NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice
Walden University NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice-Step-By-Step Guide
This guide will demonstrate how to complete the Walden University NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice assignment based on general principles of academic writing. Here, we will show you the A, B, Cs of completing an academic paper, irrespective of the instructions. After guiding you through what to do, the guide will leave one or two sample essays at the end to highlight the various sections discussed below.
How to Research and Prepare for NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice
Whether one passes or fails an academic assignment such as the Walden University NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice depends on the preparation done beforehand. The first thing to do once you receive an assignment is to quickly skim through the requirements. Once that is done, start going through the instructions one by one to clearly understand what the instructor wants. The most important thing here is to understand the required format—whether it is APA, MLA, Chicago, etc.
After understanding the requirements of the paper, the next phase is to gather relevant materials. The first place to start the research process is the weekly resources. Go through the resources provided in the instructions to determine which ones fit the assignment. After reviewing the provided resources, use the university library to search for additional resources. After gathering sufficient and necessary resources, you are now ready to start drafting your paper.
How to Write the Introduction for NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice
The introduction for the Walden University NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice is where you tell the instructor what your paper will encompass. In three to four statements, highlight the important points that will form the basis of your paper. Here, you can include statistics to show the importance of the topic you will be discussing. At the end of the introduction, write a clear purpose statement outlining what exactly will be contained in the paper. This statement will start with “The purpose of this paper…” and then proceed to outline the various sections of the instructions.
Struggling to Meet Your Deadline?
Get your assignment on NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice done on time by medical experts. Don’t wait – ORDER NOW!
How to Write the Body for NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice
After the introduction, move into the main part of the NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice assignment, which is the body. Given that the paper you will be writing is not experimental, the way you organize the headings and subheadings of your paper is critically important. In some cases, you might have to use more subheadings to properly organize the assignment. The organization will depend on the rubric provided. Carefully examine the rubric, as it will contain all the detailed requirements of the assignment. Sometimes, the rubric will have information that the normal instructions lack.
Another important factor to consider at this point is how to do citations. In-text citations are fundamental as they support the arguments and points you make in the paper. At this point, the resources gathered at the beginning will come in handy. Integrating the ideas of the authors with your own will ensure that you produce a comprehensive paper. Also, follow the given citation format. In most cases, APA 7 is the preferred format for nursing assignments.
How to Write the Conclusion for NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice
After completing the main sections, write the conclusion of your paper. The conclusion is a summary of the main points you made in your paper. However, you need to rewrite the points and not simply copy and paste them. By restating the points from each subheading, you will provide a nuanced overview of the assignment to the reader.
How to Format the References List for NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice
The very last part of your paper involves listing the sources used in your paper. These sources should be listed in alphabetical order and double-spaced. Additionally, use a hanging indent for each source that appears in this list. Lastly, only the sources cited within the body of the paper should appear here.
Stuck? Let Us Help You
Completing assignments can sometimes be overwhelming, especially with the multitude of academic and personal responsibilities you may have. If you find yourself stuck or unsure at any point in the process, don’t hesitate to reach out for professional assistance. Our assignment writing services are designed to help you achieve your academic goals with ease.
Our team of experienced writers is well-versed in academic writing and familiar with the specific requirements of the NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice assignment. We can provide you with personalized support, ensuring your assignment is well-researched, properly formatted, and thoroughly edited. Get a feel of the quality we guarantee – ORDER NOW.
A Sample Answer For the Assignment: NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice
Title: NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice
NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice
NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice
Regression analysis is one of the statistical models used in estimating the relationship between variables. The researcher has the ability to determine the effect that an independent variable has on the dependent variable (Willis & Riley, 2017). For example, an increase in one or more values on the independent variable would have an effect on the dependent variable. This paper examines regression analysis was used by an author including its weaknesses and strengths.
Article Summary
The article authored by Hatakeyama et al., (2019) aimed at finding the relationship between quality of clinical practice guideline (CPGs) and overall assessment scores. This study considered the previous studies that had been done and published between 2011 and 2015. These selected studies were subjected through an independent valuation using AGREE II. The author analyzed the results using a regression analysis. For instance, the analysis included the effect that the six domains and 23 items has on the overall assessment. The study collected a total of 206 CPGs and correlated all the domains to the items on the overall assessment to determine the strength of the relationship before taking the regression analysis on the proposed items.
Use of Regression on the Article
The author decided to subject domain 3, domain 4, domain 5, and domain 6 of the regression analysis. Domain three represented rigor of development, domain four was for clarity of presentation, domain five was for applicability and finally domain 6 was for editorial independence. The analysis was majoring on how these domains influence the overall assessment (Hatakeyama et al., 2019). The analysis showed that all the domains had a significant relationship with the overall assessment.
The author also found that four different items on AGREE II, which were item 8, 15, 19 and 22 had an effect on overall assessment. The regression analysis showed that the change in one unit of the items above had a significant change on the overall assessment which in this case acted as the dependent variable (Hatakeyama et al., 2019). Therefore, the improvement of overall assessment dependent on the increase and decrease of the items that acted as independent variables in this case.
Other statistical analysis that could have been used in the study is ANOVA analysis because it shows the strength of the relationship between the items selected. Besides, it allows the researcher to determine the effect that each dependent variables have on each other and how the relationship between the dependent variables can influence the study (Fontaine et al., 2019). Use of ANOVA tests in this study could have strengthened and relayed more information on the collection of items that could have a great impact on the overall assessment.
The strength of the regression analysis is on the ability of the author to examine more than one dependent variable. According to the study the author was interested in 22 items and their effect on overall assessment. The study is able to report on the influence of 22 items more easily as compared to other methods that could have been complex (Hatakeyama et al., 2019). Despite the strength that regression analysis has on the study, the method also has its weakness it lacks the ability to examine the relationship between the independent variables considered in the study.
Conclusion
Regression analysis is a powerful tool in assessing the relationship between dependent and independent variables. The author in the selected the study has the ability to evaluate which of the 22 items have a high or low effect on the overall assessment.
References
Fontaine, G., Cossette, S., Maheu-Cadotte, M. A., Deschênes, M. F., Rouleau, G., Lavallée, A., … & Mailhot, T. (2019). Effect of implementation interventions on nurses’ behaviour in clinical practice: a systematic review, meta-analysis and meta-regression protocol. Systematic reviews, 8(1), 1-10. https://doi.org/10.1186/s13643-019-1227-x
Hatakeyama, Y., Seto, K., Amin, R., Kitazawa, T., Fujita, S., Matsumoto, K., & Hasegawa, T. (2019). The structure of the quality of clinical practice guidelines with the items and overall assessment in AGREE II: a regression analysis. BMC health services research, 19(1), 1-8. https://doi.org/10.1186/s12913-019-4532-0
Willis, B. H., & Riley, R. D. (2017). Measuring the statistical validity of summary meta‐analysis and meta‐regression results for use in clinical practice. Statistics in medicine, 36(21), 3283-3301. https://doi.org/10.1002/sim.7372
Sample Answer for NURS 8201 Week 7 Discussion: Use of Regression Analysis in Clinical Practice Included
Discussion: Use of Regression Analysis in Clinical Practice
When a regression analysis was to be completed on the body mass index (BMI), there are several independent variables that could be included in the processes of analysis. In other words, for the regression analysis on the body mass index, the independent variable can be activity level or frequency in undertaking physical activities. The activity level can be measured in terms of the amount of time taken while undertaking physical activities (Zhang et. Al., 2019). From the theoretical perspectives and from the previous research processes, it has been established that continuous physical exercise can lead to the reduction in weight. In other words, physical activities have direct impacts on body weight. For effective outcomes of the regression analysis, there is the need for the independent variables to have a normal distribution, also, they need to be continuous variables.
Another independent variable that may relate to the Body Mass Index is the amount of fatty food intake. In most cases, increased intake of fatty foods is one of the major contributors to increase in body mass index. Individuals who consume high amount of fatty foods often tend to experience increase in body weight. As a result, their body mass indices are likely to increase. While using amount of fatty foods intake as an independent variable, there is a need ensure that it is continuous and normally distributed.
Finally, height may be considered as one of the independent variables in the regression analysis whereby BMI has been used as dependent variable. The determination of body mass index often involve the incorporation of the height of an individual. The body mass index is determined through dividing the weight of an individual with the square if the height. Therefore, height is an important determinant of the body mass index.
From the regression analysis, there is ANOVA outcomes that can be applied in the determination of whether the model is fit. From the ANOVA table, the significant values can always show if there is the relationship between the dependent and independent variables. The significant values can be tested against the alpha value at 0.05. Also, the mean square as well as the F-values obtained can be used to determine the values of body mass index. Also, the unstandardized coefficients can be applied in the determination of the correlation coefficient in the process of determining the relationship between the dependent and independent variables in the process of analysis.
Regression analysis provides the researcher with an opportunity to predict and explore future outcomes. Whether it is to determine prevention methods, promote opportunities for learning, or propose new treatments, looking towards the future can have a significant impact on patient care and sustained positive patient outcomes.
This week, you explore regression analysis, paying particular attention to linear regression. Linear regression is used to “estimate the value of a dependent variable based on the value of an independent variable” (Gray & Grove, 2020). In your Discussion, you will apply your understanding of this statistical technique as it concerns use in a research study.
Photo Credit: wutzkoh / Adobe Stock
For this Discussion, you will select an article on a study to examine the strengths and weaknesses in the use of linear regression. Consider how you might remedy the weaknesses associated with the application of linear regression and reflect on how the findings of the study that you selected might contribute to various areas of your practice.
Reference:
Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.
To Prepare:
- Review the articles in this week’s Learning Resources and evaluate their use of linear regression. Select one article that interests you to examine more closely in this Discussion.
- Critically analyze the article that you selected and consider the strengths and weaknesses described.
- Reflect on potential remedies to address these weaknesses, and how the findings from this study may contribute to evidence-based practice, the field of nursing, or society in general.
By Day 3 of Week 7
Post a brief description of the article that you selected, providing its correct APA citation. Critically analyze the article by addressing the following questions:
- What are the goals and purposes of the research study that the article describes?
- How is linear or logistic regression used in the study? What are the results of its use?
- What other quantitative and statistical methods could be used to address the research issue discussed in the article?
- What are the strengths and weaknesses of the study?
Then, explain potential remedies to address the weaknesses that you identified for the research article that you selected. Analyze the importance of this study to evidence-based practice, the nursing profession, or society. Be specific and provide examples.
Using linear regression to identify critical demographic variables affecting patient safety culture from viewpoints of physicians
Chi et al. (2017) investigated the critical demographic variables that influence patient safety culture from the perspectives of physicians and nurses using linear regression analysis. The study’s findings contribute significantly to the current scientific knowledge by exploring the relationship between demographic variables and patient safety culture. The study’s methodology utilized a cross-sectional survey design with self-administered questionnaires distributed among physicians and nurses in a teaching hospital in Taiwan. The Hospital Survey on Patient Safety Culture (HSOPSC) instrument was used to measure patient safety culture, involves five dimensions: communication openness, teamwork climate, safety climate, organizational learning, and job satisfaction. The authors also collected demographic data, including age, gender, education level, years of experience, and job title. Through linear regression analysis, the researchers determined that age, gender, education level, and years of experience significantly influenced patient safety culture. These findings align with previous studies emphasizing the impact of demographic factors on patient safety culture. For instance, younger healthcare professionals may possess a different approach or perspective toward patient safety compared to their more experienced counterparts. Chi et al. (2017) identified job satisfaction as a critical variable affecting patient safety culture. This finding shows the importance of addressing factors that contribute to job satisfaction among healthcare professionals, as it positively influences patient safety culture. The study’s implications highlight the need for healthcare organizations to consider demographic variables when developing strategies to enhance patient safety culture. Interventions targeting specific demographic groups may prove effective in fostering a positive patient safety culture and improving patient outcomes.
ALTERNATIVE METHODS
Multivariate analysis of variance (MANOVA): MANOVA is a statistical method used to compare the means of multiple dependent variables (e.g., patient safety culture scores) across multiple independent variables (e.g., demographic characteristics) (Warne, 2014). MANOVA can be used to determine whether there is a significant difference in patient safety culture between different demographic groups.
Structural equation modeling (SEM): SEM is a statistical method used to test hypothesized relationships between multiple variables (Kline, 2016). SEM can be used to develop a model of the relationship between demographic characteristics and patient safety culture, and to identify the pathways through which these variables are related.
STRENGTHS
- The study used a validated survey instrument to assess patient safety culture, which enhances the reliability and validity of the findings.
- The study included a large sample size of physicians and nurses, which increases the generalizability of the results.
- The study employed linear regression analysis to identify the critical demographic variables associated with patient safety culture, which allowed for the quantification of the relationships between these variables and patient safety culture.
- The study findings provide valuable insights into the factors that influence patient safety culture from the perspectives of both physicians and nurses, which can inform the development of targeted interventions to improve patient safety.
WEAKNESSES
- The study was cross-sectional, which limits the ability to establish causal relationships between the demographic variables and patient safety culture.
- The study was conducted in a single hospital, which limits the generalizability of the findings to other healthcare settings.
- The study did not examine the impact of other factors, such as organizational factors or leadership practices, on patient safety culture.
- The study did not explore the potential mediating or moderating effects of other variables on the relationship between demographic variables and patient safety culture.
By Day 6 of Week 7
Read a selection of your colleagues’ responses and respond to at least two of your colleagues on two different days in one or more of the following ways:
- Ask a probing question, substantiated with additional background information, evidence, or research.
Submission and Grading Information
Grading Criteria
Also Read: NURS 8201 Week 6 Assignment: Correlations
To access your rubric:
Week 7 Discussion Rubric
Post by Day 3 of Week 7 and Respond by Day 6 of Week 7
To Participate in this Discussion:
Week 7 Discussion
Regression analysis finds significant use in clinical practice. According to Hamilton et al. (2015), it helps determine how dependent and independent variables relate. It is a beneficial approach to statistical analysis. Vetter and Schober (2018) acknowledge that it provides a way to understand compound and multifactorial data. A recent research study employed this statistical method to explore how a sense of coherence (SOC) among registered nurses relates to their level of health, including work engagement (Malagon-Aguilera et al., 2019). It also evaluated stress coping skills in this nurse population based on Antonovsky’s concept regarding coherence.
The researchers utilized multiple linear regression to examine several variables comprising work engagement, job-related family tussles, health, social support, and SOC (Malagon-Aguilera et al., 2019). The results revealed that SOC had a link to the self-assessed level of well-being. The analysis also demonstrated that nurses with high work engagement did not experience job-related family conflicts. In addition, linear regression could not find an association between work engagement and SOC for nursing personnel delivering long-term care (Malagon-Aguilera et al., 2019). Finally, social support led to greater SOC.
The other quantitative and statistical method that could help tackle the research issue highlighted in this article is correlation analysis. According to Tanni et al. (2020), regression and correlation analyses enable researchers to investigate variables and their relationships with each other. The current study reveals several strengths and weaknesses. First, it recorded a good response rate of 68.9% (Malagon-Aguilera et al., 2019). The sample size further had sufficient statistical power. Generally, this study added new insights that will contribute to understanding this topic.
The main weakness in this research is that assessing causal inference across variables was impossible. Sensitivity analysis may help address this concern. Ding and VanderWeele (2016) note that this approach allows researchers to evaluate unmeasured confounding. The study also has a low determination coefficient. Adding more data points can help improve this coefficient. This research is meaningful to the nursing profession and society. It can help nurse managers determine the best approaches for promoting SOC across the nursing population to boost their work commitment and patient outcomes.
References
Ding, P., & VanderWeele, T. J. (2016). Sensitivity analysis without assumptions. Epidemiology,
27(3), 368–377. https://doi.org/10.1097/EDE.0000000000000457
Hamilton, D. F., Ghert, M., & Simpson, A. H. (2015). Interpreting regression models in clinical
outcome studies. Bone & Joint Research, 4(9), 152–153. https://doi.org/10.1302/2046-3758.49.2000571
Malagon-Aguilera, M. C., Suñer-Soler, R., Bonmatí-Tomas, A., Bosch-Farré, C., Gelabert
Vilella, S., & Juvinyà-Canal, D. (2019). Relationship between sense of coherence, health and work engagement among nurses. Journal of Nursing Management, 27(8), 1620–1630. https://doi.org/10.1111/jonm.12848
Schober, P. & Vetter, T. R. (2021). Linear regression in medical research. Anesthesia &
Analgesia, 132(1), 108-109. https://doi.org/10.1213/ANE.0000000000005206
Tanni, S. E., Patino, C. M., & Ferreira, J. C. (2020). Correlation vs. regression in association
studies. Jornal Brasileiro de Pneumologia, 46(1). https://doi.org/10.1590/1806-3713/e20200030
Linear regression is one of the most commonly used type of predictive analysis in which estimates are used to explain the relationship between two things. The overall idea of linear regression is to examine if a set of predictor variables do a good job in predicting an outcome (dependent variable) or which variables in particular are significant predictors of the outcome variables and what they do (Statistic solution, 2020). This form of analysis estimates coefficients of the linear equation, involving one or more independent variable that best predicts the value of the dependent variable.
As a result, they fit into a straight line or surface that minimizes the discrepancies between predicted and output values (Sathwick, 2020). Also, linear regressions help healthcare organizations collect massive data and use these data manage information. It would also provide better insights on patterns and relationships that would help understand its analytical connection. Since there is a new surge of Covid-19 almost every year for the past three years now, a study that I found interesting in conjunction with the Covid-19 is the associated stress that comes with this ongoing pandemic.
Being a nurse in the ICU during the outbreak, I can clearly remember the days where not only were there many patients being admitted during the outbreak, but also the frontline healthcare teams were increasingly also catching the virus. This pandemic has prompted many nurses to retire and the unit short staffed every day. Accompanied with the staff shortage is the constant PPE and infection disease management policy changes. Dealing with the unknown, often puts people in a vulnerable risk for infection and psychological effects that should be monitored and understood. This would then assist in protecting the frontline workers and research ways to increase resilience amidst the pandemic outbreak.
While being a healthcare worker as well as a being a frontline employee, stress becomes an inevitable part of our job. In a linear regression study done by Tayyib & Alsolami (2020), the role of RNs have potentially exposed them infection and its associated consequences. This study was done to assess the physiological effects of fear, stress, and level of resilience in response to Covid-19 outbreaks. In this study, questionnaires were conducted during the outbreak including sociodemographic details, job related stress, and fear of infection; the data analyzed used descriptive correlation studies and linear regression studies.
In the study result, about 314 nurses (87%) who responded to survey showed that the higher the outbreaks the higher the level of anxiety and stress during the outbreaks (mean 7.61, SD + 2.72); reporting high risk of being infected (mean 7.6, SD+ 2.72), causing stress at work (mean 6.92, SD + 2.91), and falling ill (mean 6.72, SD + 2.98). The predictive factors included social media (0.76, p= 0.03), exposure to trauma prior to outbreak (-0.95, p=0.003), and readiness of care (-0.21, p=0.001). these factors have significant impact on an RN’s psychological status which may affect the quality of patient care.
The strength of this article is that it takes into account the important aspects that should be considered regarding RNs’ perceived high level of fears and stress are the coping measures that should be taken during and after this time to help alleviate post-traumatic stress and increase their emotional resilience. The weakness of this article includes the need for further longitudinal prospective studies to capture the large population and different time series recommended to validate this study further and provide a more thorough understanding of this issue. Furthermore, it would be more beneficial to research on factors that affect their level of stress and fears during such times. Supportive interventions need to be introduced to ensure resilience among staff and ensure quality patient care.
Reference(s)
Sathwick, S. (2020). What is a linear regression? Data Science. Retrieved from
Statistic Solution (2020). What is linear regression? Stat Solution Dissertation. Retrieved from
Tayyib, N. & Alsolami, F. (2020). Measuring the extent of stress and fear among registered
nurses in KSA during the Covid-19 outbreak. Journal of Taibah University Medical Sciences. 15(5). 410-416. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7462892/
Name: NURS_8201_Week7_Discussion_Rubric
| Excellent
90–100 | Good
80–89 | Fair
70–79 | Poor
0–69 | |||
| Main Posting:
Response to the Discussion question is reflective with critical analysis and synthesis representative of knowledge gained from the course readings for the module and current credible sources. | 40 (40%) – 44 (44%)
Thoroughly responds to the Discussion question(s). Is reflective with critical analysis and synthesis representative of knowledge gained from the course readings for the module and current credible sources. No less than 75% of post has exceptional depth and breadth. Supported by at least three current credible sources. | 35 (35%) – 39 (39%)
Responds to most of the Discussion question(s). Is somewhat reflective with critical analysis and synthesis representative of knowledge gained from the course readings for the module. 50% of the post has exceptional depth and breadth. Supported by at least three credible references. | 31 (31%) – 34 (34%)
Responds to some of the Discussion question(s). One to two criteria are not addressed or are superficially addressed. Is somewhat lacking reflection and critical analysis and synthesis. Somewhat represents knowledge gained from the course readings for the module. Cited with fewer than two credible references. | 0 (0%) – 30 (30%)
Does not respond to the Discussion question(s). Lacks depth or superficially addresses criteria. Lacks reflection and critical analysis and synthesis. Does not represent knowledge gained from the course readings for the module. Contains only one or no credible references. | ||
| Main Posting:
Writing | 6 (6%) – 6 (6%)
Written clearly and concisely. Contains no grammatical or spelling errors. Adheres to current APA manual writing rules and style. | 5 (5%) – 5 (5%)
Written concisely. May contain one to two grammatical or spelling errors. Adheres to current APA manual writing rules and style. | 4 (4%) – 4 (4%)
Written somewhat concisely. May contain more than two spelling or grammatical errors. Contains some APA formatting errors. | 0 (0%) – 3 (3%)
Not written clearly or concisely. Contains more than two spelling or grammatical errors. Does not adhere to current APA manual writing rules and style. | ||
| Main Posting:
Timely and full participation | 9 (9%) – 10 (10%)
Meets requirements for timely, full, and active participation. Posts main Discussion by due date. | 8 (8%) – 8 (8%)
Meets requirements for full participation. Posts main Discussion by due date. | 7 (7%) – 7 (7%)
Posts main Discussion by due date. | 0 (0%) – 6 (6%)
Does not meet requirements for full participation. Does not post main Discussion by due date. | ||
| First Response:
Post to colleague’s main post that is reflective and justified with credible sources. | 9 (9%) – 9 (9%)
Response exhibits critical thinking and application to practice settings. Responds to questions posed by faculty. The use of scholarly sources to support ideas demonstrates synthesis and understanding of learning objectives. | 8 (8%) – 8 (8%)
Response has some depth and may exhibit critical thinking or application to practice setting. | 7 (7%) – 7 (7%)
Response is on topic and may have some depth. | 0 (0%) – 6 (6%)
Response may not be on topic and lacks depth. | ||
| First Response:
Writing | 6 (6%) – 6 (6%)
Communication is professional and respectful to colleagues. Response to faculty questions are fully answered, if posed. Provides clear, concise opinions and ideas that are supported by two or more credible sources. Response is effectively written in standard, edited English. | 5 (5%) – 5 (5%)
Communication is mostly professional and respectful to colleagues. Response to faculty questions are mostly answered, if posed. Provides opinions and ideas that are supported by few credible sources. Response is written in standard, edited English. | 4 (4%) – 4 (4%)
Response posed in the Discussion may lack effective professional communication. Response to faculty questions are somewhat answered, if posed. Few or no credible sources are cited. | 0 (0%) – 3 (3%)
Responses posted in the Discussion lack effective communication. Response to faculty questions are missing. No credible sources are cited. | ||
| First Response:
Timely and full participation | 5 (5%) – 5 (5%)
Meets requirements for timely, full, and active participation. Posts by due date. | 4 (4%) – 4 (4%)
Meets requirements for full participation. Posts by due date. | 3 (3%) – 3 (3%)
Posts by due date. | 0 (0%) – 2 (2%)
Does not meet requirements for full participation. Does not post by due date. | ||
| Second Response: Post to colleague’s main post that is reflective and justified with credible sources. | 9 (9%) – 9 (9%)
Response exhibits critical thinking and application to practice settings. Responds to questions posed by faculty. The use of scholarly sources to support ideas demonstrates synthesis and understanding of learning objectives. | 8 (8%) – 8 (8%)
Response has some depth and may exhibit critical thinking or application to practice setting. | 7 (7%) – 7 (7%)
Response is on topic and may have some depth. | 0 (0%) – 6 (6%)
Response may not be on topic and lacks depth. | ||
| Second Response: Writing | 6 (6%) – 6 (6%)
Communication is professional and respectful to colleagues. Response to faculty questions are fully answered, if posed. Provides clear, concise opinions and ideas that are supported by two or more credible sources. Response is effectively written in standard, edited English. | 5 (5%) – 5 (5%)
Communication is mostly professional and respectful to colleagues. Response to faculty questions are mostly answered, if posed. Provides opinions and ideas that are supported by few credible sources. Response is written in standard, edited English. | 4 (4%) – 4 (4%)
Response posed in the Discussion may lack effective professional communication. Response to faculty questions are somewhat answered, if posed. Few or no credible sources are cited. | 0 (0%) – 3 (3%)
Responses posted in the Discussion lack effective communication. Response to faculty questions are missing. No credible sources are cited. | ||
| Second Response: Timely and full participation | 5 (5%) – 5 (5%)
Meets requirements for timely, full, and active participation. Posts by due date. | 4 (4%) – 4 (4%)
Meets requirements for full participation. Posts by due date. | 3 (3%) – 3 (3%)
Posts by due date. | 0 (0%) – 2 (2%)
Does not meet requirements for full participation. Does not post by due date. | ||
| Total Points: 100 | ||||||
Name: NURS_8201_Week7_Discussion_Rubric
Don’t wait until the last minute
Fill in your requirements and let our experts deliver your work asap.