N508 Module 6 assignment: intervention and internet-based research paper with population estimate chart, a full sample

Testing What Nurses Do, in Person and Online: Two Intervention Studies and a Population Estimate for Recruiting a Replication

Student Name

Master of Science in Nursing Program, Aspen University

N508: Theory and Research

Instructor Name

Month Day, Year

Testing What Nurses Do, in Person and Online: Two Intervention Studies and a Population Estimate for Recruiting a Replication

Intervention research asks whether something nurses do changes patients' outcomes. Much of it still involves face-to-face care, but a growing share uses the internet, either to deliver interventions or to collect data. This paper examines a classic nursing intervention trial and a recent internet-based trial, considers the particular strengths and risks of internet-based research, and develops a population estimate chart for recruiting participants to a replication of the internet-based study.

A Nursing Intervention Study

Naylor et al. (1999) tested an advanced practice nurse-centered intervention for hospitalized older adults at high risk of poor outcomes after discharge. In a randomized controlled trial of 363 patients aged 65 and older, the intervention group received comprehensive discharge planning by advanced practice nurses during the hospital stay and home follow-up visits and telephone contact for four weeks after discharge, while the control group received usual care. By 24 weeks, 20.3 percent of intervention patients had been readmitted at least once, compared with 37.1 percent of control patients; intervention patients also had fewer multiple readmissions and fewer hospital days, and total Medicare reimbursements were about half those of the control group. There were no significant differences in functional status, depression, or patient satisfaction.

The study is a strong example of nursing intervention research. The intervention was defined clearly and delivered by nurses, random assignment supported causal conclusions, and the outcomes, readmissions and costs, mattered to patients and payers. Its limitations include attrition, since about 70 percent of intervention patients and 74 percent of controls completed the trial, and the difficulty of knowing which components of a multi-component intervention produced the effect. Its lasting influence came less from any single number than from showing that a nursing intervention could be specified, tested, and costed like a drug.

For a graduate student designing an intervention study, the trial also models good reporting: it described who delivered the intervention, how often, and for how long, which is what allowed other researchers to build on it and later versions of transitional care to be tested in different populations.

An Internet-Based Nursing Study

Chen et al. (2022) tested an internet-based self-management intervention for young adults with irritable bowel syndrome, a chronic pain condition that requires lifelong self-management. Eighty young adults recruited from two university campuses and two gastrointestinal clinics were randomized either to ten self-management online education modules alone or to the same modules plus three nurse-led one-to-one consultations at baseline, 6 weeks, and 12 weeks. Pain, symptoms, quality of life, self-efficacy, and coping were measured over 12 weeks and analyzed with linear mixed models. Both groups showed significant reductions in pain intensity and pain interference and improved quality of life at 12 weeks, and the group that also received nurse consultations had significantly greater improvement in quality of life and a reduction in anxiety.

The study illustrates how internet delivery can make an intervention scalable while testing whether adding a nurse improves it. Its comparison, online modules with and without a nurse, isolates the nurse's contribution, which is a useful design for nursing research. Its limitations include a modest sample drawn largely from university campuses and self-reported outcomes.

Two further features deserve comment. The trial also enrolled healthy controls who completed pain and symptom measures, which gives context for how far participants' scores moved toward typical levels. And the authors used a longitudinal mediation analysis, finding that the nurse-led group's benefits on pain interference and quality of life worked partly through improved self-efficacy, while the online-only group's benefits worked partly through reduced catastrophizing (Chen et al., 2022). Mediation analysis helps explain how an intervention works, not only whether it works, which is valuable when the goal is to refine a nursing intervention rather than simply to prove it.

Strengths and Risks of Internet-Based Research

Internet-based research offers reach, convenience, and lower cost. Online interventions can be delivered to participants wherever they are, and online surveys can collect data from thousands of people quickly. The same features create risks. Internet samples are self-selected and exclude people without reliable internet access or digital skills, who are often older, poorer, or rural. Online data collection makes it harder to verify identity and eligibility, and fraudulent or duplicate responses have become a recognized problem in online surveys. Engagement with online interventions often declines over time, so adherence must be measured rather than assumed.

The mode of data collection can also change the answers. A multinational study of functional gastrointestinal disorders collected data from more than 73,000 adults by internet survey in some countries and household interviews in others; the prevalence of irritable bowel syndrome by Rome IV criteria was 4.1 percent in the internet surveys but 1.5 percent in the household surveys (Sperber et al., 2021). Some of that difference reflects the different countries and populations surveyed by each method, but it is a reminder that internet-based estimates may not match those gathered in person.

Researchers can reduce these risks with deliberate design. Recruiting through several channels, including clinics and community organizations as well as online advertisements, broadens the sample beyond the most connected. Verification steps, such as confirming eligibility by phone or through clinic records, and checks for duplicate or inconsistent responses protect data quality. Tracking log-ins and module completion turns engagement into a measured variable that can be reported and analyzed. Offering devices or data plans to participants who lack them, and comparing the characteristics of those who enroll with those who do not, lets investigators say honestly whom their findings describe.

Ethical Considerations for Online Intervention Research

Internet-based studies raise ethical questions that in-person studies handle more easily. Informed consent is usually obtained online, so researchers must make sure participants actually read and understand it, for example by using short comprehension questions before enrollment. Data transmitted and stored online must be protected with encryption and access controls, and participants should be told what platforms will hold their information. When an online intervention addresses symptoms such as pain, anxiety, or depression, researchers need a plan for participants whose responses suggest they need clinical help, since no clinician may be present when a concerning answer is submitted. Finally, investigators should consider who is excluded by an online design and whether the intervention, if effective, will be offered in forms that reach people without reliable internet access.

Population Estimate Chart

Before replicating the internet-based study at a composite public university, a researcher would estimate whether enough eligible participants exist. The chart below uses illustrative assumptions for enrollment and recruitment, combined with the published Rome IV internet-survey prevalence of irritable bowel syndrome (Sperber et al., 2021). Each assumption would be replaced with local data from the registrar and student health service.

Interpreting the Estimate

The chart suggests that about 114 eligible students might consent at one university, slightly more than the 100 needed to finish with 80 analyzed participants if one in five drops out. The margin is thin, which argues for adding a second recruitment source, such as a gastroenterology clinic, as the original investigators did. The estimate is also sensitive to its assumptions: if only 20 percent of eligible students saw recruitment notices, the expected number consenting would fall to about 76, well short of the target. Planning with a chart like this lets researchers identify weak links, here the reach of recruitment, and strengthen them before the study begins rather than discovering the shortfall months into enrollment.

Conclusion

Nursing intervention research has moved from the discharge planning and home visits tested by Naylor and colleagues to online modules paired with nurse consultations, but the core logic is the same: specify what nurses do, compare it with an alternative, and measure outcomes that matter. Internet-based research widens reach and lowers cost while introducing risks of self-selection, verification problems, and mode effects. Careful population estimates before recruitment protect a study from failing for lack of participants, and they remind researchers that every study's findings describe only the people it managed to reach.

References

Chen, J., Zhang, Y., Barandouzi, Z. A., Lee, J., Zhao, T., Xu, W., Chen, M.-H., Feng, B., Starkweather, A., & Cong, X. (2022). The effect of self-management online modules plus nurse-led support on pain and quality of life among young adults with irritable bowel syndrome: A randomized controlled trial. International Journal of Nursing Studies, 132, Article 104278. https://doi.org/10.1016/j.ijnurstu.2022.104278

Naylor, M. D., Brooten, D., Campbell, R., Jacobsen, B. S., Mezey, M. D., Pauly, M. V., & Schwartz, J. S. (1999). Comprehensive discharge planning and home follow-up of hospitalized elders: A randomized clinical trial. JAMA, 281(7), 613-620. https://doi.org/10.1001/jama.281.7.613

Sperber, A. D., Bangdiwala, S. I., Drossman, D. A., Ghoshal, U. C., Simren, M., Tack, J., Whitehead, W. E., Dumitrascu, D. L., Fang, X., Fukudo, S., Kellow, J., Okeke, E., Quigley, E. M. M., Schmulson, M., Whorwell, P., Archampong, T., Adibi, P., Andresen, V., Benninga, M. A., ... Palsson, O. S. (2021). Worldwide prevalence and burden of functional gastrointestinal disorders, results of Rome Foundation Global Study. Gastroenterology, 160(1), 99-114. https://doi.org/10.1053/j.gastro.2020.04.014