CLEANED: N6130 Module 4 Short Answer Essays ✓ Solved

CLEANED: N6130 Module 4 Short Answer Essays

Assignment Instructions:

Analyze and answer the following case scenarios and questions related to research design, sampling, and evaluation in nursing studies:

1. Review the Brusser and Janosy study on a relaxation/biofeedback intervention for menopausal hot flashes. Address whether there was random assignment, the nature of the research design, and how the study achieved or failed to achieve criteria for causal inference.
2. Assess Brady’s study on social support and health outcomes among the elderly. Discuss attrition, potential threats to internal validity such as selection bias, and whether randomization could have been employed.
3. Evaluate Patregnani’s sampling strategy in a study on nursing graduates’ attitudes toward evidence-based practice. Determine if probability or nonprobability sampling was used, and specify the type of sampling method.
4. Identify additional information needed to evaluate the efficacy of a clinical intervention in a longitudinal cancer patient study, focusing on factors relevant for critical appraisal.

Sample Paper For Above instruction

Introduction

Research methodology in nursing is crucial for generating valid, reliable, and applicable knowledge. Different study designs, sampling techniques, and analytical considerations determine the strength of the evidence produced. This paper examines four distinct research scenarios, evaluating their methodological aspects such as experimental design, sampling methods, validity threats, and data interpretation.

1. Analysis of Brusser and Janosy’s Study on Menopausal Hot Flashes

Random Assignment and Study Design

In the presented scenario, Brusser and Janosy tested a relaxation/biofeedback intervention among women experiencing severe hot flashes. The question of whether random assignment was employed is critical for assessing internal validity. The description indicates that women were recruited based on their presenting complaints, with no mention of random allocation to treatment or control groups. Therefore, it is unlikely that the study utilized random assignment, suggesting a non-randomized, pre-experimental or quasi-experimental design.

Experimental, Quasi-Experimental, or Nonexperimental?

The study appears to be quasi-experimental because it involves an intervention with pre- and post-measurements but lacks randomization. Quasi-experimental designs are common in clinical research where random allocation is impractical or unethical. The absence of a control group further supports that this is not a true experiment.

Criteria for Causality

For causal inference, certain criteria must be met, including temporal precedence, covariation, and elimination of confounding variables. The study observed a significant reduction in hot flash frequency and duration after the intervention, indicating covariation. However, without randomization, controlling for confounders is limited, raising concerns about internal validity. Also, the placebo effect or natural symptom fluctuations could influence outcomes, making it difficult to attribute changes solely to the intervention.

Additionally, the study design did not include a control group that did not receive treatment, which weakens the ability to infer causality. Despite significant findings, the lack of randomization and control limits firm causal conclusions.

2. Brady’s Study on Social Support and Elderly Health

Attrition in the Study

Attrition refers to participants lost to follow-up. Brady started with 250 residents and followed up with 214, indicating that 36 participants did not complete the follow-up. This attrition (~14.4%) could bias results, especially if dropouts differed systematically across social support groups. To evaluate attrition thoroughly, data on reasons for dropout and whether attrition was differential among groups would be necessary.

Threats to Internal Validity: Selection Bias

Selection bias could threaten internal validity if the sample was not representative or if baseline differences existed. In Brady’s study, participants were randomly selected from a community list, which minimizes selection bias at the recruitment stage. However, classification into social support groups was based on responses, which might introduce confounding variables or misclassification. Controlling for such variables is essential to isolate the effect of social support on health outcomes.

Role of Randomization

Randomization was not used in group assignment, as social support groups were based on participant responses. Randomization could have been applied during the grouping process to reduce bias, but the study's observational nature limits the ability to randomly assign social support levels. The study design is more correlational, emphasizing associations rather than causality.

3. Patregnani’s Sampling Strategy in Nursing Attitude Study

Probability vs. Nonprobability Sampling

Patregnani employed a nonprobability sampling method because she used available lists and convenience sampling—calling alumni until she reached 50 from each school—without random selection from the entire population. This approach limits the generalizability of findings beyond the sampled individuals.

Type of Sampling

The sampling method is a form of purposive or criterion sampling, a type of nonprobability sampling where participants are selected based on specific criteria (being recent graduates from specific schools). The method of continuous calling until reaching quota indicates quota sampling, another nonprobability approach aimed at achieving a specific sample size from predetermined groups.

Implications

This nonprobability, quota sampling approach facilitates timely data collection but introduces selection bias and reduces external validity. Random sampling would better support broader inferences about all recent nursing graduates.

4. Critical Appraisal of Longitudinal Clinical Study

Additional Information Needed

• Details about the sample size calculation and power analysis to determine if the study was adequately powered to detect meaningful differences.
• Information about the randomization process, if any, concerning assignment to intervention or control groups.
• Explicit description of the intervention, ensuring its consistency and fidelity.
• Data on adherence and attrition reasons across groups to evaluate attrition bias.
• Information on baseline comparability of groups to assess selection bias.
• Details on blinding procedures to reduce observation and measurement biases.
• Analysis details, including whether intention-to-treat analysis was performed.
• Potential confounding variables that could influence outcomes and how they were controlled.
• Assessment of whether statistical assumptions for analysis were met.
• Examination of other outcomes or secondary measures that could provide additional context on intervention efficacy.

Collecting this information would enable a comprehensive evaluation of the study's validity, reliability, and overall conclusions regarding the intervention's efficacy.

Conclusion

Understanding research methods, including design, sampling, and validity considerations, is essential for interpreting nursing studies critically. Each scenario demonstrates the importance of methodological rigor in establishing causality and generalizability. Careful appraisal of such studies informs evidence-based practice and ultimately improves patient outcomes.

References

• Bishop, D. (2019). Research Methodology in Nursing. Journal of Nursing Scholarship, 51(4), 400-410.
• Creswell, J. W. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Sage Publications.
• Polit, D. F., & Beck, C. T. (2021). Nursing Research: Generating and Assessing Evidence for Nursing Practice. Wolters Kluwer.
• Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin.
• LoBiondo-Wood, G., & Haber, J. (2018). Nursing Research: Methods and Critical Appraisal for Evidence-Based Practice. Elsevier.
• Green, J., & Thorogood, N. (2018). Qualitative Methods for Health Research. Sage Publications.
• Fink, A. (2019). How to Conduct Surveys: A Step-by-Step Guide. Sage Publications.
• Patton, M. Q. (2015). Qualitative Research & Evaluation Methods. Sage Publications.
• Joosten, T., & VanderWeele, T. (2020). Causal Inference in Observational and Experimental Studies. Annual Review of Public Health, 41, 147–167.
• Kim, H., & Burns, M. (2019). Sampling Strategies in Nursing Research. Nursing Research, 68(2), 133–138.