptive choice by denying access to a potentially useful drug or leading the patient toward a particular decision.
This is an article published in the Wall Street Journal in November 2005.
The article states that, “around the country, a number of individual practitioners and major health care providers say they don’t want to take any chances…[one obstetrician-gynecologist in Memphis] says he has stopped writing new patch prescriptions and suggests that his…patch users try other forms of prescription contraceptives.”
These prescribing decisions were based on data that showed an increase in estrogen with the patch—not on data regarding clinical outcomes, such as VTE.
Possible sources for accurate risk information:
Reputable, peer-reviewed journals (editorials can be very helpful)
Press releases or policy statements from professional groups, such as ARHP and PPFA
Reference:
Chaker AM. Doctors Back Off Birth-Control. The Wall Street Journal. Available at: Accessed May 03, 2006.
Chaker AM. Wall Street Journal November 22, 2005.

8. Risk Misperception & the Patient
“…incorrect perceptions of excess risk of contraceptive products may lead women to use them less than effectively or not at all.”
Gardner J, Miller L. J Womens Health 2005
Talking Points
Gardner and Miller assert that the following factors may lead women to use contraceptives less than effectively or not at all:
Problems with uneven access
Prescription requirements
Conflicting information on the package instructions for initiating and continuing use
Incorrect perceptions of excess risk
Reference:
Gardner J, Miller L. Promoting the safety and use of hormonal contraceptives. J Womens Health. 2005;14:53-60.

9. Misperception Affects Health Decisions: OC Discontinuation
In 1995, the British Committee on Safety of Medicines warned of possible increased risk of VTE among users of 3rd generation OCs
Many women stopped taking OCs
Prescribing patterns changed
Pregnancy and abortion numbers increased
Deemed a “non-epidemic”
Talking Points
VTE = venous thromboembolism
The negative consequences of an inaccurate perception of the risks associated with oral contraceptives played out in Europe to unfortunate effect.
In 1995, the British Committee on Safety of Medicines issued a warning regarding a possible increased risk of venous thromboembolism among users of 3rd generation oral contraceptives.
Many women across Europe stopped taking their OCs or switched formulations.
Providers changed prescribing patterns.
There were 26,000 more pregnancies in Wales and England in 1996 than in 1995, with about 13,600 additional abortions. [1]
The abortion rate had been decreasing over the 5 years before to the event. [2]
It is now believed that preferential prescribing may have been responsible for at least part of the association between 3rd generation OCs and VTE; in any case, the risk appears to be small. [3]
Even if the reported increase in risk is true, it is clinically insignificant. [4]
Deemed a “non-epidemic” by some experts. [4]
References:
[1] Furedi A, Paintin D. Conceptions and terminations after the 1995 warning about oral contraceptives. Lancet. 1998;352:323-4.
[2] Drife J. Oral contraception and the risk of thromboembolism: what does it mean to clinicians and their patients? Drug Saf. 2002;25:
[3] Chasen-Taber L, Stampfer M. Oral contraceptives and myocardial infarction—the search for the smoking gun. N Engl J Med. 2001;345:
[4] Spitzer WO. The 1995 pill scare revisited: anatomy of a non-epidemic. Hum Reprod. 1997;12:
Chasen-Taber L, Stampfer M. N Engl J Med 2001; Drife L. Drug Saf 2002; Furedi A, Paintin D. Lancet 1998;
Spitzer WO. Hum Reprod

10. Unintended Pregnancy Rates by Age, 2001
100 90 80 70 60
Percentage of pregnancies unintended 50 40 30
Talking Points
Misperception might explain part of the relatively high unintended pregnancy rate in the US—if women choose less effective contraceptive methods due to unsubstantiated or exaggerated concerns about hormonal contraceptives.
Almost half the pregnancies in the US are unintended.
The proportion is highest among 15-to-19-year-olds but still more than 40% among 35-to-39-year-olds.
About 42% of unintended pregnancies end in abortion in the United States.
Reference:
Finer LB, Henshaw SK. Disparities in unintended pregnancy in the United States, and Perspect Sexual Reprod Health. 2006;38(2):90-96. 20 10
15-19
20-24
25-29
30-34
35-39
>40
Finer LB, Henshaw SK. Perspect Sexual Reprod Health 2006.
Age

11. Definition of Risk “The possibility of suffering harm or loss.”
The American Heritage Dictionary of the English Language
Talking Points
To effectively communicate about risk, it’s important to have a clear and accurate understanding of the basic statistics underlying risk comparisons.
What is “risk”?
Here’s a definition straight from The American Heritage Dictionary of the English Language.
A risk is the possibility of suffering harm or loss.”
Note that risk is the probability—or chance—of an event happening; it does not indicate certainty that it will occur.
Reference:
The American Heritage Dictionary of the English Language. 3rd ed. Boston: Houghton Mifflin Company; 1996.

12. Hennekens CH, Buring JE. Epidemiology in Medicine 1987.
Risk Calculations
Allow researchers to hypothesize about causality
Allow consumers and clinicians to weigh the pros and cons of treatment interventions
Allow epidemiologists to calculate the degree to which a disease or event is attributable to a particular hazard
Talking Points
By calculating the risk associated with a particular hazard:
Researchers can hypothesize about causality
Consumers and clinicians can weigh the pros and cons of treatment interventions
Epidemiologists can calculate the degree to which a disease or event is attributable to a particular hazard
Reference:
Hennekens CH, Buring JE. Epidemiology in Medicine. Boston: Little, Brown, and Company. 1987:77.
Hennekens CH, Buring JE. Epidemiology in Medicine 1987.

13. Associations vs. Causality
An association does not always mean exposure caused outcome
It could be due to random chance or bias
Talking Points
The existence of a statistical association does not necessarily mean that the exposure caused the outcome.
Reasons for an association without a true underlying causal relationship include random chance, bias, and other factors.
Making a decision about causality requires that a number of criteria be met, including (among others):
Strength of the association (as measured by relative risk, for example)
Consistency of the association over multiple studies
Temporal sequence (exposure precedes outcome)
The point is that a weak association found in a single study should not be taken as concrete evidence of a cause-and-effect relationship.
Reference:
Grimes DA, Schulz KF. Bias and causal associations in observational research. Lancet. 2002;359:
Grimes DA, Schulz KF. Lancet 2002.

14. Commonly Used Risk Calculations
Absolute risk
Absolute risk reduction (attributable risk)
Relative risk
Talking Points
There are some commonly used risk calculations that you should understand:
Absolute risk
Absolute risk reduction (attributable risk)
Relative risk
We’ll discuss these in some detail.

15. Absolute Risk Absolute risk is
The percentage of people in a group who experience a discrete event
The number of people with event/the total # of people at risk
Talking Points
Absolute risk is the percentage of people in a group who experience a discrete event.
Absolute risk = the # of people with the event divided by the total # of people at risk for the event.
References:
Evidence Based Emergency Medicine at the New York Academy of Medicine. Definitions: absolute risk and its reduction. Available at: Accessed February 3, 2006.
Misselbrook D, Armstrong D. Thinking about risk: can doctors and patients talk the same language? Fam Practice. 2002;19:1-2.
NY Academy of Medicine
Misselbrook D, Armstrong D. Fam Practice 2002.

16. Example of Absolute Risk
Of 100,000 women on 3rd generation OCs, 30 will develop venous thromboembolism (VTE) per year
Absolute risk
30 per 100,000 woman-years
Talking Points
As an example, of 100,000 women taking 3rd generation OCs, approximately 30 will develop VTE per year.
Absolute risk = 30 per 100,000 woman-years.
Reference:
Mills A. Combined oral contraception and the risk of venous thromboembolism. Hum Reprod. 1997;12:
Mills A. Hum Reprod 1997.

17. Absolute Risk Reduction
Absolute risk reduction is:
The difference in risk of the outcome between those exposed and those not exposed
Risk in exposed – risk in unexposed
Reflects the reduction in risk associated with an intervention
Talking Points
Absolute risk reduction is the difference in risk of the outcome between those exposed (to an intervention) and those not exposed.
Absolute risk reduction = risk in those exposed – risk in those who were not exposed.
Reference:
Evidence Based Emergency Medicine at the New York Academy of Medicine Definitions: absolute risk and its reduction. Available at Accessed February 3, 2006.
NY Academy of Medicine

18. Example of Absolute Risk Reduction
Of 100,000 women on 2nd generation OCs, 15 will develop VTE per year
Absolute risk
15 per 100,000 woman-years
Absolute risk reduction
= 15 per 100,000 woman-years
Talking Points
The absolute risk of VTE for 2nd generation OCs users is 15 per 100,000 woman-years.
Therefore, the absolute risk reduction is the difference in absolute risk for women taking 3rd generation and for women taking 2nd generation OCs.
Absolute risk reduction = 30 – 15 = 15 per 100,000 woman-years
Therefore, women taking 2nd generation OCs have a risk that is 15 per 100,000 lower than women taking 3rd generation OCs
Reference:
Mills A. Combined oral contraception and the risk of venous thromboembolism. Hum Reprod. 1997;12:
Mills A. Hum Reprod 1997.

19. Attributable Risk Similar to absolute risk reduction
Attributable risk is:
The difference in risk of the outcome between those exposed and those not exposed
Risk in exposed – rate in unexposed
Reflects degree of risk associated with exposure
Talking Points
Attributable risk is the difference in risk of the outcome between those exposed and those not exposed
Attributable risk = risk in exposed – risk in unexposed
Similar to absolute risk reduction, but indicates degree of risk associated with exposure, rather than specifically the reduction of risk associated with an exposure
Reference:
BMJ Collections: Comparing disease rates. Available at: Accessed March 22, 2006.
BMJ Collections 2006.

20. Relative Risk
Frequency in exposed group divided by frequency in unexposed group
Reflects likelihood of developing the outcome based on exposure
Used to identify an association between exposure and outcome
Similar to odds ratio
Talking Points
Relative risk
Is the frequency of the outcome in the exposed group divided by the frequency of the outcome in the unexposed group
Reflects the likelihood of developing the outcome based on exposure
Is used to identify an association between exposure and outcome
Is similar to odds ratio
References:
Grimes DA, Schulz KF. An overview of clinical research: the lay of the land. Lancet. 2002;359:57-61.
Hennekens CH, Buring JE. Epidemiology in Medicine. Boston: Little, Brown, and Company. 1987:77.
Grimes DA, Schulz KF. Lancet 2002.
Hennekens CH, Buring JE. Epidemiology in Medicine 1987.

21. Hennekens CH, Buring JE. Epidemiology in Medicine 1987.
Odds Ratio
Used to identify an association between exposure and outcome in a case-control study
Similar to relative risk
Talking Points
Relative risk can be calculated for cohort studies, because the underlying incidence of the condition under study is known (the incidence in the unexposed group).
For case-control studies, the underlying incidence is unknown, so relative risk cannot be calculated.
Instead, an odds ratio is used.
We won’t go into the calculation of an odds ratio; just understand that odds ratio quantifies risk for a case-control study as relative risk does for a cohort study.
Reference:
Hennekens CH, Buring JE. Epidemiology in Medicine. Boston: Little, Brown, and Company. 1987:79-81.
Hennekens CH, Buring JE. Epidemiology in Medicine 1987.

22. Example of Relative Risk
Absolute risk
3rd Generation OCs
30 per 100,000 woman-years
Absolute risk
2nd Generation OCs
15 per 100,000 woman-years
Talking Points
Absolute risk of VTE for women taking 3rd generation OCs = 30 per 100,000 woman-years
Absolute risk of VTE for women taking 2nd generation OCs = 15 per 100,000 woman-years
Relative risk = 30 divided by 15 = 2
Reference:
Mills A. Combined oral contraception and the risk of venous thromboembolism. Human Reproduction. 1997;12:
Relative risk = 30 / 15 = 2
Mills A. Hum Reprod 1997.

23. Interpreting Relative Risk
No increase in risk in exposed group compared with unexposed group
Relative risk > 1
Increased risk in exposed group
Relative risk < 1
Decreased risk in exposed group
Talking Points
To interpret relative risk:
Relative risk = 1: no increase in risk in the exposed group compared with the unexposed group
Relative risk > 1: increased risk in the exposed group
Relative risk < 1: decreased risk in exposed group
Therefore, the data that triggered the 1995 pill scare showed that women who took 3rd generation OCs had a risk of VTE 2 times that of women who took 2nd generation OCs.
Reference:
Hennekens CH, Buring JE. Epidemiology in Medicine. Boston: Little, Brown, and Company. 1987:79.
Hennekens CH, Buring JE. Epidemiology in Medicine 1987.

24. Example of Relative Risk: Induction of Labor & Cesarean Delivery
Risk of cesarean delivery with elective induction of labor
20%
Risk of cesarean delivery with spontaneous onset of labor
10%
Relative risk with induction:
20% %
Talking Points
Risk of cesarean delivery with elective induction of labor = 20%
Risk of cesarean delivery with spontaneous onset of labor = 10%
Therefore, the relative risk is 20 divided by 10 = 2
Reference:
Grimes DA, Schulz KF. An overview of clinical research: the lay of the land. Lancet. 2002;359:57-61.
= 2
Grimes DA, Schulz KF. Lancet 2002.

25. Example of Relative Risk (cont.)
Interpretation: the risk of cesarean delivery with elective induction of labor is 2 times that associated with spontaneous labor, or, stated alternatively, twice as high
Talking Points
In this example, a relative risk of 2 means that the risk of cesarean delivery with elective induction of labor is 2 times that associated with spontaneous labor.
Alternatively stated, the risk is twice as high.
Reference:
Grimes DA, Schulz KF. An overview of clinical research: the lay of the land. Lancet. 2002;359:57-61.
Grimes DA, Schulz KF. Lancet 2002.

26. Example of Relative Risk (cont.)
Interpretation: the risk of cesarean delivery with elective induction of labor is 2 times that associated with spontaneous labor, or, stated alternatively, twice as high
Graph of relative risk of 2
0.1 1 10
Relative risk (log scale)
Increased risk
Talking Points
Reference:
Grimes DA, Schulz KF. An overview of clinical research: the lay of the land. Lancet. 2002;359:57-61.
Decreased risk
Grimes DA, Schulz KF. Lancet

27. Example of Relative Risk, #2: Infection after Cesarean Delivery
Rate with prophylactic antibiotics 6%
Rate without prophylactic antibiotics:
12%
Relative risk:
6% 12%
= 0.5
Talking Points
Risk of infection after cesarean delivery with prophylactic antibiotics = 6%
Risk of infection after cesarean delivery without prophylactic antibiotics = 12%
Relative risk = 6 divided by 12 = 0.5
Reference:
Grimes DA, Schulz KF. An overview of clinical research: the lay of the land. Lancet. 2002;359:57-61.
Grimes DA, Schulz KF. Lancet

28. Example of Relative Risk, #2 (cont.)
Interpretation: Use of prophylactic antibiotics (the exposure of interest) is associated with a 50% reduction in risk of infection, or, stated alternatively, one-half the risk
Graph of relative risk of 0.5
0.1 1 10
Relative risk (log scale)
Increased risk
Decreased risk
Talking Points
In this example, a relative risk of 0.5 means that the use of prophylactic antibiotics is associated with a 50% reduction in risk of infection.
Alternatively stated, there is one-half the risk.
Reference:
Grimes DA, Schulz KF. An overview of clinical research: the lay of the land. Lancet. 2002;359:57-61.
Grimes DA, Schulz KF. Lancet 2002.

29. Comparing Relative Risk
Graph of relative risks of 2 and 0.5 10
Zone of increased risk 2
Relative Risk (log scale) 1
Zone of reduced risk
0.5
Talking Points
Relative risks above and below 1.0 are reciprocally related: a relative risk of 2 is equal in strength but opposite in direction to a relative risk of 0.5 (they are both equidistant from 1.0 on the graph)
Reference:
Grimes DA, Schulz KF. An overview of clinical research: the lay of the land. Lancet. 2002;359:57-61.
0.1
2 and 0.5 are equal in strength but opposite in direction, one harmful and one protective
Grimes DA, Schulz KF. Lancet 2002.

30. Comparative Risk of Venous Thromboembolism20 40 60
Pregnancy
High-dose OC
Low-dose OC
General population
Incidence of VTE per 100,000 woman-years
Talking Points:
When communicating about risk, it’s important to discuss and compare risks associated with relevant alternatives.
The alternative to effective contraception is unintended pregnancy, which is in itself associated with risk.
In the US approximately 470 women die each year from pregnancy-related causes (11.8 per 100,000 live births)
This slide shows one of the risks associated with unintended pregnancy: venous thromboembolism.
References:
Shulman LP, Goldzieher JW. The truth about oral contraceptives and venous thromboembolism. J Reprod Med. 2003;48:930-8.
Chang J, Elam-Evans LD, Berg CJ, et al. Pregnancy-related mortality surveillance—United States, In: Surveillance Summaries, February 21, MMWR. 2003;52(SS-2):1-8.
Shulman LP, Goldzieher JW. J Reprod Med Chang J, et al. In: Surveillance Summaries 2003.

31. Risk & Health Decisions
Decisions about risk are not technical, but value decisions.
Talking Points
Health decisions reflect a person’s values, not just his or her understanding of the technical aspects of risk.
Thus, risk communication is not about providing more information or risk calculations to change risk perception.
Reference:
Baker B. In: Bennett P, Calman K, eds. Risk Communication and Public Health. Oxford; Oxford University Press. 1999: preface, v.
Baker B. In: Risk Communication and Health 1999.

32. Causes of Risk Misperception about Hormonal Contraceptives
Lack of understanding of statistics
Psychological factors
Media influence
Factors that affect risk perception and interpretation
Talking Points
Risk misperception about combined hormonal contraceptives can exist for patients or providers.
Risk misperception is probably caused by a number of factors, including
Lack of understanding of statistics
Psychological factors
Media influences
Factors that affect risk perception and interpretation
Statistics is a complicated field, requiring a baseline of mathematical education that many people do not have.
For this reason, it may be challenging for patients to fully comprehend the mathematical basis of risk calculations about effectiveness or adverse events associated with combined hormonal contraceptives.
Psychological factors may influence a woman’s perception of risk. For example, ambivalent feelings about women’s sexuality—due to cultural or other influences—may induce a woman to avoid more effective contraceptive methods if they require advance planning.
We’ll discuss in more detail the influence of media and other factors that affect risk perception and interpretation.

33. Grimes DA. In: Oral Contraceptives and Breast Cancer 1989.
Media Influence
Positive: widespread dispersion of reproductive health information
Negative: misperception of contraceptive risks
Incomplete information; “sound bites”
Business of selling news; “if it bleeds, it leads”
Risks not put in context
TV ads conclude with adverse events
Talking Points
The media provide a means for widespread dispersion of reproductive health information.
However, they also serve as a source of risk misperception for a number of reasons:
Media provide incomplete information and are designed to deliver news in small portions, or “sound bites.”
Media stay viable through “selling” the news, often following the philosophy “if it bleeds, it leads.”
Media do not put reported risks in context.
Television advertisements for hormonal contraceptives conclude with a required, but overwhelming, list of the adverse events reported in clinical trials.
Reference:
Grimes DA. Breast cancer, the pill, and the press. In: Mann RD, ed. Oral Contraceptives and Breast Cancer. Park Ridge, NJ: The Parthenon Publishing Group. 1989:
Grimes DA. In: Oral Contraceptives and Breast Cancer 1989.

34. Degree of OC Discontinuation Related to Media Event
Percentage
Talking Points
OC discontinuation has been temporally linked to specific media events.
One study looked at monthly discontinuation rates in 1970 to 1975.
The average pill discontinuation rate was 0.9% per month.
At one month after an adverse media event, the rate was 3%
At 5 months, the rate peaked at 16%.
References:
DA Grimes. Breast cancer, the pill, and the press. In: Mann RD, ed. Oral Contraceptives and Breast Cancer. Park Ridge, NJ: The Parthenon Publishing Group. 1989: 312.
Jones EF, Beniger JR, Westoff CF. Pill and IUD discontinuations in the United States, : the influence of the media. Fam Plann Perspect. 1980;12:
Months after event
Jones EF, et al. Fam Plann Perspect Grimes DA. In: Oral Contraceptives and Breast Cancer 1989.

35. Temporal Relationship Between Product Launch & Reported Adverse Events
400
200 2 3 4 5 6 7 8 9 11 12 13 14 15 16 17
Number of Reports
Talking Points
The Weber effect is a phenomenon in which reported adverse events for a drug peak near the end of the 2nd year of marketing then decline, despite increases in prescribing.
This slide illustrates the Weber effect for diflunisal (Dolobid), a non-steroidal anti-inflammatory drug (NSAID).
Researchers speculate the effect is due to prescriber familiarity with the drug— because prescribers are exposed to many new drugs each year, 2 years may be the maximum time they sustain interest in reporting adverse events for any single drug.
Weber effect may explain why new drugs are highlighted in the media even though the reported adverse events are expected.
References:
Hartnell NR, Wilson JP. Replication of the Weber effect using postmarketing adverse event reports voluntarily submitted to the United States Food and Drug Administration. Pharmacotherapy. 2004;24:743-9.
Weber JCP. Mathematical models in adverse drug reaction assessment. In: D’Arcy FF, Griffin JP, eds. Iatrogenic Diseases. Oxford, England: Oxford University Press; 1986:102-7.
Year/Month
Hartnell NR, Wilson JP. Pharmacotherapy Weber JCP. In: Iatrogenic Diseases 1986.

36. Factors that Affect Perception & Interpretation of Risk
Factors related to the individual
Factors related to risk presentation
Factors related to the characteristics of the risk
Talking Points
Three general types of factors affect a person’s perception and interpretation of risk:
Those related to the individual
Those related to risk presentation
Those related to the characteristics of the risk

37. Factors Related to the Individual
Culture
Literacy level and education
Developmental stage
Human tendencies
Underestimate effectiveness and overestimate risk of hormonal contraception
Optimism-pessimism bias
Talking Points
A number of factors related to the individual affect his or her perception and interpretation of risk.
Culture: When discussing risk, it is important to take ethnicity, partner/family situation, religion, and experience with risk into consideration. [1]
Literacy level and education: Studies have shown that individuals with less formal education are more likely to misunderstand risk information. [2], [3]
Developmental stage: Because of their cognitive developmental stage, early and middle adolescents may not have the abstract thinking skills necessary to evaluate risk. [4], [5], [6]
Human tendencies:
Women tend to overestimate the risks and underestimate the effectiveness of hormonal contraception. [7]
Optimism-pessimism bias: People tend to believe that they are at less risk for an event than the “average person” and therefore information about a particular risk does not apply to them. [8]
References:
[1] Noone J. Cultural perspectives on contraception: a literature review. Clin Excell Nurse Pract. 2000;4:
[2] Hubertus AAMV, Grimes DA, Popkin B, Smith U. Lay persons’ understanding of the risk of Down’s Syndrome in genetic counseling. Br J Obstet Gynaecol. 2001;108:
[3] Grimes DA, Snively GR. Patients’ understanding of medical risks: implications for genetic counseling. Obstet Gynecol. 1999;93:910-4.
[4] Steinberg L. Risk taking in adolescence: what changes, and why? Ann NY Acad Sci. 2004;1021:51-8.
[5] Mann L, Harmoni R, Power C. Adolescent decision-making: the development of competence. J Adolesc. 1989;12:
[6] Steinberg L. Cognitive and affective development in adolescence. Trends Cogn Sci. 2005;9:69-74.
[7] Edwards JE, Oldman A, Smith L, et al. Women’s knowledge of, and attitudes to, contraceptive effectiveness and adverse events. Br J Fam Plann. 2000;26:73-80.
[8] Bowling A, Ebrahim S. Measuring patients’ preferences for treatment and perceptions of risk. Qual Health Care. 2001;10 (suppl I):i2-i8.
Noone J. Clin Excell Nurse Pract 2000; Hubertus AAMV. Br J Obstet Gynecol 2001; Grimes DA, Snively GR. Obstet Gynecol 1999; Steinberg L. Ann NY Acad Sci 2004; Mann L, et al. J Adolesc 1989; Steinberg L. Trends Cogn Sci 2005; Edwards JE, et al. Br J Fam Plann 2000; Bowling A, Ebrahim S. Qual Health Care 2001.

38. Developmental Stage
By age 15, reasoning is fully developed in hypothetical situations
Early adolescence: puberty causes increase in reward sensitivity
Later adolescence: self-regulation systems develop
Talking Points
When counseling an adolescent patient, keep in mind that her developmental stage affects her ability to think abstractly, and thus her understanding of risk.
By age 15, the reasoning ability of most adolescents is fully developed for hypothetical situations.
However, other developmental changes affect risk-taking and decision making in the real world.
During early adolescence, there is an increase in reward sensitivity in the limbic system, probably due to the neurological and hormonal changes of puberty.
Cognitive systems in the prefrontal cortex develop later, based on chronological age and education level, and they continue to develop into early adulthood.
The time window between the two developmental events may explain part of the high level of risk-taking behavior during adolescence.
References:
Steinberg L. Risk taking in adolescence: what changes and why? Ann NY Acad Sci. 2004;1021:51-8.
Luna B, Sweeney JA. The emergence of collaborative brain function: fMRI studies of the development of response inhibition. Ann NY Acad Sci. 2004;1021:
Steinberg L. Ann NY Acad Sci Luna B, Sweeney JA. Ann NY Acad Sci 2004.

39. Factors Related to Risk Presentation
Framing effects (positive or negative)
Uncertainty
Trust
Talking Points
This slide lists factors related to the presentation of risk information that affect the perception and interpretation of risk.
Framing effects
The message used to present information influences people’s perception of risk.
For example, using positive framing (like chance of survival) is more likely to persuade people to take risky options than negative framing (chance of death). People are more likely to choose a treatment if told that 65 of 100 of people survived, than 35 of 100 people died.
Uncertainty
People tend to be more fearful about risk information for a topic for which there is more scientific uncertainty.
Trust
People are likely to disregard information about risk if they don’t trust the source of the information.
References:
Edwards A, Elwyn G, Mulley A. Explaining risks: turning numerical data into meaningful pictures. BMJ. 2002; 324:
Bennett P. Communicating about risks to public health: pointers to good practice Available at: Accessed February 3, 2006.
Edwards A, et al. BMJ Bennett P. Dept Health UK 1997.

40. Factors Related to the Characteristics of the Risk
People worry more about risks that
The individual cannot control
Are involuntary
Are associated with particular dread
Are novel or unfamiliar
Result from man-made sources
Are more easily recalled
Talking Points
People tend to worry more about risks that
The individual cannot control (airplane v. car crash)
Are involuntary (air pollution)
Are associated with particular dread (breast cancer)
Are novel or unfamiliar (newly discovered toxin)
Result from man-made sources (radiation from mobile phones)
Are more easily recalled (recent media attention)
References:
Harvard Center for Risk Statistics. Risk in Perspective. Vol. 11. June 2003.
Bennett P. Understanding responses to risk. In: Bennett P, Calman K, eds. Risk Communication and Public Health. Oxford; Oxford University Press
Harvard Center for Risk Statistics 2003.
Bennett P. In: Risk Communication and Public Health

41. Estimated & Actual Mortality Rates
Estimated number of deaths per year
106
105
104
103
102 10 1
Actual number of deaths per year
Botulism
Tornado
Smallpox Vaccination
Flood
Electrocution
Asthma TB
Pregnancy
Homicide
Motor Vehicle Accidents
All Accidents
All Disease
All Cancer
Heart Disease
Stroke
Stomach Cancer
Diabetes
Talking Points
This slide compares the actual frequency of death from various causes and the frequency estimated by a sample of the US population.
If the actual and estimated frequencies agreed, the dots would fall on the straight line.
People tend to overestimate the risk of death due to unusual or dramatic causes, such as tornado, and underestimate the risk of death due to common causes, such as heart disease.
This reflects the availability bias: highly memorable, newsworthy but unusual events are more easily brought to mind, and thus the frequency is overestimated.
Reference:
Bennett P. Understanding responses to risk. In: Bennett P, Calman K, eds. Risk Communication and Public Health. Oxford, England: Oxford University Press;1999.
Bennett P. In: Risk Communication and Public Health 1999.

42. Understanding Risk: Relative Effectiveness of Contraceptives
Talking Points
This chart is reproduced in your handout.
In reproductive health, risk calculations are commonly used to present information on the relative effectiveness of contraceptives.
Generally, the rate of pregnancy for typical use is compared with the “lowest expected” rate or perfect-use rate.
These figures are estimates based on several types of studies.
The data are commonly presented as percentages of the women likely to become pregnant while using a particular method for 1 year, or the “failure rate.”
Reference:
Steiner MJ, Dalebout S, Condon S, et al. Understanding risk: a randomized controlled trial of communicating contraceptive effectiveness. Obstet Gynecol. 2003;102:
Steiner MJ, et al. Obstet Gynecol 2003.

43. WHO Decision Aid on Contraceptive Effectiveness
Talking Points
This chart is reproduced in your handout.
It shows another way to present information on the relative effectiveness of contraceptive methods.
Notice that
Frequencies per 100 women per year are used, rather than percentages.
A spectrum of frequencies are shown, rather than frequencies for each method.
Visual images are used along with the written names of the methods.
Reference:
World Health Organization (WHO). Comparing typical effectiveness of contraceptive methods. [Job Aid]. Geneva: World Health Organization, Available at: Accessed January 26, 2006.
World Health Organization 2006.

44. Tools: Categories Table
Effectiveness Group
Typical Success Rate
Protection Against STDs/AIDS
Sterilization (male & female)
More effective
(for all users) no
Implants
Hormone shot
Intrauterine device (hormonal)
Intrauterine device (copper)
Birth control pills (combined pill & mini)
Effective
Barrier methods
Less effective
yes
Spermicide
limited
Natural methods
Talking Points
A categories table displays risks, or in this case, contraceptive effectiveness, by grouping methods with similar risk together.
*Effective for most users; however, more effective if used consistently and correctly.
**Less effective for most users; however, effective if used consistently and correctly.
Reference:
Steiner MJ, Dalebout S, Condon S, et al. Understanding risk: a randomized controlled trial of communicating contraceptive effectiveness. Obstet Gynecol. 2003;102:
Adapted from Steiner MJ, et al. Obstet Gynecol 2003.

45. Comprehension of Contraceptive Effectiveness by Teaching Method
Pre/post percent improvement in correct score by teaching method
Hormone shot vs. pill
Numbers (FDA)
Numbers & categories (WHO)
Categories
Talking Points
This slide shows some interesting data from a 2003 study by Steiner and colleagues at Family Health International and the Office of Population Research at Princeton.
These researchers provided women with 3 different tools for understanding the effectiveness of contraceptives:
The FDA table with percentages shown in the last slide
A category table that divides contraceptive methods into most effective for most users, effective for most users, and less effective for most users
A category and numbers table from WHO
The researchers evaluated the improvement in knowledge for the relative effectiveness of the hormonal injection vs. oral contraceptives and oral contraceptives vs. condoms.
They found that the categories chart improved knowledge the most and was statistically better than the FDA numbers table.
The combination table with numbers and categories was no better at improving knowledge of effectiveness than numbers alone.
Reference:
Steiner MJ, Dalebout S, Condon S, et al. Understanding risk: a randomized controlled trial of communicating contraceptive effectiveness. Obstet Gynecol. 2003; 102:
Pill vs. condom 0%
40%
Steiner MJ, et al. Obstet Gynecol 2003.

46. Communicating Contraceptive Effectiveness (cont.)
Given only effectiveness category information, women overestimated pregnancy risk
When later shown percentage tables, majority reported rate accurately
Authors recommended category tools with general range of risk shown within each category
Talking Points
In the Steiner 2003 study, before seeing the tables with percentages, women tended to overestimate the risk of pregnancy at a given effectiveness on the category tool. For example, before looking at the table with percentages:
70% of women thought the annual risk of pregnancy with a very effective method was >5%
40% of women thought the annual risk was >15% (WHO defines very effective as 0% to 1%)
After looking at the table with percentages, more than two-thirds correctly reported the failure rate for oral contraceptives.
The authors propose that in the area of contraceptive effectiveness, it may be more important to understand relative effectiveness than absolute effectiveness.
This is because the data are average failure rates, which may not reflect actual rates for subgroups with certain characteristics (e.g., high method adherence).
At the same time, women provided only with category effectiveness tools may overestimate the risk of pregnancy associated with a particular effectiveness category.
For these reasons, the researchers suggest using category tools with a general range of risk within each category to provide understanding of both the relative and the absolute risk of pregnancy for each contraceptive method.
Reference:
Steiner MJ, Dalebout S, Condon S, et al. Understanding risk: a randomized controlled trial of communicating contraceptive effectiveness. Obstet Gynecol. 2003; 102:
Steiner MJ, et al. Obstet Gynecol 2003.

47. Understanding Risk: Cardiovascular Adverse Events
Cardiovascular events: most common major adverse events associated with combined OC use
Venous thromboembolism (VTE)
Stroke
Myocardial infarction (MI)
Talking Points
Cardiovascular events (venous thromboembolism, stroke, MI) are the most common major adverse events associated with use of combined OCs.
Reference:
Farley TMM, Collins J, Schlesselman JJ. Hormonal contraception and risk of cardiovascular disease: an international perspective. Contraception. 1998;57;
Farley TMM, et al. Contraception 1998.

48. Cardiovascular Events
Events (per million woman-years)
Talking Points
This slide shows the incidence of cardiovascular mortality by age range for women in three categories:
nonsmoker non-OC user
nonsmoker OC user
smoker OC user
Note: This graph is representative of the data provided for women aged 20-24, 30-34, and 40-44
Reference:
Farley TMM, Collins J, Schlesselman JJ. Hormonal contraception and risk of cardiovascular disease: an international perspective. Contraception. 1998;57;
(Women years old)
Farley TMM, et al. Contraception 1998.

49. Cardiovascular Mortality
Deaths (per million woman-years)
Talking Points
This slide shows the incidence of cardiovascular mortality by age range for women in three categories:
nonsmoker non-OC user
nonsmoker OC user
smoker OC user
Note: This graph is representative of the data provided for women aged 20-24, 30-34, and 40-44
Reference:
Farley TMM, Collins J, Schlesselman JJ. Hormonal contraception and risk of cardiovascular disease: an international perspective. Contraception. 1998;57;
(Women years old)
Farley TMM, et al. Contraception 1998.

50. Cardiovascular Adverse Events in Context
Context is important
Incidence is low in reproductive age women, with or without OC use
Smoking and OC use have a synergistic effect on cardiovascular event incidence and mortality at all ages
Talking Points
Context is very important here:
Incidence is low in reproductive age women, with or w/o OC use
Smoking has a larger effect on cardiovascular event incidence and mortality than OC use at all ages
Reference:
Farley TMM, Collins J, Schlesselman JJ. Hormonal contraception and risk of cardiovascular disease: an international perspective. Contraception. 1998;57;
Farley TMM, et al. Contraception 1998.

51. Cardiovascular Adverse Events: Weighing the Risks & Benefits
For most women, non-contraceptive benefits of combined hormonal contraceptives outweigh the risks
Talking Points
It is important to understand that for most women, the non-contraceptive benefits of combined hormonal contraceptives outweigh the potential risks. That said, smoking, hypertension, obesity, and diabetes are risk factors that must be considered when evaluating risks associated with combined hormonal contraceptives.
Reference:
Burkman R, Schlesselman JJ, Zieman M. Safety concerns and health benefits associated with oral contraception. Am J Obstet Gynecol. 2004;190(4 Suppl):S5-22.
Burkman R, et al. Am J Obstet Gynecol 2004.

52. Cardiovascular Adverse Events: Screening for Risk Factors
Deaths (per million woman-years)
Talking Points
This slide compares the mortality of smokers who use OCs whose blood pressure was checked before OC use and those whose blood pressure wasn’t checked.
Note that a simple screen for blood pressure lowers the risk of mortality.
Reference:
Farley TMM, Collins J, Schlesselman JJ. Hormonal contraception and risk of cardiovascular disease: an international perspective. Contraception. 1998;57;
(Women years old)
Farley TMM, et al. Contraception 1998.

53. Communicating Risk: The How To’s
What to ask
Patient needs & concerns
What to consider
Relevant factors
What to use
Tools
What to do
Guidance
Talking Points
Now, let’s turn to how to communicate risk.
You’re in your office or an exam room. A woman wants to switch contraceptive methods.
What should you tell her about risks?
How should you tell her?
What, exactly, should you say and do?
We’ll discuss 3 important aspects of communicating the risks associated with contraceptives:
Patient needs and concerns, or “What to ask”
Relevant factors, or “What to consider”
Tools, or “What to use”
Guidance, or “What to do”

54. Patient Needs & Concerns: What to Ask
How important is it to avoid pregnancy right now?
How important is privacy regarding contraception?
Do you have concerns about a particular contraceptive?
What side effects are you willing to accept?
Are you comfortable with methods that require insertion in the vagina?
Talking Points
This slide lists some questions to ask your patient to better understand her needs and concerns about risk and hormonal contraception.
Use the answers to guide your discussion of risk (e.g., how much detail to provide about comparative effectiveness).
Questions:
How important is it to avoid pregnancy right now?
Do you want your use of contraception to be private?
Do you have concerns about a particular contraceptive? (e.g., media report, friend’s experience)?
What side effects (or risk of serious adverse events) are you willing to accept?
Also, ask about risk factors to guide contraceptive choice: age, relationship status, smoking status, bleeding or clotting disorder, higher-risk sexual behavior.

55. Factors Relevant to Risk Communication
Level of trust
Framing effects
Cultural, literacy, and developmental effects
Not strictly an intellectual issue
Risk comparisons can be misleading
Talking Points
This slide lists a reminder of relevant factors we’ve already covered that you should consider when discussing the risks and benefits of combined hormonal contraceptives with patients.
Level of trust
Framing effects
Cultural, literacy, and developmental effects
Not strictly an intellectual issue
Risk comparisons can be misleading

56. Gigerenzer G, Edwards A. BMJ 2003.
Tools: Numerical Data
Try different ways to explain numerical data
SAY “3 of every 10 women develop nausea”
Talking Points
Here are some tips to improve understanding of numerical data.
Try different ways to explain numerical data:
Avoid vague statements about risk, which may be confusing.
For example, try presenting both frequency statements (3 of 10) AND probabilities (30% chance).
SAY “3 of every 10 women develop nausea.”
ALSO SAY “You have a 30% chance of nausea with this drug.”
Reference:
Gigerenzer G, Edwards A. Simple tools for understanding risks: from innumeracy to insight. BMJ. 2003;327:741-4.
ALSO SAY “You have a 30% chance of nausea”
Gigerenzer G, Edwards A. BMJ 2003.

57. Tools: Numerical Data (cont.)
Avoid shifting denominators in proportions
SAY “Headache developed in 3 of every women”
Talking Points
Avoid shifting denominators in proportions.
Use proportions of disease per unit of population exposed instead of proportions with a numerator of one and shifting denominators.
(Note that many providers will refer to 3 of every 1000 as a rate, but in actuality, it is a proportion. Proportions are ratios in which the denominator is the total number of individuals at risk, thus including the numerator. Rates are ratios that include a measure of time in the denominator.)
To many people, 1 in 400 may sound like more than 1 in 200.
SAY “Headache developed in 3 of every 1000 women.”
NOT “Headache developed in 1 of every 333 women.”
References:
Gigerenzer G, Edwards A. Simple tools for understanding risks: from innumeracy to insight. BMJ. 2003;327:741-4.
Grimes DA, Snively GR. Patients’ understanding of medical risks: implications for genetic counseling. Obstet Gynecol. 1999;93:910-4.
NOT “Headache developed in 1 of every 333 women”
Grimes DA, Snively GR. Obstet Gynecol 1999.
Gigerenzer G, Edwards A. BMJ 2003.

58. Tools: Numerical Data (cont.)
Use absolute risk
SAY “Of every 1 million OC users, 4 develop heart attack each year compared with 2 nonusers.”
Talking Points
Use absolute risk
Use absolute risk instead of or in addition to relative risk.
For conditions with a low rate in the baseline population, relative risk alone may exaggerate the hazard.
SAY “Of every 1 million OC users, about 4.2 develop heart attack each year. About 1.7 nonusers have heart attacks each year.” (Age 30-34, nonsmoker)
NOT “OC use increases risk of heart attack 1.5 fold”
References:
Gigerenzer G, Edwards A. Simple tools for understanding risks: from innumeracy to insight. BMJ. 2003;327:741-4.
Farley TMM, Collins J, Schlesselman JJ. Hormonal contraception and risk of cardiovascular disease: an international perspective. Contraception. 1998;57:
Sloman, SA, Over D, Slovak L, Stibel, JM. Frequency illusions and other fallacies. Organizational Behavior and Human Decision Processes. 2003;91:
NOT “OC use doubles the risk of heart attack”
Gigerenzer G, Edwards A. BMJ 2003; Farley TMM, et al. Contraception 1998;
Sloman SA, et al. Organizational Behavior and Human Decision Processes 2003.

59. Tools: Descriptive Terms
Risk level
High <1 in 100
Moderate 1 to 10 in 1,000
Low 1 to 10 in 10,000
Very low 1 to 10 in 100,000
Minimal 1 to 10 in 1 million
Talking Points
Descriptive terms may be helpful in that they can simplify discussions.
However, these terms are not standardized and may be defined differently by different people.
The slide shows an example of one proposed set of terms to describe risk.
Notice that using a variable denominator may be confusing, as we discussed before.
Also, at least one study has shown that people often overestimate risk when descriptive terms are used.
References:
Calman KC. Cancer: science and society and the communication of risk. BMJ. 1996;313:
Berry DC, Raynor DK, Knapp P, Bersellini E. Patients' understanding of risk associated with medication use: impact of European Commission guidelines and other risk scales. Drug Saf. 2003;26(1):1-11.
Calman KC. BMJ Berry DC, et al. Drug Saf 2003.

60. Tools: Risk Comparisons
Annual Risk of Death (per 100,000)
Skydiving 100
Driving 20
Pregnancy 11.5
Riding a bicycle 0.8
Airplane crash 0.4
Using OC* 0.06
Talking Points
This slide compares the risk of death per year for a number of different activities and events. [1] [2]
Such comparisons are often used to provide a sense of perspective for various risks.
As mentioned, in the US approximately 470 women die each year from pregnancy-related causes (11.8 per 100,000 live births). [3]
However, risk comparisons can alienate and offend the listener if they include examples of risks with different characteristics—it’s important to consider the values of the listener and the dread or worry associated with the particular risk. [4]
For example, comparing the risk of dying from breast cancer (involuntary and associated with considerable dread) with the risk of driving a car (voluntary and common) may miss the point.
In general, it is not a good idea to use risk comparisons such as these when communicating about risks with patients.
References:
[1] Trussell J, Jordan B. Reproductive health risk in perspective. Contraception. In press.
[2] Harvard Center for Risk Analysis. Risk Quiz. Available at: Accessed February 1, 2006.
[3] Chang J, Elam-Evans LD, Berg CJ, et al. Pregnancy-related mortality surveillance—United States, In: Surveillance Summaries, February 21, MMWR. 2003;52(SS-2):1-8.
[4] Bennett P. Understanding responses to risk. In: Bennett P, Calman K. Risk Communication and Public Health. Oxford, England: Oxford University Press
*Nonsmoker, under age 35
Trussell J, Jordan B. Contraception in press.
Chang J, et al. MMWR 2003.
Harvard Center for Risk Analysis Bennett P. In: Risk Communication and Public Health 1999.

61. Tools: Diagrams Categories table Numbers and categories table
Flower diagram
Paling Perspective Scale
Paling Palette
Talking Points
This is a list of some visual tools that can be used for risk communication about hormonal contraception.

62. Tools: Categories Table
Effectiveness Group
Typical Success Rate
Protection Against STDs/AIDS
Sterilization (male & female)
More effective
(for all users) no
Implants
Hormone shot
Intrauterine device (hormonal)
Intrauterine device (copper)
Birth control pills (combined pill & mini)
Effective
Barrier methods
Less effective
yes
Spermicide
limited
Natural methods
Talking Points
A categories table displays risks, or in this case, contraceptive effectiveness, by grouping methods with similar risk together.
*Effective for most users; however, more effective if used consistently and correctly.
**Less effective for most users; however, effective if used consistently and correctly.
Reference:
Steiner MJ, Dalebout S, Condon S, et al. Understanding risk: a randomized controlled trial of communicating contraceptive effectiveness. Obstet Gynecol. 2003;102:
Adapted from Steiner MJ, et al. Obstet Gynecol 2003.

63. Tools: Numbers & Categories Table
Effectiveness Group
Family Planning Method
Typical-Use Rate of Pregnancy
Lowest Expected Rate of Pregnancy
More effective
(for all users)
Male and female sterilization
0.2%-0.5%
0.1%-0.5%
Implants
0.1%
Hormone shot
0.3%
Intrauterine devices (copper and progesterone)
0.8%-2%
0.6%-1.5%
Effective
Birth control pills 5%
Less effective
Male latex condoms
14% 3%
Diaphragm
20% 6
Cervical cap
20%-40%
9%-26%
Female condoms
21%
Spermicide
26% 6%
Withdrawal
19% 4%
Natural family planning
1%-9%
No method
85%
Talking Points
A numbers and categories table displays risks, or in this case, contraceptive effectiveness, by grouping methods with similar risk together, but it also provides numerical data on risk.
*Effective for most users; however, more effective if used consistently and correctly.
**Less effective for most users; however, effective if used consistently and correctly.
Reference:
Steiner MJ, Dalebout S, Condon S, et al. Understanding risk: a randomized controlled trial of communicating contraceptive effectiveness. Obstet Gynecol. 2003;102:
Adapted from Steiner MJ, et al. Obstet Gynecol 2003.

64. Tools: Paling Perspective Scale®
Risks from smallpox: for the 115M Americans over the age of 30 - previously vaccinated and DO NO live in a major metropolitan area
1 in 100B
1 in 10B
1 in 100M
1 in 10M
1 in 100K
1 in 10K
1 in 100
1 in 1T
1 in 1B
1 in 1M
1 in 1K
1 in 10
1 in 1
Estimates of Specific Risks
Look at the consequences as well as the odds
RISK INCREASING
Risk of death from vaccination: 1 in 2 million
Risk of Smallpox Infection: 1 in 100M people (or less)
Death from Smallpox if not vaccinated post exposure: 1 in 1.7B (or less)
Talking Points
This chart is reproduced in your handout.
The Paling Perspective Scale was developed by John Paling, research director of the Risk Communication Institute in Gainesville, FL.
It shows a spectrum of risk, from minimal to very high, for various activities and could be adapted for reproductive health events.
Reference:
Paling J. Strategies to help patients understand risks. BMJ. 2003;327:745-8.
Death from Smallpox if vaccinated post exposure: 1 in 100B (or less)
Fig. 2 Paling Perspective Scale® - for giving perspective to risks of low order of probability.
Paling J. BMJ 2003.

65. Tools: Paling Palette®
Talking Points
This chart is reproduced in your handout.
John Paling also created the Paling Palette.
This visual tool shows the risk of a particular event through the use of human icons.
Reference:
Paling J. Strategies to help patients understand risks. BMJ. 2003;327:745-8.
Paling J. BMJ 2003.

66. Guidance Remember to present absolute risk
Use different forms of numerical data to explain risk
Be aware of framing effects
Use risk comparisons with care
Have multiple, complementary tools available
Talking Points
Remember to present absolute risk.
Use different forms of numerical data to explain risk.
Be aware of framing effects (the message used can influence perception of risk: % who survive v. % who died).
Use risk comparisons with care.
Have multiple, complementary tools available.

67. Decision Aid for Risk Communication
Clarify situation
Provide information
“On the benefit side…”
“On the harm side…”
Clarify patient’s values
Screen for implementation problems
Talking Points
This decision aid may help you to discuss the risks and benefits of hormonal contraception with your patients.
Clarify the situation.
Provide information on benefits and harms.
Clarify patient values.
Screen for implementation problems.
Reference:
O’Connor A, Legare F, Stacey D. Risk communication in practice: the contribution of decision aids. BMJ. 2003;327:
O’Connor A, et al. BMJ 2003.

68. Case Study: Michelle Gavin
19-year-old college student
Using patch for 6 months
Talking Points
Let’s walk through this case study using the decision aid we just reviewed.
Clarify the situation
“I hear that you are concerned about the possibility of a serious problem with the patch.”
“It is your choice to stop or keep using the patch, but let me put the possibility of a serious problem with the patch into perspective.”
Provide information
“On the benefit side, the patch is very good at preventing pregnancy and because women find it easy to use, they are more likely to remember to use it. Pregnancy itself increases the risk of blood clots, heart attack, and stroke—although these problems are not common.”
“On the harm side, the chance of having a serious problem like heart attack, stroke, or blood clot is greater for women using hormonal contraceptives like the patch than for women who don’t use them. This is especially true if they smoke or have had a blood clot before. But the chance is still very small and is actually smaller than the chance of these problems happening when a woman is pregnant.”
Clarify patient values: “Do you think the benefits of the patch are more important to you than the chance of a serious problem?”
Screen for implementation problems: “How important is it to you to make this change [to remain on patch or stop patch]?” [scale 1-10] ; “How confident are you in making this change?” [scale 1-10]
Reference:
O’Connor A, Legare F, Stacey D. Risk communication in practice: the contribution of decision aids. BMJ. 2003;327:
“I want off the patch—it killed that girl in New York”
O’Connor A et al. BMJ 2003.

69. Case Study: Michelle Gavin
Clarify situation
Provide information
Clarify patient’s values
Screen for implementation problems
Talking Points
Let’s walk through this case study using the decision aid we just reviewed.
Clarify the situation
“I hear that you are concerned about the possibility of a serious problem with the patch.”
“It is your choice to stop or keep using the patch, but let me put the possibility of a serious problem with the patch into perspective.”
Provide information
“On the benefit side, the patch is very good at preventing pregnancy and because women find it easy to use, they are more likely to remember to use it. Pregnancy itself increases the risk of blood clots, heart attack, and stroke—although these problems are not common.”
“On the harm side, the chance of having a serious problem like heart attack, stroke, or blood clot is greater for women using hormonal contraceptives like the patch than for women who don’t use them. This is especially true if they smoke or have had a blood clot before. But the chance is still very small and is actually smaller than the chance of these problems happening when a woman is pregnant.”
Clarify patient values: “Do you think the benefits of the patch are more important to you than the chance of a serious problem?”
Screen for implementation problems: “How important is it to you to make this change [to remain on patch or stop patch]?” [scale 1-10] ; “How confident are you in making this change?” [scale 1-10]
Reference:
O’Connor A, Legare F, Stacey D. Risk communication in practice: the contribution of decision aids. BMJ. 2003;327:
O’Connor A et al. BMJ 2003.

70. Tips for Effective Communication
Be an active listener
Eliminate internal & external distractions
Present information in several ways
Ensure understanding z
Know your purpose
Talking Points
Remember these basic principles to communicate effectively:
Know your purpose: to help your patients reach the decision that is best for them.
Present information in several ways.
Be an active listener: demonstrate interest through eye contact, posture, and facial expression.
Eliminate internal and external distractions.
Ensure understanding: ask the patient to repeat what she heard.
Reference:
Principles of Communication. Center for Urban Transportation Studies. University of Wisconsin-Milwaukee. Available at: Accessed February 24, 2006.
Center for Urban Transportation Studies UWM 2006.

71. Communication: What Patients Want
Explain the reasoning behind your questions
Present the options (pro and con) and let her know what she can do
Treat woman as a partner
Talking Points
This slide shows some of the qualitative data obtained from a focus group study of young African-American and Latino women.
Explain the reasoning behind your questions (e.g., a woman presents for OCs and is asked about her home life. She wonders why.)
Present the options (pro and con) and let her know what she can do.
Treat the woman as an equal partner.
Reference:
Pro Choice Public Education Project. She Speaks: African-American and Latino Young Women on Reproductive Health and Rights. 2004:17-8.
Pro Choice Public Education Project 2004.

72. Tips for Communicating About Alarming Media Reports
Gather reputable information: PPFA, ARHP, ACOG, CDC
Review relevant editorials in peer- reviewed journals
Help patients gain perspective
Talking Points
These points and resources may help you communicate effectively in the wake of alarming media reports
Gather reputable information: PPFA, ARHP, ACOG, CDC.
Review relevant editorials in peer-reviewed journals.
Help patients gain perspective on degree of risk (e.g., use absolute risk or NNH; compare with truly relevant alternatives).

73. Learning Objectives
Define relative risk, attributable risk and absolute risk
List three different means of presenting risk and describe the advantages of each
Identify at least three patient characteristics to consider when counseling about risks and benefits
Describe at least one patient education tool that can be used to effectively communicate the risks and benefits of hormonal contraceptives
This slide should be shown at each presentation.

74. Summary
A misperception of risks about contraception may unnecessarily limit a women’s choices
Risk perception is affected by a number of factors
Clinicians should consider relevant factors and expert guidance about risk communication
Several tools are available to aid risk communication

75. Two times a very rare event is
A Final Thought
Two times a very rare event is
still a very rare event.
David Grimes, MD 2006.