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Alzheimer's Association International Conference 2026

July 12-15, 2026 | London, United Kingdom, and Online

4535

Financial Decision-making Ability And Subjective Cognitive Decline In Older Adults: Armcada Project

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Poster Presenter

Emily Ho

Authors

Emily H. Ho, Berivan Ece, Patricia Bucko, Y. Catherine Han, Elizabeth M. Dworak, Shahin Davoudpour, Sarah Pila, S. Duke Han, Peter Lichtenberg, Sandra Weintraub, Richard C. Gershon

Affiliations

Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Institute of Gerontology, Wayne State University, Department of Psychology, University of Southern California, Mesulam Institute for Cognitive Neurology and Alzheimer’s Disease, Northwestern University Feinberg School of Medicine

Part of Topic

Financial decision-making ability and subjective cognitive decline in older adults: ARMCADA Project

P-0798

*Emily H. Ho1, Berivan Ece1, Patricia Bucko1, Y. Catherine Han1, Elizabeth M. Dworak1, Shahin Davoudpour1, Sarah Pila1, S. Duke Han2, Peter Lichtenberg3, Sandra Weintraub 4,5, and Richard Gershon1

1Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL  2Department of Psychology, University of Southern California, Los Ange

les, CA  3Institute of Gerontology, Wayne State University, Detroit, MI  4Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL  5Mesulam Institute for Cognitive Neurology and Alzheimer’s Disease, Northwestern University Feinberg School of Medicine, Chicago, IL     

BRIEF, EASILY ADMINISTERED FINANCIAL DECISION-MAKING MEASURES CAN HELP IDENTIFY INDIVIDUALS WITH GREATER FINANCIAL VULNERABILITY AND SUBJECTIVE COGNITIVE CONCERNS, HIGHLIGHTING THEIR PROMISE AS EARLY INDICATORS OF COGNITIVE DECLINE AND DEMENTIA-RELATED RISK.

Financial decision-making (FDM) is the ability to independently manage finances by evaluating options that align with personal values and interests, while avoiding errors or loss.1

Well-validated FDM assessment tools are critical for detecting subtle functional changes linked to early neurodegeneration and for distinguishing normal aging from cognitive loss caused by Alzheimer’s disease and related dementias (AD/ADRD).

The ARMCADA (Advancing Reliable Measurement in Cognitive Aging and Decision-making Ability) project identified FDM measures with high potential to be included in a multidomain DM battery for adults (45+).

We evaluate the feasibility and reliability of these measures and examine their associations with self-reported subjective cognitive decline (SCD) and behavioral measures of vulnerability to financial fraud. 

This pilot study included 152 adults over 40 (61.8% participants aged 60 and above; 59.9% female) from rural (20.4%), suburban (57.9%), and urban (20.4%) regions in the United States.

Participants completed measures assessing FDM (Table 1) along with:

Measures of SCD (Everyday Cognition Scale [Ecog-12]2; Memory Complaint Scale [MCS])

PROMIS depression, anxiety, and social isolation scales

Contextual financial questions

Feasibility: >97% completion; <1–3 min/measure.

Reliability: α/KR-20 = .48–.91.

Financial ignorance: Higher ignorance linked to greater FE vulnerability (r = .54).

Phishing susceptibility: Higher credibility ratings linked to greater scam susceptibility and financial ignorance, and poorer judgment and financial knowledge (rs = |.23–.31|).

Financial security: Contextual questions related to greater financial/retirement security, future confidence, and financial knowledge linked to lower FE vulnerability (rs= −.35 to −.66).

Cognition: Greater financial ignorance and FE vulnerability linked to poorer everyday cognition and more memory complaints (rs = .28–.50).

Significance: All associations p < .05.

Findings support the feasibility of administering the selected FDM measures in adults over 40.

Distinct aspects of financial knowledge and vulnerability appear to be associated with the ability to identify individuals at increased risk of phishing and subjective cognitive decline.

Further refinement of these measures can increase predictive validity for detecting early cognitive changes and financial vulnerability associated with AD/ADRD.

1 Chiong, W., Hsu, M., Wudka, D., Miller, B. L., & Rosen, H. J. (2014). Financial errors in dementia: testing a neuroeconomic conceptual framework. Neurocase, 20(4), 389–396. https://doi.org/10.1080/13554794.2013.770886

2 Tomaszewski Farias, S., Mungas, D., Harvey, D. J., Simmons, A., Reed, B. R., & Decarli, C. (2011). The measurement of everyday cognition: development and validation of a short form of the Everyday Cognition scales. Alzheimer's & dementia : the journal of the Alzheimer's Association, 7(6), 593–601. https://doi.org/10.1016/j.jalz.2011.02.007

3 Ho, E. H., Budescu, D. V., & Himmelstein, M. (2025). Measuring probabilistic coherence to identify superior forecasters. International Journal of Forecasting, 41(2), 596–612. https://doi.org/10.1016/j.ijforecast.2024.02.005

4 Forsythe, R., Horowitz, J. L., Savin, N. E., & Sefton, M. (1994). Fairness in simple bargaining experiments. Games and Economic Behavior, 6(3), 347–369.

5 Lichtenberg, P. A., Campbell, R., Hall, J. R., & Gross, E. Z. (2020). Developing and validating the Financial Exploitation Vulnerability Scale. Journal of Elder Abuse & Neglect, 32(2), 125–145.

6 Lusardi, A., & Mitchell, O. S. (2006). Financial literacy and retirement preparedness: Evidence and implications for financial education programs (Working Paper). Michigan Retirement Research Center. https://doi.org/10.2139/ssrn.957796

7 Lichtenberg, P. A., Campbell, R., Hall, J. R., & Gross, E. Z. (2020). Developing and validating the Financial Exploitation Vulnerability Scale. Journal of Elder Abuse & Neglect, 32(2), 125–145.

8 Beach, S. R., Czaja, S. J., & Schulz, R. (2023). Novel methods for assessment of vulnerability to financial exploitation (FE). Journal of elder abuse & neglect, 35(4-5), 151–173. https://doi.org/10.1080/08946566.2023.2281672

9 Fagerlin, A., Zikmund-Fisher, B. J., Ubel, P. A., Jankovic, A., Derry, H. A., & Smith, D. M. (2007). Measuring numeracy without a math test: Development of the Subjective Numeracy Scale. Medical Decision Making, 27(5), 672-680. doi: 10.1177/0272989X07304449

10 Cokely, E. T., Galesic, M., Schulz, E., Ghazal, S., & Garcia-Retamero, R. (2012). Berlin Numeracy Test [Database record]. APA PsycTests. https://doi.org/10.1037/t45862-000

11 Barrafrem, K., Västfjäll, D., & Tinghög, G. (2024). Financial Homo Ignorans: Development and validation of a scale to measure individual differences in financial information ignorance. Journal of Behavioral and Experimental Finance, 42, 100936. https://doi.org/10.1016/j.jbef.2024.100936

12 James, B. D., Boyle, P. A., & Bennett, D. A. (2014). Susceptibility to Scams Scale [Database record]. APA PsycTests. https://doi.org/10.1037/t62359-000

13 Federal Trade Commission. (n.d.). Phishing quiz. U.S. Department of Commerce. https://www.ftc.gov/tips-advice/business-center/small-businesses/cybersecurity/quiz/phishing

14 Rabin, L. A., Borgos, M. J., Saykin, A. J., Wishart, H. A., Crane, P. K., Nutter-Upham, K. E., & Flashman, L. A. (2007). Judgment in older adults: Development and psychometric evaluation of the Test of Practical Judgment (TOP-J). Journal of Clinical and Experimental Neuropsychology, 29(7), 752–767. https://doi.org/10.1080/13825580601025908

This work is supported by NIA grant #1U24AG082022. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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