12.7
Deneylerdeki Kontroller
Bir deney yürütürken ön yargıyı azaltmak ve bağımlı değişkenleri doğru bir şekilde ölçmek için kontrole sahip olmak çok önemlidir. Ayrıca sonuçların d…
Bir deneydeki kontroller, sabit tutulan ve bağımsız değişkenlerden etkilenmeyen öğelerdir. Tedaviye yanıt olarak bağımlı değişkenlerin tarafsız ve doğru ölçümü için kontroller gereklidir.
Örneğin, yüksek dereceli ateş, solunum güçlüğü, öksürük, soğuk algınlığı ve şiddetli vücut ağrısı olan bir hastanede başvuran hastalardan COVID enfeksiyonu şüphelenilir. Ancak diğer solunum yolu enfeksiyonlarının da aynı semptomlara neden olması mümkündür. Bu nedenle, doktor bir COVID testi önerir.
Hastanın burun sürüntüleri toplanır ve COVID testi yapılır. Ek olarak, COVID viral RNA'sına sahip olmayan bir kontrol numunesi tutulur. Bu kontrol türüne negatif kontrol de denir. Hastaların numunelerinde yanlış pozitif raporların önlenmesine yardımcı olur.
Pozitif kontrol, bir deneyde yaygın olarak kullanılan başka bir kontrol türüdür. Negatif kontrolün aksine, pozitif kontrol gerçek bir örnek içerir - viral RNA. Bu, test numunelerindeki viral RNA'nın varlığıyla eşleşmeye yardımcı olur ve testin prosedürünü ve doğruluğunu doğrular.
View the full transcript and gain access to JoVE Core videos
Q1: What is the purpose of controls in an experiment?
Controls are elements held constant and unaffected by independent variables, enabling unbiased and accurate measurement of dependent variables in response to treatment. They reduce bias and make results more reliable by allowing researchers to isolate the relationship between variables and distinguish treatment effects from other factors.
Q2: How does a negative control differ from a positive control?
A negative control lacks the main ingredient or treatment but includes everything else, preventing false positives by showing what happens without the treatment. A positive control contains the actual sample or ingredient, validating test accuracy and confirming the procedure works as expected by demonstrating the expected result.
Q3: Why are positive and negative controls used in diagnostic tests?
Positive and negative controls prevent false positive and false negative reports in diagnostic procedures. In COVID RT-PCR testing, a negative sample without viral RNA confirms the test doesn't produce false positives, while a positive sample with viral RNA validates the test's ability to detect the target accurately.
Q4: What role does a control group play in randomized experiments?
In randomized experiments, a control group receives an inactive treatment but is managed identically to other groups. This helps researchers balance the effects of being in an experiment with the effects of active treatments, ensuring that observed differences result from the treatment itself rather than experimental participation.
Q5: How do controls help establish relationships between variables?
By sorting data into control and experimental conditions, researchers can draw clear relationships between dependent and independent variables. Controls ensure that changes in the dependent variable result from the independent variable alone, not from confounding factors or experimental bias affecting the study design.
Q6: What is an example of controls in a clinical diagnostic scenario?
In COVID testing, when a patient's nasal swab is collected, a control sample without COVID viral RNA is maintained alongside the patient sample. This negative control prevents false positive diagnoses, while a positive control containing viral RNA validates the test procedure and confirms the accuracy of results.
Q7: Why are controls essential for reliable experimental results?
Controls ensure that experimental results accurately reflect the effect of the independent variable by holding all other factors constant. Without controls, researchers cannot distinguish between treatment effects and effects from other variables, making it impossible to draw valid conclusions about cause-and-effect relationships.