NUR 550 Evidence-Based Practice Project Proposal: PICOT
Grand Canyon University NUR 550 Evidence-Based Practice Project Proposal: PICOT – Step-By-Step Guide
This guide will demonstrate how to complete the Grand Canyon University NUR 550 Evidence-Based Practice Project Proposal: PICOT 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 NUR 550 Evidence-Based Practice Project Proposal: PICOT
Whether one passes or fails an academic assignment such as the Grand Canyon University NUR 550 Evidence-Based Practice Project Proposal: PICOT 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 NUR 550 Evidence-Based Practice Project Proposal: PICOT
The introduction for the Grand Canyon University NUR 550 Evidence-Based Practice Project Proposal: PICOT 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.
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How to Write the Body for NUR 550 Evidence-Based Practice Project Proposal: PICOT
After the introduction, move into the main part of the NUR 550 Evidence-Based Practice Project Proposal: PICOT 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 NUR 550 Evidence-Based Practice Project Proposal: PICOT
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 NUR 550 Evidence-Based Practice Project Proposal: PICOT
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.
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Sample Answer for NUR 550 Evidence-Based Practice Project Proposal: PICOT
PICOT Final
| PICOT Question | |||
| P | Population | Older adults with type 2 diabetes | |
| I | Intervention | Twice-weekly tailored physical exercise training | |
| C | Comparison | No exercise interventions | |
| O | Outcome | Improved functional fitness and independent living | |
| T | Timeframe | 8 weeks | |
| PICOT Create a complete PICOT statement. | In older adults with type 2 diabetes (P), does a twice-weekly tailored physical exercise training program (I), compared to no exercise interventions (C), improve functional fitness and independent living (O) in 8 weeks (T)? | ||
| Problem Statement Create a problem statement for your PICOT. You will use this problem statement throughout your final written paper. | Older adults are a unique population with complex and highly demanding health problems. The prevalence of type 2 diabetes among older adults is a significant nursing practice problem since it increases hospitalizations, healthcare costs, and the risk for cardiovascular disease (Atak Tel et al., 2023; Evans et al., 2022). These outcomes denote a significant gap between the delivered and desired patient care. Nursing and healthcare research further shows that type 2 diabetes is associated with reduced functional performance and independence among older adults (Kirwan et al., 2021; Pfeifer et al., 2022). As a result, interventions tailored to improve functional capacity and independence among older adults with type 2 diabetes are crucial for improved health outcomes and reduced clinical visits. | ||
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References
Atak Tel, B. M., Aktas, G., Bilgin, S., Baltaci, S. B., & Taslamacioglu Duman, T. (2023). Control level of type 2 diabetes mellitus in the elderly is associated with polypharmacy, accompanied comorbidities, and various increased risks according to the Beers Criteria. Diagnostics (Basel, Switzerland), 13(22), 3433. https://doi.org/10.3390/diagnostics13223433
Evans, M., Chandramouli, A. S., Faurby, M., Matthiessen, K. S., Mogensen, P. B., & Verma, S. (2022). Healthcare costs and hospitalizations in US patients with type 2 diabetes and cardiovascular disease: a retrospective database study (OFFSET). Diabetes, Obesity & Metabolism, 24(7), 1300–1309. https://doi.org/10.1111/dom.14703
Kirwan, M., Chiu, C. L., Hay, M., & Laing, T. (2021). Community-based exercise and lifestyle program improves health outcomes in older adults with type 2 diabetes. International Journal of Environmental Research and Public Health, 18(11), 6147. https://doi.org/10.3390/ijerph18116147
Pfeifer, L. O., De Nardi, A. T., da Silva, L. X. N., Botton, C. E., do Nascimento, D. M., Teodoro, J. L., … & Umpierre, D. (2022). Association between physical exercise interventions participation and functional capacity in individuals with type 2 diabetes: a systematic review and meta-analysis of controlled trials. Sports Medicine-Open, 8(1), 1-22. https://doi.org/10.1186/s40798-022-00422-1
Research involving subjects may pose significant risks to participants, hence the need for adequate control. Besides, individuals may participate in unbeneficial studies, and their protection is among the cardinal roles of Institutional Review Boards (IRBs). In the research context, IRBs are federally mandated boards that review research with human participants to ensure it meets the appropriate ethical guidelines (White, 2020). Under the FDA’s authorization, an IRB can approve, request modifications, or disapprove research. The decisions are made after the IRB’s group process of reviewing research protocols and materials (U.S. Food & Drug Administration, 2019). Generally, the advance and periodic review of research ensures adequate protection of human subjects’ rights and welfare.
Before proposing or commencing population health research, researchers should understand and adhere to its ethical considerations. The basic ethical considerations include respect for persons, beneficence, and justice. Respect for persons obligates researchers to promote autonomy and protect individuals with diminished autonomy (Gordon, 2020; White, 2020). Informed consent ensures autonomous decision-making and voluntary participation in research. Beneficence involves not harming participants and maximizing potential benefits (Mondragón Barrios et al., 2022). Justice is accomplished by fair participation and distribution of research benefits and burdens.
Before commencing research, the researchers and participants should look forward to studies benefitting patients, populations, and the broader society. One way of accomplishing this objective is balancing respect for the persons, potential research benefits and burdens, and research. For instance, after obtaining informed consent from participants in a study on mHealth apps and diabetes self-care, researchers should carefully examine who should receive the research benefits and bear its burdens. To ensure justice, the National Commission proposes equal share and distribution of benefits according to individual needs, effort, and societal contribution (White, 2020). Merit should also be a critical consideration when distributing research benefits and burdens.
NUR-550 Evidence-Based Practice Project Evaluation of Literature Table Sample
Literature Evaluation Table
Learner Name:
PICOT:
Author, Journal (Peer-Reviewed), and Permalink or Working Link to Access Article
| Article Title and Year Published
| Research Questions/ Hypothesis, and Purpose/Aim of Study
| Design (Quantitative, Qualitative, or other)
| Setting/Sample
| Methods: Intervention/ Instruments
| Analysis/Data Collection
| Outcomes/Key Findings
| Recommendations
| Explanation of How the Article Supports Your Proposed EBP Practice Project Proposal |
Coahran, M., Hillier, L. M., Van Bussel, L., Black, E., Churchyard, R., Gutmanis, I., Ioannou, Y., Michael, K., Ross, T., & Mihailidis, A Journal on Aging = La Revue Canadienne Du Vieillissement, https://doi.org/10.1017/S0714980818000181 | Automated Fall Detection Technology in Inpatient Geriatric Psychiatry: Nurses’ Perceptions and Lessons Learned. 2018
| The aim of this study was to describe the performance of the HELPER system and obtain nurses’ perceptions about its use | Qualitative | Nurses working in two geriatric psychiatry units within a regional mental health hospital in Ontario. | Patients and their decision-makers admitted to rooms with HELPER device were recruited to the study. All night-shift nursing staff were invited to participate in the research. They were trained on the use of HELPER system and it use when on shift. | Interviews were conducted over two days at the end of the research period. The interviews were digitally recorded and transcribed. Qualitative naturalistic inquiry approach was adopted for data analysis. | The HELPER system missed only one documented fall but detected four undocumented falls. The system had high sensitivity. Nurses expressed positive experiences and perception towards the system. | Future studies should focus on minimizing false alarms in system development. | The research supports my proposed study by showing the effectiveness of automated systems in detecting and preventing falls. It also shows that it has high sensitivity. |
Gaspar, A. G. M., & Lapão, L. V. Journal of Medical Internet Research, https://doi.org/10.2196/22215 | eHealth for Addressing Balance Disorders in the Elderly: Systematic Review. 2020 | The aim of this study was to determine the clinical applicability of eHealth devices and guide their use in screening, assessment, and treating elderly people with balance disorders. | Quantitative | 21 articles | A search for relevant articles was done in Google Scholar, PubMed, Embase, and SciELO databases. The systematic review was done according to the PRISMA statement. Randomized controlled trials or quasi experimental studies published between 2015 and 2019 were included in the review. | Narrative synthesis was adopted as the approach to data analysis. The articles were first categorized according to study design followed by categorizing them based on eHealth services and their applicability. | eHealth interventions such as those utilized in detecting risks for falls and assessing balance have the potentials of improving care outcomes. They are effective in patients at risk of falling as well as those with balance disorder. | The researchers recommended the large-scale implementation of eHealth interventions to improve patient monitoring and outcomes. | The study supports my proposed project by showing that sensor technologies improve outcomes in patients with balance disorders and those at risk of falls. |
Joshi, M., Archer, S., Morbi, A., Ashrafian, H., Arora, S., Khan, S., Cooke, G., & Darzi, A. JMIR Formative Research, 6(2), e27866. https://doi.org/10.2196/27866 | Perceptions on the Use of Wearable Sensors and Continuous Monitoring in Surgical Patients: Interview Study Among Surgical Staff. 2022 | The aim of this study was to examine the views of surgical team members regarding the use of novel wearable sensors for surgical patients | Qualitative | 48 senior and junior surgeons and senior and junior nurses. | Semi-structured interviews were conducted with the participants to obtain insights into their experiences with novel wearable sensors for surgical patients. An interview guide was used during face-to-face interviews, which were audio-recorded and transcribed verbatim. | Semi-structured interviews were conducted with the participants. All transcripts were reviewed and coded by second independent research. Any discrepancies were discussed until agreement was reached. | The participants’ perception towards the use of wearable sensors for continuous monitoring was positive. They expressed optimism that the technology will improve patient safety. | The researchers recommended the need for future studies to explore how to manage concerns raised including the potentials of alarm fatigue among healthcare providers. | The study supports my proposed project by showing the potentials of automated technologies in improving safety in the patient care process and positive experiences by healthcare providers. |
Maneeprom, N., Taneepanichskul, S., Panza, A., & Suputtitada, A. Clinical Interventions in Aging, https://doi.org/10.2147/CIA.S182336 | Effectiveness of robotics fall prevention program among elderly in senior housings, Bangkok, Thailand: A quasi-experimental study. 2019 | The aim of this study was to investigate the effectiveness of a robotic fall prevention program on exercises, knowledge, balance, and falls incidence among elderly in senior housings. | Quantitative | 64 elderly patients | Two-tailed statistical hypothesis was used for calculating the sample size. Two senior housings were purposively sampled for use in the study. Fall risk screening was conducted to identify the participants that met the inclusion criteria. The intervention entailed the implementation of a robotic fall prevention program, where a small robot-installed fall prevention software were installed alongside personal coaching and fall prevention handbook. | Data on socioeconomic backgrounds of the participants were obtained. BI scale of ADL was used to determine the level of physical activities. TUG was used for fall screening while BBS was used for assessing balance. Fall prevention questionnaire was used for knowledge on fall prevention. | The intervention led to statistically significant improvement in knowledge, number of exercises, TUG, BBS, and fall in the intervention group as compared to control group. | The researchers recommended future studies to take a longer period to determine its effectiveness over time. | The article supports my proposed project by showing that automated fall technologies reduce the risk of falls as well as increasing awareness among patients at risk of falls. |
Mulas, I., Putzu, V., Asoni, G., Viale, D., Mameli, I., & Pau, M. . Aging Clinical and Experimental Research, https://doi.org/10.1007/s40520-020-01715-9 | Clinical assessment of gait and functional mobility in Italian healthy and cognitively impaired older persons using wearable inertial sensors. 2021 | The purpose of this study was to verify the feasibility of wearable inertial sensors in a clinical site to screen functional mobility and gait in Italian older persons. | Quantitative | 213 adults aged over 65 years | Cognitive assessments were performed on the participants. Instrumental gait analysis and Timed Up and Go (TUG) test were also undertaken using a wearable inertial sensor. | Data on gait and TUG tests were obtained using the wearable inertia sensors. Gait analysis was done while patients walked for 30 meters. The data were processed using Matlab routine for parameters of gait and TUG. | Wearable inertial sensors effectively identified mobility parameters and indicators of physical and cognitive impairments in clinical settings. | The authors recommended the use of the wearable inertia technology in reducing and preventing mobility limitations in cognitively impaired patients, including the elderly. | The research supports my project by demonstrating the accuracy and effectiveness of automated technologies in detecting and preventing mobility limitations such as falls. |
Saod, A. H. M., Mustafa, A. A., Soh, Z. H. C., Ramlan, S. A., & Harron, N. A. 2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE), https://doi.org/10.1109/ICCSCE52189.2021.9530983 | Fall Detection System Using Wearable Sensors with Automated Notification. 2021 | The purpose of this study was to determine the efficacy of wearable sensors in fall detection | Quantitative | Experimental study using volunteers | Wearable sensors were installed to the volunteers. They engaged in activities that can cause falls such as walking, standing, laying on the bed, and changing positions. The sensors analyzed the movements and notified any potentials of falls. | Sensors analyzed the positional changes and notified in case of a potential for a fall. | Wearable sensors had accuracy rate of 97%. They also demonstrated enhanced sensitivity to detecting falls and notifying detected fall occurrence. | Wearable sensors should be incorporated in clinical monitoring of patients to identify risk of falls. | The article supports the proposed project by showing that automated fall detectors have high accuracy in fall detection and notification. |
Seow, J. P., Chua, T. L., Aloweni, F., Lim, S. H., & Ang, S. Y. Japan Journal of Nursing Science, https://doi.org/10.1111/jjns.12446 | Effectiveness of an integrated three-mode bed exit alarm system in reducing inpatient falls within an acute care setting. 2022 | The aim of this study was to examine the effectiveness of an integrated three-mode bed exit alarm system in reducing inpatient falls in an acute care hospital in Singapore | Quantitative | The retrospective study was conducted in a 1700 bed acute tertiary teaching hospital in Singapore. Data from 17398 patients was used. | The bed-exit alarm systems were implemented in July 2016. The pre-implementation phase was between October 2015 and June 2016. Three inpatient wards with similar conditions were used. | Data was extracted from the hospital’s electronic database. Fall incidents were obtained from the hospital’s risk management system. Managers verified the information contained in this system. | The use of bed exit alarms led to a reduction in falls incidence. | Hospitals should consider the effect of alarms fatigue on the potential benefits of this technology for fall prevention. | This article supports my project proposal by showing the effectiveness of automated technologies in reducing fall incidences in healthcare. |
Shahzad, A., & Kim, K. IEEE Transactions on Industrial Informatics, https://doi.org/10.1109/TII.2018.2839749 | FallDroid: An Automated Smart-Phone-Based Fall Detection System Using Multiple Kernel Learning. 2019 | The aim of this study was to examine the effectiveness of FallDropid system in monitoring and detecting fall events among patients at risk. | Quantitative | Two user trials carried out in a laboratory setting and week-long monitoring of the application in real-world scenarios. The trials involved 20 participants | The study was experimental in nature. The first experiment utilized young volunteers in a simulated environment in a laboratory setting. The second phase entailed the analysis of system performance in real-world scenarios to determine false alarm rate and system accuracy in fall detection and prevention. | Data on weight, height, and ability to perform scripted fall-like activities of daily living were performed in a simulated environment. The systems analyzed the different types of falls that elderly people experience such as forward, lateral, backwards, vertical, and syncope. | The researchers found that FallDrop system had an accuracy of 97.8% and 91.7%, sensitivity of 99.5% and 95.8%, and specificity of 95.2% and 88.0%. It also had the lowest alarm rate of 1 alarm per 59 hours of usage. These findings demonstrate that the system is highly efficient and effective in fall detection and prevention. | The researchers recommended the practical adoption of the system to determine its effectiveness in real-life scenarios in detecting and preventing falls among the elderly. | This article supports the proposed project by demonstrating the accuracy, sensitivity, and specificity of automated systems in fall detection and prevention. |
Usmani, S., Saboor, A., Haris, M., Khan, M. A., & Park, H. Sensors, https://doi.org/10.3390/s21155134 | Latest Research Trends in Fall Detection and Prevention Using Machine Learning: A Systematic Review. 2021 | The aim of this research was to examine latest research trends in fall detection and prevention systems using machine learning | Quantitative. It was a systematic review | Review of the existing literature on fall detection and prevention systems obtained from 33 articles | Data from the selected articles was extracted with a focus on fall detection and prevention systems, frequently used systems, trends in fall detection and prevention systems, and performance parameters. | The data was extracted and analyzed thematically to identify the common intersections on the effectiveness of fall detection and prevention systems. | Fall detection and prevention systems have a high accuracy. The accuracy ranges from 86% to 100% in fall detection and prevention. | The researchers recommended the inclusion of fall detection and prevention systems in the care of patients at risk of falls. They also recommended future studies to focus on aspects such as randomization to increase the reliability of evidence on the use of technology for fall detection and prevention. | This article supports my project proposal by showing the enhanced accuracy associated with automated technologies in fall detection and prevention. |
Wilmink, G., Dupey, K., Alkire, S., Grote, J., Zobel, G., Fillit, H. M., & Movva, S. JMIR Aging, https://doi.org/10.2196/19554 | Artificial Intelligence–Powered Digital Health Platform and Wearable Devices Improve Outcomes for Older Adults in Assisted Living Communities: Pilot Intervention Study. 2020 | The goal of this study was to analyze the ways in which artificial intelligence-powered digital health and wearable platforms improve health outcomes for older adults in assisted living communities. | Quantitative. It was a pilot study | 490 residents from six assisted living communities | Data for the participants were analyzed retrospectively for 24 months. The participants in the intervention group utilized CarePredict while those in control did not utilize it. Measures of focus included fall rate, hospitalization rate, staff response time, and length of stay. | The data for this study were collected and reported by staff in each facility using community’s online electronic healthcare software platform. They extracted anonymized data for scientific evaluation. | The use of artificial intelligence-powered digital health platform and wearable devices led to a reduction in hospitalization rate by 39%, fall rate by 69%, and length of hospital stay by 67%. The system also increased alert acknowledgement and reach resident times. | The researchers recommended the incorporation of the system and wearable devices into elderly care to enable early detection and prevention of mobility issues such as falls. | The article supports my proposed project by showing that automated technologies and systems improve fall detection and rates in healthcare. |
References
Coahran, M., Hillier, L. M., Van Bussel, L., Black, E., Churchyard, R., Gutmanis, I., Ioannou, Y., Michael, K., Ross, T., & Mihailidis, A. (2018). Automated Fall Detection Technology in Inpatient Geriatric Psychiatry: Nurses’ Perceptions and Lessons Learned. Canadian Journal on Aging = La Revue Canadienne Du Vieillissement, 37(3), 245–260. https://doi.org/10.1017/S0714980818000181
Gaspar, A. G. M., & Lapão, L. V. (2021). eHealth for Addressing Balance Disorders in the Elderly: Systematic Review. Journal of Medical Internet Research, 23(4), e22215. https://doi.org/10.2196/22215
Joshi, M., Archer, S., Morbi, A., Ashrafian, H., Arora, S., Khan, S., Cooke, G., & Darzi, A. (2022). Perceptions on the Use of Wearable Sensors and Continuous Monitoring in Surgical Patients: Interview Study Among Surgical Staff. JMIR Formative Research, 6(2), e27866. https://doi.org/10.2196/27866
Maneeprom, N., Taneepanichskul, S., Panza, A., & Suputtitada, A. (2019). Effectiveness of robotics fall prevention program among elderly in senior housings, Bangkok, Thailand: A quasi-experimental study. Clinical Interventions in Aging, 14, 335–346. https://doi.org/10.2147/CIA.S182336
Mulas, I., Putzu, V., Asoni, G., Viale, D., Mameli, I., & Pau, M. (2021). Clinical assessment of gait and functional mobility in Italian healthy and cognitively impaired older persons using wearable inertial sensors. Aging Clinical and Experimental Research, 33(7), 1853–1864. https://doi.org/10.1007/s40520-020-01715-9
Saod, A. H. M., Mustafa, A. A., Soh, Z. H. C., Ramlan, S. A., & Harron, N. A. (2021). Fall Detection System Using Wearable Sensors with Automated Notification. 2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE), 182–187. https://doi.org/10.1109/ICCSCE52189.2021.9530983
Seow, J. P., Chua, T. L., Aloweni, F., Lim, S. H., & Ang, S. Y. (2022). Effectiveness of an integrated three-mode bed exit alarm system in reducing inpatient falls within an acute care setting. Japan Journal of Nursing Science, 19(1), e12446. https://doi.org/10.1111/jjns.12446
Shahzad, A., & Kim, K. (2019). FallDroid: An Automated Smart-Phone-Based Fall Detection System Using Multiple Kernel Learning. IEEE Transactions on Industrial Informatics, 15(1), 35–44. https://doi.org/10.1109/TII.2018.2839749
Usmani, S., Saboor, A., Haris, M., Khan, M. A., & Park, H. (2021). Latest Research Trends in Fall Detection and Prevention Using Machine Learning: A Systematic Review. Sensors, 21(15), Article 15. https://doi.org/10.3390/s21155134
Wilmink, G., Dupey, K., Alkire, S., Grote, J., Zobel, G., Fillit, H. M., & Movva, S. (2020). Artificial Intelligence–Powered Digital Health Platform and Wearable Devices Improve Outcomes for Older Adults in Assisted Living Communities: Pilot Intervention Study. JMIR Aging, 3(2), e19554. https://doi.org/10.2196/19554