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Self-Efficacy in Insurance Decision Making Among Older Adults

The American Journal of Managed CareApril 2015
Volume 21
Issue 4

Older adults who prefer to delegate insurance decisions tend to be female and married, to have less Medicare knowledge, and to have someone in their lives they trust to make decisions for them.

ABSTRACTObjectives: The aim was to understand older adults’ self-efficacy with insurance decision making by examining their preferences for delegating insurance decisions to others.

Study Design: Cross-sectional analysis of data from an observational cohort study. Methods: English- and Spanish-speaking adults aged ≥60 years were recruited and interviewed in residential and senior center locations in New York City neighborhoods with median annual household incomes <$50,000. The analyses included the subset of individuals 65 years and older and without Medicaid. Self-efficacy in insurance decision making was measured with a 7-item assessment of perceived understanding of Medicare, preferences for decision support, and decision-making anxiety. We used multivariable linear regression to examine the association of self-efficacy with subject characteristics, including sociodemographics, insurance coverage, and health and functional status.

Results: Among the 250 subjects, 55% were aged ≥75 years, 29% were black, and 33% were Hispanic. Half (53%) reported difficulty understanding insurance information and concern (45%) about making wrong insurance choices, yet 89% preferred to make decisions themselves. In adjusted analysis, greater decision-making self-efficacy was associated with male gender (P = .02), higher educational attainment (P = .04), better health (P = .0003), greater Medicare knowledge (P = .0002), and lack of a spouse or partner (P = .04) or any person who they trust to assist with decision making (P <.0001).

Conclusions: Most older adults preferred to make insurance decisions themselves while also wanting to receive advice, and those who preferred to delegate decisions had less Medicare knowledge. Programs that support insurance decisions among older adults should identify clients who prefer delegating decisions and have the right support available to them.

Am J Manag Care. 2015;21(4):e247-e254

Older adults often prefer to delegate the selection of health plans. Those with that preference have poorer health, less education, and less knowledge of Medicare. They also tend to have a spouse and/or another person in their lives that they trust to make decisions for them.

  • This research extends existing knowledge by identifying the characteristics of older adults who prefer to delegate decisions about insurance coverage.
  • This information can be used by managed care decision makers to design programs that meet the decision support needs of their current and potential beneficiaries.
  • Such programs should be designed to promote confidence and trust.

Older Americans face a large number of health and prescription plan options through Medicare. In 2013, there were an estimated 37.5 million older adults enrolled in a Medicare Part D plan—two-thirds of them in a stand-alone prescription drug plan (PDP), and the remaining in a Medicare Advantage plan.1 In 2014, 1169 PDPs were offered nationwide, and on average, beneficiaries chose from 35 stand-alone plans.1 The vast number of choices in health and prescription plan options may enhance opportunities to obtain plans of higher quality at competitive costs, but also presents a challenge to informed decision making.2,3 Research shows that having many options to choose from increases the complexity of the decision-making process, affects the decision strategy utilized, and can result in suboptimal decision making.4-6 This may be a particularly challenging problem for older adults, in whom limitations in literacy and numeracy are fairly prevalent and significant.4,5 Further, multi-morbidity and polypharmacy add to the complexity of plan selection.4,5,7-12

The combination of a daunting array of insurance options, complex personal needs to consider (eg, provider choice, formularies, affordability), and barriers to understanding coverage options (eg, limited health literacy) may diminish an individual’s self-efficacy regarding his or her health insurance or prescription coverage decisions. Within the reasoned action framework, self-efficacy (or control), attitude, and social norms determine intentions, which ultimately influence behavior.13 Health literacy is a faculty realized in Medicare knowledge that affects self-efficacy, potentially influencing decision-making behaviors about insurance coverage. Self-efficacy—or the belief in one’s ability to organize and execute the courses of action needed to manage new situations&mdash;is a situation-specific internal evaluation14 and is associated with a wide range of behaviors.15 For example, older adults with high self-efficacy expectations are more likely to engage in positive health behaviors such as exercising and maintaining a low-fat diet.16 Similarly, an individual with high self-efficacy regarding insurance plan selection may be more likely to seek out information and take steps proactively to optimize their coverage. On the other hand, those with low self-efficacy may be more likely to delegate decisions about coverage

to others.

A preference for delegating insurance decisions to others may place individuals at greater risk of obtaining inadequate coverage upon initial enrollment, particularly if those assisting them are also not experts. Additionally, these individuals may be less likely to switch plans during open enrollment when their healthcare needs or current plan benefits change. However, whether older adults are “self-effective” decision makers, and how self-efficacy relates to the quality of the insurance choices they make, remain open questions. To inform this critical gap, we examined preferences for delegating insurance decisions in a cohort of community-dwelling older adults in New York City along with characteristics that might be associated with these preferences, including low health literacy.17


We examined perceived self-efficacy in prescription drug insurance decision making among independently living, English- and Spanish-speaking adults aged ≥60 years in Manhattan, New York City. Participants were recruited from 30 community-based settings, including 11 senior centers and 19 Naturally Occurring Retirement Communities (so designated by the New York City Department for the Aging) in zip code areas with median household incomes below $50,000. Senior centers were identified through New York City Department for the Aging listings, and federally supported low-income housing facilities were identified using a listing from the US Department of Housing and Urban Development. Each adult received $20 for a baseline interview and $20 for a follow-up interview—both were performed in English or Spanish by bilingual interviewers. For the purpose of this analysis, we excluded participants with Medicaid because New York state auto-assigns Medicaid beneficiaries to health plans and those below age 65 because we were focused on decision making among Medicare beneficiaries.

The study was approved by the Institutional Review Board of the Icahn School of Medicine at Mount Sinai, and written informed consent was obtained from all participants prior to the start of interviews. The funding organization had no role in the collection of data, its analysis or interpretation, or in the right to approve or disapprove publication of the finished manuscript.

Outcome Measures

The study’s main outcome is a validated measure of self-efficacy in insurance decision making.18,19 The 7 items in the survey address understanding of Medicare materials, individuals’ preferences for support when making insurance decisions, and anxiety associated with decision making. Self-efficacy contains 2 subdomains: capacity, the belief that one has the ability to accomplish a task; and autonomy, the belief that accomplishing the task is “up to you.”13 In our self-efficacy scale, items such as “I have difficulty understanding information about my health insurance” appear to reflect the capacity domain, while items such as “I would prefer to make decisions about my health insurance with the help of someone in my family” reflect aspects of the autonomy domain.13 Each question had 5 response options ranging from strongly agree to strongly disagree. Responses to all questions were summed to create a summary score of overall self-efficacy, with higher scores indicating greater preference for delegating decisions.

We also assessed subjects’ knowledge of the Medicare program with 9 true-or-false questions.18 These items required participants to identify Medicare fee-for-service and Medicare Advantage covered services (ie, mammography, prostate-specific antigen testing, flu shots), plan selection options, costs associated with fee-for-service Medicare and Medicare Advantage plans, prescription coverage, premium support, and access to clinicians. Correct answers were summed to provide an overall knowledge score.

Independent Variables

We included various measures that are associated with self-efficacy and which we hypothesized would be associated with a preference to delegate insurance decisions.14,20-23 These variables fell into demographic and experiential categories. Demographic characteristics included age, gender, race and ethnicity, English speaking ability, education, and health literacy. Health literacy was assessed with the Short Test of Functional Health Literacy in Adults (S-TOFHLA)24—a 36-item reading and 4-item numeracy assessment. There are 2 timed (7-minute) clinically oriented reading passages that omit key words and phrases from sentences, and the study participant chooses from 4 options to correctly complete the sentence. The numeracy section assesses the patient’s ability to read health information, such as that found on a prescription label, and to interpret numerical information. Overall scores range from 0 to 100. We dichotomized health literacy as adequate (score ≥67) or marginal and low (score <67).25 The S-TOFHLA has been validated for use in both English and Spanish.24

Experiential variables included current insurance coverage. The source of the primary insurance coverage was determined by the research assistant who reviewed the subjects’ insurance and prescription cards at the time of the interview. Coverage was categorized as traditional Medicare (fee-for-service), Medicare Advantage (private Medicare plan), and employer-sponsored or self-purchased insurance (excluding Medigap plans). Participants were also asked whether they knew of someone they could trust to help them if they needed help making a health insurance decision.

To further characterize study participants, we also assessed health status with a measure of general health, as well as number of chronic diseases and medications, history of hospitalization and emergency department (ED) use, and functional status. Functional status was measured using the basic and instrumental Activities of Daily Living (ADL and IADL, respectively) scales.26


Our analyses focused on the subset of individuals who were 65 years and older and did not have Medicaid as their primary source of coverage. We calculated Cronbach’s alpha to determine the inter-item correlation for the self-efficacy scale in the study sample. Since the scale was normally distributed, we conducted univariate analysis of the self-efficacy scale with subject characteristics using the t test or analysis of variance. Key variables of interest were then included in linear regression models. Post hoc model diagnostics found no evidence of collinearity among our regressors. All analyses were conducted with SAS version 9.3 (SAS Institute, Cary, North Carolina).


Subject Characteristics

A total of 451 individuals were recruited during site-sponsored meals or special events in the parent study. From this pool, 396 adults fully completed the portion of the survey assessing preferences for delegating insurance decisions. After exclusion of individuals 64 years and younger and those with Medicaid coverage, the final analytic sample was composed of 250 individuals.

Table 1

Of the 250 subjects, 55% were 75 years and older, and 35% were men (). The racial and ethnic distribution of the sample was 29% black, 38% white, and 33% Hispanic; 19% had less than a high school education, and 26% had low health literacy. Primary insurance coverage was evenly distributed between traditional (fee-for-service) Medicare (33%), Medicare Advantage (35%), and employer-sponsored coverage (31%); one-fourth (26%) had both Medicare and Medicaid coverage.

The health status of the population was mixed, but a significant burden of poor health was evident. Twenty-nine percent reported fair or poor health; two-thirds (65%) had hypertension, 24% had diabetes, 16% reported coronary heart disease, and 19% had 5 or more chronic health problems. Physical impairment was common, including ADL deficiencies in 17% and IADL deficiencies in 43%. With this level of illness and physical dysfunction, healthcare use was predictably high, including polypharmacy (48% used 5 or more prescription medications), and hospitalization (23%) and ED use (59%) in the past 12 months.

Knowledge About Medicare

Table 2

The average number of correct items on the Medicare knowledge assessment was 6.2 (SD = 1.6) (). Before adjustment, scores on the knowledge assessment were worse among individuals with lower health literacy (P = .01) and those who reported using the ED (P = .01), although those with Medicare Advantage had better Medicare knowledge—a measure that was of borderline statistical significance (P = .06). In multivariate analysis, having Medicare Advantage coverage was associated with having higher scores on the Medicare knowledge assessment compared with those with fee-for-service Medicare (β = 0.60 [0.26]; P = .02). No other variable was significantly associated with Medicare knowledge in the multivariate analysis.

Insurance Decision Self-Efficacy

Table 3

Half of patients (53%) reported having difficulty understanding information about their insurance and 45% expressed concern about making a wrong choice if they were to make the decision themselves (). Among 47% of subjects, having more insurance options was a source of concern about making wrong insurance choices.

A large majority of subjects (89%) expressed a desire for support with their decision making but wanted autonomy in the process, while only 15% reported letting another make the decision for them. However, there appeared to be some ambivalence regarding autonomous decision making, as 45% also agreed that they prefer to have someone knowledgeable about insurance decide for them.

Table 4

Cronbach’s alpha for the scale that combined the 7 items in the self-efficacy scale was 0.76, indicating high internal consistency. The mean (SD) value for the score was 13.7 (6.5), the median was 14.0, and the range was 0 to 28. Mean scores differed significantly across a number of demographic and experiential characteristics (). Before adjustment, variables associated with lower self-efficacy in insurance-related decisions included less knowledge about Medicare (P <.0001), education (P = .003), knowing a person who could help make insurance decisions (P = .0002), poor general health (P <.0001), and impairments in IADLs (P = .007).

A number of variables were significantly associated with self-efficacy in the multivariate regression analysis (Table 4). Variables associated with higher self-efficacy included high scores on the Medicare knowledge assessment (P = .0002) and male gender (P = .02). Variables associated with a lower insurance decision self-efficacy included having less than a high school education (P = .04), having a spouse or partner (P = .04), and being in worse health (P <.01).


The US healthcare system provides a rich array of insurance options; these options, however, present challenging decisions for older adults, and the implications for personal health and finances are significant.27,28 In this study of community-dwelling elders, we found that despite the complexity of insurance decisions, the large majority of subjects preferred to make the decisions themselves. Yet, in a nod to that complexity, they also expressed a preference for receiving advice, and many demonstrated a preference toward delegating insurance-related decisions to others. In other words, they had less insurance decision self-efficacy. Preference for delegating Medicare Part D decisions was associated with less Medicare knowledge, being female, having a spouse or partner, and having worse health.

We also found that those with less self-efficacy were less confident that their insurance was optimal for their needs. We did not determine directly if this reflects dissatisfaction with the choices others have made on their behalf or whether preference for delegating decisions is a marker of factors that directly impacts confidence. The latter possibility may be more likely since prior research found that the availability of a trusted source of advice (eg, a spouse) raised beneficiary confidence with insurance decisions.29 Overall, being able to depend on someone in the role of trusted social support is critical for many older adults who are otherwise ill-prepared to make decisions about coverage that best suits their needs.30

Our findings are consistent with previous research demonstrating that older adults and those with greater healthcare utilization are also more likely to make decisions about insurance on their own than are younger adults, yet are more likely to seek advice.31 The quality of insurance-related decisions made by older adults—that is, how well their decisions match their needs&mdash;is poorly understood. Nevertheless, preference for delegating has a significant impact on various health-related outcomes. Consumers who are more engaged in their decision making get more of the information they seek from their healthcare providers and have better health outcomes.32 This observation is consistent with findings of studies of self-efficacy, where greater self-efficacy is associated with better behavioral and health outcomes.16,23,33-36

Studies have shown that literacy levels in about 30% of the senior population are inadequate to perform health-related tasks10,11,37 and are related to lower levels of knowledge of Medicare38,39 as well as difficulty choosing between multiple plans.19 Older adults are also known to possess lower numeracy abilities due to declining cognitive functioning, which have been linked to poorer decision making, greater difficulty comprehending their medical condition, and worse mental and physical health.40 We found that older adults with low health literacy had lower Medicare knowledge scores, as did those with stronger preferences to delegate their insurance decisions. The findings suggest that those with limited health literacy may need greater assistance with selection of healthcare and prescription plans.


Our findings have important implications for support provided to older adults who face insurance decisions, such as upon initial enrollment in Medicare or during annual open enrollment periods. Specifically, individuals with a greater preference for delegating decisions were also less likely to be confident about their coverage, suggesting that persons making decisions on their behalf may not be making optimal decisions. Indeed, individuals providing social support frequently lack the skills to make optimal decisions for themselves or the beneficiary.29 For those managing or designing insurance counseling and support programs, attention should be paid to ensure that those who are less self-effective (ie, have a need or preference to delegate insurance decisions) have the right support available to them. This is especially important given that individuals who may have barriers to understanding insurance information, like poor English language skills, may also lack such supports. There is also a need to ensure that those who are more confident in their abilities to make sound coverage choices themselves have the right information available to them when it is needed. Additional research should be conducted to determine how well the choices made by such individuals match actual coverage needs and personal preferences, and how satisfied beneficiaries are with their choices.


This study has several limitations that deserve mention. We did not examine actual delegation of decisions by the study subjects nor did we evaluate the decisions that the subjects or their proxies made regarding their real-life insurance and prescription options. Such decisions might differ from hypothetical considerations about delegation preferences. While we studied a diverse sample of older adults from 30 community-based sites in New York City, the experience and preferences of adults in other areas could differ. Moreover, we used convenience sampling methods, which could have introduced bias. Nonetheless, the findings from this diverse sample of older, community-dwelling adults provide important insight into the process of insurance decision making in this population.


Evaluating those who have low self-efficacy in insurance decision making is important for appropriately targeting older adults for special support in the decision-making process. This is especially important given that those with more limited health literacy skills and greater healthcare burden are also less likely to have trusted social support. Meanwhile, additional research is needed to better understand the impact of insurance decision making and preference for delegating insurance decisions to others on satisfaction with coverage and aligning plan choices and beneficiaries’ coverage needs.Author Affiliations: Department of Urology (KK), and Division of General Internal Medicine (ADF), Icahn School of Medicine at Mount Sinai, New York, NY; Department of Healthcare Policy and Research, Virginia Commonwealth University School of Medicine (AJB), Richmond, VA; School of Psychology, Plymouth University (YH), Plymouth, United Kingdom.

Source of Funding: Paul B. Beeson Career Development Award in Aging from the National Institute on Aging (Dr Federman, 1K23AG028955-01).

Author Disclosures: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (KK, ADF); acquisition of data (ADF); analysis and interpretation of data (KK, AJB, YH, ADF); drafting of the manuscript (KK, AJB, YH, ADF); critical revision of the manuscript for important intellectual content (KK, AJB, YH, ADF); statistical analysis (ADF); provision of study materials or patients (ADF); obtaining funding (ADF); administrative, technical, or logistic support (ADF); and supervision (ADF).


Address correspondence to: Alex D. Federman, MD, MPH, Division of General Internal Medicine, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, Box 1087, New York, NY 10029. E-mail: alex.federman@mssm.edu.

1. The Medicare prescription drug benefit fact sheet. Kaiser Family Foundation website. http://kff.org/medicare/fact-sheet/the-medicareprescription-drug-benefit-fact-sheet/. Updated September 19, 2014. Accessed March 20, 2015.

2. Finucane ML, Mertz CK, Slovic P, Schmidt ES. Task complexity and older adults’ decision-making competence. Psychol Aging. 2005;20(1):71-84.

3. Finucane ML, Slovic P, Hibbard JH, Peters E, Mertz CK, MacGregor DG. Aging and decision-making competence: an analysis of comprehension and consistency skills in older versus younger adults considering health-plan options. J Behav Dec Mak. 2002;15(2):141-164.

4. Rice T, Hanoch Y, Cummings J. What factors influence seniors’ desire for choice among health insurance options? survey results on the Medicare prescription drug benefit. Health Econ Policy Law. 2010;5(4):437-457.

5. Hanoch Y, Rice T, Cummings J, Wood S. How much choice is too much? the case of the Medicare prescription drug benefit. Health Serv Res. 2009;44(4):1157-1168.

6. Hanoch Y, Miron-Shatz T, Cole H, Himmelstein M, Federman AD. Choice, numeracy, and physicians-in-training performance: the case of Medicare Part D. Health Psychol. 2010;29(4):454-459.

7. Petersen RC, Roberts RO, Knopman DS, et al. Mild cognitive impairment: ten years later. Arch Neurol. 2009;66(12):1447-1455.

8. Lopez OL, Jagust WJ, DeKosky ST, et al. Prevalence and classification of mild cognitive impairment in the Cardiovascular Health Study Cognition Study: part 1. Arch Neurol. 2003;60(10):1385-1389.

9. Baker DW, Gazmararian JA, Sudano J, Patterson M, Parker RM, Williams MV. Health literacy and performance on the Mini-Mental State Examination. Aging Ment Health. 2002;6(1):22-29.

10. Baker DW, Gazmararian JA, Sudano J, Patterson M. The association between age and health literacy among elderly persons. J Gerontol B Psychol Sci Soc Sci. 2000;55(6):S368-S374.

11. Gazmararian JA, Baker DW, Williams MV, et al. Health literacy among Medicare enrollees in a managed care organization. JAMA. 1999;281(6):545-551.

12. Sudore RL, Mehta KM, Simonsick EM, et al. Limited literacy in older people and disparities in health and healthcare access. J Am Geriatr Soc. 2006;54(5):770-776.

13. Perceived behavioral control and its determinants. Fishbein M, Ajzen I. In: Predicting and Changing Behavior: The Reasoned Action Approach. 1st ed. New York, NY: Psychology Press; 2010:153-178.

14. Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84(2):191-215.

15. Stajkovic AD, Luthans F. Self-efficacy and work-related performance: a meta-analysis. Psychological Bulletin. 1998;124(2):240-261.

16. Grembowski D, Patrick D, Diehr P, et al. Self-efficacy and health behavior among older adults. J Health Soc Behav. 1993;34(2):89-104.

17. Paasche-Orlow MK, Wolf MS. The causal pathways linking health literacy to health outcomes. Am J Health Behav. 2007;31(suppl 1):S19-S26.

18. Hibbard JH, Slovic P, Peters E, Finucane M. Older consumers’ skill in using comparative data to inform health plan choice: a preliminary assessment. AARP website. http://assets.aarp.org/rgcenter/health/2000_14_choice.pdf. Published September 2000. Accessed January 29, 2014.

19. Hibbard JH, Slovic P, Peters E, Finucane ML, Tusler M. Is the informed-choice policy approach appropriate for Medicare beneficiaries? Health Aff (Millwood). 2001;20(3):199-203.

20. Arora NK, Ayanian JZ, Guadagnoli E. Examining the relationship of patients’ attitudes and beliefs with their self-reported level of participation in medical decision-making. Med Care. 2005;43(9):865-872.

21. Clark NM, Dodge JA. Exploring self-efficacy as a predictor of disease management. Health Educ Behav. 1999;26(1):72-89.

22. Mancuso CA, Rincon M, McCulloch CE, Charlson ME. Self-efficacy, depressive symptoms, and patients’ expectations predict outcomes in asthma. Med Care. 2001;39(12):1326-1338.

23. Anderson ES, Winett RA, Wojcik JR. Self-regulation, self-efficacy, outcome expectations, and social support: social cognitive theory and nutrition behavior. Ann Behav Med. 2007;34(3):304-312.

24. Baker DW, Williams MV, Parker RM, Gazmararian JA, Nurss J. Development of a brief test to measure functional health literacy. Patient Educ Couns. 1999;38(1):33-42.

25. Federman AD, Wisnivesky JP, Wolf MS, Leventhal H, Halm EA. Inadequate health literacy is associated with suboptimal health beliefs in older asthmatics. J Asthma. 2010;47(6):620-626.

26. Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179-186.

27. Scanlon DP, Chernew M, Lave JR. Consumer health plan choice: current knowledge and future directions. Annu Rev Public Health. 1997;18:507-528.

28. Uhrig JD, Short PF. Testing the effect of quality reports on the health plan choices of Medicare beneficiaries. Inquiry. 2002-2003;39(4):355-371.

29. Sofaer S, Kreling B, Kenney E, Swift EK, Dewart T. Family members and friends who help beneficiaries make health decisions. Health Care Financ Rev. 2001;23(1):105-121.

30. Hanoch Y, Rice T. Can limiting choice increase social welfare? the elderly and health insurance. Milbank Q. 2006;84(1):37-73.

31. Bann CM, Berkman N, Kuo TM. Insurance knowledge and decision-making practices among Medicare beneficiaries and their caregivers. Med Care. 2004;42(11):1091-1099.

32. Hibbard JH, Cunningham PJ. How engaged are consumers in their health and health care, and why does it matter? Res Briefs. 2008;(8):1-9.

33. Cameron KA, Ross EL, Clayman ML, et al. Measuring patients’ selfefficacy in understanding and using prescription medication. Patient Educ Couns. 2010;80(3):372-376.

34. Chen SY, Sheu S, Chang CS, Wang TH, Huang MS. The effects of the self-efficacy method on adult asthmatic patient self-care behavior. J Nurs Res. 2010;18(4):266-274.

35. Lavoie KL, Bouchard A, Joseph M, Campbell TS, Favreau H, Bacon SL. Association of asthma self-efficacy to asthma control and quality of life. Ann Behav Med. 2008;36(1):100-106.

36. Martin MA, Catrambone CD, Kee RA, et al; Chicago Initiative to Raise Asthma Health Equity Investigative Team. Improving asthma self-efficacy: developing and testing a pilot community-based asthma intervention for African American adults. J Allergy Clin Immunol. 2009;123(1):153-159.e3.

37. Paasche-Orlow MK, Parker RM, Gazmararian JA, Nielsen-Bohlman LT, Rudd RR. The prevalence of limited health literacy. J Gen Intern Med. 2005;20(2):175-184.

38. Hibbard JH, Jewett JJ, Engelmann S, Tusler M. Can Medicare beneficiaries make informed choices? Health Aff (Millwood). 1998;17(6):181-193.

39. McCormack L, Bann C, Uhrig J, Berkman N, Rudd R. Health insurance literacy of older adults. J Consumer Affairs. 2009;43(2):223-248.

40. Wolf MS, Gazmararian JA, Baker DW. Health literacy and functional health status among older adults. Arch Intern Med. 2005;165(17):1946-1952.

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