{"scen_lbl":"Bowel cancer screening","scen_lng":"en","scen_txt":"A worked example from Wikipedia that is used to explain positive and negative predictive values (PPV and NPV).","popu_lbl":"General population","cond_lbl":"Bowel cancer","cond_true_lbl":"ill","cond_false_lbl":"healthy","dec_lbl":"Screening","dec_pos_lbl":"positive test","dec_neg_lbl":"negative test","hi_lbl":"TP","mi_lbl":"FN","fa_lbl":"FP","cr_lbl":"TN","prev":0.015,"sens":0.667,"spec":0.91,"fart":0.09,"N":2030,"scen_src":"Wikipedia: https://en.wikipedia.org/wiki/Positive_and_negative_predictive_values#Worked_example","scen_apa":"Retrieved from Wikipedia: https://en.wikipedia.org/wiki/Positive_and_negative_predictive_values#Worked_example"}
{"scen_lbl":"Cab problem","scen_lng":"en","scen_txt":"A cab was involved in a hit and run accident at night.  Two companies, the Green and the Blue, operate in the city. You are given the following data: A witness identified the cab as Blue.  The court tested the reliability of the witness under the same circumstances that existed on the night of the accident and concluded that the witness correctly identified each one of the two colors at 80% of the time and failed 20% of the time.  85% of the cabs in the city are Green and 15% are Blue.  What is the probability that the cab invoved in the accident was Blue rather than Green?","popu_lbl":"Cabs in a city","cond_lbl":"Company ","cond_true_lbl":"blue","cond_false_lbl":"green","dec_lbl":"Identification","dec_pos_lbl":"correct ","dec_neg_lbl":"not correct","hi_lbl":"blue correct ","mi_lbl":"blue false","fa_lbl":"green false","cr_lbl":"green correct","prev":0.15,"sens":0.8,"spec":0.8,"fart":0.2,"N":100,"scen_src":"Tversky & Kahneman (1980, 1982); Sedlmaier & Gigerenzer (2001), p. 391","scen_apa":"Tversky, A., & Kahneman, D. (1980). Causal schemas in judgments under uncertainty. Progress in Social Psychology, 1, 49-72."}
{"scen_lbl":"Hemoccult test","scen_lng":"en","scen_txt":"To diagnose colorectal cancer, the hemoccult test --- among others --- is conducted to detect occult blood in the stool. This test is used from a particular age on, but also on routine screening for early detection of colorectal cancer. Imagine you conduct a screening using the hemoccult test in a certain region. For symptom-free people over 50 years old who participate in screening using the hemoccult test, the following information is available for this region:   (A) Conditional probabilities format:  The probability that one of these people has colorectal cancer is 0.3 percent. If a person has colorectal cancer, the probability is 50 percent that he will have a positive hemoccult test. If a person does not have colorectal cancer, the probability is 3 percent that he will still have a positive hemoccult test. Imagine a person (over age 50, no symptoms) who has a positive hemoccult test in your screening. What is the probability that this person actually has colorectal cancer?   (B) Natural frequencies format:  Thirty out of every 10,000 people have colorectal cancer. Of these 30 people with colorectal cancer, 15 will have a positive hemoccult test. Of the remaining 9970 people without colorectal cancer, 300 will still have a positive hemoccult test. Imagine a sample of people (over age 50, no symptoms) who have a positive hemoccult tests in your screening. How many of these people actually have colorectal cancer? ","popu_lbl":"General population","cond_lbl":"Colorectal cancer","cond_true_lbl":"ill","cond_false_lbl":"healthy","dec_lbl":"Hemoccult test","dec_pos_lbl":"positive test","dec_neg_lbl":"negative test","hi_lbl":"hi","mi_lbl":"mi","fa_lbl":"fa","cr_lbl":"cr","prev":0.3,"sens":0.05,"spec":0.97,"fart":0.03,"N":100000,"scen_src":"Gigerenzer (2002), p. 104--107","scen_apa":"Gigerenzer, G. (2003). Reckoning with risk: learning to live with uncertainty. Penguin UK."}
{"scen_lbl":"Mammography","scen_lng":"en","scen_txt":"A reporter for a women's monthly magazine would like to write an article about breast cancer.  As a part of her research, she focuses on mammography as an indicator of breast cancer.  She wonders what it really means if a woman tests positive for breast cancer during her routine mammography examination.  She has the following data: The probability that a woman who undergoes a mammography will have breast cancer is 1%.  If a woman undergoing a mammography has breast cancer, the probability that she will test positive is 80%.  If a woman undergoing a mammography does not have cancer, the probability that she will test positive is 10%.  What is the probability that a woman who has undergone a mammography actually has breast cancer, if the tests positive? ","popu_lbl":"Women (general population)","cond_lbl":"Breast cancer","cond_true_lbl":"Cancer","cond_false_lbl":"No cancer","dec_lbl":"Screening","dec_pos_lbl":"positive test","dec_neg_lbl":"negative test","hi_lbl":"TP","mi_lbl":"FN","fa_lbl":"FP","cr_lbl":"TN","prev":0.01,"sens":0.8,"spec":0.9,"fart":0.1,"N":1000,"scen_src":"Sedlmaier & Gigerenzer (2001), p.381ff.","scen_apa":"Sedlmeier, P., & Gigerenzer, G. (2001). Teaching Bayesian reasoning in less than two hours. Journal of Experimental Psychology: General, 130(3), 380--400."}
{"scen_lbl":"Mammography (freq)","scen_lng":"en","scen_txt":"10 out of every 1000 women at age 40 who participate in routine screening have breast cancer.  8 out of every 10 women with breast cancer will get a positive mammography.  95 out of every 990 women without breast cancer will also get a positive mammography.  Here is a new representative sample of women at age 40 who got a positive mammography in a routine screening.  How many of these women do you expect to actually have breast cancer?","popu_lbl":"Women (age 40) ","cond_lbl":"Breast cancer","cond_true_lbl":"ill","cond_false_lbl":"healthy","dec_lbl":"Screening","dec_pos_lbl":"positive test","dec_neg_lbl":"negative test","hi_lbl":"TP","mi_lbl":"FN","fa_lbl":"FP","cr_lbl":"TN","prev":0.01,"sens":0.8,"spec":0.90404,"fart":0.09596,"N":1000,"scen_src":"Hoffrage et al. (2015), p. 4","scen_apa":"Hoffrage, U., Krauss, S., Martignon, L., & Gigerenzer, G. (2015). Natural frequencies improve Bayesian reasoning in simple and complex inference tasks. Frontiers in Psychology, 6, 1473."}
{"scen_lbl":"Mammography (prob)","scen_lng":"en","scen_txt":"The probability of breast cancer is 1% for a woman at age 40 who participates in routine screening.  If a woman has breast cancer, the probability is 80% that she will get a positive mammography.  If a woman does not have breast cancer, the probability is 9.6% that she will also get a positive mammography.  A woman in this age group had a positive mammography in a routine screening.  What is the probability that she actually has breast cancer?","popu_lbl":"Women (age 40) ","cond_lbl":"Breast cancer","cond_true_lbl":"ill","cond_false_lbl":"healthy","dec_lbl":"Screening","dec_pos_lbl":"positive test","dec_neg_lbl":"negative test","hi_lbl":"TP","mi_lbl":"FN","fa_lbl":"FP","cr_lbl":"TN","prev":0.01,"sens":0.8,"spec":0.904,"fart":0.096,"N":1000,"scen_src":"Hoffrage et al. (2015), p. 3","scen_apa":"Hoffrage, U., Krauss, S., Martignon, L., & Gigerenzer, G. (2015). Natural frequencies improve Bayesian reasoning in simple and complex inference tasks. Frontiers in Psychology, 6, 1473."}
{"scen_lbl":"Mushrooms","scen_lng":"en","scen_txt":"In a forest 20% of mushrooms are red, 50% brown and 30% white.  A red mushroom is poisonous with a probability of 20%.  A mushroom that is not red is poisonous with a probability of 5%.  What is the probability that a poisonous mushroom in the forest is red?","popu_lbl":"Mushrooms in a forest","cond_lbl":"Color","cond_true_lbl":"red","cond_false_lbl":"not red","dec_lbl":"Identification","dec_pos_lbl":"poisonous","dec_neg_lbl":"not poisonous","hi_lbl":"red and poisonous","mi_lbl":"red and not poisonous","fa_lbl":"not red and poisonous","cr_lbl":"not red and not poisonous","prev":0.2,"sens":0.2,"spec":0.95,"fart":0.05,"N":100,"scen_src":"BNT (Cokeley et al., 2012), p. 46","scen_apa":"Cokely, E. T., Galesic, M., Schulz, E., Ghazal, S., & Garcia-Retamero, R. (2012). Measuring risk literacy: The Berlin numeracy test. Judgment and Decision Making, 7(1), 25--47."}
{"scen_lbl":"Musical town","scen_lng":"en","scen_txt":"Out of 1,000 people in a small town 500 are members of a choir.  Out of these 500 members in the choir 100 are men.  Out of the 500 inhabitants that are not in the choir 300 are men.  What is the probability that a randomly drawn man is a member of the choir?","popu_lbl":"Small town","cond_lbl":"Choir membership","cond_true_lbl":"Member","cond_false_lbl":"No Member","dec_lbl":"Gender","dec_pos_lbl":"man","dec_neg_lbl":"woman","hi_lbl":"man in choir","mi_lbl":"woman in choir","fa_lbl":"man not in choir","cr_lbl":"woman not in choir","prev":0.5,"sens":0.2,"spec":0.4,"fart":0.6,"N":1000,"scen_src":"BNT (Cokeley et al., 2012), p. 46","scen_apa":"Cokely, E. T., Galesic, M., Schulz, E., Ghazal, S., & Garcia-Retamero, R. (2012). Measuring risk literacy: The Berlin numeracy test. Judgment and Decision Making, 7(1), 25--47."}
{"scen_lbl":"PSA test (baseline)","scen_lng":"en","scen_txt":"Now let us consider using the same screening test when prostate cancer is a low-base-rate event.  If the test is used to screen the general population of males, the base rate will be much lower than the 50% depicted in Table 1.  In one of the largest studies of prostate-cancer screening (Schroeder et al., 2009), the base rate of prostate cancer was only 6.3%.  Table 2 depicts this low-base-rate situation.  Now the positive predictive value is down to 19%. This means that 81% of the positive test results are false positives!  Many of the men with these positive test results will have biopsies with associated morbidity (Loeb et al., 2011).  Some of these men will have prostatectomies, radiation therapy, or hormone therapy with their associated morbidities (Chou et al., 2011).  The problem is that a test with modest sensitivity or specificity is not appropriate for screening the general population unless the cost of false positives or false negatives is very low.","popu_lbl":"Males (general population)","cond_lbl":"Prostate cancer","cond_true_lbl":"ill","cond_false_lbl":"healthy","dec_lbl":"PSA-Test","dec_pos_lbl":"positive test","dec_neg_lbl":"negative test","hi_lbl":"TP","mi_lbl":"FN","fa_lbl":"FP","cr_lbl":"TN","prev":0.063,"sens":0.21,"spec":0.94,"fart":0.06,"N":1000,"scen_src":"Arkes & Gaissmaier (2012), p. 550","scen_apa":"Arkes, H. R., & Gaissmaier, W. (2012). Psychological research and the prostate-cancer screening controversy. Psychological Science, 23(6), 547--553."}
{"scen_lbl":"PSA test (patients)","scen_lng":"en","scen_txt":"With a cutoff point of 4 ng/ml, the PSA test is reported to have a sensitivity of approximately 21% and a specificity of approximately 94% (Thompson et al., 2005).  That means the PSA test will correctly classify 21% of the men with prostate cancer and 94% of the men who do not have prostate cancer.  Conversely, the test will miss about 79% of the men who actually have prostate cancer, and raise a false alarm in 6% of the men who actually do not have prostate cancer. Suppose that this test is given to 1,000 patients at a urology clinic who have symptoms diagnostic of prostate cancer.  Perhaps 50% of these men truly have prostate cancer. Table 1 depicts this situation.  Of the 135 men who test positive, 105 actually have prostate cancer.  Thus, the positive predictive value of the PSA test in this situation is approximately 78% (i.e., 105/135 _ 100).","popu_lbl":"Male patients with symptoms","cond_lbl":"Prostate cancer","cond_true_lbl":"ill","cond_false_lbl":"healthy","dec_lbl":"PSA-Test","dec_pos_lbl":"positive test","dec_neg_lbl":"negative test","hi_lbl":"TP","mi_lbl":"FN","fa_lbl":"FP","cr_lbl":"TN","prev":0.5,"sens":0.21,"spec":0.94,"fart":0.06,"N":1000,"scen_src":"Arkes & Gaissmaier (2012), p. 550","scen_apa":"Arkes, H. R., & Gaissmaier, W. (2012). Psychological research and the prostate-cancer screening controversy. Psychological Science, 23(6), 547--553."}
{"scen_lbl":"Psylicraptis screening","scen_lng":"en","scen_txt":"A device has been invented for screening a population for a disease known as psylicrapitis. The device is a very good one, but not perfect. If someone is a sufferer, there is a 90 percent chance that he will be recorded positively. If he is not a sufferer, there is still a 1 percent chance that he will be recorded positively. Roughly 1 percent of the population has the disease. Mr. Smith has been tested, and the result is positive. The chance that he is in fact a sufferer is (blank space)?  (p. 213)\nThink of 100 people. One has the disease psylicrapitis, and he is likely to test positive. Of those 99 who do not have the disease, 1 will also test positive. How many of those who test positive do have the disease? (p. 214)\n","popu_lbl":"General population","cond_lbl":"Psylicraptis","cond_true_lbl":"ill","cond_false_lbl":"healthy","dec_lbl":"Screening","dec_pos_lbl":"positive test","dec_neg_lbl":"negative test","hi_lbl":"hi","mi_lbl":"mi","fa_lbl":"fa","cr_lbl":"cr","prev":0.01,"sens":0.9,"spec":0.99,"fart":0.01,"N":100,"scen_src":"Gigerenzer (2002), p. 211--214","scen_apa":"Gigerenzer, G. (2003). Reckoning with risk: learning to live with uncertainty. Penguin UK."}
{"scen_lbl":"Sepsis","scen_lng":"en","scen_txt":"You are working in an outpatient clinic where the record shows that during the past year 10% of the walk-in patients have had sepsis.  A patient walkes in with high fever abd chills, and you also note that he has skin lesions.  According to the records:  If a patient has sepsis, there is an 80% chance that he or she will have these symptoms.  If a patient does not have sepsis, there is still a 10% chance that he or she will show these symptoms.  What is the probability that a person who tests positive has sepsis?  ","popu_lbl":"General population","cond_lbl":"Sepsis","cond_true_lbl":"Sepsis","cond_false_lbl":"No sepsis","dec_lbl":"Screening","dec_pos_lbl":"positive test","dec_neg_lbl":"negative test","hi_lbl":"hi","mi_lbl":"mi","fa_lbl":"fa","cr_lbl":"cr","prev":0.1,"sens":0.8,"spec":0.9,"fart":0.1,"N":100,"scen_src":"Sedlmaier & Gigerenzer (2001), p.381ff.","scen_apa":"Sedlmeier, P., & Gigerenzer, G. (2001). Teaching Bayesian reasoning in less than two hours. Journal of Experimental Psychology: General, 130(3), 380--400."}
{"scen_lbl":"Amniozentese","scen_lng":"de","scen_txt":"Die Amniozentese ist eine Fruchtwasseruntersuchung, die bei positivem NFT durchgefuehrt wird.  Von 100,000 Frauen zwischen 40 und 44 mit positivem NFT haben 800 ein Kind, dass an Trisomie 21 leidet.  Von diesen 800 Kindern, werden durch die Test 5 faelschlicherweise nicht erkannt.  Von den 9200 gesunden Kindern, erhalten 46 faelschlicherweise ein positives Testeregbnis.  Wie hoch die Wahrscheinlichkeit, dass ein Kind an Trisomie 21 erkrankt ist, wenn das Testergebnis positiv ist?","popu_lbl":"Frauen (40 bis 44) mit positivem NFT","cond_lbl":"Trisomie 21","cond_true_lbl":"erkrankt","cond_false_lbl":"gesund","dec_lbl":"Testergebnis","dec_pos_lbl":"negativ","dec_neg_lbl":"negativ","hi_lbl":"richtig positiv","mi_lbl":"falsch negativ","fa_lbl":"falsch positiv","cr_lbl":"richtig negativ","prev":0.08,"sens":0.994,"spec":0.995,"fart":0.005,"N":10000,"scen_src":"dkfz workshop","scen_apa":"ohne Quellenangabe"}
{"scen_lbl":"HIV-Test","scen_lng":"de","scen_txt":"Betrachten wir 10,000 Frauen aus der allgemeinen Bevoelkerung, die einem HIV-Screening unterzogen werden. Laut Statistik sind rund 10 infiziert (das ist die sogenannte Praevalenz oder Krankheitshaeufigkeit), die durch den Test mit an Sicherheit grenzender Wahrscheinlichkeit entdeckt werden. Bei der Mehrheit der Frauen, die nicht infiziert sind, koennen wir laut Amys Arzt erwarten, dass fuenf weitere Frauen positiv getestet werden. Das ergibt 10 richtige und 5 falsch positive Ergebnisse, also eine Infektionswahrscheinlichkeit von 2/3, was weit entfernt von absoluter Gewissheit ist.  ","popu_lbl":"Frauen (allg.)","cond_lbl":"HIV","cond_true_lbl":"positiv","cond_false_lbl":"negativ","dec_lbl":"Testergebnis","dec_pos_lbl":"positiv","dec_neg_lbl":"negativ","hi_lbl":"richtig positiv","mi_lbl":"falsch negativ","fa_lbl":"falsch positiv","cr_lbl":"richtig negativ","prev":0.0001,"sens":1,"spec":0.99995,"fart":0.00005,"N":100000,"scen_src":"Gigerenzer (2013),  p. 53","scen_apa":"Gigerenzer, G. (2013). Risiko: Wie man die richtigen Entscheidungen trifft. C. Bertelsmann Verlag."}
{"scen_lbl":"HIV-Test","scen_lng":"de","scen_txt":"Hier betraegt die Falsch-positiv Rate 1 von 250,000, wie aus den neuesten Studien hervorgeht, die  bessere Tests verwenden. Von 250,000 Frauen, die an dem Test teilnehmen, sind 25 wahrscheinlich infiziert; alle richterigerweise mit einem positiven Testergebnis. Von den 249975 nicht infizierten Frauen wird das Testergebnis wahrscheinlich in einem Fall falsch sein. Wir koennen also erwarten, dass von je 26 positiv getesteten Frauen, eine nicht infiziert ist. ","popu_lbl":"Frauen (allg.)","cond_lbl":"HIV","cond_true_lbl":"positiv","cond_false_lbl":"negativ","dec_lbl":"Testergebnis","dec_pos_lbl":"positiv","dec_neg_lbl":"negativ","hi_lbl":"richtig positiv","mi_lbl":"falsch negativ","fa_lbl":"falsch positiv","cr_lbl":"richtig negativ","prev":0.0001,"sens":1,"spec":1,"fart":4e-06,"N":250000,"scen_src":"Gigerenzer (2013),  p. 53","scen_apa":"Gigerenzer, G. (2013). Risiko: Wie man die richtigen Entscheidungen trifft. C. Bertelsmann Verlag."}
{"scen_lbl":"HIV-Test","scen_lng":"de","scen_txt":"Von 100,000,000 Maennern ohne Risikoverhalten, die einen HIV Test durchfuehren, werden 997 Maenner korrekterweise als HIV positiv diagnostiziert.  Die Praevalenz der Erkrankung liegt bei 0.01% liegt und die Spezifitaet des Testes bei 99.99996%.  Wie hoch ist die Wahrscheinilchkeit, dass ein Mann mit einem positiven Testergebnis tatsaechlich HIV hat?","popu_lbl":"Maenner ohne Risikoverhalten","cond_lbl":"HIV","cond_true_lbl":"erkrankt","cond_false_lbl":"gesund","dec_lbl":"Testergebnis","dec_pos_lbl":"positiv","dec_neg_lbl":"negativ","hi_lbl":"richtig positiv","mi_lbl":"falsch negativ","fa_lbl":"falsch positiv","cr_lbl":"richtig negativ","prev":0.0001,"sens":0.997,"spec":1,"fart":4e-06,"N":10000000,"scen_src":"dkfz workshop","scen_apa":"ohne Quellenangabe"}
{"scen_lbl":"HIV-Test","scen_lng":"de","scen_txt":"Bei Maennern ohne Risiko, die an der Vorsorge teilnehmen, liegt die Praevalenz fuer eine HIV Erkrankung bei 0.001%. Die Sensitivitaet des HIV Testes liegt bei 99.7% und die Spezifitaet des Tests betraegt 99.9996%.  Wie hoch ist die Wahrscheinlichkeit, dass ein Mann, der ein positives Testergebnis hat, tatsaechlich HIV positiv ist?  ","popu_lbl":"Maenner ohne Risiko-, mit Vorsorgeverhalten","cond_lbl":"HIV","cond_true_lbl":"erkrankt","cond_false_lbl":"gesund","dec_lbl":"Testergebnis","dec_pos_lbl":"positiv","dec_neg_lbl":"negativ","hi_lbl":"richtig positiv","mi_lbl":"falsch negativ","fa_lbl":"falsch positiv","cr_lbl":"richtig negativ","prev":0.0001,"sens":0.997,"spec":1,"fart":4e-06,"N":10000000,"scen_src":"dkfz workshop","scen_apa":"ohne Quellenangabe"}
{"scen_lbl":"Mammografie","scen_lng":"de","scen_txt":"Ich werde Ihnen jetzt die Informationen geben, die sie brauchen, um die Frage der Krebswahrscheinlichkeit nach einem positiven Test zu beantworten. Zuerst werde ich sie  Ihnen auf die in der Medizin uebliche Weise praesentieren als Wahrscheinlichkeiten: Die Wahrscheinlichkeit, dass eine Frau Brustkrebs hat, betraegt 1% (Praevalenz).  Wenn eine Frau Brustkrebs hat, betraegt die Wahrscheinlichkeit eines positiven Testergebnisses 90% (Sensitivitaet).  Wenn eine Frau keinen Brustkrebs hat, betraegt die Wahrscheinlichkeit, dass das Testergebnis trotzdem positiv ausfaellt neun Prozent (Falschalarmrate).     Dann erklaerte ich ihnen, dass eine einfache Methode gibt, ihrem Verstaendnis auf die Spruenge zu helfen.  Man muss nur die Wahrscheinlichkeiten in natuerliche Haeufigkeiten umwandeln:  Zehn von jeweils 1000 Frauen haben Brustkrebs. Von diesen zehn Frauen mit Brustkrebs werden 9 positiv getestet.  Von 990 Frauen ohne Brustkrebs werden 89 trotzdem positiv getestet. ","popu_lbl":"Frauen (allg.)","cond_lbl":"Brustkrebs","cond_true_lbl":"Krebs","cond_false_lbl":"kein Krebs","dec_lbl":"Testergebnis","dec_pos_lbl":"positiv","dec_neg_lbl":"negativ","hi_lbl":"korrekt positiv","mi_lbl":"falsch negativ","fa_lbl":"falsch positiv","cr_lbl":"korrekt negativ","prev":0.01,"sens":0.9,"spec":0.91,"fart":0.09,"N":1000,"scen_src":"Gigerenzer (2013),  p. 213--221","scen_apa":"Gigerenzer, G. (2013). Risiko: Wie man die richtigen Entscheidungen trifft. C. Bertelsmann Verlag."}
{"scen_lbl":"Mammografie","scen_lng":"de","scen_txt":"Die Praevalenz von Brustkrebs bei Frauen ueber 50 mit einem regelmaessigem Screening liegt bei 1%.  Von 1000 Frauen, die eine Mammografie erhalten werden 10 richtigerweise als krank diagnostiziert.  Von diesen 10 Frauen werden durch den Test 9 Frauen als krank erkannt. Weitere 89 gesunde Frauen erhalten ein positives Testergebnis.  Wie hoch ist die Wahrscheinlichkeit, dass eine Frau tatsaechlich an Brustkrebs erkrankt ist, wenn der Test positiv ist?","popu_lbl":"Frauen ab dem Alter 50  ","cond_lbl":"Brustkrebs","cond_true_lbl":"erkrankt","cond_false_lbl":"gesund","dec_lbl":"Screening","dec_pos_lbl":"positiv","dec_neg_lbl":"negativ","hi_lbl":"richtig positiv","mi_lbl":"falsch negativ","fa_lbl":"falsch positiv","cr_lbl":"richtig negativ","prev":0.01,"sens":0.9,"spec":0.91,"fart":0.09,"N":1000,"scen_src":"dkfz workshop","scen_apa":"ohne Quellenangabe"}
{"scen_lbl":"Mammografie","scen_lng":"de","scen_txt":"Die Praevalenz von Brustkrebs bei Frauen ueber 50 mit BRCA1 Mutation liegt bei 60%.  Von 1000 Frauen, die eine Mammografie erhalten werden 540 richtigerweise als krank diagnostiziert.  Weitere 36 gesunde Frauen erhalten ein positives Testergebnis.  Wie hoch ist die Wahrscheinlichkeit, dass eine Frau tatsaechlich an Brustkrebs erkrankt ist, wenn der Test positiv ist?","popu_lbl":"Frauen ab 50 mit BRCA1 Mutation","cond_lbl":"Brustkrebs","cond_true_lbl":"erkrankt","cond_false_lbl":"gesund","dec_lbl":"Mammografie","dec_pos_lbl":"positiv","dec_neg_lbl":"negativ","hi_lbl":"richtig positiv","mi_lbl":"falsch negativ","fa_lbl":"falsch positiv","cr_lbl":"richtig negativ","prev":0.6,"sens":0.9,"spec":0.91,"fart":0.09,"N":1000,"scen_src":"dkfz workshop","scen_apa":"ohne Quellenangabe"}
{"scen_lbl":"Mammografie","scen_lng":"de","scen_txt":"Bei Frauen ueber 50 mit BRCA1 Mutation und positivem Befund liegt die Praevalenz fuer Brustkrebs bei 94%.  Die Wahrscheinlichkeit, dass eine Frau korrekterweise ein negatives Ergebnis erhaelt liegt bei 91%.  Die Wahrscheinlichkeit, dass eine Frau korrekterweise ein positives Ergebnis erhaelt bei 90%.  Wie hoch ist die Wahrscheinlichkeit, dass eine Frau, die ein positives Testergebnis hat, tatsaechlich Brustkrebs hat?","popu_lbl":"Frauen ab 50 mit Mutation und positivem Befund","cond_lbl":"Brustkrebs","cond_true_lbl":"erkrankt","cond_false_lbl":"gesund","dec_lbl":"Mammografie","dec_pos_lbl":"positiv","dec_neg_lbl":"negativ","hi_lbl":"richtig positiv","mi_lbl":"falsch negativ","fa_lbl":"falsch positiv","cr_lbl":"richtig negativ","prev":0.94,"sens":0.9,"spec":0.91,"fart":0.09,"N":1000,"scen_src":"dkfz workshop","scen_apa":"ohne Quellenangabe"}
{"scen_lbl":"Nackenfaltentest (NFT)","scen_lng":"de","scen_txt":"Damit koennen wir erkennen, was ein positiver Test fuer eine 40-jaehrige Frau bedeutet.  Ungefaehr 1% der Kinder haben das Downsyndrom.  Wenn das Kind das Downsyndrom hat, besteht eine 90-prozentige Wahrscheinlichkeit, dass das Testergebnis positiv ist.  Wenn das Kind nicht betroffen ist, besteht trotzdem noch eine 5-prozentige Wahrscheinlichkeit, dass das Testergebnis positiv ist.  Eine Schwangere wurde getestet und das Ergebnis ist positiv. Wie gross ist die Wahrscheinlichkeit, dass das Kind tatsaechlich das Downsyndrom hat?    Abermals wird das Problem einfacher, wenn wir die verwirrenden Wahrscheinlichkeiten durch natuerliche Haeufigkeiten ersetzen:  Rund 10 von 1000 Kindern haben das Downsyndrom.  Von diesen 10 Kindern mit Downsyndrom werden 9 ein positives Testergebnis bekommen.  Von den verbleibenden 990 nicht betroffenen Kindern werden etwa 50 trotzdem ein positives Ergebnis haben.  Wie viele schwangere Frauen mit einem positiven Ergebnis haben tatsaechlich ein Kind mit Downsyndrom?","popu_lbl":"Schwangere (40-jaehrig)","cond_lbl":"Trisomie 21","cond_true_lbl":"erkrankt","cond_false_lbl":"gesund","dec_lbl":"Testergebnis","dec_pos_lbl":"positiv","dec_neg_lbl":"negativ","hi_lbl":"richtig positiv","mi_lbl":"falsch negativ","fa_lbl":"falsch positiv","cr_lbl":"richtig negativ","prev":0.01,"sens":0.9,"spec":0.95,"fart":0.05,"N":1000,"scen_src":"Gigerenzer (2013),  p. 222--226","scen_apa":"Gigerenzer, G. (2013). Risiko: Wie man die richtigen Entscheidungen trifft. C. Bertelsmann Verlag."}
{"scen_lbl":"Nackenfaltentest (NFT)","scen_lng":"de","scen_txt":"Der Nackenfaltentest (NFT) ist ein Test, um zu erkennen, ob ein Kind an Downsyndron erkrankt ist.  Von 100,000 schwangeren Frauen zwischen 40 und 44 Jahren, die den Test durchfuehren lassen, haben 192 ein Kind mit Downsyndrom. 154 von den erkrankten Kindern werden durch den Test richtig erkannt.  Weitere 1765 Kinder erhalten ein positives Testergebnis, obwohl sie nicht an Downsyndrom erkrankt sind.  Wie hoch ist die Wahrscheinlichkeit, dass ein Kind, dass ein negatives Testergenis hat, tatsaechlich gesund ist?","popu_lbl":"Frauen (40 bis 44)","cond_lbl":"Trisomie 21","cond_true_lbl":"erkrankt","cond_false_lbl":"gesund","dec_lbl":"Testergebnis","dec_pos_lbl":"negativ","dec_neg_lbl":"negativ","hi_lbl":"richtig positiv","mi_lbl":"falsch negativ","fa_lbl":"falsch positiv","cr_lbl":"richtig negativ","prev":0.0192,"sens":0.8,"spec":0.82,"fart":0.18,"N":10000,"scen_src":"dkfz workshop","scen_apa":"ohne Quellenangabe"}
{"scen_lbl":"Sigmoidoskopie","scen_lng":"de","scen_txt":"Ungefaehr 0.035% der Frauen der Allgemeinbevoelkerung sind an Darmkrebs erkrannt.  Wenn 1,000,000 Frauen an einer Sigmoidoskopie teilnehmen, werden 245 der kranken Frauen richtig erkannt.  Weitere 99965 Frauen erhalten irrtuemlich ein positives Testergebnis.  Wie hoch ist die Wahrscheinlichkeit, dass eine Frau, bei der der Test positiv ist, tatsaechlich Dramkrebs hat?","popu_lbl":"Frauen (allg.)","cond_lbl":"Darmkrebs","cond_true_lbl":"erkrankt","cond_false_lbl":"gesund","dec_lbl":"Screening","dec_pos_lbl":"positiv","dec_neg_lbl":"negativ","hi_lbl":"richtig positiv","mi_lbl":"falsch negativ","fa_lbl":"falsch positiv","cr_lbl":"richtig negativ","prev":0.00035,"sens":0.7,"spec":0.9,"fart":0.1,"N":1000000,"scen_src":"dkfz workshop","scen_apa":"ohne Quellenangabe"}
{"scen_lbl":"Sigmoidoskopie","scen_lng":"de","scen_txt":"Bei Frauen mit erhoehtem Risiko fuer Darmkrebs liegt die Praevalenz bei 3.5%. Die Wahrscheinichkeit,  dass eine erkankte Frau richtig diagostiziert wird liegt bei 90%. Die Wahrscheinlichkeit, dass eine gesunde Frau richtigerweise keine Diagnose erhaelt liegt bei 91%. Wie hoch ist die Wahrscheinlichkeit, dass eine von 1,000,000 Frauen, die ein positives Testergebnis hat, tatsaechlich an Darmkrebs erkrankt ist?","popu_lbl":"Frauen mit erhoehtem Risiko  ","cond_lbl":"Darmkrebs","cond_true_lbl":"erkrankt","cond_false_lbl":"gesund","dec_lbl":"Screening","dec_pos_lbl":"positiv","dec_neg_lbl":"negativ","hi_lbl":"richtig positiv","mi_lbl":"falsch negativ","fa_lbl":"falsch positiv","cr_lbl":"richtig negativ","prev":0.035,"sens":0.7,"spec":0.9,"fart":0.1,"N":1000000,"scen_src":"dkfz workshop","scen_apa":"ohne Quellenangabe"}