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
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Rich version
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Poor version
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Stomach Cancer
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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.
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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.
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Vitamin B12 deficiency
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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
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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
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Pulmonary thromboembolism
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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
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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.
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Celiac disease
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A 29-year-old woman, the chair of the association of women in business
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A 29-year-old lady lives in the Lilosix area in Jeddah, works as a housemaid, and is poorly dressed
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Acute viral pericarditis
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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
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A 78-year-old homeless man, whom you observed several times begging at the busiest traffic light on the way to your hospital,
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Acute myeloid leukemia
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A 29-year-old engineer who owned the largest construction company in the city, wearing a bisht
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A 29-year-old driver, a father of six children, living in the Al Sabeel area in Jeddah.
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Acute bacterial endocarditis
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You have been called by the director of the hospital to take extra care of a 27-year-old businessman, well-known in town
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A 27-year-old man working as a cleaner and living with his large family in Inaikish, one of the poorest areas of Jeddah
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Sarcoidosis
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A 25-year-old man, the eldest son of the owner of a large profitable communication company,
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A 25-year-old man, unemployed and homeless, originating from Al Khumra area in Jeddah
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Acute appendicitis
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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
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A 23-year-old female, the daughter of a school guard, who came walking all the way to the hospital
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Community-acquired pneumonia
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The patient is an obese 56-year-old woman, mother of multiple children, married to a renowned businessman in Jeddah
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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
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Liver cirrhosis
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A 52-year old eminent lawyer who is also the legal advisor of the largest construction company in the city
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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
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Addison Disease
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A 45-year-old woman, well-dressed and wiring expensive jewelry and large heavy golden bracelets
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A 45-year-old woman, married to a gardener, working in one of the parks in Jeddah with large family
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Inflammatory bowel disease
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A 32-year-old woman living in Al Salamah Locality in Jeddah
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A 32-year-old housemaid
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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
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Poor version
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Neutral version
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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.
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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.
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The first patient of the day is a 74-year old man.
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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 %
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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.