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DataWatch

Public Attitudes About Genetic Testing For Alzheimer’s Disease

Peter J. Neumann, James K. Hammitt, Curt Mueller, Howard M. Fillit, Jerrold Hill, Nii A. Tetteh and Kenneth S. Kosik

Abstract

 
In a general population survey (N = 314), 79 percent of respondents stated that they would take a hypothetical genetic test to predict whether they will eventually develop Alzheimer’s disease. The proportion fell to 45 percent for a "partially predictive" test (which had a one in ten chance of being incorrect). Inclination to obtain testing was similar across age groups. Respondents were willing to pay $324 for the completely predictive test. Respondents stated that if they tested positive, they would sign advance directives (84 percent), get their finances in order (74 percent), and purchase long-term care insurance (69 percent). Only a third of respondents expressed concern about confidentiality. The results suggest that people value genetic testing for personal and financial reasons, but they also underscore the need to counsel potential recipients carefully about the accuracy and implications of test information.

Some patients are already demanding testing to predict if they carry the "Alzheimer’s gene."¹ The anticipation of genetic testing for Alzheimer’s and other diseases raises a host of policy questions, with large social, economic, and ethical ramifications. Early diagnosis could offer patients and families more time for planning for future care and financing. On the other hand, it could lead to increased anxiety or false reassurance if tests are inaccurate or if results are misinterpreted. Widespread testing also could greatly increase health costs and could lead to job or insurance discrimination.

This paper reports on a general population survey of attitudes toward genetic testing for Alzheimer’s disease. We examine five questions: (1) What share of people would take a genetic test for Alzheimer’s disease? (2) How much does the choice depend on the accuracy of the test? (3) How much would people pay for the information? (4) What would people do with information from a positive test? (5) How worried are people about confidentiality?

Genetic aspects of Alzheimer’s disease. Knowledge about genetic aspects of Alzheimer’s disease has advanced considerably in the past decade. Family members with early-onset dementia (under age sixty) have led to the discovery of three genes in which mutations cause Alzheimer’s disease.² Other than its early onset, this genetic form of Alzheimer’s disease is nearly indistinguishable from sporadic disease. While all known mutations in the three genes can cause early-onset Alzheimer’s disease, not all early-onset disease has been linked to mutations. Also, mutations are rare, likely representing fewer than 1 percent of Alzheimer’s disease cases.³

A second means by which genetic factors influence disease expression is by enhancing the risk for late-onset disease. The apolipoprotein E4 allele (APOE*E4), which has received attention as a genetic risk factor, increases the risk of developing Alzheimer’s disease. Apolipoprotein E is a monomeric glycoprotein originally identified as an important intermediary in lipid metabolism. The APOE gene, on chromosome 19, has three well-studied alleles: APOE*E2, APOE*E3, and APOE*E4. Several studies have shown an increased frequency of the APOE*E4 allele in persons with Alzheimer’s disease compared with controls.⁴ But not all persons with APOE*E4 alleles will develop Alzheimer’s disease, nor do all persons with Alzheimer’s disease carry an APOE*E4 allele. Therefore, APOE is neither necessary nor sufficient for the development of Alzheimer’s disease.

There is also an increased risk of developing Alzheimer’s disease associated with increasing copies of the APOE*E4 allele. However, the relatively low frequency of the allele in the general and Alzheimer’s disease populations limits the utility of APOE genotype testing. Based on published data, the presence or absence of the APOE*E4 allele is not very useful to distinguish Alzheimer’s disease from other causes of dementia, given its low sensitivity and specificity.⁵

Recommendations from leaders in the field state that APOE genotype testing not be ordered to diagnose Alzheimer’s disease in persons with dementia or possible dementia.⁶ They also state that it should not be ordered as a screening test to predict Alzheimer’s disease in asymptomatic persons, although they state that research on APOE genotype testing is appropriate. Other genetic risk factors are beginning to emerge; they require further evaluation.⁷

Public attitudes about and understanding of genetic testing. Relatively little is known about attitudes regarding genetic testing for Alzheimer’s disease. One study of a convenience sample of cognitively normal persons found that 69 percent would obtain predictive testing; the desire for testing did not vary with age, sex, race, or income but was higher among those with a family history of Alzheimer’s disease.⁸ Studies of family members of Alzheimer’s patients have revealed a high interest in predictive testing, although other studies have found that many persons, both at risk and not, would not favor testing, because of concerns about the effect of unfavorable results on children, spouses, or themselves.⁹

Researchers have found that most older persons would want to be told of a diagnosis of Alzheimer’s disease.¹⁰ Those wanting to know were more likely to know someone who had dementia. Reasons for wanting to know the diagnosis included financial planning (84.7 percent) and settling family matters (76.6 percent).

Some research on genetic testing for cancer has found strong support for presymptomatic genetic testing among at-risk persons.¹¹ Others have reported that many persons at low risk of hereditary cancer would seek testing as a means of obtaining reassurance.¹² Perceived risk of getting cancer has been found to be predictive of who obtains or states an intention to get genetic testing.¹³ However, a body of studies underscore the confusion and anxiety surrounding genetic testing.¹⁴

Data And Methods

Top Data And Methods Study Results Discussion And Policy... NOTES

 
Survey design. A telephone survey was administered to a random sample of U.S. adults in February–March 2001. The survey instrument was refined based on 200 respondents at a public festival in Boston. The instrument briefly described Alzheimer’s disease, noting that most people who get Alzheimer’s are older than age sixty-five and that the prevalence rate is one in ten Americans. The instrument also stated that there is no prevention or cure. Respondents were then asked about their willingness to take a blood test that would tell them now whether they would one day develop Alzheimer’s disease. Respondents’ maximum willingness to pay for the test was elicited for those willing to take the test. Willingness to pay is a standard measure of how people value health interventions, consistent with individual preferences and welfare economics.¹⁵

The willingness-to-pay questions followed a binary (yes/no) bidding game format, with respondents randomized to one of four initial amounts: $100, $500, $1,000, and $1,500. If respondents answered yes to the initial bid, they were asked whether they would pay double that amount. Those answering no to the initial bid were asked whether they would pay half. The double-bounded, dichotomous-choice format permits an analysis of the willingness-to-pay data as a survival analysis with censoring.¹⁶

Respondents also were asked if they would take an "imperfect" or partially predictive blood test to predict Alzheimer’s disease. They were told to assume that there was a one in ten chance that they would not get the disease, despite a positive test, and that there was a one in ten chance that they would get it when the test said they would not. Willingness to pay for this test was also assessed with respondents randomized to $50, $200, $400, or $800.¹⁷

Finally, respondents were asked what they would do with information from a positive test, whom they would tell, how worried they would be about others gaining access to test information, and a series of background questions about whether they had a family history of Alzheimer’s disease and whether they had ever personally cared for someone with the disease.

Study sample. Data were collected by CODA Inc., a survey research firm with expertise in health-related data collection. Potential respondents were identified using random-digit-dialing techniques. Contact with an adult in the household was obtained during the first call, and the potential survey respondent was identified as the household resident age eighteen or older, with the most recent birthday. The survey was administered during the initial call if possible, or at a later time when the identified adult respondent was available. Respondents were offered $5 as an incentive for their participation. Information was obtained from 314 interviews—47 percent of eligible households. The lower-than-desired response rate largely reflects difficulties making initial contacts with persons, rather than outright refusals to participate, a common problem in random-digit-dialed surveys.¹⁸

Study Results

Top Data And Methods Study Results Discussion And Policy... NOTES

 
The mean age of respondents was 43.3 years. Respondents were predominantly female; white, non-Hispanic; and in excellent or very good health (Exhibit 1). Sixteen percent reported having had a family member with Alzheimer’s disease, and 24 percent reported providing care to someone with Alzheimer’s.¹⁹

Respondents stating that they would not want to take the test cited living with the burden of the disease (68.5 percent) and the fact that there were no preventive treatments (61.1 percent) as their main concerns.²² Only 30.4 percent of negative respondents noted privacy/confidentiality as an important concern.

When asked what they would do with information from a positive test, a majority of respondents (who were allowed to choose one or more options from a list) stated that they would sign advance directives, spend more time with family, get their finances in order, and/or buy long-term care insurance (Exhibit 4). Nearly one-third stated that they were worried that someone other than themselves or their physician would gain access to the information. Most respondents stated that if they received a positive test, they would tell their spouse, children, family, and friends.

Top Data And Methods Study Results Discussion And Policy... NOTES

The data suggest that people would value this knowledge for both personal and economic reasons. Respondents stated, for example, that they would spend more time with family and organize their finances. Moreover, a majority stated that they would obtain advance directives or purchase long-term care insurance. Importantly, though, many fewer people wanted the partially predictive test. The results have implications for a number of key decision makers.

Implications for individuals and families. For individuals, the availability of genetic testing will inevitably create new choices and dilemmas. Our data suggest that people may have strong personal preferences for testing information, although not necessarily for immediate health or medical reasons. Inclination to take the genetic test was strongest among those stating a family history of Alzheimer’s disease or experience caring for someone with the illness; this suggests that more knowledge may increase demand for testing. Relatively few expressed concerns over others’ obtaining access to their test information. This may indicate a perception that test information about a geriatric disease is less likely to affect employment or insurance.

But the data also suggest the value of counseling potential test recipients. While a large majority of respondents wanted the completely predictive test, many more declined testing after being given information about the possibility of inaccurate results. Research on preferences for genetic testing for Huntington’s disease yielded similar findings.²³ The results highlight the importance of having a genetic counselor involved in the process before and after testing.

Implications for clinicians. For health professionals, the data raise questions about patients’ access to information. Clinicians have actively debated whether to inform patients about a diagnosis of Alzheimer’s disease, especially given that patients may not be able to comprehend or remember the information.²⁴ Current guidelines recommend that patients be told about an Alzheimer’s diagnosis, although many clinicians do not follow this practice.²⁵

Telling people about their genetic predisposition for Alzheimer’s disease raises additional questions. Individuals’ rights to know about their genetic composition must be weighed against concerns that they will misinterpret the data or be unduly burdened or stigmatized, given the low sensitivity and specificity of existing tests and the lack of preventive or curative measures. As noted, leaders in the field currently recommend against APOE genotype testing for these reasons.²⁶ Our data generally support these recommendations, particularly since the predictive values of the hypothetical tests in our survey are higher than would be expected with currently available tests. But the results also suggest that more work is needed in this area. Importantly, our data suggest that genetic testing could lead more people to obtain advance directives and long-term care insurance. Testing also could encourage people to engage in behavior that promotes cognitive vitality in aging, including exercise, social engagement, stress reduction, and proper nutrition.²⁷

Cost and access. Widespread testing for Alzheimer’s and other diseases could raise health costs. Questions will increasingly emerge about optimal strategies for testing, given the costs and predictive values of tests, the availability of treatments, and individual preferences. Formal cost-effectiveness analyses of testing and treatment options would be helpful.²⁸ The high rates of caregiving in our sample also highlight the societal impact of Alzheimer’s disease on individuals, families, and employers.²⁹

Discrimination and stigma. The results also have implications for ongoing debates about genetic discrimination. Conceivably, one’s decision about whether to obtain a genetic test for Alzheimer’s disease could be influenced by concerns about the general stigma associated with the disease or by anxiety over one’s ability to obtain health insurance, life insurance, or employment.³⁰

Recent legislation and administrative rulings have begun to address the issue. At the federal level, for example, the Health Insurance Portability and Accountability Act (HIPAA) of 1996 prohibits insurers from considering a genetic trait without the manifestation of disease as a preexisting condition for coverage purposes.³¹ A year 2000 executive order signed by President Bill Clinton prohibits federal agencies from using genetic information in hiring or promotion of employees.³² Most states have passed legislation that limits genetic-discrimination in employment, and several have passed genetic privacy laws that restrict disclosure of, and access to, genetic information without informed consent.³³ However, enforcement is uneven and the extent to which the laws influence behavior is not clear.

Study limitations. The results presented here should be interpreted with caution for a number of reasons. First, the relatively low response rate to our survey (47 percent) raises questions about representativeness. In particular, persons who chose to participate may be more familiar with Alzheimer’s disease than is the general population. If true, this could have inflated our estimates regarding respondents’ inclination to take the genetic test, as well as their willingness to pay for test information, and could have affected their conclusions about what they would do with test information.

The fact that 24 percent said that they had cared for someone with Alzheimer’s disease may suggest a possible response bias, because the number seems high, given the prevalence of the disease in the population (6–8 percent of persons over age sixty-five). But the estimate may simply reveal heightened awareness of and experience with the disease and may itself be inflated because people may mistake other forms of dementia for Alzheimer’s disease.³⁴ In addition, the caregiver estimate in our sample may include caregiving by respondents who are health professionals. Furthermore, it is important to note that even if knowledge about the disease in our sample is somewhat higher than average, inclination to receive testing was not substantially higher among those with family history or caregiving experience, compared with those without, and differences were not significant.

Another concern relates to the hypothetical nature of the questions. While people may claim on surveys that they would obtain a genetic test, in reality they may not actually do so; in similar fashion, respondents who stated that they would purchase long-term care insurance might not follow through with this action.

There are also concerns about the effect of the framing of questions, particularly with respect to how responses might vary with alternative wording about the accuracy of the partially predictive test, and with alternative sequences of questions.

Finally, the predictive values of the tests stated in our survey were higher than would be expected with existing genetic testing. For the sake of simplicity, we told respondents to assume that the partially predictive test had a one in ten chance of being incorrect. Given the low sensitivity and specificity of currently available APOE tests, actual predictive rates would be much lower.

We thus recommend that caution be exercised in interpreting our results and that this study be viewed as exploratory in nature. As noted, little is known about public preferences toward genetic testing for Alzheimer’s disease. This study contributes new information to the debate, but more research is needed in many areas.

Editor's Notes

 
Peter Neumann is assistant professor of policy and decision sciences and deputy director of the Program on the Economic Evaluation of Medical Technology at the Harvard School of Public Health in Boston, Massachusetts. James Hammitt is associate professor of economics and decision sciences, Center for Risk Analysis, Harvard School of Public Health. Curt Mueller is a senior research director at the Project HOPE Center for Health Affairs in Bethesda, Maryland. Howard Fillit is executive director of the Institute for the Study of Aging in New York City. Jerrold Hill is director of outcomes research there. Nii Tetteh is a student at Harvard Medical School, in the Harvard/MIT Division of Health Sciences and Technology. Ken Kosik is professor of neurology and neuroscience, Brigham and Women’s Hospital and Harvard Medical School.

This project was funded by a grant from the Institute for the Study of Aging. The authors are grateful to Richard Chapman and Ying Zhou for statistical and programming assistance.

NOTES

Top Data And Methods Study Results Discussion And Policy... NOTES

 

1. J. Kahn, "Ethical Issues in Genetic Testing for Alzheimer’s Disease," Geriatrics 52 (Supp. 2 1997): S30–S32.
2. T.W. Kim and R.E. Tanzi, "Presenilins and Alzheimer’s Disease," Current Opinion-in Neurobiology 7, no. 5 (1997): 683–688; and D.J. Selkoe, "Translating Cell Biology into Therapeutic Advances in Alzheimer’s Disease," Nature 399, no. 6738 Supp. (1999): A23–A31.[Medline]
3. K.S. Kosik, S.G. Post, and K.A. Quaid, "An Ethical Context for Presymptomatic Testing in Alzheimer’s Disease," in Early Diagnosis of Alzheimer’s Disease, ed. L.F.M. Scinto and K.R. Dafner (Totowa, N.J.: Humana Press, 2000).
4. E.H. Corder et al., "Gene Dose of Apolipoprotein E Type 4 Allele and the Risk of Alzheimer’s Disease in Late Onset Families," Science 261, no. 5123 (1993): 921–923[Abstract/Free Full Text]; and T. Polvikoski et al., "Apolipoprotein E, Dementia, and Cortical Deposition of Beta-Amyloid Protein," New England Journal of Medicine 333, no. 19 (1995): 1242–1247.[Abstract/Free Full Text]
5. R. Mayeux et al., "Utility of the Apolipoprotein E Genotype in the Diagnosis of Alzheimer’s Disease," New England Journal of Medicine 338, no.8 (1998): 506–511[Abstract/Free Full Text]; A.M. Saunders et al., "Specificity, Sensitivity, and Predictive Value of Apolipoprotein-E Genotyping for Sporadic Alzheimer’s Disease," Lancet 348, no. 9020 (1996): 90–93[Medline]; and M.R. Meyer, J.T. Tschanz, and M.C. Norton, "APOE Genotype Predicts When—Not Whether—One Is Predisposed to Develop Alzheimer Disease," Nature Genetics (August 1998): 321–322.
6. S.G. Post et al., "The Clinical Introduction of Genetic Testing for Alzheimer Disease: An Ethical Perspective," Journal of the American Medical Association 277, no. 10 (1997): 832–836.[Abstract/Free Full Text]
7. L. Bertram et al., "Evidence for Genetic Linkage of Alzheimer’s Disease to Chromosome 10q," Science 290, no. 5500 (2000): 2302–2303[Abstract/Free Full Text]; A. Myers et al., "Susceptibility Locus for Alzheimer’s Disease on Chromosome 10," Science 290, no. 5500 (2000): 2304–2305[Abstract/Free Full Text]; and N. Ertekin-Taner et al., "Linkage of Plasma ABeta42 to a Quantitative Locus on Chromosome 10 in Late-Onset Alzheimer’s Disease Pedigrees," Science 290, no. 5500 (2000): 2303–2304.[Abstract/Free Full Text]
8. R.C. Green et al., "Early Detection of Alzheimer Disease: Methods, Markers, and Misgivings," Alzheimer Disease and Related Disorders 11, Supp. 5 (1997): S1–S5.
9. See, for example, C.P. Maguire et al., "Family Members’ Attitudes toward Telling the Patient with Alzheimer’s Disease Their Diagnosis," British Medical Journal 313, no. 7056 (1996): 529–530[Free Full Text]; J.S. Roberts, "Anticipating Response to Predictive Genetic Testing for Alzheimer’s Disease: A Survey of First-Degree Relatives," Gerontologist 40, no. 1 (2000): 43–52[Abstract]; and M. Welkenhuysen et al., "Attitudes toward Predictive Testing for Alzheimer’s Disease in a Student Population," Psychiatric Genetics (Autumn 1997): 121–126.
10. See, for example, E.L. Erde, E.C. Nadal, and T.O. Scholl, "On Truth Telling and the Diagnosis of Alzheimer’s Disease," Journal of Family Practice 26, no. 4 (1988): 401–406.[Medline]
11. See, for example, O. Bratt et al., "Risk Perception, Screening Practice, and Interest in Genetic Testing among Unaffected Men with Hereditary Prostate Cancer," European Journal of Cancer 36, no. 2 (2000): 235–241.
12. M. Andrykowski et al., "Hereditary Cancer Risk Notification and Testing: How Interested Is the General Population?" Journal of Clinical Oncology 15, no. 5 (1997): 2139–2148.[Abstract/Free Full Text]
13. A.M. Codori et al., "Attitudes toward Colon Cancer Gene Testing: Factors Predicting Test Uptake," Cancer Epidemiology, Biomarkers, and Prevention 8, no. 4 (1999): 345–351[Medline]; and K. Glanz et al., "Correlates of Intentions to Obtain Genetic Counseling and Colorectal Cancer Gene Testing among At-Risk Relatives from Three Ethnic Groups," Cancer Epidemiology, Biomarkers, and Prevention 8, no. 4 (1999): 329–336.[Medline]
14. A.L. Wroe, P.M. Salkovskis, and K.A. Rimes, "The Prospect of Predictive Testing for Personal Risk: Attitudes And Decision Making," Behavior Research and Therapy 36, no. 6 (1998): 599–619[Medline]; Kahn, "Ethical Issues";; M.A. Drickamer and M.S. Lachs, "Should Patients with Alzheimer’s Disease Be Told Their Diagnosis?" New England Journal of Medicine 326, no. 14 (1992): 947–951[Medline]; and J.L. Benkendorf et al., "Patients’ Attitudes about Autonomy and Confidentiality in Genetic Testing for Breast-Ovarian Cancer Susceptibility," American Journal of Medical Genetics 73, no. 3 (1997): 296–303.[Medline]
15. J.A. Olsen and R.C. Smith, "Theory versus Practice: A Review of ‘Willingness-to-Pay’ in Health and Health Care," Health Economics 10, no. 1 (2001): 39–52.[Medline]
16. For each person, we have lower and upper bounds on willingness to pay (where the lower bound may be zero and the upper bound may be infinite). The analysis typically requires an assumption about the underlying distribution of data, although nonparametric alternatives are available. For the results reported here, we assumed a lognormal distribution, although we also conducted the analysis under alternative assumptions with similar results. All analyses were conducted using the lifereg procedure in SAS. See, for example, W.M. Hanemann, J. Loomis, and B. Kanninen, "Statistical Efficiency of Double-Bounded Dichotomous Choice Contingent Valuation," American Journal of Agricultural Economics (November 1991): 1255–1263.
17. Initial bid amounts for the imperfect test were based on the bids for the perfect tests (complete randomization to bid amounts for the imperfect test was deemed illogical, because it meant that a person could be asked a much higher bid for an imperfect test after rejecting a much lower bid for the perfect test). Specifically, respondents who received an initial bid of $100 for the perfect test received a bid of $50 for the imperfect test. Respondents who received initial bids of $500, $1,000, and $1,500 for the perfect test received initial bids of $200, $400, and $800, respectively, for the imperfect test.
18. See R.M. Hoffman and F.D. Gilliland, "A Population-Based Survey of Prostate Cancer Testing in New Mexico," Journal of Community Health (December 1999): 409–419; and K.B. Weiss, E.N. Grant, and T. Li, "The Effects of Asthma Experience and Social Demographic Characteristics on Responses to the Chicago Community Asthma Survey-32," Chest 116, 4 Supp. 1 (October 1999): 183S–189S. In general, a survey’s response rate is the number of completed survey interviews divided by the total number of "eligible units" sampled for study. In this survey, an "eligible unit" was a household that met the survey’s screening criteria. Screening criteria required that at least one adult reside in the household and that the selected adult be present and capable of communicating with the interviewer. In this random-digit-dialed survey, the number of eligible units was not simply the number of completed interviews plus the number of households refusing to participate. In our survey, callers failed to reach someone at more than 230 telephone numbers, believed to be households and likely eligible units, because calls ended with a hang-up or an answering machine response. The mean number of callbacks by interviewers to these numbers was 15.4, and the median number was 18. In estimating our response rate, we used data from completed interviews to make assumptions about the eligibility of phone numbers at which no definitive contact could be ascertained. We assumed that about 99 percent of numbers were households and that 90 percent of households met eligibility criteria. Therefore, about 89 percent (0.99 x 0.90) of the noncontacts were assumed to be eligible units.
    Our response rate calculation follows recommendations published by the American Association for Public Opinion Research, using the approach developed for the National Immunization Survey sponsored by the U.S. Centers for Disease Control and Prevention, a random-digit-dialed survey with a household screener. AAPOR, Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for RDD Telephone Surveys and In-Person Household Surveys (Ann Arbor, Mich.: AAPOR, 1998); and T.M. Ezzati-Rice et al., "Estimating Response Rates in Random-Digit-Dialing Surveys That Screen for Eligible Subpopulations" (Paper presented at the International Conference on Survey Non-response, Portland, Oregon, 28–31 October 1999), <www.jpsm.umd.edu/icsn/papers/EzzatiRiceCoronado.htm> (29 June 2001).
19. Specifically, respondents were asked whether any of their grandparents, parents, or brothers or sisters had ever had Alzheimer’s disease.
20. In multivariate analysis the independent predictors of taking the completely predictive test included lower income (p = .05) and lower education (p = .03). Results were similar for analyses predicting inclination to take the partially predictive test.
21. In multivariate analysis predicting willingness to pay for the completely predictive test, age was negatively related to willingness to pay (p = .002), and nonwhites had higher willingness to pay than whites did (p = .004). Other variables, including income, family history, and experience caring for someone with Alzheimer’s disease, were not independent predictors. For the partially predictive test, only sex was an independent predictor, with males having higher willingness to pay (p = .03).
22. These responses were assessed on a five-point scale, where 1 was that the factor was "not important at all" and 5, "very important." These figures represent those who answered 4 or 5.
23. R. Babul et al., "Attitudes toward Direct Predictive Testing for the Huntington Disease Gene: Relevance for Other Adult-Onset Disorders," Journal of the American Medical Association 270, no. 19 (1993): 2321–2325[Abstract/Free Full Text]; and M. Burgess, "Ethical Issues in Genetic Testing for Alzheimer’s Disease: Lessons from Huntington’s Disease," Alzheimer Disease and Associated Disorders 8, no. 2 (1994): 71–78.[Medline]
24. Erde et al., "On Truth Telling";; Drickamer and Lachs, "Should Patients with Alzheimer’s Disease Be Told?" and Maguire et al., "Family Members’ Attitudes toward Telling the Patient."
25. R.A. Clafferty, K.W. Brown, and E. McCabe, "Under Half of Psychiatrists Tell Patients Their Diagnosis of Alzheimer’s Disease," British Medical Journal 317, no. 7158 (1998): 603.[Free Full Text]
26. Post et al., "The Clinical Introduction of Genetic Testing."
27. Institute for the Study of Aging, "Achieving and Maintaining Cognitive Vitality with Aging," Workshop Report (New York: ISA, 2001).
28. S.S. Araki, K.M. Kuntz, and P.J. Neumann, "Cost-Effectiveness of Screening and Treating Early Alzheimer’s Disease," Medical Decision Making 18, no. 4 (1998): 456 (abstract)[Free Full Text]; and P.M. McMahon et al., "The Cost-Effectiveness of Functional Imaging Tests in the Diagnosis of Alzheimer’s Disease," Radiology 217, no. 1 (2000): 58–68.[Abstract/Free Full Text]
29. D.P. Rice et al., "The Economic Burden of Alzheimer’s Disease Care," Health Affairs (Summer 1993): 164–176; and J. Leon, C.K. Cheng, and P.J. Neumann, "Alzheimer’s Disease Care: Costs and Potential Savings," Health Affairs (Nov/Dec 1998): 206–216.
30. K. Hudson et al., "Genetic Discrimination and Health Insurance: An Urgent Need for Reform," Science 270, no. 5235 (1995): 391–393[Abstract/Free Full Text]; and S.M. Wolf, "Beyond ‘Genetic Discrimination’: Toward the Broader Harm of Geneticism," Journal of Law, Medicine and Ethics 23, no. 4 (1995): 345–349.[Medline]
31. P.L. 104–191, 104th Congress, 2d sess. (1996).
32. Federal Register 65 (10 February 2000): 6877.[Medline]
33. L.O. Gostin et al., "The Public Health Information Infrastructure: A National Review of the Law on Health Information Privacy," Journal of the American Medical Association 275, no. 24 (1996): 1921, 1923–1925[Abstract/Free Full Text]; R.A. Bornstein, "Genetic Discrimination Insurability and Legislation: A Closing of the Legal Loopholes," Journal of Law and Policy 4,no. 2 (1996): 551–610; and K. Rothenberg et al., "Genetic Information and the Work-Place: Legislative Approaches and Policy Challenges," Science 275, no. 5307 (1997): 1755–1757.[Free Full Text]
34. Also, the fact that 16 percent indicated family history of Alzheimer’s disease is plausible; if, for example, the risk of Alzheimer’s is 7 percent for those over age sixty-five, the probability that one has family history, given two family members over age sixty-five, is 1–(1–0.07)² = 14 percent.

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