NUR4053 Module 3 research design comparison paper example

Reviewed by Junia Fairbank, MSN, RN · American College of Education · True APA form, annotated

This page holds a complete NUR 4053 Module 3 example in true APA form: a research design comparison paper for American College of Education's Research Methods and Evidence-Based Practice in Nursing course. It takes one question that matters to nurses, whether working nights raises breast cancer risk, and reads real studies of it through three designs, showing what a cohort study, a case-control study and a randomized trial can and cannot establish.

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Does Night Shift Work Raise Breast Cancer Risk? One Question Read Through a Cohort Study, a Case-Control Study and the Trial No One Can Run

Student Name

American College of Education

NUR4053: Research Methods and Evidence-Based Practice in Nursing

Module 3 Assignment

Instructor Name

July 20, 2026

What this page is doingThe title poses a question nurses care about personally and then promises to read it through three designs, including one that cannot be used. That promise signals analysis rather than a list of definitions. The APA 7 title page carries the course line and module assignment as the classroom lists it.
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Why This Question Suits a Design Comparison

Research design is easiest to understand when the question stays the same and only the method changes. The question used here has personal weight for many nurses: does working night shifts increase a woman's risk of developing breast cancer? The biological reasoning behind it is that light at night suppresses melatonin, a hormone that may have anticancer properties, and may disturb other hormonal rhythms. The question has been studied with several designs over two decades, and the answers have not always agreed.

Polit and Beck (2021) organize quantitative designs by the researcher's control over the independent variable. In experimental designs, the researcher assigns the intervention; in observational designs, the researcher measures an exposure people already have. Night shift work is an exposure people choose or are assigned by employers, not one a researcher can hand out, so most of the evidence comes from observational designs. The question is therefore a good test of what observational research can establish when the ideal design is off the table.

What this page is doingThe opening explains why one topic is used for every design, which is the organizing idea of the paper, and it gives the biological rationale so the reader understands why the question is plausible. The design taxonomy is taken from the course text, and the highlighted sentence frames the rest of the analysis.
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The Cohort Design

A cohort study selects people by exposure status before the outcome has occurred and follows them forward in time. Schernhammer et al. (2001) used the Nurses' Health Study, a large cohort of registered nurses in the United States. In 1988, 78,562 women reported how many years they had worked rotating night shifts with at least three nights a month, and they were followed for ten years, during which 2,441 cases of breast cancer were identified. Women who had worked rotating nights for 30 or more years had a moderately increased risk compared with women who had never worked them, with a relative risk of 1.36, and the test for trend across increasing years of night work was statistically significant. Shorter durations showed only small, nonsignificant increases.

The strength of this design is timing. Because night work was recorded before any cancer was diagnosed, the women's memories of their work history could not have been shaped by a diagnosis. The cohort was also large enough to examine duration, which strengthens a causal argument when risk rises with dose. The weakness is that exposure was measured once, as a self-reported number of years, and the women who worked nights for three decades may have differed from other nurses in ways the analysis could not fully adjust for, such as reproductive history, body weight or access to screening. A cohort study can show that risk and exposure travel together; it cannot rule out that something else travels with them.

What this page is doingThe design is defined by how participants are selected and when exposure is measured, and then the study is reported with its sample, follow-up, case count and main finding, including the null results for shorter durations. The strengths and weakness are tied to specific features of this study, not generic textbook statements.
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The Case-Control Design

A case-control study starts from the outcome. It selects people who already have the disease and a comparison group who do not, then looks backward to compare their past exposures. Davis et al. (2001) identified 813 women aged 20 to 74 diagnosed with breast cancer and 793 control women selected by random-digit dialing and matched in five-year age groups. In-person interviews collected lifetime occupational history, sleep habits and bedroom lighting over the previous ten years. Women who had worked the graveyard shift had a higher risk of breast cancer, with an odds ratio of 1.6, and risk tended to rise with more years and more hours per week of graveyard shift work.

The strength of this design is efficiency: it can study a relatively uncommon disease without following hundreds of thousands of people for years, and it can collect detailed exposure information, such as bedroom lighting, that a large cohort rarely measures. The weakness is recall. Women with a recent cancer diagnosis may search their memories more thoroughly than healthy controls, which can inflate reported exposures among cases. Selection of controls also matters; random-digit dialing reaches people with landline telephones who agree to participate, who may differ from the population the cases came from. A case-control study answers quickly, but it asks people to remember, and memory is not a neutral instrument.

What this page is doingThe case-control design is defined by its direction, from outcome back to exposure, which is the feature students most often confuse with a cohort study. The study details are exact, and the discussion of recall bias and control selection shows the writer understands why the design's result needs caution.
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The Trial No One Can Run

The strongest design for a causal question is the randomized controlled trial, in which participants are randomly assigned to an exposure or its absence so that other factors are balanced between groups. For this question, a trial would assign women at random to decades of night shift work or to day work and then count breast cancer diagnoses. That trial cannot be done. It would be unethical to assign a possible carcinogen, impossible to keep people in their assigned shifts for thirty years and impractical to follow them long enough for cancer to develop.

When a trial is impossible, the evidence has to be assembled from observational designs, and consistency across studies becomes the main safeguard. Here the evidence is not consistent. Travis et al. (2016) analyzed three large prospective cohorts in the United Kingdom, including more than half a million women in the Million Women Study, and found no increase in breast cancer incidence among women who reported night shift work, and their meta-analysis of prospective studies reached the same conclusion. The International Agency for Research on Cancer nonetheless classified night shift work as probably carcinogenic to humans, relying on limited evidence in humans together with stronger experimental evidence in animals and mechanistic studies (International Agency for Research on Cancer [IARC], 2020).

What this page is doingExplaining why the ideal design cannot be used is the part of the paper that shows real understanding of research ethics and feasibility. The paper then introduces a large null cohort and the IARC classification, so the reader sees that designs can disagree and that expert bodies weigh different kinds of evidence together.
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What the Designs Can Support Together

Read side by side, the designs tell a careful story. The earlier cohort and case-control studies found moderate associations, strongest for long durations of night work. Later cohorts that were larger but measured night work more briefly, often with a single question about ever working nights, found no association. Differences in how exposure was defined may explain part of the disagreement: thirty years of rotating nights in the Nurses' Health Study is a very different exposure from any night work at all. Polit and Beck (2021) stress that the credibility of an association depends on its strength, its consistency across studies, a dose-response pattern and a plausible mechanism, and on this question the evidence meets some of those tests but not all.

For a nurse deciding whether to leave night work, the honest summary is that long-term night shift work may carry a modest increase in breast cancer risk, that the evidence is mixed and that no design available can settle it with certainty. That is not a weak conclusion. It is the most accurate one the evidence supports, and reaching it requires knowing what each design can and cannot show.

What this page is doingThe synthesis explains the disagreement between studies with a specific reason, how exposure was defined, and applies recognized criteria for judging associations. The conclusion translates the evidence into a statement a nurse could act on without overstating it, which is the point of learning designs in the first place.
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Conclusion

Keeping one question fixed makes the differences between designs plain. The cohort study measured exposure before the outcome and could examine duration, but it could not exclude hidden differences between groups. The case-control study answered efficiently and measured exposure in detail, but it relied on memory. The randomized trial that would settle the question cannot ethically be run. Reading these designs together, with their strengths and weaknesses in view, is what allows a nurse to move from a frightening headline to a measured judgment about what the evidence actually shows.

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References

Davis, S., Mirick, D. K., & Stevens, R. G. (2001). Night shift work, light at night, and risk of breast cancer. Journal of the National Cancer Institute, 93(20), 1557-1562. https://doi.org/10.1093/jnci/93.20.1557

International Agency for Research on Cancer. (2020). Night shift work (IARC Monographs on the Identification of Carcinogenic Hazards to Humans, Vol. 124).

Polit, D. F., & Beck, C. T. (2021). Nursing research: Generating and assessing evidence for nursing practice (11th ed.). Wolters Kluwer.

Schernhammer, E. S., Laden, F., Speizer, F. E., Willett, W. C., Hunter, D. J., Kawachi, I., & Colditz, G. A. (2001). Rotating night shifts and risk of breast cancer in women participating in the Nurses' Health Study. Journal of the National Cancer Institute, 93(20), 1563-1568. https://doi.org/10.1093/jnci/93.20.1563

Travis, R. C., Balkwill, A., Fensom, G. K., Appleby, P. N., Reeves, G. K., Wang, X.-S., Roddam, A. W., Gathani, T., Peto, R., Green, J., Key, T. J., & Beral, V. (2016). Night shift work and breast cancer incidence: Three prospective studies and meta-analysis of published studies. Journal of the National Cancer Institute, 108(12), Article djw169. https://doi.org/10.1093/jnci/djw169

How this NUR 4053 Module 3 example is structured

NUR 4053 Module 3 usually introduces research designs so that a cohort, a case control and a trial stop blurring; your classroom's instructions decide whether the paper compares designs in general or through studies of one topic. This example uses one question for all three designs, which makes the differences visible. For each design it explains how participants are selected, when exposure and outcome are measured, what the study found and the design's main weakness. A separate section explains why a randomized trial cannot be done here, and the conclusion states what the combined evidence can support. Keeping the question fixed and letting only the design change is what makes the comparison teach.

NUR4053 Module 3 questions, answered

What is NUR4053 Module 3 usually about?

NUR4053 Module 3 usually introduces quantitative research designs so students can tell a cohort study, a case-control study and a randomized controlled trial apart. Many sections ask for a paper or discussion that explains each design and applies it to a topic. Your classroom's instructions decide whether you compare designs in general or through specific published studies.

What is the easiest way to tell a cohort study from a case-control study?

Look at how participants were chosen. A cohort study selects people by exposure, before the outcome, and follows them forward. A case-control study selects people by outcome, those with and without the disease, and looks back at their exposures. If the paper starts with diagnosed cases, it is almost always case-control.

Why are some questions never studied with a randomized trial?

Because assigning the exposure would be unethical, impractical or impossible. Researchers cannot randomly assign people to smoke, to work nights for decades or to live in poverty. For those questions, evidence comes from observational designs, and confidence depends on consistency across studies, dose-response patterns and a plausible biological mechanism.

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