Optimism and participation in breast cancer screening: evidence from the United States
DOI:
https://doi.org/10.71014/sieds.v80i2.511Abstract
This study investigates the influence of the personality trait of optimism on participation in breast cancer screening in the US. Breast cancer is the most common cancer among women in the US, accounting for approximately 30% of all new cancer diagnoses annually (American Cancer Society, 2025). Beyond sociodemographic factors, recent literature highlights the significant role of psychological factors, norms, and beliefs in the decision to participate in breast cancer screening. However, the impact of optimistic beliefs on screening uptake has not yet been explored. This study aims to address this gap.
We analyse a sample of approximately 4,500 women aged 50 and older from the US Health and Retirement Study (HRS) spanning 2006 to 2020. A dynamic probit panel data model with random effects is estimated, employing Mundlak’s (1978) approach to account for correlated individual effects. Our findings indicate that mammography uptake exhibits strong state dependence. Furthermore, optimism negatively influences mammography uptake among younger women (under 61 years) but positively affects the uptake among women aged 70 and over. These results can be interpreted through the lens of Prospect Theory (Kahneman and Tversky, 1979; Rothman and Salovey, 1997) and Socioemotional Selectivity Theory (Carstensen, 1995). Our findings suggest that policymakers should consider age-specific and psychologically tailored messaging strategies to enhance breast cancer screening adherence across diverse population groups.
References
AMERICAN CANCER SOCIETY. 2025. Key Statistics for Breast Cancer. https://www.cancer.org/cancer/types/breast-cancer/about/how-common-is-breast-cancer.html (last accessed 30 June 2025).
ASCHWANDEN D., GEREND M.A. LUCHETTI M., STEPHAN Y., SUTIN A.R., TERRACCIANO A. 2019. Personality traits and preventive cancer screenings in the Health Retirement Study, Preventive Medicine, Vol. 126.
ASPINWALL L. G., BRUNHART S. M. 1996. Distinguishing optimism from denial: Optimistic beliefs predict attention to health threats. Personality and Social Psychology Bulletin, Vol. 22, No. 6, pp. 993–1003.
ASPINWALL, L. G., TAYLOR, S. E. 1992. Modeling cognitive adaptation: A longitudinal investigation of the impact of individual differences and coping on college adjustment and health. Journal of Personality and Social Psychology, Vol. 63, No. 6, pp. 989–1003.
BAHAT E. 2021. The Big Five personality traits and adherence to breast cancer early detection and prevention, Personality and Individual Differences, Vol. 172.
BERTONI M., CORAZZINI L., ROBONE S. 2020. The good outcome of bad news. A Field Experiment on Formatting Breast Cancer Screening Invitation Letters, American Journal of Health Economics, Vol. 6, No. 3, p.p. 372-409.
BRUNNERMEIER M.K., PARKER J.A. 2005. Optimal Expectations. American Economic Review, Vol. 95, No. 4, p.p. 1092–118.
CARNEY P., O'NEILL S., O'NEILL C. 2013. Determinants of breast cancer screening uptake in women, evidence from the British Household Panel Survey, Social Science & Medicine, Vol. 82, pp. 108-114.
CARVER C.S., SCHEIER M.F., SEGERSTROM S.C., 2010. Optimism, Clinical Psychology Review, Vol. 30, No. 7, pp. 879-889.
CENTRE FOR DISEASE CONTROL (CDC). 2024. Screening for Breast Cancer.
CLARKE P., FISHER G., HOUSE J., SMITH J., WEIR D. 2008. https://hrs.isr.umich.edu/sites/default/files/biblio/HRS2006LBQscale.pdf.
CARSTENSEN L.L. 1995. Evidence for a life-span theory of socioemotional selectivity. Current Directions in Psychological Science, Vol. 4, No. 5, pp. 151–156.
GOLMAN R., HAGMANN D., LOEWENSTEIN G. 2017. Information avoidance, Journal of Economic Literature, Vol. 55, No. 1.
HAJEK A., KRETZLER B., KÖNIG H-H. 2020. Personality and the use of cancer screenings. A systematic review, PLOS One, Vol. 15, No. 12.
KAHNEMAN D., TVERSKY A. 1979. Prospect theory: An analysis of decision under risk. Econometrica, Vol. 47, No. 2, pp. 263–291.
LE CLAINCHE C., MARSAUDON A., ROCHAIX L., HAON B., VERGNAUD J-C. 2024. Do Behavioral Characteristics Influence the Breast Cancer Diagnosis Delay? Evidence From French Retrospective Data, Value Health, Vol. 27, No. 10, pp. 1408-1416.
MOYER C.A., EKPO G., CALHOUN C.L., GREENE J., NAIK S., SIPPOLA E., et al. 2008. Quality of life, optimism/pessimism, and knowledge and attitudes toward HIV Screening among pregnant women in Ghana, Women’s Health Issues, Vol. 18, No. 4, pp. 301-309.
MUNDLAK Y. 1978. On the Pooling of Time Series and Cross Section Data. Econometrica, Vol. 46, No. 1, pp. 69-85.
NATIONAL CANCER INSTITUTE. 2025. Breast cancer screening.
NIEDZWIEDZ C.L., ROBB K.A., VITTAL KATIKIREDDI S., PELL J.P., SMITH D.J. 2019. Depressive symptoms, neuroticism, and participation in breast and cervical cancer screening: Cross‐sectional and prospective evidence from UK Biobank, Psychooncology, Vol. 29, No. 2, pp. 381–388.
OSTER E., SHOULSON I., RAY DORSEY E. 2013. Optimal Expectations and Limited Medical Testing: Evidence from Huntington Disease, The American Economic Review, Vol. 103, No. 2, pp. 804-830.
PROWSE S.R., BRAZZELLI M., TREWEEK S. 2024. What factors influence the uptake of bowel, breast and cervical cancer screening? An overview of international research, European Journal of Public Health, Vol. 34, No. 4, pp. 818–825.
RICE N., ROBONE S. 2022. The effects of health shocks on risk preferences: Do personality traits matter? Journal of Economic Behavior and Organization, Vol. 204, pp. 356-371.
ROTHMAN A.J., SALOVEY P. 1997. Shaping perceptions to motivate healthy behavior: the role of message framing, Psychological Bulletin, Vol. 121, No. 1, pp. 3-19.
TAVAKOLI B., FEIZI A., ZAMANI-ALAVIJEH F., SHAHNAZI H. 2024. Factors influencing breast cancer screening practices among women worldwide: a systematic review of observational and qualitative studies, BMC Women's Health, Vol. 24, No. 268.
WEINSTEIN N. D. 1980. Unrealistic optimism about future life events, Journal of Personality and Social Psychology, Vol. 39, No. 5, pp. 806–820.
WOOLDRIDGE J.M. 2005. Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity, Journal of Applied Econometrics, Vol. 20, No. 1, pp. 39-54.
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