Tolerance of ambiguity and psychological well-being in medical training: A systematic review

Context The prevalence of stress, burnout and mental health disorders in medical students and doctors is high. It has been proposed that there may be an association between levels of tolerance of ambiguity (ie an ability to tolerate a lack of reliable, credible or adequate information) in clinical work and psychological well-being within this population. The aims of this systematic review were: (i) to assess the nature and extent of the literature available, in order to determine if there is an association, and (ii) to develop a conceptual model proposing possible mechanisms to underpin any association, in order to inform subsequent research. Methods MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and PsycINFO databases were searched for articles published from inception to September 2018. Additional literature was identified by searching the reference lists of included articles, forward searches of included articles, hand searches of key journals and a grey literature search. Of the 671 studies identified, 11 met the inclusion criteria. A qualitative synthesis of included studies was performed. Results All 11 included studies reported an association between a lower level of tolerance of ambiguity or uncertainty and reduced psychological well-being. Included studies were heterogeneous in terms of population and measurement approach, and were often of low methodological quality. Subsets of items from previously developed scales were often used without sufficient consideration of the impact of new combinations of items on scale validity. Similar scales were also scored inconsistently between studies, making comparison difficult. Conclusions There appears to be an association between tolerance of ambiguity and psychological well-being. This provides new opportunities to understand and prevent the development of stress, burnout and mental health disorders in medical students and doctors. The conceptual model developed provides a framework for future research, which we hope will prevent wasted research effort through duplication and promote higher methodological quality.