Impact of Physicians’ Personalities and Behavioral Traits on Treatment-Related Decision-making for Elderly Acute Myeloid Leukemia

Journal of General Internal Medicine (2021)Cite this article

Abstract

Background

Elderly patients with acute myeloid leukemia (AML) can be treated with intensive therapy, low-intensity therapy, or best supportive care. Medical decision-making might be affected by physicians’ occupational and non-occupational factors.

Objective

To explore the impact of physicians’ personalities and behavioral traits on treatment-related decision-making for elderly AML patients.

Design

A nationwide cross-sectional survey.

Participants

Hematologists in mainland China (N = 529; response rate 64.5%).

Main Measures

The medical decision-making for elderly AML patients was evaluated using 6 clinical vignettes. Hematologists’ attitudes toward risk and uncertainty, Big Five personality traits, and decision-making styles were assessed using binary lottery choices and well-recognized self-report inventories.

Key Results

The resulting binary regression model in predicting treatment intensity contained professional title group (OR = 0.012, 95% CI 0.001 to 0.136, P < 0.001), conscientiousness (OR = 0.336, 95% CI 0.121 to 0.932, P = 0.036), extraversion (OR = 0.403, 95% CI 0.166 to 0.974, P = 0.044), conscientiousness by title group (OR = 2.009, 95% CI 1.100 to 3.667, P = 0.023), and extraversion by title group (OR = 1.627, 95% CI 0.965 to 2.743, P = 0.068) as predictors of therapy intensity preference. Junior physicians with a higher level of extraversion (mean difference = 0.27; 95% CI 0.07 to 0.45; P = 0.009) or conscientiousness (mean difference = 0.19; 95% CI 0.01 to 0.36; P = 0.028) tended to prescribe more intensive therapy. Meanwhile, no significant correlation was found between physicians’ personalities or behavioral traits and treatment-related decision-making in senior physicians.

Conclusions

Physicians’ personalities contribute to treatment-related decision-making for elderly AML patients, depending on the professional titles. More extravert or conscientious attending physicians tended to prescribe more intensive therapy. Meanwhile, the decisions made by chief and associate chief physicians were not impacted by their personal traits. Junior physicians should be aware of such potential influence when making medical decisions.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

US$ 39.95

Tax calculation will be finalised during checkout.

Figure 1

References

  1. 1.

    Institute SEaERPotNC. SEER cancer stat facts: acute myeloid leukemia (AML) 2018. Available from: https://seer.cancer.gov/statfacts/html/amyl.html. Accessed 10 Sept 2019.

  2. 2.

    Kantarjian HM, Thomas XG, Dmoszynska A, et al. Multicenter, randomized, open-label, phase III trial of decitabine versus patient choice, with physician advice, of either supportive care or low-dose cytarabine for the treatment of older patients with newly diagnosed acute myeloid leukemia. J Clin Oncol 2012;30(21):2670.

    CAS  Article  Google Scholar 

  3. 3.

    Podoltsev NA, Stahl M, Zeidan AM, et al. Selecting initial treatment of acute myeloid leukaemia in older adults. Blood Rev 2017;31(2):43–62.

    Article  Google Scholar 

  4. 4.

    Dombret H, Seymour JF, Butrym A, et al. International phase 3 study of azacitidine vs conventional care regimens in older patients with newly diagnosed AML with>30% blasts. Blood. 2015;126(3):291–299.

    CAS  Article  Google Scholar 

  5. 5.

    Rao AV. Fitness in the elderly: how to make decisions regarding acute myeloid leukemia induction. ASH Education Program Book 2016;2016(1):339–347.

    Google Scholar 

  6. 6.

    Loberiza Jr FR, Cannon AC, Cannon AJ, et al. Insights on practice variations in the management of lymphoma and leukemia. Leuk Lymphoma 2014;55(11):2449–2456.

    CAS  Article  Google Scholar 

  7. 7.

    Hajjaj FM, Salek MS, Basra MK, et al. Non-clinical influences on clinical decision-making: a major challenge to evidence-based practice. J R Soc Med 2010;103(5):178–187.

    CAS  Article  Google Scholar 

  8. 8.

    Saposnik G, Redelmeier D, Ruff CC, et al. Cognitive biases associated with medical decisions: a systematic review. BMC Med Inform Decis Mak 2016;16(1):138.

    Article  Google Scholar 

  9. 9.

    Poulton B, Ridley S, Mackenzie-Ross R, et al. Variation in end-of-life decision making between critical care consultants. Anaesthesia. 2005;60(11):1101–1105.

    CAS  Article  Google Scholar 

  10. 10.

    Malhotra J, Rotter D, Tsui J, et al. Impact of patient–provider race, ethnicity, and gender concordance on cancer screening: findings from Medical Expenditure Panel Survey. Cancer Epidemiol Prev Biomarkers 2017;26(12):1804–1811.

    Article  Google Scholar 

  11. 11.

    Cutler D, Skinner JS, Stern AD, et al. Physician beliefs and patient preferences: a new look at regional variation in health care spending. Am Econ J Econ Pol 2019;11(1):192–221.

    Article  Google Scholar 

  12. 12.

    Bories P, Lamy S, Simand C, et al. Physician uncertainty aversion impacts medical decision making for older patients with acute myeloid leukemia: results of a national survey. Haematologica. 2018;103(12):2040–2048.

    Article  Google Scholar 

  13. 13.

    Tencent. Tencent Announces 2019 First Quarter Results 2019. Available from: https://www.tencent.com/en-us/articles/8003551557911908.pdf. Accessed 15 Sept 2019.

  14. 14.

    Dong JH. The influential factor and construction of factor model of risk decision-making. MS thesis, Northwest Normal University. 2006, 57 pages.

  15. 15.

    Schmitt DP, Allik J, McCrae RR, et al. The geographic distribution of Big Five personality traits: Patterns and profiles of human self-description across 56 nations. J Cross-Cult Psychol 2007;38(2):173–212.

    Article  Google Scholar 

  16. 16.

    Huang R. The relationship between power and decision-making style. MS thesis, Hunan Normal University. 2016, 40 pages.

  17. 17.

    John OP, Naumann LP, Soto CJ. Paradigm shift to the integrative big five trait taxonomy. Handbook of personality: Theory and research 2008;3(2):114–158.

  18. 18.

    Mann L, Burnett P, Radford M, et al. The Melbourne Decision Making Questionnaire: An instrument for measuring patterns for coping with decisional conflict. J Behav Decis Mak 1997;10(1):1–19.

    Article  Google Scholar 

  19. 19.

    Spicer DP, Sadler-Smith E. An examination of the general decision making style questionnaire in two UK samples. J Manag Psychol 2005;20(2):137–149.

    Article  Google Scholar 

  20. 20.

    Meyer AN, Payne VL, Meeks DW, et al. Physicians’ diagnostic accuracy, confidence, and resource requests: a vignette study. JAMA Intern Med 2013;173(21):1952–1958.

    Article  Google Scholar 

  21. 21.

    Michel-Lepage A, Ventelou B, Nebout A, et al. Cross-sectional survey: risk-averse French GPs use more rapid-antigen diagnostic tests in tonsillitis in children. BMJ Open 2013;3(10):e003540.

    Article  Google Scholar 

  22. 22.

    Massin S, Ventelou B, Nebout A, et al. Cross-sectional survey: risk-averse French general practitioners are more favorable toward influenza vaccination. Vaccine. 2015;33(5):610–614.

    Article  Google Scholar 

  23. 23.

    Massin S, Nebout A, Ventelou B. Predicting medical practices using various risk attitude measures. Eur J Health Econ 2018;19(6):843–860.

    Article  Google Scholar 

  24. 24.

    Deschepper R, Grigoryan L, Lundborg CS, et al. Are cultural dimensions relevant for explaining cross-national differences in antibiotic use in Europe? BMC Health Serv Res 2008;8(1):123.

    Article  Google Scholar 

  25. 25.

    Borg MA. Prolonged perioperative surgical prophylaxis within European hospitals: an exercise in uncertainty avoidance? J Antimicrob Chemother 2013;69(4):1142–1144.

    Article  Google Scholar 

  26. 26.

    Wilt J, Revelle W. Extraversion. The Oxford handbook of the Five Factor Model. Oxford library of psychology. New York: Oxford University Press; 2017. p. 57–81.

    Google Scholar 

  27. 27.

    Oehler A, Wedlich F. The relationship of extraversion and neuroticism with risk attitude, risk perception, and return expectations. J Neurosci Psychol Econ 2018;11(2):63–92.

    Article  Google Scholar 

  28. 28.

    Anderson C, Spataro SE, Flynn FJ. Personality and organizational culture as determinants of influence. J Appl Psychol 2008;93(3):702.

    Article  Google Scholar 

  29. 29.

    Peabody JW, Luck J, Glassman P, et al. Comparison of vignettes, standardized patients, and chart abstraction: a prospective validation study of 3 methods for measuring quality. Jama. 2000;283(13):1715–1722.

    CAS  Article  Google Scholar 

  30. 30.

    Peabody JW, Luck J, Glassman P, et al. Measuring the quality of physician practice by using clinical vignettes: a prospective validation study. Ann Intern Med 2004;141(10):771–780.

    Article  Google Scholar 

  31. 31.

    Hojat M, Louis DZ, Markham FW, et al. Physicians' empathy and clinical outcomes for diabetic patients. Acad Med 2011;86(3):359–364.

    Article  Google Scholar 

  32. 32.

    Buining EM, Kooijman MK, Swinkels IC, et al. Exploring physiotherapists’ personality traits that may influence treatment outcome in patients with chronic diseases: a cohort study. BMC Health Serv Res 2015;15(1):558–569.

    Article  Google Scholar 

Download references

Acknowledgments

The authors thank all the hematologists who participated in the survey.

Funding

Institutional research funding was provided by the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (Grant No. 2019-RC-HL-001, for X.-x.C.), the National Natural Science Foundation of China (Grant No. 81570195, for L.J.), and Beijing Natural Science Foundation (Grant No. 7182128, for L.J.).

Author information

Author notes

  1. Xia Wu and Yi-nan Jiang contributed equally to this study.

  2. Jian Li and Xin-xin Cao contributed equally as co-corresponding authors.

Affiliations

  1. Department of Hematology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People’s Republic of China

    Xia Wu MD, Jia Chen MD, Yue-ying Mao MD, Lu Zhang MD, Dao-bin Zhou MD, Xin-xin Cao MD & Jian Li MD

  2. Department of Psychology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People’s Republic of China

    Yi-nan Jiang MD

  3. Medical Research Center, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People’s Republic of China

    Yue-lun Zhang PhD

Authors
  1. Xia Wu MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yi-nan Jiang MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yue-lun Zhang PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jia Chen MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yue-ying Mao MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Lu Zhang MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Dao-bin Zhou MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Xin-xin Cao MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jian Li MD
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Xin-xin Cao MD or Jian Li MD.

Ethics declarations

Conflict of Interest

The authors declare that they do not have a conflict of interest.

Disclaimer

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Prior Presentations

This work was presented as a poster at the 62nd ASH Annual Meeting and Exposition (December 5, 2020).

Supplementary Information

ESM 1

(DOCX 27.8 kb)

ESM 2

(PNG 457 kb)

ESM 3

(JPEG 636 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wu, X., Jiang, Yn., Zhang, Yl. et al. Impact of Physicians’ Personalities and Behavioral Traits on Treatment-Related Decision-making for Elderly Acute Myeloid Leukemia. J GEN INTERN MED (2021). https://doi.org/10.1007/s11606-020-06467-w

Download citation

KEY WORDS

  • elderly acute myeloid leukemia
  • treatment-related decision-making
  • personality
  • physician