Chapter 2: Benefits of Developing Healthcare Professionals’ Skills for Effectively Managing Uncertainty

Much of the healthcare research about uncertainty focuses on medical doctors and, to a lesser extent, nurses (Cranley et al., 2012; Stephens, Karim, et al., 2022; Strout et al., 2018). Looking across this healthcare literature, it appears that in healthcare systems, practice, and education, individuals’ unique thoughts, unpredictable behaviours, and different ways of thinking are significant sources of uncertainty (Lazarus et al., 2024; Lazarus et al., 2022)). This ‘human element‘ as a source of uncertainty means that lessons about uncertainty tolerance can likely be drawn from a wide range of fields beyond healthcare.

Case Study 1.1  (about ‘Mei’) explored the uncertainty experienced by an individual patient, doctors involved in her care, and her family. Sources of healthcare uncertainty extend beyond the care of individuals (e.g., to population health, policy development), and are influenced by external factors such (e.g., economics, climate change, etc.). Conceptual models of uncertainty tolerance which serve to define this construct and explain the influence of these factors on one’s responses to uncertainty across cognitive, emotional, and behavioural domains (Hillen et al., 2017) are described in Chapter 3.

Impacts of Healthcare Professionals’ Uncertainty Tolerance

Because of the ubiquity of uncertainty, the impacts of uncertainty tolerance on healthcare contexts extends from the healthcare practitioners themselves, to patients, and to the healthcare system more broadly. Healthcare professionals can benefit from developing strategies for effectively managing uncertainty (i.e., uncertainty tolerance) with impacts such as improved patient care and enhanced staff wellbeing (Strout et al., 2018), with the latter well represented in the literature (Hancock & Mattick, 2020).

The evidence supporting claims about uncertainty tolerance in healthcare professionals typically relies on scales which evaluate individuals’ levels of uncertainty tolerance (Strout et al., 2018). Validity evidence supporting the use of such scales is most well established among populations of medical practitioners; hence, scale implementation in these groups provides several key insights into the impacts of uncertainty tolerance in the broader healthcare setting (Stephens, Karim, et al., 2022; Stephens, Lazarus, et al., 2022; Strout et al., 2018). However, the validity and reliability evidence supporting scale implementation among health professions learners currently has substantive limitations, as described in more detail in Chapter 6 (Stephens, Karim, et al., 2022; Stephens, Lazarus, et al., 2022). With this in mind, there is valuable evidence regarding the impacts of uncertainty tolerance on healthcare professionals, the healthcare system, and patients.

Healthcare Professionals

According to a growing body of evidence, there are many benefits for healthcare professionals when they are aware of the inevitable uncertainties within healthcare (Kennedy, 2017). Uncertainty tolerant healthcare professionals may be less likely to experience psychological distress or burnout (Hancock & Mattick, 2020), less likely to blame themselves when the inevitable unexpected event does occur (Katsaros et al., 2014), and less likely to waste precious healthcare resources on low-value approaches to care (Allman et al., 1985; Begin, Hidrue, Lehrhoff, Lennes, et al., 2022; Forrest et al., 2006; Strout et al., 2018).

A 2020 systematic review of the literature (opens in new tab) by psychiatrist Dr Jason Hancock and medical education researcher Professor Karen Mattick found a strong association between psychological distress and lower levels of uncertainty tolerance across 11 studies, illustrating the historical correlation between low uncertainty tolerance and burnout. A 2022 study (opens in new tab) by Begin, Hidrue, Lehrhoff, del Carmen, and colleagues (pp. 1417–1418) explored this relationship further and found that

physicians with low tolerance of uncertainty were more likely to be burned-out than those with high tolerance of uncertainty … less likely to be engaged at work … less likely to be satisfied with their career … [and] more likely to have higher rates of exhaustion … cynicism … and reduced personal efficacy.

Given the reported impacts of burnout on workforce numbers (Murthy, 2022) and healthcare systems (Shanafelt et al., 2002, 2010), this relationship between burnout and low uncertainty tolerance potentially has substantial implications for the healthcare workforce – for example, in relation to absenteeism and employee retention.

Begin, Hidrue, Lehrhoff, del Carmen, and colleagues’ (2022) work explores some factors that may be influenced by the link between low uncertainty tolerance and burnout, in particular personal efficacy. The identified reduction in personal efficacy in those who are less tolerant of uncertainty is supported by evidence in other fields, such as business. For instance, a study of bank administrators’ uncertainty tolerance found that there was a link between personal beliefs about control and the level of uncertainty tolerance: those with lower uncertainty tolerance tended to blame themselves when the unexpected arose (Katsaros et al., 2014), despite uncertainty, and not the lack of human control, being responsible for the unexpected. Although, at first glance, healthcare and banking may seem like very different fields, they share a reliance on professionals needing to manage unpredictable aspects of their work, due to the ambiguity, complexity, and probability discussed in Chapter 1. Both sectors also require decision-making with associated stakes and potential impacts on others.

Healthcare professionals’ actions impact many individuals, from the healthcare system, to the healthcare team, to the patient and their family. There is evidence that the ability to make effective decisions and to make them independently also relies on uncertainty tolerance. In the auditing sector, where decisions command similarly high stakes and have impacts on the financial stability of a workforce, those with lower uncertainty tolerance have been found to be less able to make informed decisions when the uncertainty of the case being audited was high, and they also required increased supervision in order to proceed (Gupta & Fogarty, 1993; Makkawi & Rutledge, 2000). In healthcare, there are times when collaboration and teamwork are appropriate for managing uncertainty; however, if consultation and supervision are excessive to the point of hindering appropriate care, uncertainty intolerance (e.g. maladaptive responses to uncertainty) may be a factor.

Lower levels of uncertainty tolerance are also linked to how healthcare professionals communicate and engage with patients. For instance, healthcare professionals with lower uncertainty tolerance appear to have a greater propensity to display paternalistic attitudes, rather than engage in shared decision-making and person-centred care (Geller et al., 1993). In another example, one study found that lower uncertainty tolerance in medical students was linked to less desire to work in underserved communities (Caulfield et al., 2014), while another found that higher uncertainty tolerance in medical students seemed protective against negative attitudes towards underserved populations (Wayne et al., 2011). These studies suggest that a fear of disclosing uncertainty to others (Geller et al., 1993) or the increased uncertainty introduced by including the perspectives of others (Lazarus & Funtowicz, 2023), can result in healthcare professionals with lower uncertainty tolerance making decisions for rather than with people, and avoiding caring for underserved communities.

Healthcare Systems

As healthcare systems are made of many individuals (including administrators, patients, and healthcare professionals), collectively addressing uncertainty tolerance in individuals has the potential to make widespread and powerful impacts on the healthcare system (Schattner, 2008). There is evidence that healthcare professionals’ uncertainty tolerance influences healthcare costs, supervision needs, and management of patients (Strout et al., 2018). For instance, healthcare professionals with lower uncertainty tolerance are reported to order more investigations than those with higher uncertainty tolerance, and this is repeated across multiple healthcare settings and professions, including general practice and emergency medicine (Begin, Hidrue, Lehrhoff, Lennes, et al., 2022; van der Weijden et al., 2002). Such investigations include medical imaging (Allman et al., 1985; Lysdahl & Hofmann, 2009) and laboratory tests (van der Weijden et al., 2002). Although individual health professionals request investigations, these actions are occurring in a system and society that typically values certainty, even when further investigation may be not evidence-based (Scott et al. 2023).

The irony is that by seeking certainty, sometimes further uncertainties are uncovered that further impact the healthcare system. For example, investigations may identify anomalies that are of no significance or danger but may trigger a chain of follow-up tests, referrals, or procedures that ultimately risk harm to people engaging with healthcare, and increase healthcare expenditure. Such incidentally found abnormalities, or incidentalomas, may lead to further medical imaging, which can expose people to radiation, or biopsies, which can risk damage to nearby structures. Ultimately, unnecessary healthcare interventions may place people at greater risk, and add further demands on the healthcare system (O’Sullivan et al., 2018, Ganguli et al., 2020, Scott et al., 2023).

Healthcare systems, given their complexity, work to manage their uncertainty through modelling, standardised operating procedures and checklists (Lazarus et al., in  press). These approaches predominately focus on quantifiable uncertainty (e.g. risk), and provide a means for the complex healthcare system to generate the appearance of certainty (Lazarus, 2023). While checklists can provide an ‘illusion of compliance,’ the rigid applications of checklists without considering how it relates to individual circumstances can lead to inappropriate actions or omissions, risking patient safety (Facey et al., 2024, p. 12). The tension between what is needed to treat the patient, and these healthcare systems’ attempts to control uncertainty may also be contributing to healthcare professional burnout (Lazarus, 2023).

Patients

There is evidence that healthcare professionals’ uncertainty tolerance is tied to the overall experience of patients and may influence patient’s behaviour. A study of primary care providers in the United States revealed that people whose primary care provider had less uncertainty tolerance were more likely to visit emergency departments than those whose primary care provider had more uncertainty tolerance; the patients of providers with less uncertainty tolerance also tended to give their primary care provider a lower rating for their healthcare experience (Begin, Hidrue, Lehrhoff, Lennes, et al., 2022).

How healthcare professionals communicate uncertainty to patients also appears to influence people’s trust in these healthcare professionals (Dahm & Crock, 2021; Politi et al., 2007). For patients who prefer to lead the decision making about their own health and believe they have high health literacy, explicitly communicating uncertainty may be preferred and enhance trust (Politi et al., 2007). By contrast, patients who prefer their healthcare provider to lead decision making may prefer more implicit communication about uncertainty, or even that uncertainties are withheld by the provider (Politi et al., 2007; Dahm & Crock, 2021).

Additional factors such as gender and perceived expertise of the health processional may also influence how patients experience uncertainty in healthcare encounters. For instance, there is some evidence that women who are healthcare professionals are perceived as less credible when communicating uncertainties compared to men (Cousin et al., 2013). Non-verbal communication may also influence perceptions of uncertainty in healthcare encounters. In western cultures, for example, eye contact is typically paramount in communication, so patients who don’t make eye-contact with their providers may stimulate uncertainty related to communication. However, in many other cultures, lowering one’s gaze signifies respect and reverence for the healthcare professional.

There are currently no best practice guidelines on communicating uncertainty (Politi et al., 2007), which may relate to effective communication of uncertainty being highly variable, depending on patient preferences, social constructs and societal norms (Politi et al., 2007, Cousin et al., 2013). As such, the extent to which there is adequate time for healthcare professionals and their patients to explore the best approach for communicating in general, and communicating healthcare uncertainty more specifically, may play an important role in the professionals’ uncertainty tolerance.

Influence of the Healthcare System on Uncertainty Tolerance

Healthcare professionals’ capacity for uncertainty tolerance is influenced by the broader healthcare system. Van der Weijden and colleagues’ (2002) qualitative study (opens in new tab) exploring elements influencing general practitioners’ tendency to order laboratory tests found that time pressures, psychological safety, culture, team dynamics, and so on can impact the capacity of individuals within the system to be adaptive to healthcare uncertainty. Societal pressures (such as litigiousness and perceived costs) and healthcare system technology also impacted physicians’ decisions about care when diagnostic uncertainty was present.

‘Levels’ of Uncertainty Tolerance

The research findings discussed above raise the question, what is the right uncertainty tolerance for healthcare professionals? The answer, at least based on current evidence, is less than satisfying: it depends (Reis-Dennis et al., 2021; Stephens et al., 2023). Some suggest that too much uncertainty tolerance can result in a lack of motivation to wade through the uncertainty (Hancock & Mattick, 2012; Reis-Dennis et al., 2021), but contemporary understanding of the concept of uncertainty tolerance suggests that this actually defines uncertainty intolerance, by representing disengagement or inaction in the face of uncertainty (Hillen et al., 2017; Stephens et al., in press). Others suggest that the speciality area or health profession chosen may be influenced by an individual’s uncertainty tolerance (Babenko et al., 2021; Borracci et al., 2021). However, this view implies that uncertainty tolerance is a static personality trait that is unchangeable, and findings from research evaluating this claim are inconsistent across the literature (Strout et al., 2018). While there is evidence that individual factors impact on one’s uncertainty tolerance, a host of factors work together (some synergistically, others antagonistically) to influence an individual’s responses to uncertainty (Hillen et al., 2017; Stephens et al., 2022; Strout et al., 2018).

Moreover, how researchers define tolerance versus intolerance is also changing. There is emerging evidence that uncertainty tolerance may be based more on how humans act in the face of uncertainty and less on how they feel about uncertainty (Stephens et al., 2023). Contemporary literature implies that multiple contextual factors (i.e., moderators) influence whether an individual’s responses to uncertainty are adaptive or maladaptive in a given situation (Stephens et al., in press; Strout et al., 2018). Take, for instance, the referral of a person from one healthcare professional to another. Referral rates have been linked to uncertainty tolerance in research using scales, with evidence that higher rates are associated with lower levels of uncertainty tolerance (Strout et al., 2018). This could suggest that healthcare professionals with higher referral rates than their peers may be displaying maladaptive responses to uncertainty and that those with lower uncertainty tolerance may be inappropriately referring people on. However, this doesn’t take into consideration how different moderators may influence experiences of uncertainty or whether referrals are genuinely indicated. Consider a scenario in which a healthcare professional is practising in an area whose population is typically older and in which individuals tend to have multiple health conditions and complex social needs. The professional may have already tried to manage a condition within their own skillset, may be at the limits of the care they can provide, and may be uncertain about what to do next, so they refer on. This professional may have a higher-than-average referral rate, but in this context, they may be adaptively responding to uncertainty.

Summary

While research is ongoing, there appear to be many benefits extending from healthcare professionals who can adaptively respond to (i.e., ‘tolerate’) uncertainty. These benefits ripple through the healthcare system and society at large. The healthcare system also plays a role in influencing responses to uncertainty. Maladaptive responses also appear to have significant impacts on the healthcare systems. The challenge with the state of the current body of research is in defining what an appropriate ‘level’ of uncertainty tolerance is to reap the greatest benefits for all invested parties.

---

---

References

Allman, R. M., Steinberg, E. P., Keruly, J. C., & Dans, P. E. (1985). Physician tolerance for uncertainty: Use of liver-spleen scans to detect metastases. JAMA, 254(2), 246–248. https://doi.org/10.1001/jama.1985.03360020078028

Babenko, O., Linkiewich, D., Lodewyk, K., & Lee, A. (2021). Ambiguity tolerance and prospective specialty choice among third-year medical students. PRiMER: Peer Reviewed Reports in Medical Education, 5(2). https://doi.org/10.22454/PRiMER.2021.453158

Begin, A. S., Hidrue, M., Lehrhoff, S., del Carmen, M. G., Armstrong, K., & Wasfy, J. H. (2022). Factors associated with physician tolerance of uncertainty: An observational study. Journal of General Internal Medicine, 37(6), 1415–1421. https://doi.org/10.1007/s11606-021-06776-8

Begin, A. S., Hidrue, M. K., Lehrhoff, S., Lennes, I. T., Armstrong, K., Weilburg, J. B., del Carmen, M. G., & Wasfy, J. H. (2022). Association of self-reported primary care physician tolerance for uncertainty with variations in resource use and patient experience. JAMA Network Open, 5(9), Article e2229521. https://doi.org/10.1001/jamanetworkopen.2022.29521

Borracci, R. A., Ciambrone, G., & Arribalzaga, E. B. (2021). Tolerance for uncertainty, personality traits and specialty choice among medical students. Journal of Surgical Education, 78(6), 1885–1895. https://doi.org/10.1016/j.jsurg.2021.03.018

Caulfield, M., Andolsek, K., Grbic, D., & Roskovensky, L. (2014). Ambiguity tolerance of students matriculating to U.S. medical schools. Academic Medicine, 89(11), 1526–1532. https://doi.org/10.1097/acm.0000000000000485

Cousin, G., Schmid Mast, M., & Jaunin-Stalder, N. (2013). When physician-expressed uncertainty leads to patient dissatisfaction: A gender study. Medical Education, 47(9), 923–931. https://doi.org/10.1111/medu.12237

Cranley, L. A., Doran, D. M., Tourangeau, A. E., Kushniruk, A., & Nagle, L. (2012). Recognizing and responding to uncertainty: A grounded theory of nurses’ uncertainty. Worldviews on Evidence-Based Nursing, 9(3), 149–158. https://doi.org/10.1111/j.1741-6787.2011.00237.x

Dahm, M., & Crock, C. (2021). Communication of uncertainty, diagnosis and trust [Conference presentation abstract]. BMJ Open, 11(Suppl. 1), A3–A4. https://doi.org/10.1136/bmjopen-2021-QHRN.9

Facey, M., Baxter, N., Hammond Mobilio, M., Moulton, C., & Paradis, E. (2024). The ritualisation of the surgical safety checklist and its decoupling from patient safety goals. Sociology of  Health & Illnesss. Advance online publication. https://doi.org/10.1111/1467-9566.13746

Forrest, C.B., Nutting, P.A., von Shrader, S., Rohde, C., & Starfield, B. (2006). Primary care physician specialty referral decision making: Patient, physician, and health care system determinants. Medical Decision Making, 26(1), 76–85. https://doi.org/10.1177/0272989×05284110

Ganguli, I., Simpkin, A.L., Colla, C.H., Weissman, A., Mainor, A.J., Rosenthal, M.B. & Sequist T.D. (2020). Why do physicians pursue cascades of care after incidental findings? A national survey. Journal of General Internal Medicine, 35 (4), 1352-1354. https://doi.org/10.1007/s11606-019-05213-1

Geller, G., Faden, R. R., & Levine, D. M. (1990). Tolerance for ambiguity among medical students: Implications for their selection, training and practice. Social Science & Medicine, 31(5), 619–624. https://doi.org/10.1016/0277-9536(90)90098-d

Geller, G., Tambor, E. S., Chase, G. A., & Holtzman, N. A. (1993). Measuring physicians’ tolerance for ambiguity and its relationship to their reported practices regarding genetic testing. Medical Care, 31(11), 989–1001. https://doi.org/10.1097/00005650-199311000-00002

Gupta, P. P., & Fogarty, T. J. (1993). Governmental auditors and their tolerance for ambiguity: An examination of the effects of a psychological variable. Government Accountants Journal, 42(3), 25.

Haggerty, J., Tudiver, F., Brown, J. B., Herbert, C., Ciampi, A., & Guibert, R. (2005). Patients’ anxiety and expectations: How they influence family physicians’ decisions to order cancer screening tests. Canadian Family Physician, 51(12), 1658–1659.

Han, P. K., Babrow, A., Hillen, M. A., Gulbrandsen, P., Smets, E. M., & Ofstad, E. H. (2019). Uncertainty in health care: Towards a more systematic program of research. Patient Education and Counseling, 102(10), 1756–1766. https://doi.org/10.1016/j.pec.2019.06.012

Hancock, J., & Mattick, K. (2012). Increasing students’ tolerance of ambiguity: The need for caution. Academic Medicine, 87(7), 834–835. https://doi.org/10.1097/ACM.0b013e318257d085

Hancock, J., & Mattick, K. (2020). Tolerance of ambiguity and psychological well-being in medical training: A systematic review. Medical Education, 54(2), 125–137. https://doi.org/10.1111/medu.14031

Hillen, M. A., Gutheil, C. M., Strout, T. D., Smets, E. M. A., & Han, P. K. J. (2017). Tolerance of uncertainty: Conceptual analysis, integrative model, and implications for healthcare. Social Science & Medicine, 180, 62–75. https://doi.org/10.1016/j.socscimed.2017.03.024

Katsaros, K., Tsirikas, A., & Nicolaidis, C. (2014). Managers’ workplace attitudes, tolerance of ambiguity and firm performance: The case of Greek banking industry. Management Research Review, 37, 442–465. https://doi.org/10.1108/MRR-01-2013-0021

Kennedy, A. G. (2017). Managing uncertainty in diagnostic practice. Journal of Evaluation in Clinical Practice, 23(5), 959–963. https://doi.org/10.1111/jep.12328

Lazarus, M. D. (2023). The uncertainty effect: How to survive and thrive through the unexpected. Monash University Press.

Lazarus, M. D., & Funtowicz, S. (2023). Learning together: Facing the challenges of sustainability transitions by engaging uncertainty tolerance and post-normal science. Sustainable Earth Reviews, 6(18).  https://doi.org/10.1186/s42055-023-00066-3

Lazarus, M. D., Gouda-Vossos, A., Parasnis, J., Davis, E., Mujumdar, S., Ziebell, A., & Brand, G. (2024). The human element: How educators can prepare learners for future workplace uncertainties and troublesome knowledge. In J. P. Davies, E. Gironacci, S. McGowan, A. Nyamapfene, J. Rattray, A. M. Tierney & A. S. Webb (Eds.), Threshold concepts in the moment (pp. 186-208). Brill. https://doi.org/10.1163/9789004680661_013

Lazarus, M. D., Gouda-Vossos, A., Ziebell, A., & Brand, G. (2022). Fostering uncertainty tolerance in anatomy education: Lessons learned from how humanities, arts and social science (HASS) educators develop learners’ uncertainty tolerance. Anatomical Sciences Education, 16(1), 128–147. https://doi.org/10.1002/ase.2174

Lysdahl, K. B., & Hofmann, B. M. (2009). What causes increasing and unnecessary use of radiological investigations? A survey of radiologists’ perceptions. BMC Health Services Research, 9, Article 155. https://doi.org/10.1186/1472-6963-9-155

Makkawi, B. A., & Rutledge, R. W. (2000). Evaluating audit risk: The effects of tolerance-for-ambiguity, industry characteristics, and experience. In Advances in Accounting Behavioral Research (pp. 69–89). Emerald. https://doi.org/10.1016/S1474-7979(00)03026-X

Murthy, V. H. (2022). Confronting health worker burnout and well-being. New England Journal of Medicine, 387(7), 577–579. https://doi.org/10.1056/NEJMp2207252

O’Sullivan, J. W., Muntinga, T., Grigg, S., & Ioannidis, J. P. (2018). Prevalence and outcomes of incidental imaging findings: Umbrella review. BMJ, 361, Article k2387. https://doi.org/10.1136/bmj.k2387

Politi, M. C., Han, P. K. J., & Col, N. F. (2007). Communicating the uncertainty of harms and benefits of medical interventions. Medical Decision Making, 27(5), 681–695. https://doi.org/10.1177/0272989×07307270

Reis-Dennis, S., Gerrity, M. S., & Geller, G. (2021). Tolerance for uncertainty and professional development: A normative analysis. Journal of General Internal Medicine, 36(8), 2408–2413. https://doi.org/10.1007/s11606-020-06538-y

Schattner, A. (2008). The unbearable lightness of diagnostic testing: Time to contain inappropriate test ordering. Postgraduate Medical Journal, 84(998), 618–621. https://doi.org/10.1136/pgmj.2008.072579

Scott, I.A., Slavotinek, J., and Glasziou, P.P. (2024). First, do no harm in responding to incidental imaging findings. Medical Journal of Australia, 220 (1), 7-9. https://doi.org/10.5694/mja2.52177

Shanafelt, T. D., Balch, C. M., Bechamps, G., Russell, T., Dyrbye, L., Satele, D., Collicott, P., Novotny, P. J., Sloan, J., & Freischlag, J. (2010). Burnout and medical errors among American surgeons. Annals of Surgery, 251(6), 995–1000. https://doi.org/10.1097/SLA.0b013e3181bfdab3

Shanafelt, T. D., Bradley, K. A., Wipf, J. E., & Back, A. L. (2002). Burnout and self-reported patient care in an internal medicine residency program. Annals of Internal Medicine, 136(5), 358–367. https://doi.org/10.7326/0003-4819-136-5-200203050-00008

Stephens, G. C., Karim, M. N., Sarkar, M., Wilson, A. B., & Lazarus, M. D. (2022). Reliability of uncertainty tolerance scales implemented among physicians and medical students: A systematic review and meta-analysis. Academic Medicine, 97(9), 1413–1422. https://doi.org/10.1097/acm.0000000000004641

Stephens, G. C., Lazarus, M. D., Sarkar, M., Karim, M. N., & Wilson, A. B. (2022). Identifying validity evidence for uncertainty tolerance scales: A systematic review. Medical Education, 57(9), 844–856. https://doi.org/10.1111/medu.15014

Stephens, G. C., Sarkar, M., & Lazarus, M. D. (2022). Medical student experiences of uncertainty tolerance moderators: A longitudinal qualitative study. Frontiers in Medicine, 9, Article 864141. https://doi.org/10.3389/fmed.2022.864141

Stephens, G. C., Sarkar, M., & Lazarus, M. D. (2023). ‘I was uncertain, but I was acting on it’: A longitudinal qualitative study of medical students’ responses to uncertainty. Medical Education. Advance online publication. https://doi.org/10.1111/medu.15269

Strout, T. D., Hillen, M., Gutheil, C., Anderson, E., Hutchinson, R., Ward, H., Kay, H., Mills, G. J., & Han, P. K. (2018). Tolerance of uncertainty: A systematic review of health and healthcare-related outcomes. Patient Education & Counseling, 101(9), 1518–1537. https://doi.org/10.1016/j.pec.2018.03.030

van der Weijden, T., van Bokhoven, M. A., Dinant, G. J., van Hasselt, C. M., & Grol, R. P. (2002). Understanding laboratory testing in diagnostic uncertainty: A qualitative study in general practice. British Journal of General Practice, 52(485), 974–980.

Wayne, S., Dellmore, D., Serna, L., Jerabek, R., Timm, C., & Kalishman, S. (2011). The association between intolerance of ambiguity and decline in medical students’ attitudes toward the underserved. Academic Medicine, 86(7), 877–882. https://doi.org/10.1097/ACM.0b013e31821dac01