respond to to discussion


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Those for a cross-sectional design in relation to the perception of pain severity and quality of life in advanced care patients would argue that this design studies a specific group of individuals to understand their characteristics or relationships with each other. This would be beneficial to compare the relationship between how pain severity affects quality of life in advanced cancer patients. In the journal article Chronic pain: Its impact on the quality of life and gender, they explain “This indicates that these individuals experienced intense and debilitating pain that significantly impacted their ability to carry out daily activities, engage in social interactions, and maintain a satisfactory quality of life. Managing severe chronic pain often necessitates comprehensive treatment approaches to address the intensity of the pain and alleviate the associated physical, emotional, and social burdens (Pandelani et al., 2023)”. This cross sectional study concluded that intensity of pain affects quality of life and that the data correlates with each other with just comparison of individuals with chronic pain. In a quasi-experimental design exploring the relationship between pain severity and quality of life in advanced cancer patients, specific hypotheses play an important role in framing the research objectives and guiding the study. These hypotheses serve as explicit statements of what the study aims to test or confirm. For example, a specific hypothesis might propose that an intervention aimed at reducing pain severity (such as a new medication or therapy) will lead to significant improvement in the quality of life for the participating patients. Another hypothesis could suggest that the level of pain severity, when classified into different categories (e.g., mild, moderate, severe), will have varying and predictable effects on specific aspects of the patients’ quality of life, such as their ability to engage in daily activities or emotional well-being. These specific hypotheses in a quasi-experimental design help researchers focus their efforts, and assess the causal relationships between pain severity and quality of life while considering the potential impact of interventions or treatments. Its important to keep both of these experimental methods open for trial as they both could be uses appropriately to determine causal relationships between one another. Having an interprofessional team that are able to review and be involved in the study will better enhance outcomes and provide a more thorough evaluation for each step whether it be a cross sectional or quasi-experiemntal design.





Some research team members hold differing opinions on whether our study should be categorized as a cross-sectional or quasi-experimental design. To resolve this disagreement, both groups must provide a compelling argument for why they believe their perspective is correct. Those favoring the cross-sectional design perspective must emphasize that only data is being gathered in the study. Cross-sectional studies usually collect information from a group of people at one particular moment (Bruneau et al., 2021). In our specific scenario, we would gauge the extent of pain and the level of well-being experienced by cancer patients with advanced illness at once. Although this design is effective for analyzing relationships and making observations within a particular group, it fails to demonstrate the cause-and-effect relationship over some time. It would offer a justification for reflecting on their conclusion about the design.

Conversely, colleagues favoring a quasi-experimental design would underscore the significance of possessing well-defined concepts and hypotheses in our research. Quasi-experimental designs are similar to experimental methods but do not entirely control the independent variable(Baumann et al., 2020). Our research has specific ideas that suggest we are not just watching and taking notes, but we want to discover how different things are connected and how one thing can cause another. Various interventions and treatments may be trialed to gauge the impact on patient’s pain levels and quality of life. The argument would be more robust and indispensable.

It is crucial to acknowledge that our research may possess elements of both cross-sectional and quasi-experimental methodologies when collaborating to resolve these discrepancies. We might be gathering information at the same time as we are carrying out specific actions and therapies. The design choice can vary depending on the questions we want to answer and how much control we have over the variables. By examining the initial dataset, we can discover associations between elements and, if necessary, carry out a supplementary study to explore the causal relationship between them.

The success of our study heavily relies on the team’s varied skills and expertise. Professionals spanning different domains, such as nursing, medicine, psychology, and statistics, are part of our knowledgeable staff. They possess varying perspectives and skill sets. Including multiple perspectives in this investigation enables us to thoroughly analyze the study, resulting in a well-rounded and complete research project (Spaulding et al., 2021). Working with diverse healthcare professionals allows us to create research that is both scientifically accurate, useful in practice, and focused on meeting the needs of patients. It also helps us to think about the ethics and patient results, making our study stronger and usable in real-life healthcare situations. Therefore, our collaboration and knowledge utilization is crucial to finding a solution that effectively combines the strengths of both cross-sectional and quasi-experimental designs.

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