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      ‘There is no such thing as getting sick justly or unjustly’ – a qualitative study of clinicians’ beliefs on the relevance of personal responsibility as a basis for health prioritisation

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          Abstract

          Background

          Concerns have been raised regarding the reasonableness of using personal health responsibility as a principle or criterion for setting priorities in healthcare. While this debate continues, little is known about clinicians’ views on the role of patient responsibility in clinical contexts. This paper contributes to the knowledge on the empirical relevance of personal responsibility for priority setting at the clinical level.

          Methods

          A qualitative study of Norwegian clinicians ( n = 15) was designed, using semi-structured interviews with vignettes to elicit beliefs on the relevance of personal responsibility as a basis for health prioritisation. Sampling was undertaken purposefully. The interviews were conducted in three hospital trusts in South-Eastern Norway between May 2018 and February 2019 and were analysed with conceptually driven thematic analysis.

          Results

          The findings suggest that clinicians endorsed a general principle of personal health responsibility but were reluctant to introduce personal health responsibility as a formal priority setting criterion. Five main objections were cited, relating to avoidability, causality, harshness, intrusiveness, and inequity. Still, both retrospective and prospective attributions of personal responsibility were perceived as relevant in specific clinical settings. The most prominent argument in favour of personal health responsibility was grounded in the idea that holding patients responsible for their conduct would contribute to the efficient use of healthcare resources. Other arguments included fairness to others, desert and autonomy, but such standpoints were controversial and held only marginal relevance.

          Conclusions

          Our study provides important novel insights into the clinicians’ beliefs about personal health responsibility improving the empirical knowledge concerning its fairness and potential applications to healthcare prioritisation. These findings suggest that although personal health responsibility would be difficult to implement as a steering criterion within the main priority setting framework, there might be clinical contexts where it could figure in prioritisation practices. Additional research on personal health responsibility would benefit from considering the multiple clinical encounters that shape doctor-patient relationships and that create the information basis for eligibility and prioritisation for treatment.

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          Most cited references55

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          Implicit bias in healthcare professionals: a systematic review

          Background Implicit biases involve associations outside conscious awareness that lead to a negative evaluation of a person on the basis of irrelevant characteristics such as race or gender. This review examines the evidence that healthcare professionals display implicit biases towards patients. Methods PubMed, PsychINFO, PsychARTICLE and CINAHL were searched for peer-reviewed articles published between 1st March 2003 and 31st March 2013. Two reviewers assessed the eligibility of the identified papers based on precise content and quality criteria. The references of eligible papers were examined to identify further eligible studies. Results Forty two articles were identified as eligible. Seventeen used an implicit measure (Implicit Association Test in fifteen and subliminal priming in two), to test the biases of healthcare professionals. Twenty five articles employed a between-subjects design, using vignettes to examine the influence of patient characteristics on healthcare professionals’ attitudes, diagnoses, and treatment decisions. The second method was included although it does not isolate implicit attitudes because it is recognised by psychologists who specialise in implicit cognition as a way of detecting the possible presence of implicit bias. Twenty seven studies examined racial/ethnic biases; ten other biases were investigated, including gender, age and weight. Thirty five articles found evidence of implicit bias in healthcare professionals; all the studies that investigated correlations found a significant positive relationship between level of implicit bias and lower quality of care. Discussion The evidence indicates that healthcare professionals exhibit the same levels of implicit bias as the wider population. The interactions between multiple patient characteristics and between healthcare professional and patient characteristics reveal the complexity of the phenomenon of implicit bias and its influence on clinician-patient interaction. The most convincing studies from our review are those that combine the IAT and a method measuring the quality of treatment in the actual world. Correlational evidence indicates that biases are likely to influence diagnosis and treatment decisions and levels of care in some circumstances and need to be further investigated. Our review also indicates that there may sometimes be a gap between the norm of impartiality and the extent to which it is embraced by healthcare professionals for some of the tested characteristics. Conclusions Our findings highlight the need for the healthcare profession to address the role of implicit biases in disparities in healthcare. More research in actual care settings and a greater homogeneity in methods employed to test implicit biases in healthcare is needed.
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            Weight bias among health professionals specializing in obesity.

            To determine the level of anti-fat bias in health professionals specializing in obesity and identify personal characteristics that correlate with both implicit and explicit bias. The Implicit Associations Test (IAT) and a self-report questionnaire assessing explicit attitudes, personal experiences with obesity, and demographic characteristics was administered to clinicians and researchers attending the opening session of an international obesity conference (N = 389). The IAT was used to assess overall implicit weight bias (associating "obese people" and "thin people" with "good" vs. "bad") and three ranges of stereotypes: lazy-motivated, smart-stupid, and valuable-worthless. The questionnaire assessed explicit bias on the same dimensions, along with personal and professional experiences with obesity. Health professionals exhibited a significant pro-thin, anti-fat implicit bias on the IAT. In addition, the subjects significantly endorsed the implicit stereotypes of lazy, stupid, and worthless using the IAT. Level of bias was associated with several personal characteristics. Characteristics significantly predictive of lower levels of implicit anti-fat bias include being male, older, having a positive emotional outlook on life, weighing more, having friends who are obese, and indicating an understanding of the experience of obesity. Even professionals whose careers emphasize research or the clinical management of obesity show very strong weight bias, indicating pervasive and powerful stigma. Understanding the extent of anti-fat bias and the personal characteristics associated with it will aid in developing intervention strategies to ameliorate these damaging attitudes.
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              Implicit and Explicit Anti-Fat Bias among a Large Sample of Medical Doctors by BMI, Race/Ethnicity and Gender

              Overweight patients report weight discrimination in health care settings and subsequent avoidance of routine preventive health care. The purpose of this study was to examine implicit and explicit attitudes about weight among a large group of medical doctors (MDs) to determine the pervasiveness of negative attitudes about weight among MDs. Test-takers voluntarily accessed a public Web site, known as Project Implicit®, and opted to complete the Weight Implicit Association Test (IAT) (N = 359,261). A sub-sample identified their highest level of education as MD (N = 2,284). Among the MDs, 55% were female, 78% reported their race as white, and 62% had a normal range BMI. This large sample of test-takers showed strong implicit anti-fat bias (Cohen’s d = 1.0). MDs, on average, also showed strong implicit anti-fat bias (Cohen’s d = 0.93). All test-takers and the MD sub-sample reported a strong preference for thin people rather than fat people or a strong explicit anti-fat bias. We conclude that strong implicit and explicit anti-fat bias is as pervasive among MDs as it is among the general public. An important area for future research is to investigate the association between providers’ implicit and explicit attitudes about weight, patient reports of weight discrimination in health care, and quality of care delivered to overweight patients.
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                Author and article information

                Contributors
                gloria.traina@medisin.uio.no
                eli.feiring@medisin.uio.no
                Journal
                BMC Health Serv Res
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central (London )
                1472-6963
                3 June 2020
                3 June 2020
                2020
                : 20
                : 497
                Affiliations
                GRID grid.5510.1, ISNI 0000 0004 1936 8921, Department of Health Management and Health Economics, , University of Oslo, ; Post box 1089 Blindern, 0317 Oslo, Norway
                Author information
                http://orcid.org/0000-0003-1068-4509
                Article
                5364
                10.1186/s12913-020-05364-6
                7268691
                32493300
                3ddbda3b-6f3c-4249-a1be-6ad1033b15d9
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 22 December 2019
                : 25 May 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100005366, Universitetet i Oslo;
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                Health & Social care
                norway,personal health responsibility,clinical priority setting,clinicians’ beliefs,vignettes,conceptually driven thematic analysis

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