Do Poor Patients Suffer from Inaccurate Diagnoses More than Well-to-do Patients? A Randomized Control Trial

Do Poor Patients Suffer from Inaccurate Diagnoses More than Well-to-do Patients? 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A Randomized Control Trial Ibrahim Alwan Al Alwan, Mohi Eldin Mohammed Ali Magzoub, Ali Al Haqwi, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.2.10096/v2 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Oct, 2019 Read the published version in BMC Medical Education → Version 2 posted 4 You are reading this latest preprint version Show more versions Abstract Abstract Background. Poor patients have greater morbidity and die up to ten years earlier than patients who have higher socio-economic status. These findings are often attributed to differences in life-style between groups. The present study aimed at investigating the extent to which physicians contribute to the effect by providing relative poorer care, perhaps resulting in relative neglect in terms of time spent with a poor patient and more inaccurate diagnoses. Methods. A randomised experiment with 45 internal medicine residents. Doctors diagnosed twelve written clinical vignettes that were exactly the same except for the description of the patients' socio-economic status. Each participant diagnosed four of the vignettes in a poor-patient version, four in a rich-patient version, and four in a version that did not contain socio-economic markers, in a balanced within-subjects incomplete block design. Main measurements were: diagnostic accuracy scores and time spent on diagnosis. Results. Mean diagnostic accuracy scores (range 0-1) did not significantly differ among the conditions of the experiment (for poor patients: 0.48; for rich patients: 0.52; for patients without socio-economic markers: 0.54; p > 0.05). While confronted with patients not presenting with socio-economic background information, the participants spent significantly less time-to-diagnosis ((for poor patients: 168 seconds; for rich patients: 176 seconds; for patients without socio-economic markers: 151 seconds; p < 0.01), however due to the fact that the former vignettes were shorter. Conclusion. There is no reason to believe that physicians are prejudiced against poor patients and therefore treat them differently from rich patients or patients without discernible socio-economic background. Educational Philosophy and Theory Health Economics & Outcomes Research Medical errors clinical reasoning poor rich Introduction People of lower socio-economic status are generally in poorer health than the better educated ( 1-5 ). They engage in unhealthy behaviors, such as smoking, alcohol consumption, and physical inactivity ( 3 ), are suffering from stress to a larger extent ( 6-8 ), and consume unhealthy food more often ( 9 ). In addition, people in the most-disadvantaged socio-economic-status quartile have an almost three-fold increased risk of mortality relative to those in the least-disadvantaged quartile ( 3 ). On average, poor people die up to ten years earlier than their more well-to-do counterparts ( 2 ). Studies in search of causal factors have concentrated on the lifestyle factors mentioned above. Less is known yet about institutional factors that contribute to poor health, such as differential access to health care facilities ( 10 ), or late-stage diagnosis of disease ( 11 ). Even less is known about how physicians deal with poor, as opposed to well-to-do, patients. It is possible that part of the greater morbidity and mortality of poor people is due to relative neglect of their doctors. There are some studies that seem to imply that this is indeed the case, for instance in referral to psychotherapy ( 12 ), or in the diagnosis of late-stage breast cancer ( 13 ). Rathore, Berger (14) found that poor patients were treated less adequately when acute myocardial infarction was concerned. These studies were however observational in nature. We only came across two studies in which social class was experimentally controlled. In the first study ( 15 ), participating primary care doctors viewed two video-vignettes of a scripted consultation in which the patient presented with standardized symptoms of coronary heart disease. Videotapes were identical apart from varying patients’ gender, age, class and race. Gender of patient significantly influenced doctors’ diagnostic and management activities. However, there was no influence of social class, neither on the doctor's diagnosis, nor on the management activities undertaken. It is however possible that the actors playing the various roles were not able to present sufficiently different personalities. In a second study ( 16 ), our own research group presented residents in internal medicine with identical case vignettes for diagnosis. However, half of the subjects received the vignettes accompanied by a picture of a clearly poor person—clothes looked second-hand and contained rips; faces were dirty—while the other half received a picture of the same person, but in clearly well-to-do clothing. The expectation was that poor-looking patients would receive less attention (as measured by the amount of time needed to reach a diagnosis) and would be subject to less accurate diagnosis. However, we failed to find such differences. In hindsight, the latter study had three potential shortcomings. The first was that we only presented two patients—a man and a woman in two different guises-- rather than a more diverse group of patients. The second was that a more or less classless version of our patients was not included in the design. It is possible that social class information—whatever its nature--influences diagnostic decision making mainly by increasing the number of possible alternative diagnoses. For instance, a poor miner plagued with headaches may lead the doctor to think of lung-related diseases, whereas the presentation of an obese businessman with headaches may lead him or her to think of cardiovascular causes. A presentation of the same patient without class-related characteristics may not be burdened by such possibly unproductive hypotheses. And the third shortcoming was similar to the Arber, McKinlay (15) study, in that the patients still may have looked too much alike. It is for instance possible that doctors deduce social class from characteristics other than poor clothing or dirt on faces. We therefore, decided to follow a strategy that we successfully employed in two earlier studies on the effect of difficult patients on diagnostic decision-making ( 17 , 18 ): we did not show videos or pictures of the patients, but described them. This article reports results of an experiment that attempted to test the hypothesis that greater morbidity and mortality of patients with low socio-economic status may (also) be caused by physicians providing relative poorer care, resulting perhaps in relative neglect in terms of time spent with a poor patient and more inaccurate diagnoses. In this experiment, physicians were confronted with twelve vignettes of patients of different socio-economic status but with the same symptoms and the same underlying diseases. Using a within-subjects design, each participant was confronted, in random order, with four poor, four rich, and four patients for whom no class information was available. The number of accurate diagnoses, and time needed to reach a diagnosis, were recorded. Method Participants Participants were 45 internal medicine residents (mean age = 28.91; standard deviation = 2.45; 31 male) from the College of Medicine, King Saud bin Abdelaziz University for Health Sciences, Jeddah, Saudi Arabia. The residents had on average 3.60 years of post-medical-school experience (standard deviation = 1.90). All 60 residents of this group were invited to participate in the study between December 2012 and March 2014, and volunteers were recruited. No incentive was provided for participation. The ethics review committee from King Abdullah International Medical Research Center ( KAIMRC ), approved this study. As the nature of the experiment prevented disclosure of its objectives beforehand, participants were informed about their tasks and debriefed later. All participants signed consent to use their data. The sample sizes were computed based on similar studies demonstrating that mean differences tend to revolve around .35 with a mean standard deviation of .55. The sample size can then be computed with the formula n = 1 + 2C (s/d) 2 ( https://www.ncbi.nlm.nih.gov/books/NBK43321/ ) where s is the standard deviation to be expected and d is the difference between means. C is a constant based on a-level and power of the test. With an a < .05 and power = .80, C = 7.85. From this it follows that n should be at least equal to 40. This suggests that our sample was sufficiently large to find treatment effects if they exist. Materials Twelve clinical cases, prepared by one of the senior researchers (M.E.M.) and based on cases used in previous studies ( 17-19 ), were employed in this experiment. All cases had a confirmed diagnosis and consisted of a brief description of a patient’s history, complaints, symptoms, and findings from physical examination and tests. Table 1 contains the twelve diagnoses. Table 1. Diseases involved in the study; descriptions of rich and poor patients Cases Rich version Poor version Stomach Cancer The first patient of the day is a 74-year-old businessman. He is married and lives in the Al Shati locality in Jeddah. You noticed him even before he entered your office because of his luxurious car that you have seen through the window of the clinic. The first patient of the day is a 74-year-old unemployed man. He is married and lives in Al Kirinteana Locality in Jeddah. You notice the bad smell that comes from his dirty clothes when he enters your office. Vitamin B12 deficiency A 62-year-old man who is a Minister and an owner of a big mall accompanied by two security guards comes to your clinic A 62-year-old man who lives in the Gholail locality in Jeddah, working as a school guard, living in a two-bedroom house with his wife and ten children between ages five and twenty one Pulmonary thromboembolism A 31-year-old lady, the second wife of the owner of the largest company in Jeddah. She is well-dressed, wearing a pure golden watch A 31-year-old divorced lady living with her large family in Inaikish locality. The family includes six single sisters, two unemployed brothers, her retired father and blind mother. Celiac disease A 29-year-old woman, the chair of the association of women in business A 29-year-old lady lives in the Lilosix area in Jeddah, works as a housemaid, and is poorly dressed Acute viral pericarditis A 78-year-old man who owns a five-star hotel in Mecca, lives in a palace located in Al Basatean locality in Jeddah with his four wives A 78-year-old homeless man, whom you observed several times begging at the busiest traffic light on the way to your hospital, Acute myeloid leukemia A 29-year-old engineer who owned the largest construction company in the city, wearing a bisht A 29-year-old driver, a father of six children, living in the Al Sabeel area in Jeddah. Acute bacterial endocarditis You have been called by the director of the hospital to take extra care of a 27-year-old businessman, well-known in town A 27-year-old man working as a cleaner and living with his large family in Inaikish, one of the poorest areas of Jeddah Sarcoidosis A 25-year-old man, the eldest son of the owner of a large profitable communication company, A 25-year-old man, unemployed and homeless, originating from Al Khumra area in Jeddah Acute appendicitis A 23-year-old female, the daughter of the Secretary General of Jeddah municipality, accompanied by two housemaids and a driver in addition to her mother A 23-year-old female, the daughter of a school guard, who came walking all the way to the hospital Community-acquired pneumonia The patient is an obese 56-year-old woman, mother of multiple children, married to a renowned businessman in Jeddah The patient is an obese 56-year-old woman, mother of multiple children, and the wife of a teaman (Sabbab) living in Bani Malik area in Jeddah Liver cirrhosis A 52-year old eminent lawyer who is also the legal advisor of the largest construction company in the city A 52-year-old retired laborer in the civil service who is a single father of six daughters and two younger sons who are still in school Addison Disease A 45-year-old woman, well-dressed and wiring expensive jewelry and large heavy golden bracelets A 45-year-old woman, married to a gardener, working in one of the parks in Jeddah with large family Inflammatory bowel disease A 32-year-old woman living in Al Salamah Locality in Jeddah A 32-year-old housemaid In each case, a few sentences described aspects of the patient’s socio-economic status. These sentences portrayed either a patient of apparently high socio-economic position, a patient of apparently low socio-economic position, or a patient without any socio-economic markers (called “rich,” “poor,” and “neutral” patients from here), effectively producing three versions of the same clinical case. Two co-authors (I.A.; M.E.M.) prepared the descriptions based on the kind of patients one would see in the consulting room in Saudi Arabia. Table 1 also contains the short descriptions of rich and poor patients included. The neutral patient description only contained age information. In all other respects the different versions were identical, leading to the same diagnosis. Table 2 presents an example of three versions of the same case. Table 2. Example of three versions of a clinical case Rich version Poor version Neutral version The first patient of the day is a 74-year-old businessman. He is married and lives in the Al Shati locality in Jeddah. You noticed him even before he entered your office because of his luxurious car that you have seen through the window of the clinic. The first patient of the day is a 74-year-old unemployed man. He is married and lives in Al Kirinteana Locality in Jeddah. You notice the bad smell that comes from his dirty clothes when he enters your office. The first patient of the day is a 74-year old man. He has had complaints of slight pain in the epigastric area, anorexia and progressive weight loss in the past 4 months. He started to get fatigued easily and to have dizziness when walking, over the past two days. He refers occasional dark stools. The patient is a smoker. He refers chronic use of NSAID for osteoarthritis of the knees. Family history: father had a gastric ulcer. Physical examination: Patient considerably emaciated. Bp 135/80 mmHg; Pulse 88/ min.; Respiration 24/ min.; Temp 37.4 degrees of C. Heart: no abnormalities. Lungs: no abnormalities. Abdomen: slight pain on palpation in the epigastric area. Lab tests: Hb: 8.4; Ht: 20.9 % Procedure The study employed a within-subjects design. A full within-subjects design would imply the presentation of all three versions of each case to the participants. Such presentation of three versions of the same case would however likely lead to carry-over effects: when one has seen one version, diagnosing the second, or a third, may become easier. An alternative is to present to each participant one-third of the cases in rich, one-third in poor, and one-third of the cases in neutral format, however in different combinations. In other words: Every participant received four rich patients, four poor patients, and four neutral patients such that all twelve diseases were seen once. For instance, if A1 represents a rich-patient version of diagnosis A, A2 its poor version and A3 its neutral version, then the first participant would receive the cases A1, B2, C3, D1, E2, and F3, etc., whereas the second participant would receive the cases A2, B3, C1, D2, E3, and F1, etc. Such balanced within-subjects incomplete block design enabled us to compare mean diagnostic performance scores and time-to diagnosis under the three experimental conditions. The cases were presented on a computer screen using Qualtrics software (Qualtrics XM Platform™) First, they were informed that the study aimed to better understand the nature of clinical problem-solving in Internal Medicine. Second, they were informed that their responses were anonymous since no identifying information would be collected and that their results would have no implications for their work. Their task was to diagnose the clinical cases presented shortly. All cases were based on real patients and had a confirmed diagnosis. Further, they were asked to work as quickly as possible; suggesting that a first impression is often correct. They should, however, not compromise accuracy. They were instructed to type only one complete and precise diagnosis which they found to be the MOST accurate for the case presented. They were also informed that once they clicked to the next case, they could not go back to previous screens. After being informed, they received a practice case, unrelated to the hypotheses tested. Data analysis The accuracy of participants’ diagnoses was evaluated by considering the confirmed diagnosis of each case as a standard. Two physicians (I.A.; M.E.M.) independently evaluated each diagnosis, without knowing the condition under which it was provided, as correct, partially correct, or incorrect (scored as 1, 0.5, or 0 points, respectively). A response was considered correct whenever it mentioned the core diagnosis, and partially correct when the core diagnosis was not cited but a constituent element of the diagnosis was mentioned. For example, in a case of gastric cancer, “Gastric malignancy” was considered correct, and “Malignancy; most likely colorectal cancer” was evaluated as partially correct. The two experts agreed in 85% of the diagnoses and solved discrepancies through discussion. A repeated-measures ANOVA with patient socio-economic status (rich vs poor vs neutral) as within-subjects factors was performed on the mean diagnostic accuracy scores. This analysis tested the hypothesis that the description of poor patients would negatively affect diagnostic accuracy. To check whether the description of poor patients led doctors to speed up the diagnostic process, we performed a repeated-measures ANOVA with socio-economic status as a within-subjects factor on time spent to make the diagnosis. Significance levels were set at p < 0.05 for all comparisons. SPSS version 24.0 (SPSS Inc, Chicago, Illinois) was used for the statistical analyses. Results Table 3 contains the findings from this study. Table 3. Mean diagnostic accuracy scores (range 0 – 1; standard deviations into brackets) and mean time spent in diagnosing the written clinical cases (seconds) as a function of patients’ socio-economic status, N = 45 Poor patients Rich patients Neutral patients Diagnostic accuracy 0.48 (0.23) 0.52 (0.26) 0.54 (0.24) Time spent on diagnosis 167.57 (60.01) 176.10 (65.57) 150.66 (54.08) Participants made more mistakes when diagnosing poor patient cases relative to neutral or rich patient cases, but this effect did not reach statistical significance: F (2, 43) = 0.47, p > .05. Time spent on diagnosis did however significantly differ, F (2, 43) = 7.57, p < .01. Participants needed significantly less time to diagnose neutral patients; this effect was however entirely due to the fact that the neutral patient versions were shorter than the other cases: F (2, 43) = 2.27, p > .05. Discussion Poor patients die much earlier than their more well-to-do fellow citizens ( 2 , 3 ). The question central to the present study was the extent to which doctor neglect contributes to this empirical finding. To that end, 45 residents of a Saudi medical school were presented with twelve cases in three different versions. One version described a rich patient, one a poor patient, and the third a patient from which no socio-economic characteristics could be deduced. Each version presented the same disease underlying the signs and symptoms presented. We failed to find any meaningful differences in diagnostic accuracy and time-to-diagnosis. Our experiment presents a third attempt to experimentally study the influence of socio-economic status on the precision of physicians’ diagnoses and their engagement with patients of different socio-economic backgrounds, expressed as the amount of time they spent on diagnosing the cases. Two previous attempts, also failing to find differences ( 15 , 16 ), had serious methodological shortcomings, and our design remediated these. The common assumption was, that doctors, perhaps due to implicit prejudices, would attach less value to the health of poorer patients and therefore would provide less appropriate care. Prejudices against poor people are broadly shared ( 20 , 21 ). Paul Gorski ( 22 ), in his “Myth of the culture of poverty” mentions a number of these preconceptions with regard to poor people: Poor people would be unmotivated and have weak work ethics; poor parents are supposed to be uninvolved in their children's learning, largely because they do not value education; and poor people tend to abuse drugs and alcohol (all turn out to be largely false). Our participants did not seem to suffer from those prejudices, at least not within the context of the present experiment: they spent equal amounts of time on each of the patients presented, and came to similar diagnostic decisions, irrespective of the socio-economic background of the patient. With some confidence, and in the light of the previous findings, we conclude that, at least within the realm of experimental approaches to the issue, doctors do not deal with their patients differently based on whether they are rich or poor. We state this conclusion with some certainty because our study used a within-group design, excluding the possibility of confounding factors due to poor randomization. In addition, we have used the same methodology in similar studies, demonstrating that our procedures are sensitive to experimental manipulations of the kind attempted in this study ( 23 , 24 ). For instance, in a study on the negative influence of so called “difficult patients,” using the same methods, we were able to demonstrate rather strong effects with similarly subtle differences in the descriptions of patients ( 17 , 18 ). Finally, within-group variances are similar to those of other studies using the same methods. There are several limitations to our findings. First, we used written case vignettes rather than more authentic representations of patients. This may have biased the results. However, previous studies comparing vignettes with other methods (standardized patients, chart abstraction) have demonstrated that case vignettes reliably detect differences in clinical decision-making among different groups and they are therefore a good proxy for examining physicians’ behaviours in real settings ( 25-27 ). A second problem is the external validity of our findings. An experimental approach forces researchers to reduce complexity of the event studied, so that internal validity is assured. (Internal validity guaranties that causal conclusions drawn from the findings are accurate). However, it is possible that physicians do not so much respond to more or less “objective” indicators of poverty, such as a job that someone has, or the community where he or she comes from, but to more subtle characteristics of people in the consulting room, such as their smell, the way they talk, or the way they interact. Such characteristics cannot be studied with the approach used in this study and the ones summarized here. This implies that there is room for further study. Declarations Ethics approval and consent to participate. This research is approved by the IRB committee of King Abdullah International Medical Recearch Center, Saudi Arabia Consent for Publication Not Applicable Availability of data and materials. The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request Competing interest. The corresponding author (MM) is the member of the Editorial Board of BMC medical education (Associate editors. Other authors no competing interest Funding. This research is funded by King Abduaziz Medical City, Saudi Arabia Grant Number 84/34. The funding agent has no reole in the design of the study; data collection, analysis, and interpretation of data; and the writing of manuscript. Authors contribution IA help in the design of the study, data collection and manuscript revision, MM help in the writing proposal, study design data collection and manuscript writing, AA helped in data collection and manuscript revision, SM helped in study design, data analysis and manuscript writing, SA helped in data collection and manuscript revision, AB Helped in Manuscript revision and data collection, HS helped in study design, data analysis and manuscript writing. Acknowledgement. The authors would kike to appreciate the contribution of King Abdulaziz Medical City for funding this study. References Adler NE, Boyce T, Chesney MA, Cohen S, Folkman S, Kahn RL, et al. Socioeconomic status and health: the challenge of the gradient. American psychologist. 1994;49(1):15. Meara ER, Richards S, Cutler DM. The Gap Gets Bigger: Changes In Mortality And Life Expectancy, By Education, 1981–2000. Health Affairs. 2008;27(2):350-60. Nandi A, Glymour MM, Subramanian S. Association among socioeconomic status, health behaviors, and all-cause mortality in the United States. Epidemiology. 2014;25(2):170-7. Starfield B. Effects of poverty on health status. Bulletin of the New York Academy of Medicine. 1992;68(1):17. Winkleby MA, Jatulis DE, Frank E, Fortmann SP. Socioeconomic status and health: how education, income, and occupation contribute to risk factors for cardiovascular disease. American Journal of Public Health. 1992;82(6):816-20. Baum A, Garofalo J, Yali A. Socioeconomic status and chronic stress: does stress account for SES effects on health? Annals of the New York Academy of Sciences. 1999;896(1):131-44. Taylor SE, Seeman TE. Psychosocial resources and the SES‐health relationship. Annals of the New York Academy of Sciences. 1999;896(1):210-25. Vliegenthart J, Noppe G, Van Rossum E, Koper J, Raat H, Van den Akker E. Socioeconomic status in children is associated with hair cortisol levels as a biological measure of chronic stress. Psychoneuroendocrinology. 2016;65:9-14. Darmon N, Drewnowski A. Contribution of food prices and diet cost to socioeconomic disparities in diet quality and health: a systematic review and analysis. Nutrition reviews. 2015;73(10):643-60. Shortt SE, Shaw RA. Equity in Canadian health care: Does socioeconomic status affect waiting times for elective surgery? Canadian Medical Association Journal. 2003;168(4):413-6. Breen N, Figueroa JB. Stage of breast and cervical cancer diagnosis in disadvantaged neighborhoods: a prevention policy perspective. American journal of preventive medicine. 1996;12(5):319-26. Garb HN. Race bias, social class bias, and gender bias in clinical judgment. Clinical Psychology-Science and Practice. 1997;4(2):99-120. Mandelblatt J, Andrews H, Kerner J, Zauber A, Burnett W. Determinants of late stage diagnosis of breast and cervical cancer: the impact of age, race, social class, and hospital type. American Journal of Public Health. 1991;81(5):646-9. Rathore SS, Berger AK, Weinfurt KP, Feinleib M, Oetgen WJ, Gersh BJ, et al. Race, sex, poverty, and the medical treatment of acute myocardial infarction in the elderly. Circulation. 2000;102(6):642-8. Arber S, McKinlay J, Adams A, Marceau L, Link C, O'Donnell A. Patient characteristics and inequalities in doctors' diagnostic and management strategies relating to CHD: A video-simulation experiment. Social Science & Medicine. 2006;62(1):103-15. Mohamed F, Mamede S, Mohamedani M, Alwan IA, Magzoub MEM, Schmidt HG. The Effect of Patients׳ Appearance on Doctors’ Diagnostic Decision Making: Do Poor People Get Poorer Medical Care? Health Professions Education. 2016;2(1):18-23. Mamede S, Van Gog T, Schuit SCE, Van den Berge K, Van Daele PLA, Bueving H, et al. Why patients' disruptive behaviours impair diagnostic reasoning: a randomised experiment. BMJ Quality & Safety. 2017;26(1):13-8. Schmidt HG, van Gog T, Schuit SCE, Van den Berge K, Van Daele PLA, Bueving H, et al. Do patients' disruptive behaviours influence the accuracy of a doctor's diagnosis? A randomised experiment. BMJ Quality & Safety. 2017;26(1):19-23. Mamede S, van Gog T, van den Berge K, van Saase JLCM, Schmidt HG. Why Do Doctors Make Mistakes? A Study of the Role of Salient Distracting Clinical Features. Academic Medicine. 2014;89(1):114-20. Cozzarelli C, Wilkinson AV, Tagler MJ. Attitudes toward the poor and attributions for poverty. Journal of Social Issues. 2001;57(2):207-27. Lott B. Cognitive and behavioral distancing from the poor. American Psychologist. 2002;57(2):100. Gorski P. The Myth of the``Culture of Poverty''. Educational leadership. 2008;65(7):32. ALQahtani DA, Rotgans JI, Mamede S, ALAlwan I, Magzoub MEM, Altayeb FM, et al. Does Time Pressure Have a Negative Effect on Diagnostic Accuracy? Academic Medicine. 2016;91(5):710-6. Mamede S, van Gog T, Sampaio AM, de Faria RMD, Maria JP, Schmidt HG. How Can Students' Diagnostic Competence Benefit Most From Practice With Clinical Cases? The Effects of Structured Reflection on Future Diagnosis of the Same and Novel Diseases. Academic Medicine. 2014;89(1):121-7. Peabody JW, Luck J, Glassman P, Jain S, Hansen J, Spell M, et al. Measuring the quality of physician practice by using clinical vignettes: A prospective validation study. Annals of Internal Medicine. 2004;141(10):771-80. Peabody JW, Luck J, Glassman P, Dresselhaus TR, Lee M. Comparison of vignettes, standardized patients, and chart abstraction - A prospective validation study of 3 methods for measuring quality. Jama-Journal of the American Medical Association. 2000;283(13):1715-22. Mohan D, Fischhoff B, Farris C, Switzer GE, Rosengart MR, Yealy DM, et al. Validating a Vignette-Based Instrument to Study Physician Decision Making in Trauma Triage. Medical Decision Making. 2014;34(2):242-52. Cite Share Download PDF Status: Published Journal Publication published 22 Oct, 2019 Read the published version in BMC Medical Education → Version 2 posted Editorial decision: Accept 11 Sep, 2019 Editor assigned by journal 09 Sep, 2019 Submission checks completed at journal 08 Sep, 2019 Editor invited by journal 08 Sep, 2019 You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1181","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":153295,"identity":"2014b45e-e59c-45ec-9761-d10063fdeb6e","order_by":1,"name":"Ibrahim Alwan Al Alwan","email":"","orcid":"","institution":"King Saud bin Abdulaziz University for Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ibrahim","middleName":"Alwan Al","lastName":"Alwan","suffix":""},{"id":153296,"identity":"899db2b7-c890-4f1e-b32d-ec694e9b7c1c","order_by":2,"name":"Mohi Eldin Mohammed Ali Magzoub","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYBCDBH7StUg2kKzF4ACxSnWnHX788kfF4TzjG8kPH/Mw2MkzsB/Gr9vsdpqZhcSZw8VmN9KMjXkYkg0beNISCGhJMDMwbDucuO1Ggpk0DwMzUHmOAQEt6d8MEoFaNs9I//6bh6E+gYH//QcCWnKMHxwEatkgkWPGzMNwOIFBIgevDpCWMsaGM+nFEmfeFEvOMThu2CbxjKDDNn/8UWGdx9+evvHDm4pqeX7+5Af4rWFgYJNAsIHmsxFSDwTM+H07CkbBKBgFowAADcRGQBm1CwUAAAAASUVORK5CYII=","orcid":"","institution":"United Arabs Emirates University","correspondingAuthor":true,"prefix":"","firstName":"Mohi","middleName":"Eldin Mohammed Ali","lastName":"Magzoub","suffix":""},{"id":153297,"identity":"ff29dc8e-549e-43e6-a29d-1dd82d1b8e7a","order_by":3,"name":"Ali Al Haqwi","email":"","orcid":"","institution":"King Saud bin Abdulaziz University for health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"Al","lastName":"Haqwi","suffix":""},{"id":153298,"identity":"37ed8953-e4ca-4e07-b076-ce038a2f053e","order_by":4,"name":"Motasim Badri","email":"","orcid":"","institution":"King Saud bin Abdulaziz University for health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Motasim","middleName":"","lastName":"Badri","suffix":""},{"id":153299,"identity":"193d772a-938f-45dd-bfa5-04117d3c5fb4","order_by":5,"name":"Sarah Al Yousif","email":"","orcid":"","institution":"King Saud bin Abdulaziz University for health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"Al","lastName":"Yousif","suffix":""},{"id":153300,"identity":"aa065440-0154-4179-835b-e4a9cdfeb1f2","order_by":6,"name":"Amir Babiker","email":"","orcid":"","institution":"King Saud bin Abdulaziz University for health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Amir","middleName":"","lastName":"Babiker","suffix":""},{"id":153301,"identity":"6012f8bd-c4bc-4cb4-95cd-44126fff6816","order_by":7,"name":"Silvia Mamede","email":"","orcid":"","institution":"Institute of Medical Education Research, Erasmus University of Rotterdam","correspondingAuthor":false,"prefix":"","firstName":"Silvia","middleName":"","lastName":"Mamede","suffix":""},{"id":153302,"identity":"573520da-4d1e-4eea-83f4-1633b349fb83","order_by":8,"name":"Henk Schmidt","email":"","orcid":"","institution":"King Saud Bin Abdulaziz University ofr Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Henk","middleName":"","lastName":"Schmidt","suffix":""}],"badges":[],"createdAt":"2019-06-03 15:20:30","currentVersionCode":2,"declarations":"","doi":"10.21203/rs.2.10096/v2","doiUrl":"https://doi.org/10.21203/rs.2.10096/v2","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12909-019-1805-6","type":"published","date":"2019-10-22T12:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":13476823,"identity":"9d8baffb-8bde-4081-afcb-fdfe8b5d5a0d","added_by":"auto","created_at":"2021-09-16 21:28:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":225225,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1181/v2/bdfe7a9c-1bb1-4925-9416-f143dd0743df.pdf"}],"financialInterests":"","formattedTitle":"Do Poor Patients Suffer from Inaccurate Diagnoses More than Well-to-do Patients? A Randomized Control Trial","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePeople of lower socio-economic status are generally in poorer health than the better educated (\u003ca href=\"#_ENREF_1\"\u003e1-5\u003c/a\u003e). They engage in unhealthy behaviors, such as smoking, alcohol consumption, and physical inactivity (\u003ca href=\"#_ENREF_3\"\u003e3\u003c/a\u003e), are suffering from stress to a larger extent (\u003ca href=\"#_ENREF_6\"\u003e6-8\u003c/a\u003e), and consume unhealthy food more often (\u003ca href=\"#_ENREF_9\"\u003e9\u003c/a\u003e). In addition, people in the most-disadvantaged socio-economic-status quartile have an almost three-fold increased risk of mortality relative to those in the least-disadvantaged quartile (\u003ca href=\"#_ENREF_3\"\u003e3\u003c/a\u003e). On average, poor people die up to ten years earlier than their more well-to-do counterparts (\u003ca href=\"#_ENREF_2\"\u003e2\u003c/a\u003e).\u003c/p\u003e\n\u003cp\u003eStudies in search of causal factors have concentrated on the lifestyle factors mentioned above. Less is known yet about institutional factors that contribute to poor health, such as differential access to health care facilities (\u003ca href=\"#_ENREF_10\"\u003e10\u003c/a\u003e), or late-stage diagnosis of disease (\u003ca href=\"#_ENREF_11\"\u003e11\u003c/a\u003e). Even less is known about how \u003cem\u003ephysicians\u003c/em\u003e deal with poor, as opposed to well-to-do, patients. It is possible that part of the greater morbidity and mortality of poor people is due to relative neglect of their doctors.\u003c/p\u003e\n\u003cp\u003eThere are some studies that seem to imply that this is indeed the case, for instance in referral to psychotherapy (\u003ca href=\"#_ENREF_12\"\u003e12\u003c/a\u003e), or in the diagnosis of late-stage breast cancer (\u003ca href=\"#_ENREF_13\"\u003e13\u003c/a\u003e). \u0026nbsp;\u003ca href=\"#_ENREF_14\"\u003eRathore, Berger (14)\u003c/a\u003e found that poor patients were treated less adequately when acute myocardial infarction was concerned. These studies were however observational in nature. We only came across two studies in which social class was experimentally controlled. In the first study (\u003ca href=\"#_ENREF_15\"\u003e15\u003c/a\u003e), participating primary care doctors viewed two video-vignettes of a scripted consultation in which the patient presented with standardized symptoms of coronary heart disease. Videotapes were identical apart from varying patients\u0026rsquo; gender, age, class and race. Gender of patient significantly influenced doctors\u0026rsquo; diagnostic and management activities. However, there was no influence of social class, neither on the doctor's diagnosis, nor on the management activities undertaken. It is however possible that the actors playing the various roles were not able to present sufficiently different personalities. In a second study (\u003ca href=\"#_ENREF_16\"\u003e16\u003c/a\u003e), our own research group presented residents in internal medicine with identical case vignettes for diagnosis. However, half of the subjects received the vignettes accompanied by a picture of a clearly poor person\u0026mdash;clothes looked second-hand and contained rips; faces were dirty\u0026mdash;while the other half received a picture of the same person, but in clearly well-to-do clothing. The expectation was that poor-looking patients would receive less attention (as measured by the amount of time needed to reach a diagnosis) and would be subject to less accurate diagnosis. However, we failed to find such differences.\u003c/p\u003e\n\u003cp\u003eIn hindsight, the latter study had three potential shortcomings. The first was that we only presented two patients\u0026mdash;a man and a woman in two different guises-- rather than a more diverse group of patients. The second was that a more or less classless version of our patients was not included in the design. It is possible that social class information\u0026mdash;whatever its nature--influences diagnostic decision making mainly by increasing the number of possible alternative diagnoses. For instance, a poor miner plagued with headaches may lead the doctor to think of lung-related diseases, whereas the presentation of an obese businessman with headaches may lead him or her to think of cardiovascular causes. A presentation of the same patient without class-related characteristics may not be burdened by such possibly unproductive hypotheses. And the third shortcoming was similar to the \u003ca href=\"#_ENREF_15\"\u003eArber, McKinlay (15)\u003c/a\u003e study, in that the patients still may have looked too much alike. It is for instance possible that doctors deduce social class from characteristics other than poor clothing or dirt on faces. We therefore, decided to follow a strategy that we successfully employed in two earlier studies on the effect of difficult patients on diagnostic decision-making (\u003ca href=\"#_ENREF_17\"\u003e17\u003c/a\u003e, \u003ca href=\"#_ENREF_18\"\u003e18\u003c/a\u003e): we did not show videos or pictures of the patients, but described them.\u003c/p\u003e\n\u003cp\u003eThis article reports results of an experiment that attempted to test the hypothesis that greater morbidity and mortality of patients with low socio-economic status may (also) be caused by physicians providing relative poorer care, resulting perhaps in relative neglect in terms of time spent with a poor patient and more inaccurate diagnoses. In this experiment, physicians were confronted with twelve vignettes of patients of different socio-economic status but with the same symptoms and the same underlying diseases. Using a within-subjects design, each participant was confronted, in random order, with four poor, four rich, and four patients for whom no class information was available. The number of accurate diagnoses, and time needed to reach a diagnosis, were recorded.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants were 45 internal medicine residents (mean age = 28.91; standard deviation = 2.45; 31 male) from the College of Medicine, King Saud bin Abdelaziz University for Health Sciences, Jeddah, Saudi Arabia. The residents had on average 3.60 years of post-medical-school experience (standard deviation = 1.90). All 60 residents of this group were invited to participate in the study between December 2012 and March 2014, and volunteers were recruited. No incentive was provided for participation. The ethics review committee from King Abdullah International Medical Research Center (\u003ca href=\"http://kaimrc.med.sa/\"\u003eKAIMRC\u003c/a\u003e), approved this study. As the nature of the experiment prevented disclosure of its objectives beforehand, participants were informed about their tasks and debriefed later. All participants signed consent to use their data. The sample sizes were computed based on similar studies demonstrating that mean differences tend to revolve around .35 with a mean standard deviation of .55. The sample size can then be computed with the formula\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cspan style=\"font-size: xx-small;\"\u003en = 1 + 2C (s/d) \u003csup\u003e2\u003c/sup\u003e\u003c/span\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e(\u003ca href=\"https://www.ncbi.nlm.nih.gov/books/NBK43321/\"\u003ehttps://www.ncbi.nlm.nih.gov/books/NBK43321/\u003c/a\u003e) where s is the standard deviation to be expected and d is the difference between means. C is a constant based on a-level and power of the test. With an a \u0026lt; .05 and power = .80, C = 7.85. From this it follows that n should be at least equal to 40. This suggests that our sample was sufficiently large to find treatment effects if they exist.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwelve clinical cases, prepared by one of the senior researchers (M.E.M.) and based on cases used in previous studies (\u003ca href=\"#_ENREF_17\"\u003e17-19\u003c/a\u003e), were employed in this experiment. All cases had a confirmed diagnosis and consisted of a brief description of a patient\u0026rsquo;s history, complaints, symptoms, and findings from physical examination and tests. Table 1 contains the twelve diagnoses.\u003c/p\u003e\n\u003cp style=\"margin-bottom: 6.0pt; text-indent: .5in; line-height: 200%;\"\u003e\u003cspan style=\"color: black;\"\u003eTable 1. Diseases involved in the study; descriptions of rich and poor patients\u003c/span\u003e\u003c/p\u003e\n\u003ctable style=\"width: 100.0%; border-collapse: collapse; border: none;\" width=\"100%\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 20.34%; border-top: solid windowtext 1.0pt; border-left: none; border-bottom: solid windowtext 1.0pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"20%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt; text-align: center;\"\u003eCases\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 42.02%; border-top: solid windowtext 1.0pt; border-left: none; border-bottom: solid windowtext 1.0pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"42%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt; text-align: center;\"\u003eRich version\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 37.64%; border-top: solid windowtext 1.0pt; border-left: none; border-bottom: solid windowtext 1.0pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"37%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt; text-align: center;\"\u003ePoor version\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 20.34%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"20%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eStomach Cancer\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 42.02%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"42%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eThe first patient of the day is a 74-year-old businessman. He is married and lives in the Al Shati locality in Jeddah. You noticed him even before he entered your office because of his luxurious car that you have seen through the window of the clinic.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 37.64%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"37%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eThe first patient of the day is a 74-year-old unemployed man. He is married and lives in Al Kirinteana Locality in Jeddah. You notice the bad smell that comes from his dirty clothes when he enters your office.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 20.34%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"20%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eVitamin B12 deficiency\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 42.02%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"42%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 62-year-old man who is a Minister and an owner of a big mall accompanied by two security guards comes to your clinic\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 37.64%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"37%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 62-year-old man who lives in the Gholail locality in Jeddah, working as a school guard, living in a two-bedroom house with his wife and ten children between ages five and twenty one\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 20.34%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"20%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003ePulmonary thromboembolism\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 42.02%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"42%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 31-year-old lady, the second wife of the owner of the largest company in Jeddah.\u0026nbsp; She is well-dressed, wearing a pure golden watch\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 37.64%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"37%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 31-year-old divorced lady living with her large family in Inaikish locality. The family includes six single sisters, two unemployed brothers, her retired father and blind mother.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 20.34%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"20%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eCeliac disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 42.02%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"42%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 29-year-old woman, the chair of the association of women in business\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 37.64%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"37%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 29-year-old lady lives in the Lilosix area in Jeddah, works as a housemaid, and is poorly dressed\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 20.34%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"20%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eAcute viral pericarditis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 42.02%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"42%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 78-year-old man who owns a five-star hotel in Mecca, lives in a palace located in Al Basatean locality in Jeddah with his four wives\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 37.64%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"37%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 78-year-old homeless man, whom you observed several times begging at the busiest traffic light on the way to your hospital,\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 20.34%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"20%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eAcute myeloid leukemia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 42.02%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"42%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 29-year-old engineer who owned the largest construction company in the city, wearing a bisht\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 37.64%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"37%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 29-year-old driver, a father of six children, living in the Al Sabeel area in Jeddah.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 20.34%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"20%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eAcute bacterial endocarditis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 42.02%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"42%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eYou have been called by the director of the hospital to take extra care of a 27-year-old businessman, well-known in town\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 37.64%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"37%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 27-year-old man working as a cleaner and living with his large family in Inaikish, one of the poorest areas of Jeddah\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 20.34%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"20%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eSarcoidosis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 42.02%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"42%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 25-year-old man, the eldest son of the owner of a large profitable communication company,\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 37.64%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"37%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 25-year-old man, unemployed and homeless, originating from Al Khumra area in Jeddah\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 20.34%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"20%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eAcute appendicitis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 42.02%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"42%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 23-year-old female, the daughter of the Secretary General of Jeddah municipality, accompanied by two housemaids and a driver in addition to her mother\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 37.64%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"37%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 23-year-old female, the daughter of a school guard, who came walking all the way to the hospital\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 20.34%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"20%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eCommunity-acquired pneumonia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 42.02%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"42%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eThe patient is an obese 56-year-old woman, mother of multiple children, married to a renowned businessman in Jeddah\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 37.64%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"37%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eThe patient is an obese 56-year-old woman, mother of multiple children, and the wife of a teaman (Sabbab) living in Bani Malik area in Jeddah\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 20.34%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"20%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eLiver cirrhosis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 42.02%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"42%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 52-year old eminent lawyer who is also the legal advisor of the largest construction company in the city\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 37.64%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"37%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 52-year-old retired laborer in the civil service who is a single father of six daughters and two younger sons who are still in school\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 20.34%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"20%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eAddison Disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 42.02%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"42%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 45-year-old woman, well-dressed and wiring expensive jewelry and large heavy golden bracelets\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 37.64%; padding: 0in 5.4pt 0in 5.4pt;\" width=\"37%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 45-year-old woman, married to a gardener, working in one of the parks in Jeddah with large family\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 20.34%; border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\" width=\"20%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eInflammatory bowel disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 42.02%; border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\" width=\"42%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 32-year-old woman living in Al Salamah Locality in Jeddah\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 37.64%; border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\" width=\"37%\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eA 32-year-old housemaid\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/br\u003e\u003c/br\u003e\n\u003cp\u003eIn each case, a few sentences described aspects of the patient\u0026rsquo;s socio-economic status. These sentences portrayed either a patient of apparently high socio-economic position, a patient of apparently low socio-economic position, or a patient without any socio-economic markers (called \u0026ldquo;rich,\u0026rdquo; \u0026ldquo;poor,\u0026rdquo; and \u0026ldquo;neutral\u0026rdquo; patients from here), effectively producing three versions of the same clinical case. Two co-authors (I.A.; M.E.M.) prepared the descriptions based on the kind of patients one would see in the consulting room in Saudi Arabia. Table 1 also contains the short descriptions of rich and poor patients included. The neutral patient description only contained age information. In all other respects the different versions were identical, leading to the same diagnosis. Table 2 presents an example of three versions of the same case.\u003c/p\u003e\n\u003cp style=\"margin-bottom: 6.0pt; line-height: 200%;\"\u003eTable 2. Example of three versions of a clinical case\u003c/p\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable style=\"border-collapse: collapse; border: none;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 221.45pt; border-top: solid windowtext 1.0pt; border-left: none; border-bottom: solid windowtext 1.0pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"295\"\u003e\n\u003cp style=\"text-align: center; line-height: 150%; margin: 6.0pt 0in 6.0pt 0in;\"\u003eRich version\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 274.7pt; border-top: solid windowtext 1.0pt; border-left: none; border-bottom: solid windowtext 1.0pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"366\"\u003e\n\u003cp style=\"text-align: center; line-height: 150%; margin: 6.0pt 0in 6.0pt 0in;\"\u003ePoor version\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 200.35pt; border-top: solid windowtext 1.0pt; border-left: none; border-bottom: solid windowtext 1.0pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"267\"\u003e\n\u003cp style=\"text-align: center; line-height: 150%; margin: 6.0pt 0in 6.0pt 0in;\"\u003eNeutral version\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 221.45pt; border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\" width=\"295\"\u003e\n\u003cp style=\"margin: 6.0pt 0in 12.0pt 0in;\"\u003eThe first patient of the day is a 74-year-old businessman. He is married and lives in the Al Shati locality in Jeddah. You noticed him even before he entered your office because of his luxurious car that you have seen through the window of the clinic.\u003c/p\u003e\n\u003cp style=\"margin: 6.0pt 0in 12.0pt 0in;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 274.7pt; border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\" width=\"366\"\u003e\n\u003cp style=\"margin: 6.0pt 0in 12.0pt 0in;\"\u003eThe first patient of the day is a 74-year-old unemployed man. He is married and lives in Al Kirinteana Locality in Jeddah. You notice the bad smell that comes from his dirty clothes when he enters your office.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 200.35pt; border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\" width=\"267\"\u003e\n\u003cp style=\"margin: 6.0pt 0in 12.0pt 0in;\"\u003eThe first patient of the day is a 74-year old man.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 221.45pt; border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\" width=\"295\"\u003e\n\u003cp style=\"margin: 6.0pt 0in 12.0pt 0in;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 274.7pt; border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\" width=\"366\"\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eHe has had complaints of slight pain in the epigastric area, anorexia and progressive weight loss in the past 4 months. He started to get fatigued easily and to have dizziness when walking, over the past two days. He refers occasional dark stools. The patient is a smoker. He refers chronic use of NSAID for osteoarthritis of the knees. Family history: father had a gastric ulcer.\u003c/p\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003e\u003cstrong\u003ePhysical examination:\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; \u003c/strong\u003e\u003c/p\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003ePatient considerably emaciated. Bp 135/80 mmHg; Pulse 88/ min.; Respiration 24/ min.; Temp 37.4 degrees of C.\u003c/p\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003eHeart: no abnormalities. Lungs: no abnormalities. Abdomen: slight pain on palpation in the epigastric area.\u003c/p\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin-bottom: 6.0pt;\"\u003e\u003cstrong\u003eLab tests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp style=\"line-height: 200%; margin: 6.0pt 0in 12.0pt 0in;\"\u003eHb: 8.4; Ht: 20.9 %\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 200.35pt; border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\" width=\"267\"\u003e\n\u003cp style=\"margin: 6.0pt 0in 12.0pt 0in;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/br\u003e\u003c/br\u003e\n\u003cp\u003e\u003cstrong\u003eProcedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study employed a within-subjects design. A full within-subjects design would imply the presentation of all three versions of \u003cem\u003eeach\u003c/em\u003e case to the participants. Such presentation of three versions of the same case would however likely lead to carry-over effects: when one has seen one version, diagnosing the second, or a third, may become easier. An alternative is to present to each participant \u003cem\u003eone-third\u003c/em\u003e of the cases in rich, one-third in poor, and one-third of the cases in neutral format, however in different combinations. In other words: Every participant received four rich patients, four poor patients, and four neutral patients such that all twelve diseases were seen once. For instance, if A1 represents a rich-patient version of diagnosis A, A2 its poor version and A3 its neutral version, then the first participant would receive the cases A1, B2, C3, D1, E2, and F3, etc., whereas the second participant would receive the cases A2, B3, C1, D2, E3, and F1, etc. Such \u003cem\u003ebalanced within-subjects incomplete block\u003c/em\u003e\u003cem\u003e design \u003c/em\u003eenabled us to compare mean diagnostic performance scores and time-to diagnosis under the three experimental conditions.\u003c/p\u003e\n\u003cp\u003eThe cases were presented on a computer screen using Qualtrics software (Qualtrics XM Platform\u0026trade;) First, they were informed that the study aimed to better understand the nature of clinical problem-solving in Internal Medicine.\u0026nbsp;Second, they were informed that their responses were anonymous since no\u0026nbsp;identifying information would be collected and that their results would have no implications for their work.\u0026nbsp;Their task was to diagnose the clinical cases presented shortly.\u0026nbsp;All cases were based on real patients and had a confirmed diagnosis.\u003c/p\u003e\n\u003cp\u003eFurther, they were asked to work as quickly as possible; suggesting that a first impression is often correct. They should, however, not compromise accuracy. They were instructed to type only one complete and precise diagnosis which they found to be the MOST accurate for the case presented.\u0026nbsp;They were also informed that once they clicked to the next case, they could not go back to previous screens. After being informed, they received a practice case, unrelated to the hypotheses tested.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe accuracy of participants\u0026rsquo; diagnoses was evaluated by considering the confirmed diagnosis of each case as a standard. Two physicians (I.A.; M.E.M.) independently evaluated each diagnosis, without knowing the condition under which it was provided, as correct, partially correct, or incorrect (scored as 1, 0.5, or 0 points, respectively). A response was considered correct whenever it mentioned the core diagnosis, and partially correct when the core diagnosis was not cited but a constituent element of the diagnosis was mentioned. For example, in a case of gastric cancer, \u0026ldquo;Gastric malignancy\u0026rdquo; was considered correct, and \u0026ldquo;Malignancy; most likely colorectal cancer\u0026rdquo; was evaluated as partially correct. The two experts agreed in 85% of the diagnoses and solved discrepancies through discussion.\u003c/p\u003e\n\u003cp\u003eA repeated-measures ANOVA with patient socio-economic status (rich \u003cem\u003evs\u003c/em\u003e poor \u003cem\u003evs\u003c/em\u003e neutral) as within-subjects factors was performed on the mean diagnostic accuracy scores. This analysis tested the hypothesis that the description of poor patients would negatively affect diagnostic accuracy. To check whether the description of poor patients led doctors to speed up the diagnostic process, we performed a repeated-measures ANOVA with socio-economic status as a within-subjects factor on time spent to make the diagnosis. Significance levels were set at p \u0026lt; 0.05 for all comparisons. SPSS version 24.0 (SPSS Inc, Chicago, Illinois) was used for the statistical analyses.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTable 3 contains the findings from this study.\u003c/p\u003e\n\u003cp style=\"line-height: 200%;\"\u003eTable 3. Mean diagnostic accuracy scores (range 0 \u0026ndash; 1; standard deviations into brackets) and mean time spent in diagnosing the written clinical cases (seconds) as a function of patients\u0026rsquo; socio-economic status, N = 45\u003c/p\u003e\n\u003ctable style=\"border-collapse: collapse; border: none;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: none; border-top: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"border: none; border-top: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cstrong\u003ePoor patients\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"border: none; border-top: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cstrong\u003eRich patients\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"border: none; border-top: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cstrong\u003eNeutral patients \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: none; border-top: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\"\u003e\n\u003cp style=\"line-height: 200%; margin: 6.0pt 0in 6.0pt 0in;\"\u003eDiagnostic accuracy\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"border: none; border-top: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\"\u003e\n\u003cp style=\"text-align: center; line-height: 200%; margin: 6.0pt 0in 6.0pt 0in;\"\u003e\u003cspan style=\"color: black;\"\u003e0.48 (0.23)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"border: none; border-top: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\"\u003e\n\u003cp style=\"text-align: center; line-height: 200%; margin: 6.0pt 0in 6.0pt 0in;\"\u003e\u003cspan style=\"color: black;\"\u003e0.52 (0.26)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"border: none; border-top: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\"\u003e\n\u003cp style=\"text-align: center; line-height: 200%; margin: 6.0pt 0in 6.0pt 0in;\"\u003e\u003cspan style=\"color: black;\"\u003e0.54 (0.24)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\"\u003e\n\u003cp style=\"line-height: 200%; margin: 6.0pt 0in 6.0pt 0in;\"\u003eTime spent on diagnosis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\"\u003e\n\u003cp style=\"text-align: center; line-height: 200%; margin: 6.0pt 0in 6.0pt 0in;\"\u003e\u003cspan style=\"color: black;\"\u003e167.57 (60.01)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\"\u003e\n\u003cp style=\"text-align: center; line-height: 200%; margin: 6.0pt 0in 6.0pt 0in;\"\u003e\u003cspan style=\"color: black;\"\u003e176.10 (65.57)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\"\u003e\n\u003cp style=\"text-align: center; line-height: 200%; margin: 6.0pt 0in 6.0pt 0in;\"\u003e\u003cspan style=\"color: black;\"\u003e150.66 (54.08)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/br\u003e\u003c/br\u003e\n\u003cp\u003eParticipants made more mistakes when diagnosing poor patient cases relative to neutral or rich patient cases, but this effect did not reach statistical significance: \u003cem\u003eF\u003c/em\u003e(2, 43) = 0.47,\u003cem\u003e p \u003c/em\u003e\u0026gt; .05. Time spent on diagnosis did however significantly differ, \u003cem\u003eF\u003c/em\u003e(2, 43) = 7.57, \u003cem\u003ep \u003c/em\u003e\u0026lt; .01. Participants needed significantly less time to diagnose neutral patients; this effect was however entirely due to the fact that the neutral patient versions were shorter than the other cases: \u003cem\u003eF\u003c/em\u003e(2, 43) = 2.27, \u003cem\u003ep \u003c/em\u003e\u0026gt; .05.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePoor patients die much earlier than their more well-to-do fellow citizens (\u003ca href=\"#_ENREF_2\"\u003e2\u003c/a\u003e, \u003ca href=\"#_ENREF_3\"\u003e3\u003c/a\u003e). The question central to the present study was the extent to which doctor neglect contributes to this empirical finding. To that end, 45 residents of a Saudi medical school were presented with twelve cases in three different versions. One version described a rich patient, one a poor patient, and the third a patient from which no socio-economic characteristics could be deduced. Each version presented the same disease underlying the signs and symptoms presented. We failed to find any meaningful differences in diagnostic accuracy and time-to-diagnosis.\u003c/p\u003e\n\u003cp\u003eOur experiment presents a third attempt to experimentally study the influence of socio-economic status on the precision of physicians\u0026rsquo; diagnoses and their engagement with patients of different socio-economic backgrounds, expressed as the amount of time they spent on diagnosing the cases. Two previous attempts, also failing to find differences (\u003ca href=\"#_ENREF_15\"\u003e15\u003c/a\u003e, \u003ca href=\"#_ENREF_16\"\u003e16\u003c/a\u003e), had serious methodological shortcomings, and our design remediated these. The common assumption was, that doctors, perhaps due to implicit prejudices, would attach less value to the health of poorer patients and therefore would provide less appropriate care. Prejudices against poor people are broadly shared (\u003ca href=\"#_ENREF_20\"\u003e20\u003c/a\u003e, \u003ca href=\"#_ENREF_21\"\u003e21\u003c/a\u003e). Paul Gorski (\u003ca href=\"#_ENREF_22\"\u003e22\u003c/a\u003e), in his \u0026ldquo;Myth of the culture of poverty\u0026rdquo; mentions a number of these preconceptions with regard to poor people: Poor people would be unmotivated and have weak work ethics; poor parents are supposed to be uninvolved in their children's learning, largely because they do not value education; and poor people tend to abuse drugs and alcohol (all turn out to be largely false). \u0026nbsp;Our participants did not seem to suffer from those prejudices, at least not within the context of the present experiment: they spent equal amounts of time on each of the patients presented, and came to similar diagnostic decisions, irrespective of the socio-economic background of the patient. With some confidence, and in the light of the previous findings, we conclude that, at least within the realm of experimental approaches to the issue, doctors do not deal with their patients differently based on whether they are rich or poor. We state this conclusion with some certainty because our study used a within-group design, excluding the possibility of confounding factors due to poor randomization. In addition, we have used the same methodology in similar studies, demonstrating that our procedures are sensitive to experimental manipulations of the kind attempted in this study (\u003ca href=\"#_ENREF_23\"\u003e23\u003c/a\u003e, \u003ca href=\"#_ENREF_24\"\u003e24\u003c/a\u003e). For instance, in a study on the negative influence of so called \u0026ldquo;difficult patients,\u0026rdquo; using the same methods, we were able to demonstrate rather strong effects with similarly subtle differences in the descriptions of patients (\u003ca href=\"#_ENREF_17\"\u003e17\u003c/a\u003e, \u003ca href=\"#_ENREF_18\"\u003e18\u003c/a\u003e). \u0026nbsp;Finally, within-group variances are similar to those of other studies using the same methods.\u003c/p\u003e\n\u003cp\u003eThere are several limitations to our findings. First, we used written case vignettes rather than more authentic representations of patients. This may have biased the results. However, previous studies comparing vignettes with other methods (standardized patients, chart abstraction) have demonstrated that case vignettes reliably detect differences in clinical decision-making among different groups and they are therefore a good proxy for examining physicians\u0026rsquo; behaviours in real settings (\u003ca href=\"#_ENREF_25\"\u003e25-27\u003c/a\u003e).\u003c/p\u003e\n\u003cp\u003eA \u0026nbsp;second problem is the external validity of our findings. An experimental approach forces researchers to reduce complexity of the event studied, so that internal validity is assured. (Internal validity guaranties that causal conclusions drawn from the findings are accurate). However, it is possible that physicians do not so much respond to more or less \u0026ldquo;objective\u0026rdquo; indicators of poverty, such as a job that someone has, or the community where he or she comes from, but to more subtle characteristics of people in the consulting room, such as their smell, the way they talk, or the way they interact. Such characteristics cannot be studied with the approach used in this study and the ones summarized here. This implies that there is room for further study.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp data-xsweet-list-level=\"0\"\u003eEthics approval and consent to participate. This research is approved by the IRB committee of King Abdullah International Medical\n Recearch Center, Saudi Arabia\u003c/p\u003e\n \n \n \n\u003cp data-xsweet-list-level=\"0\"\u003eConsent for Publication Not Applicable\u003c/p\u003e\n \n \n \n\u003cp data-xsweet-list-level=\"0\"\u003eAvailability of data and materials. The datasets used and/or analyzed during the current study are available from the\n corresponding author on reasonable request\u003c/p\u003e\n \n \n \n\u003cp data-xsweet-list-level=\"0\"\u003eCompeting interest. The corresponding author (MM) is the member of the Editorial Board of BMC medical\n education (Associate editors. Other authors no competing interest\u003c/p\u003e\n \n \n \n\u003cp data-xsweet-list-level=\"0\"\u003eFunding. This research is funded by King Abduaziz Medical City, Saudi Arabia Grant Number 84/34.\n The funding agent has no reole in the design of the study; data collection, analysis,\n and interpretation of data; and the writing of manuscript.\u003c/p\u003e\n \n \n \n\u003cp data-xsweet-list-level=\"0\"\u003eAuthors contribution IA help in the design of the study, data collection and manuscript revision, MM help\n in the writing proposal, study design data collection and manuscript writing, AA helped\n in data collection and manuscript revision, SM helped in study design, data analysis\n and manuscript writing, SA helped in data collection and manuscript revision, AB Helped\n in Manuscript revision and data collection, HS helped in study design, data analysis\n and manuscript writing.\u003c/p\u003e\n \n \n \n\u003cp data-xsweet-list-level=\"0\"\u003eAcknowledgement. The authors would kike to appreciate the contribution of King Abdulaziz Medical City\n for funding this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdler NE, Boyce T, Chesney MA, Cohen S, Folkman S, Kahn RL, et al. Socioeconomic status and health: the challenge of the gradient. American psychologist. 1994;49(1):15.\u003c/li\u003e\n\u003cli\u003eMeara ER, Richards S, Cutler DM. The Gap Gets Bigger: Changes In Mortality And Life Expectancy, By Education, 1981\u0026ndash;2000. Health Affairs. 2008;27(2):350-60.\u003c/li\u003e\n\u003cli\u003eNandi A, Glymour MM, Subramanian S. Association among socioeconomic status, health behaviors, and all-cause mortality in the United States. Epidemiology. 2014;25(2):170-7.\u003c/li\u003e\n\u003cli\u003eStarfield B. Effects of poverty on health status. Bulletin of the New York Academy of Medicine. 1992;68(1):17.\u003c/li\u003e\n\u003cli\u003eWinkleby MA, Jatulis DE, Frank E, Fortmann SP. Socioeconomic status and health: how education, income, and occupation contribute to risk factors for cardiovascular disease. American Journal of Public Health. 1992;82(6):816-20.\u003c/li\u003e\n\u003cli\u003eBaum A, Garofalo J, Yali A. Socioeconomic status and chronic stress: does stress account for SES effects on health? Annals of the New York Academy of Sciences. 1999;896(1):131-44.\u003c/li\u003e\n\u003cli\u003eTaylor SE, Seeman TE. Psychosocial resources and the SES‐health relationship. Annals of the New York Academy of Sciences. 1999;896(1):210-25.\u003c/li\u003e\n\u003cli\u003eVliegenthart J, Noppe G, Van Rossum E, Koper J, Raat H, Van den Akker E. Socioeconomic status in children is associated with hair cortisol levels as a biological measure of chronic stress. Psychoneuroendocrinology. 2016;65:9-14.\u003c/li\u003e\n\u003cli\u003eDarmon N, Drewnowski A. Contribution of food prices and diet cost to socioeconomic disparities in diet quality and health: a systematic review and analysis. Nutrition reviews. 2015;73(10):643-60.\u003c/li\u003e\n\u003cli\u003eShortt SE, Shaw RA. Equity in Canadian health care: Does socioeconomic status affect waiting times for elective surgery? Canadian Medical Association Journal. 2003;168(4):413-6.\u003c/li\u003e\n\u003cli\u003eBreen N, Figueroa JB. Stage of breast and cervical cancer diagnosis in disadvantaged neighborhoods: a prevention policy perspective. American journal of preventive medicine. 1996;12(5):319-26.\u003c/li\u003e\n\u003cli\u003eGarb HN. Race bias, social class bias, and gender bias in clinical judgment. Clinical Psychology-Science and Practice. 1997;4(2):99-120.\u003c/li\u003e\n\u003cli\u003eMandelblatt J, Andrews H, Kerner J, Zauber A, Burnett W. Determinants of late stage diagnosis of breast and cervical cancer: the impact of age, race, social class, and hospital type. American Journal of Public Health. 1991;81(5):646-9.\u003c/li\u003e\n\u003cli\u003eRathore SS, Berger AK, Weinfurt KP, Feinleib M, Oetgen WJ, Gersh BJ, et al. Race, sex, poverty, and the medical treatment of acute myocardial infarction in the elderly. Circulation. 2000;102(6):642-8.\u003c/li\u003e\n\u003cli\u003eArber S, McKinlay J, Adams A, Marceau L, Link C, O'Donnell A. Patient characteristics and inequalities in doctors' diagnostic and management strategies relating to CHD: A video-simulation experiment. Social Science \u0026amp; Medicine. 2006;62(1):103-15.\u003c/li\u003e\n\u003cli\u003eMohamed F, Mamede S, Mohamedani M, Alwan IA, Magzoub MEM, Schmidt HG. The Effect of Patients׳ Appearance on Doctors\u0026rsquo; Diagnostic Decision Making: Do Poor People Get Poorer Medical Care? Health Professions Education. 2016;2(1):18-23.\u003c/li\u003e\n\u003cli\u003eMamede S, Van Gog T, Schuit SCE, Van den Berge K, Van Daele PLA, Bueving H, et al. Why patients' disruptive behaviours impair diagnostic reasoning: a randomised experiment. BMJ Quality \u0026amp; Safety. 2017;26(1):13-8.\u003c/li\u003e\n\u003cli\u003eSchmidt HG, van Gog T, Schuit SCE, Van den Berge K, Van Daele PLA, Bueving H, et al. Do patients' disruptive behaviours influence the accuracy of a doctor's diagnosis? A randomised experiment. BMJ Quality \u0026amp; Safety. 2017;26(1):19-23.\u003c/li\u003e\n\u003cli\u003eMamede S, van Gog T, van den Berge K, van Saase JLCM, Schmidt HG. Why Do Doctors Make Mistakes? A Study of the Role of Salient Distracting Clinical Features. Academic Medicine. 2014;89(1):114-20.\u003c/li\u003e\n\u003cli\u003eCozzarelli C, Wilkinson AV, Tagler MJ. Attitudes toward the poor and attributions for poverty. Journal of Social Issues. 2001;57(2):207-27.\u003c/li\u003e\n\u003cli\u003eLott B. Cognitive and behavioral distancing from the poor. American Psychologist. 2002;57(2):100.\u003c/li\u003e\n\u003cli\u003eGorski P. The Myth of the``Culture of Poverty''. Educational leadership. 2008;65(7):32.\u003c/li\u003e\n\u003cli\u003eALQahtani DA, Rotgans JI, Mamede S, ALAlwan I, Magzoub MEM, Altayeb FM, et al. Does Time Pressure Have a Negative Effect on Diagnostic Accuracy? Academic Medicine. 2016;91(5):710-6.\u003c/li\u003e\n\u003cli\u003eMamede S, van Gog T, Sampaio AM, de Faria RMD, Maria JP, Schmidt HG. How Can Students' Diagnostic Competence Benefit Most From Practice With Clinical Cases? The Effects of Structured Reflection on Future Diagnosis of the Same and Novel Diseases. Academic Medicine. 2014;89(1):121-7.\u003c/li\u003e\n\u003cli\u003ePeabody JW, Luck J, Glassman P, Jain S, Hansen J, Spell M, et al. Measuring the quality of physician practice by using clinical vignettes: A prospective validation study. Annals of Internal Medicine. 2004;141(10):771-80.\u003c/li\u003e\n\u003cli\u003ePeabody JW, Luck J, Glassman P, Dresselhaus TR, Lee M. Comparison of vignettes, standardized patients, and chart abstraction - A prospective validation study of 3 methods for measuring quality. Jama-Journal of the American Medical Association. 2000;283(13):1715-22.\u003c/li\u003e\n\u003cli\u003eMohan D, Fischhoff B, Farris C, Switzer GE, Rosengart MR, Yealy DM, et al. Validating a Vignette-Based Instrument to Study Physician Decision Making in Trauma Triage. Medical Decision Making. 2014;34(2):242-52.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Medical errors, clinical reasoning, poor, rich","lastPublishedDoi":"10.21203/rs.2.10096/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.2.10096/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Abstract\nBackground. Poor patients have greater morbidity and die up to ten years earlier than patients who have higher socio-economic status. These findings are often attributed to differences in life-style between groups. The present study aimed at investigating the extent to which physicians contribute to the effect by providing relative poorer care, perhaps resulting in relative neglect in terms of time spent with a poor patient and more inaccurate diagnoses.\nMethods. A randomised experiment with 45 internal medicine residents. Doctors diagnosed twelve written clinical vignettes that were exactly the same except for the description of the patients' socio-economic status. Each participant diagnosed four of the vignettes in a poor-patient version, four in a rich-patient version, and four in a version that did not contain socio-economic markers, in a balanced within-subjects incomplete block design. Main measurements were: diagnostic accuracy scores and time spent on diagnosis.\nResults. Mean diagnostic accuracy scores (range 0-1) did not significantly differ among the conditions of the experiment (for poor patients: 0.48; for rich patients: 0.52; for patients without socio-economic markers: 0.54; p \u003e 0.05). While confronted with patients not presenting with socio-economic background information, the participants spent significantly less time-to-diagnosis ((for poor patients: 168 seconds; for rich patients: 176 seconds; for patients without socio-economic markers: 151 seconds; p \u003c 0.01), however due to the fact that the former vignettes were shorter.\nConclusion. There is no reason to believe that physicians are prejudiced against poor patients and therefore treat them differently from rich patients or patients without discernible socio-economic background.","manuscriptTitle":"Do Poor Patients Suffer from Inaccurate Diagnoses More than Well-to-do Patients? A Randomized Control Trial","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2019-10-15 11:53:18","doi":"10.21203/rs.2.10096/v2","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accept","date":"2019-09-11T12:00:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2019-09-09T12:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2019-09-08T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2019-09-08T12:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2019-06-07 21:50:34","doi":"10.21203/rs.2.10096/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2019-07-27T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2019-07-26T12:00:00+00:00","index":3,"fulltext":"Form responses:\n---\n* Does the work include the necessary controls?\nIf not, please specify which controls are required in your comments to the authors.\tUnable to assess: **Are the conclusions drawn adequately supported by the data shown?\nIf not, please explain in your comments to the authors.\tNo**\n"},{"type":"editorInvitedReview","content":"","date":"2019-07-12T12:00:00+00:00","index":2,"fulltext":"Form responses:\n---\n* Does the work include the necessary controls?\nIf not, please specify which controls are required in your comments to the authors.\tNo: **Are the conclusions drawn adequately supported by the data shown?\nIf not, please explain in your comments to the authors.\tNo**\n"},{"type":"reviewerAgreed","content":"","date":"2019-07-09T12:00:00+00:00","index":3,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2019-07-04T12:00:00+00:00","index":1,"fulltext":"Form responses:\n---\n* Does the work include the necessary controls?\nIf not, please specify which controls are required in your comments to the authors.\tYes: **Are the conclusions drawn adequately supported by the data shown?\nIf not, please explain in your comments to the authors.\tNo**\n"},{"type":"reviewerAgreed","content":"","date":"2019-06-23T12:00:00+00:00","index":2,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2019-06-21T12:00:00+00:00","index":1,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2019-06-06T12:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2019-06-03T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2019-06-03T12:00:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2019-06-03T12:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"","date":"2019-05-27T12:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical 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