The INICET May 2026 PSM exam was moderate in difficulty with 10 out of 12 questions directly testing core epidemiological concepts including ecological studies, nested case-control studies, odds ratio calculation, population attributable risk, meta-analysis with forest plots, screening test performance metrics (sensitivity, positive predictive value), efficacy versus effectiveness in clinical trials, Pearl Index for contraceptive efficacy, ABC model of attitude (affective, behavioral, cognitive components), and RMNCH+A scorecard indicators for health program evaluation.
Deep Dive
Prerequisite Knowledge
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Deep Dive
INI-CET | MAY-2026 | RECALL SESSION - PSM | DR. Dr Velmuragan | ADRPLEXUSAdded:
session for 2026 May, for PS.
So, how was the session? How did you feel?
So, I felt the paper was very easy to moderate.
So, out of the 12 questions asked, 10 questions we had seen throughout our course during the past year. The questions tested the direct application of the main concepts.
Overall, there were 12 core PSM questions.
They were epidemiology heavy.
And there was also a question on recent updates, especially with regards to HPV wax.
See, they started with ecological studies, then they asked about nested case-control study, then they went into odds ratio, then population attributable risk, efficacy versus effectiveness, which is also a part of RCT. So, mostly it was epidemiology heavy paper.
Then a few questions on programs, RMNCH+A, measles, and then the WHO HPV. So, these were the questions. Overall, it was a moderate easy, like a direct application questions.
So, one question was difficult in the sense it was a it was new to you, like the scorecard.
Scorecard used in the program of RMNCH+A or RMNCHA+N.
The other 11 were basic or standard with regards to epidemiology, health programs, screening tests, vaccines, health education. There was a question on health education. Health education means knowledge, attitude, practice. In this, there was a question on attitude.
So, researchers they're analyzing the data from 10 countries.
They are examining whether higher per capita alcohol consumption, the countries with higher per capita alcohol had increased liver cirrhosis or not, they were seeing. See, what is the type of data? In page 37 of our workbook we had seen it is comparing what level of data? It is comparing population level data.
So population population comparing. So what type of study it is? It is clearly a ecological study. So ecological study the unit of the study is a population.
In only one study where the unit of the study is a population is the ecological study.
So next question. It was a assertion and a reason based question.
So they are doing a nested case control study. What is a nested case control study? What I had told in the class we are are having a cohort study. Inside the cohort study we are doing a case control study. So he is a male but his heart is soft like a female. So we are putting a case control study inside a cohort study. But it is actually a cohort study. So in a cohort study what we can do? We can find the incidence. We can do the person time exposure. We can do follow up. Since it is a case control study done within the cohort study, the odds ratio obtained in the study will be more valid than a conventional case control study. So both assertion are true and reason are true and hence it is the the right reason for this assertion. So both A and R are true and R are correctly explains the A. So this is what we have seen in our workbook in page number 35. See we can see the nested case control study a type of case a cohort study. We are putting a case control study inside a cohort study. So it has a decreased recall bias. So it is more valid and it also has decreased the selection bias.
So nested case control study gives a precise estimate of odds ratio.
Next question.
In a case control study, we are investigating the association between smoking and lung cancer. We are having a following data. The numbers are changed.
I did not know the exact numbers that was asked in the exam. So, this is plus, this is minus. Two cross two table.
What is there in the upper upper what is God is telling? This is plus, this is minus. Left side exposure. Smoking plus, smoking minus. Many times we had did this sum in the exam, sorry, in our class. Many times we did this sum. So, odds ratio one of the easiest questions.
So, what is odds ratio? It is the cross product ratio. Cross multiplying. What is ABCD? Always write in the exam. AB, then only you go to the next line, CD.
So, it is AD by BC. So, page 31 of our workbook, we had discussed this.
So, the answer is nine.
The answer is nine. Odds ratio or cross product ratio. The odds of lung cancer in smokers compared to the non-smokers.
We can tell it either based on exposure odds ratio or also on disease odds ratio. There are two types of odds ratio. That also you should know.
So, next question. We are doing a meta-analysis.
So, what is a meta-analysis? It is nothing but a combination of collection of studies. Like a pan India movie.
Heroes from Tamil Nadu, heroes from Karnataka, Andhras. All are acting together and we are getting a final output. What is the final result? See, there will be many heroes who are acting. So, there will be variation among. That is called as the heterogeneity.
So, we have to see the heterogeneity and we have to assess. So, what is the difference among the heroes? We are getting the final outcome of 1,500 crore collection. How much collection is due to the hero from this state, that state, that state? So, we are combining. So, in a meta-analysis, each hero has a different type of outcome he can get. So, each study has different outcomes. We are combining the outcomes. We can measure the variability in the study findings. So, whether the heroes are having a like a superstar of all the cinemas or like the second level heroes or third level heroes. So, depending on that, we can use a fixed effect model or a random effect model.
Next to one is we can detect the inconsistency in the effect estimates.
So, in the final estimates, what are the differences? These all we can do, but we cannot find out the publication bias because we have seen in the class publication bias what plot it needs, funnel plot.
So, we cannot directly calculate publication bias. So, what is the plot we get in a meta-analysis? We get in a forest plot. Do you remember the forest?
So, the forest plot from lot of studies, study one in Africa, America, Australia, combining everything into a single study estimate. If you are just doing the literature and we are defining that literature systematically, it is called literature review or it is called as a systematic review. And then, we are combining it and finding out the final answer, it becomes the meta-analysis.
So, meta-analysis, at first, it will be only a systematic review. So, meta-analysis will get a definite number like 32, 42, or odds ratio of 3.0, relative risk of 4.3.
Okay. So, we cannot calculate publication bias directly. Why? To calculate publication bias, as we saw in our workbook in the page number 285, we need a funnel plot. What is this plot?
Funnel plot for publication bias. Then, we also had this forest plot in our workbooks in page number 43 as well as in the 285 also.
Next, we are having this forest plot.
So, impact of treatment on mortality.
So, this is the forest plot result of each study combining and giving together a single.
So, in our thing, we also discussed about the vertical line in the VSV the page 28, we also discussed about the heterogeneity.
So, it is defined by what statistics? I square statistics. More the I square statistics, it is more heterogeneous.
The studies are more difficult. So, heterogeneity.
So, the square it tells the result of each study and the diamond it tells the overall effect estimate.
So, next question we are going. The public health survey we are doing. In this public health survey, we are evaluating a large proportion of COPD cases. And then, they are associated with the long-term tobacco smoking.
Health officials are telling like if you remove the smoking, how much amount of COPD can be reduced? 20%, 30%. So, that is nothing but the population attributable risk. So, in a cohort study, what is the normal thing we get?
In a cohort study, we get relative risk.
What is relative risk? We see in our workbook in the page number 33.
Incidence in exposed by incidence in not exposed.
What is attributable risk? Incidence in exposed minus not exposed divided by incidence in exposed.
Like if we remove the smoking component, how much percentage of lung cancer can be reduced in the smokers? That is called as the attributable risk. Then what is population attributable risk?
Now, here instead of the incidence in exposed minus non-exposed by incidence in exposed into 100, this is the attributable risk. Instead of applying to the exposed population, here we are applying it to the population level. So, incidence in population minus incidence in non-exposed divided by incidence in population into 100.
So, if we remove this risk factor from the population, how much disease can be prevented? This we discussed in the workbook page number 33. That is the population attributable risk.
So, attributable risk, population attributable risk, attributable risk at the population level. Reduction of risk factor to the entire population's burden.
So, next we are doing a public health survey. It reveals that a large proportion of COPD, we saw this. This is the population attributable risk.
So, next question. There is an outbreak investigation in a residential school.
We are getting a epidemic curve. How is the epidemic curve is coming? It has multiple successive peaks.
And what is the difference between the peaks? It is equal to the incubation period.
So, this pattern suggests person-to-person transmission. So, only by person-to-person. So, we can solve this question by two ways. First way, by person-to-person transmission. Food poisoning and staphylococcal food poisoning or salmonella food poisoning, they are all point source epidemic. What type of transmission? They are mainly a transmission through the food. Or mainly they can also occur mainly through the food or the food products. So, it is not a option.
Then typhoid and measles both can occur from person to person, but measles strictly only person to person mainly.
Mainly respiratory droplets, maybe other droplets maybe in the country for sure also it can tell, but mainly is the person to person is the measles. But typhoid more than person to person like from the hand we are having some material, we are touching another hand.
More than that transmission more common is food. Do you remember the typhoid Mary? We are eating this pani puri We ate pani puri. So by a cow cow cow now we are eating because of this we are getting that disease. So in typhoid main type of transmission is due to the food source.
So because of this person to person, I will always prefer measles for this answer.
So it can be a common source.
Salmonella and Staphylococcus, they can be a point source.
So measles is only the person to person, so it is a propagated epidemic.
So this we had seen in the book in the page number 28 of our workbook we had seen.
So point source single rise and fall rapidly. Common source contaminated with supplying a drinking water. So it is a continuous exposure, it will be like a plateau.
Or if it is like a interrupted exposure, we have some interruptions.
But in propagated epidemic it spreads from person to person. So what we saw in COVID, we saw this full curve no? But what is actually happening is slowly one incubation period one incubation period successive peaks which will get progressively taller.
So we are seeing only the outline, but inside will be like this.
So all the things like HIV, TB, COVID-19 which spreads from person to person propagated epidemic.
So, point source So, it is a continuous common source. We can see the plateau.
If it is a plateau, it is a continuous common source.
So, only this is the point source.
Rapid rise and fall, this is a propagated epidemic.
So, here it is divided by there is a gap of one incubation period. It will take the time to spread from one person to another person. This definitely defines the propagated epidemic.
So, this is a intermittent exposure epidemic.
See here, the peaks get progressively taller and there will be difference of one incubation period.
This is a typical propagated epidemic.
Difference of one incubation period.
So, next, a community-based screening program we are doing to detect that diabetes mellitus among 1,200 others.
So, it is a question known as screening test.
We are having how many individuals? 150 individuals. So, whenever whatever I have told in the class, always disease will be coming in the group or or in the above. So, always what God tells. So, totally how many are having the disease?
150. Now, we are giving a screening test.
So, screening test plus screening test minus.
Okay. So, 150 are having the disease.
The screening test correctly identified 120 as positive.
Okay. So, if you go from above to below, what I have told you it is sensitivity.
So, AB, CD. So, sensitivity is A by A plus C. So, sensitivity is 120 by 150.
Now, what they are asking the question?
positive predictive value. For positive predictive value, we go what I told in the class, we go to the right side.
So, however, 30 individuals without diabetes also tested positive, so that is false positive.
So, truly having the disease is true positive.
They do not have the disease, but the screening test identified as positive is false positive. So, what is positive predictive value? So, positive predictive value is A by A plus B. We have to go this side, right side, A by A plus B. The denominator is total positives. The numerator is true positives, which we saw in the page number 94, and we also did lot of sums in the class about this.
What is a positive predictive value? It is a post test probability of having the disease. You are doing a test, screening test, and you are coming out. After that, you are telling, "Okay, I got the positive result." Whether the positive result is really true or not, that is called as the post test probability of having the disease. What is negative predictive value? Post test probability of not having the disease.
So, this is the infographics.
So, true positives, false positives. So, positive predictive value is equal to A by A plus B.
So, we here we got it as 80, but in the exam, the numbers were different. The answer was coming around uh maybe 64 percentage.
Next, it was a question based on RCT, as well as it is a question mainly it is based on a like the uh trials we use this word, efficacy and effectiveness. So, we are introducing a new dengue vaccine. It demonstrated a efficacy of 92 percentage. Controlled clinical trial. See, you are studying in a library. In a library, no one is going to to you.
So, your retention will be higher, 92%.
Then you are studying in your home.
In your home, there is a marriage is happening.
So, there will be a lot of noise. So, the type the retention is only 84%.
So, in a library, that is in a lab controlled settings, that is called efficacy. But in the real world, we cannot control the noise. Our daddy will get a WhatsApp. Ding ding ding.
Uh mommy will see the reels. Ding ding ding ding ding ding ding. So, that is effectiveness.
So, you have to withstand everything and you have to win in your life. You have to clear the exams. That is called effectiveness. So, effectiveness in the real world the setting.
So, efficacy, it is in the lab controlled setting.
So, efficacy will always be higher.
Because they are doing it in a controlled setting. Mostly, it will be higher. So, in ideal trial conditions, vaccinated have 92% reduction disease risk. Yes, this is correct. In real world setting, they will experience an 84% lower risk of disease. Yes, this is correct.
The vaccine guarantees absolute protection. No, the vaccine will never guarantee 100% protection. It will never be 100 %.
It will be 80 or 90 because of any vaccine cannot be 100% perfect. Nobody can be 100% perfect. Vaccine efficacy in field conditions may be lower. Yes.
Working in a field lab condition, it can be lower compared to what is being happening in the lab. So, we have A, B, and D. These are the correct options.
So, we saw confirmatory trials, we will confirm the efficacy.
So, sometimes I would have explained in some centers, but in other centers, I could not have explained about the difference between the efficacy and effectiveness. it. very nuanced. They asked. So efficacy we saw in the RCT trials we do it in the real world. So with that clue you could have solved this.
So efficacy ideal clinical trial, effectiveness in the real world settings.
Next question. It was also a direct question. Which of the following best describes the Pearl Index? So Pearl you can remember Pearl I usually the women wear it. So you can remember okay contraceptive. So contraceptive efficacy. For how many months? So it comes as 100 women years. So what is 100 women years? So 100 women are using it for 1 year each.
That is called 100 women years. So number of pregnancies occurring per 100 women years. This we saw in page number 193 of our workbook. The Pearl Index with the formula. Failure rate per 100 women years of exposure is equal to total accidental pregnancies by total months of exposure into 1,200.
So we solved it.
So next question. So this was also a tricky question because it's easy but we should have known about this. According to that ABC model in psychology and health education, which of the following represents the three major domains of attitude? So in our Q bank we had something about the behavior change communication and uh what is the knowledge attitude practice? So here we are discussing about knowledge attitude practice. But in this exam they have specifically asked about attitude. They have gone to further one step above. So attitude means there is a model called a tripartite model of attitude. That is called A B C. Affective, behavioral, and cognitive. This is the three components of attitude.
So, first of all, I'll tell you. So, normally when we do study or something, how the medical education should be is it is based on KAP.
Like knowledge. What is hypertension?
That is called as the knowledge. Okay, hypertension is systolic more than or equal to 140, diastolic more than or equal to 90. Okay.
Attitude. What is attitude? Okay, if you are seeing a hypertensive patient, how you should behave. Or if you are seeing the someone in the road, how should you behave. Or looking at the salt, I should think like no, I should not take salt.
Salt will increase my BP. What is my attitude towards salt?
Then practices. In my food, I do not put salt. I eat food without salt. That is the practice. So, these are the basic three things we learn by in the medical education by these three things. So, ultimately, whatever you are learning, it should change your practice. That is called BCC, behavior change communication. Ultimately, whatever you are learning in life, if it does not change your behavior, then the education is not successful. So, the ultimate success of the health education is behavior change communication. Now, in this exam, they have specifically asked about attitude. So, attitude has three components, affective component, behavioral component, cognitive component. Cognitive component means thinking. Okay, I know that having a dog reduces stress.
Behavior component. Okay, daily I'm going to play with my dog. Affective component. Your feelings or emotion.
Okay, while playing with dog, I get so much of joy. That is in this attitude itself, we have these three. ABC, affective, behavioral, cognitive.
Affective means feeling that. Behavioral means doing it. Cognitive means thinking about that.
So, this is called as the tripartite model of attitude, ABC. Affective, behavioral, cognitive. So, affective, feelings. What is my feeling?
I feel very much attached to my dog. I feel happy when I think about my dog or when I am with my dog. Behavioral, I will take care of my dog. I will make my dog go for a walk with me. Cognitive, so I believe that dogs are loyal. I believe that that dogs are friendly. So the cognitive is thinking component.
So this is the tripart type model of attitude. So next question it was based on a recent update because before and all they were having a two dose schedule for HPV.
Okay, but now recently the government of India gave a one dose schedule for HPV and also in a specific age group because we cannot cover all the age group at the same time. Lot of population. So they are going by age age age age wise. So with that background we see the question. With reference to current recommendations on HPV vaccination, identify the current state and correct statements. Primary target group is 9 to 14 years. Yes, primary target group is 9 to 14. Now at present we are focusing on the 14 year girls. So this we had saw in our workbook in the vaccines chapter. Girls 9 to 14 years.
You can see.
Girls 9 to 14 years. HPV vaccine on the four types of human papilloma virus.
So at that [laughter] time there were only two doses, but later the government of India introduced in our vital capsules we had seen. So 14 years first India is initially covering the 14 year girls. We are giving a only one injection. We are giving it free of cost through the UWIN portal. So based on the recommendation, see the single dose schedule.
They are giving it. So this was correct. India has a single dose HPV vaccine. So if India is giving ultimately WHO would have accepted that.
Then, HPV vaccination provides absolute protection. No, no vaccine can provide absolute protection. Achieving 90% coverage is essential. Yes. So, that is a strategy for WHO. What is the strategy? This strategy is called 90-70-90 rule. We have to vaccinate 90% of the children, 90% fully vaccinated by age 15. And after that, we have to screen at least 70% by age 35 as well as by 45.
And then, 90% should get treatment, those who are having some cancerous lesion or pre-cancerous lesion. This is called 90-70-90 targets for 2030. And also, they give another target which could be asked in the next exam, that is the incident should be less than four per 100,000 women. That is the target of WHO of the cervical cancer of the cervical cancer.
So, coming to the last question, this was completely new.
This one was like out of the portion because it was also not there in our workbook and in our Q-bank also. This only one question or completely new for us.
So, Arman CH plus CH scorecard system because it is mainly associated with the health management health programs the scorecard. So, everything has a scorecard. So, if you try to compile everything in the book, it will take even more than 200-300 pages for the scorecard alone. So, here how could you have solved this question is it is based on logic. Based on logic, we can solve it. Which of the following indicators would be categorized as red flag indicators? So, MMR more than 20% above national average. See, we can take the national average.
Every year we have something.
So, what they are telling is we are having the national average.
Okay, this is 20% above. This is 20% below.
Okay, things like What are the things?
Things like mortality MMR, IMR, then fertility.
If they are more than 20% above the national average, then it is a red flag sign.
Or even there is something like malnutrition. [clears throat] Then things like care health care, how many people are having the health care access.
How many people go to the hospital? How many people get treated for ARI?
How many people get treated for ADD? So, if they access to the health care is 20% lower in a state, maybe we can take a state like Bihar Assam Jharkhand. If it is less than 20% below the national average, then the state is having a problem. Then it is a red flag sign. So, the mortality, fertility, and malnutrition indicators, if they are more than 20% above the national average, then more many mothers are dying, many infants are dying. It is a bad thing. If the people are not able to get health care access, which is less than 20% below the national average, then it is a red flag sign. So, they are dividing into three things and they are giving color. So, for best, if you have the state is doing best, it is green color. If the state is average state, it is yellow color. If the state is not doing good, it is a red color.
So, we are having MMR, IMR, and TFR. So, MMR more than 20% above national average, IMR more than 20% below. So, here the option is below, we can rule out, it will not come. So, TFR 20% above, yes. So, one, three, and fourth, proportion of children with ARI receiving treatment is more than 20% below the national average. So, see the one, three, and four, they are having some problems, so they are a red flag sign.
So, this RMNCH+A scorecard, it is a 19 survey-based scorecard. It has mortality indicators, nutrition indicators, and fertility indicators.
So, you can see, under-5 mortality rate, IMR, NMR, MMR, fertility, total fertility rate, nutrition. So, if it is more than 20% above the national average, it is a red flag sign. So, other things like the immunization level is below the 20% below the national average, and number of children getting treated for diarrhea is 20% below the national average. The number of children getting treated for pneumonia is 20% below the national average. That is health care delivery or the health service utilization. If it is below the national average, it is a red flag. So, red flag. So, green is good, yellow is average, then if it is 20% below the national average, it is a red flag. So, mortality, fertility, more than 20% higher, it is a red flag.
Health care coverage, it is more than 20% lower, it is a red flag. So, they will use a color-coded matrix. So, okay, now take for the state state of maybe state A, with regards to this maternal mortality, it is in the yellow zone. With regards to IMR, it is in the red zone. Uh some states with regards to the TFR, it is in the green zone. So, like this thing do.
This is called as the RMNCH+A scorecard matrix.
So, in the workbook, we got nine out of 12, right? So, one was completely new, one was from a related content, and one was from a recent update which was covered in the VSB. Uh so, we got almost around 10 out of 12, right? So, that will like guys. Thank you. See you next time.
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