| Course | NURS 8310 Epidemiology and Population Health |
|---|---|
| Week | Week 6 |
| Paper type | Discussion post with two peer replies |
| Length | About 670 words, 4 pages |
| Format | Discussion post, APA 7 citations |
| School | Walden University |
| Program | Doctor of Nursing Practice (DNP) |
| Updated | September 2026 |
Free sample paper for NURS 8310 Week 6
Week 6 Discussion: Initial Post
What a Positive Screen Means at the Shelter Door: Predictive Value, Error Costs and Tuberculosis Symptom Screening at Intake
Our composite county's largest shelter asks every new guest at intake about cough lasting two weeks or more, fever, night sweats and weight loss. A yes to any question is a positive screen, and the guest is referred for a chest radiograph at the county clinic. Staff want to know what a positive screen means. I want to explain sensitivity, specificity and predictive value in words, apply them to the shelter and then argue that the consequences of each kind of error, not the test's accuracy alone, decide whether the screen helps.
Sensitivity is the share of people who truly have active tuberculosis whom the screen correctly flags. Specificity is the share of people without tuberculosis whom the screen correctly clears. Both are properties of the screen. Positive predictive value is the share of people who screen positive who actually have the disease, and negative predictive value is the share who screen negative who are actually free of it. Unlike sensitivity and specificity, predictive values shift with the share of screened people who actually have the disease (Trevethan, 2017).
The shelter in numbers, illustrative only. Suppose 1,000 new guests are screened in a quarter, and active tuberculosis is present in 2 per 1,000, which is far higher than in the general population, consistent with the concentration of tuberculosis among people experiencing homelessness reported in US surveillance (Haddad et al., 2005). Suppose also that a broad symptom screen has a sensitivity of 70% and a specificity of 65%, in the general range reviews have described for screening on any symptom (van't Hoog et al., 2022). Then about 1.4 of the 2 people with tuberculosis screen positive, and about 349 of the 998 without it also screen positive. The positive predictive value is roughly 1.4 out of 350, or 0.4%. Fewer than 1 in 200 positive screens is tuberculosis. The negative predictive value is above 99.9%, but 0.6 of a case in every 1,000 guests is missed.
Why accuracy alone does not decide. Each error has a cost. A false positive sends a guest for a radiograph they do not need. If the clinic is across town, has limited hours or requires the guest to leave the shelter until cleared, many guests will lose their bed or not go at all, and the screen will push vulnerable people back onto the street for no benefit. A false negative lets an infectious person sleep in a crowded dormitory, where one case can infect many. The screen helps only if false positives are cheap and false negatives are rare enough.
So my argument is that the shelter should keep the screen but change what happens after a positive: a same-day radiograph on site or by a mobile unit, with the guest kept in a separate sleeping area rather than turned away. That makes the false positives cheap and keeps the screen's sensitivity working for the dormitory.
Question for the thread: in your setting, what does a false positive cost the person who receives it?
Reply to Hannah
Hannah, you suggested narrowing the screen to cough of two weeks or more to reduce false positives. That would raise specificity, but it would also lower sensitivity, so more cases would be missed in a setting where a missed case is costly. Before narrowing, I would want to know what the extra false positives cost once on-site radiography is in place. If they cost little, the broader screen is worth keeping (Trevethan, 2017).
Reply to Owen
Owen, your point that chest radiography itself can be the first screen is supported by reviews showing that radiography is generally more sensitive than symptom questions alone (van't Hoog et al., 2022). For a shelter with a mobile radiography unit, screening everyone by radiograph at intake might find more cases and avoid the bed-loss problem altogether. The question becomes cost and access, which is an operational decision the county could test.
References
Haddad, M. B., Wilson, T. W., Ijaz, K., Marks, S. M., & Moore, M. (2005). Tuberculosis and homelessness in the United States, 1994-2003. JAMA, 293(22), 2762-2766. https://doi.org/10.1001/jama.293.22.2762
Trevethan, R. (2017). Sensitivity, specificity, and predictive values: Foundations, pliabilities, and pitfalls in research and practice. Frontiers in Public Health, 5, Article 307. https://doi.org/10.3389/fpubh.2017.00307
van't Hoog, A., Viney, K., Biermann, O., Yang, B., Leeflang, M. M. G., & Langendam, M. W. (2022). Symptom- and chest-radiography screening for active pulmonary tuberculosis in HIV-negative adults and adults with unknown HIV status. Cochrane Database of Systematic Reviews, 2022(5), Article CD010890. https://doi.org/10.1002/14651858.CD010890.pub2
What the NURS 8310 Week 6 instructions ask for
The Week 6 thread generally has you unpack sensitivity, specificity and predictive value using a screening program in a real or composite setting. Sections usually ask for about five hundred words up front and two peer responses after. Define each measure in plain words and say which depend on the population. Work a simple illustrative calculation for your setting, labeling the assumptions. Then go beyond accuracy: describe what each kind of error costs the person and the setting. Argue whether and how the screen helps once those costs are considered, and propose a practical change if one follows. End by asking classmates what a false positive costs in their own setting.
How this NURS 8310 Week 6 example is built
The opening paragraph describes the intake questions and the referral for a radiograph. The second defines the four measures and cites Trevethan. The third works an illustrative quarter of 1,000 guests, citing Haddad and colleagues on concentration and van't Hoog and colleagues on screen accuracy, reaching a positive predictive value near 0.4% while almost every negative screen is correct. The fourth describes the cost of false positives, including lost beds, and of false negatives in a crowded dormitory. A highlighted paragraph proposes same-day radiography with a separate sleeping area. The reply to Hannah explains the sensitivity trade-off. The reply to Owen credits radiograph-first screening.
Where the marks sit in the NURS 8310 Week 6 rubric
Screening posts are usually marked on correct definitions, accurate calculation, attention to the consequences of errors and engagement with peers. Definition credit rewards plain explanations that distinguish test properties from population-dependent values. Calculation credit depends on labeled assumptions and correct arithmetic. Faculty weight the analysis of error costs heavily, since accuracy alone rarely decides whether screening helps. Replies earn credit when they name trade-offs or credit a stronger alternative with evidence. Citations and punctual posting cover the rest. Posts that recommend a practical change tied to error costs tend to score well. Faculty also look for assumptions stated before the arithmetic, so the calculation can be checked. Some rubrics reward naming who bears the cost of each kind of error.
NURS 8310 Week 6 help: mistakes that cost marks
Screening posts lose marks when they define the measures and stop. Another common loss is treating predictive value as fixed for a given test. Some posts calculate predictive values without stating the assumed prevalence. Others judge screening by accuracy alone and ignore what happens to people after a positive result. Define the measures, calculate with labeled assumptions, describe the cost of each error and propose a change that lowers the cost of the most common error. The desk can draft a post about a screening program in your own setting. Ask staff what happens to a person after a positive screen before writing, since that step usually decides whether the screen helps or harms.
Get a NURS 8310 Week 6 example written to your instructions
Include the Week 6 discussion prompt, your rubric and the screening test your section is examining, if one is named. The post explains its properties in words, shows how predictive value shifts with prevalence using labeled illustrative numbers, and weighs both errors in your setting. First sample free, within 24-48 hours.
More NURS 8310 papers and DNP samples
- NURS 8310 Week 1: Epidemiologic Measure Post
- NURS 8310 Week 2: Incidence and Prevalence Paper
- NURS 8310 Week 3: Rate Standardization Problem Set
- NURS 8310 Week 4: Outbreak Design Memo
- NURS 8310 Week 5: Observational Study Critique
- NURS 8310 Week 7: Social Epidemiology Analysis
- NURS 8310 Week 8: Population Burden Estimate
- NURS 8310 Week 9: Causal Inference Post
- NURS 8310 Week 10: Population Health Analysis
- NURS 8310 Week 11: Epidemiologic Implications Report
- NURS 8301 Week 6: Driver Diagram Paper
- NURS 8250 Week 6: Middle-Range Theory Application
- NURS 8211 Week 6: Missing Data and Bias Post
- NURS 8210 Week 6: Virtual Care Safety Debate Post
NURS 8310 Week 6 questions, answered
Why is predictive value not a fixed property of a test?
Because it depends on how many people in the tested group actually have the condition. With sensitivity and specificity unchanged, a higher prevalence raises positive predictive value and a lower one reduces it. That is why the same screen can look useful in one population and wasteful in another. The illustrative table makes the effect visible without any real accuracy figures.
Where can I find a free NURS 8310 Week 6 sample paper?
The screening post with its replies and three sources is free to read. A post on a screening program in your own setting can be requested.
What is the positive predictive value in the NURS 8310 Week 6 example?
About 0.4% under the illustrative assumptions, meaning fewer than 1 in 200 guests who screen positive actually have tuberculosis.
What change does the post recommend?
A same-day chest radiograph on site or by mobile unit, with the guest kept in a separate sleeping area rather than turned away, so false positives cost little.
Why do error costs matter more than accuracy here?
A false positive can cost a guest a bed if follow-up is far away, while a false negative can expose a crowded dormitory, so the screen's value depends on what each error does.