Submit a summary of six of your articles on the discussion board. Discuss one strength and one weakness to each of these six articles on
Topic 3 DQ 1
Submit a summary of six of your articles on the discussion board. Discuss one strength and one weakness to each of these six articles on why the article may or may not provide sufficient evidence for your practice change
Expert Answer and Explanation
Article one: Booth, V., Logan, P., Harwood, R., & Hood, V. (2015). Falls prevention interventions in older adults with cognitive impairment: a systematic review of reviews. International Journal of Therapy and Rehabilitation, 22(6), 289-296. DOI: http://dx.doi.org/10.12968/ijtr.2015.22.6.289
Summary: “This critical review explores the review material on falls prevention interventions in older adults with a cognitive impairment such as dementia (Booth et al., 2015).”
Strength: Credible and reliable databases were used to identify articles to be used as sample populations of the study.
Weakness: The article did not highlight the actual number of articles included.
Article two: Dykeman, C. S., Markle-Reid, M. F., Boratto, L. J., Bowes, C., Gagné, H., McGugan, J. L., & Orr-Shaw, S. (2018). Community service provider perceptions of implementing older adult fall prevention in Ontario, Canada: a qualitative study. BMC geriatrics, 18(1), 34. https://link.springer.com/article/10.1186/s12877-018-0725-3
Summary: “This study aimed to describe the perceived barriers to and effective strategies for the implementation of evidence-based fall prevention practices within and across diverse community organizations.”
Strength: The article used interview instruments, a method that allowed the scholars to effectively collect data.
Weakness: The response rate of the participants was fairly low.
Article three: Elliott, S., & Leland, N. E. (2018). Occupational therapy fall prevention interventions for community-dwelling older adults: A systematic review. American Journal of Occupational Therapy, 72,7204190040. https://doi.org/10.5014/ajot.2018.030494
Summary: The article aimed to investigate fall prevention strategies among older people in a community setup.
Strength: The article employed proper inclusion and exclusion criteria, a practice that allowed the scholars to access vital sources.
Weakness: The originality of the articles used is questioning.
Article four: Peach, T., Pollock, K., van der Wardt, V., das Nair, R., Logan, P., & Harwood, R. H. (2017). Attitudes of older people with mild dementia and mild cognitive impairment and their relatives about falls risk and prevention: A qualitative study. PLoS One, 12(5). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5438143/
Summary: The article investigates patients’ views about falls.
Strength: The article has used the best methods for data collection, analysis, and sampling. Thematic analysis was used to conduct the study.
Weakness: The study recorded self-reported bias and this affected the credibility of its findings a some point.
Article five: Womack, J. A., Novick, G., & Fried, T. (2018). The beginning of the end: A qualitative study of falls among HIV+ individuals. PLoS one, 13(11). Retrieved from https://journals.plos.org/plosone/article/file?type=printable&id=10.1371/journal.pone.0207006
Summary: “The purpose of this study was to understand perceptions of HIV+ individuals who had fallen regarding what caused their falls, prevention strategies that they used, and the impact of falls on their lives.”
Strength: The response rate of the study was high. More than 95% of the participants responded .
Weakness: However, the sample population used cannot be generalized to a larger group.
Article six: Howland J, Hackman H, Taylor A, O’Hara K, Liu J, Brusch J (2018) Older adult fall prevention practices among primary care providers at accountable care organizations: A pilot study. PLoS ONE 13(10): e0205279. https://doi.org/10.1371/journal.pone.0205279
Summary: The article investigated the best practices that can be applied by primary care providers at accountable care organizations to reduce the incidences of falls among adult populations.
Strength: The article realized a high response rate. The authors note that 73% of the participants responded to the questionnaires distributed.
Weakness: The authors did not analyze the sample population quite well.
Booth, V., Logan, P., Harwood, R., & Hood, V. (2015). Falls prevention interventions in older adults with cognitive impairment: a systematic review of reviews. International Journal of Therapy and Rehabilitation, 22(6), 289-296. DOI: http://dx.doi.org/10.12968/ijtr.2015.22.6.289
Dykeman, C. S., Markle-Reid, M. F., Boratto, L. J., Bowes, C., Gagné, H., McGugan, J. L., & Orr-Shaw, S. (2018). Community service provider perceptions of implementing older adult fall prevention in Ontario, Canada: a qualitative study. BMC geriatrics, 18(1), 34. https://link.springer.com/article/10.1186/s12877-018-0725-3
Elliott, S., & Leland, N. E. (2018). Occupational therapy fall prevention interventions for community-dwelling older adults: A systematic review. American Journal of Occupational Therapy, 72,7204190040. https://doi.org/10.5014/ajot.2018.030494Peach, T., Pollock, K., van der Wardt, V., das Nair, R., Logan, P., & Harwood, R. H. (2017). Attitudes of older people with mild dementia and mild cognitive impairment and their relatives about falls risk and prevention: A qualitative study. PLoS One, 12(5). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5438143/
Howland J, Hackman H, Taylor A, O’Hara K, Liu J, Brusch J (2018) Older adult fall prevention practices among primary care providers at accountable care organizations: A pilot study. PLoS ONE 13(10): e0205279. https://doi.org/10.1371/journal.pone.0205279
Peach, T., Pollock, K., van der Wardt, V., das Nair, R., Logan, P., & Harwood, R. H. (2017). Attitudes of older people with mild dementia and mild cognitive impairment and their relatives about falls risk and prevention: A qualitative study. PLoS One, 12(5). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5438143/
Womack, J. A., Novick, G., & Fried, T. (2018). The beginning of the end: A qualitative study of falls among HIV+ individuals. PLoS one, 13(11). Retrieved from https://journals.plos.org/plosone/article/file?type=printable&id=10.1371/journal.pone.0207006
Alternative Answer 2:
Summary of Six Articles
Tawfik et al. (2018) concluded in their article that medical errors are associated with fatigue and physician burnout. The strength of this article is that it has highlighted all the limitations and followed the ethical considerations in research. However, the statistical analysis was too simple, and this tampered with the accuracy of the results.
Rahman et al. (2019) found that poor quality sleep is among the factors that can lead to medical errors. The authors concluded that medical errors could be reduced by ensuring that physicians have a quality sleep. The weakness of the study is that there were inadequate controls. However, they followed all ethical considerations.
Lawson et al. (2018) mentioned that nurse burnout could not lead to medical errors. The authors gave sufficient data to support the argument. However, they did not say the limitations of the study.
Davis-Coan et al. (2016) found that developing nurses was one of the ways to reduce medical errors within hospitals. The strength of this study is that the authors collected adequate data. However, the controls were not sufficient.
According to AbuMustafa and Jaber (2019) concluded in their study that medical errors can be caused by work pressure and inadequate medical staff. They recommend that the issue can be solved by creating a healthy working environment. The strength of the study is that it used quality methodology. However, the population cannot be used to generalize the study results.
Pereira-Lima et al. (2019), on the other hand, concluded that depressive doctors could cause medical errors. Reliable databases were used to collect data. However, the study did not mention any limitations recorded.
AbuMustafa, A. M., & Jaber, M. (2019). Factor affecting Medical errors Reporting among medical team in Pediatric Hospitals in Gaza governorate. Journal of Medical Research and Health Sciences, 2(11), 794-801. http://jmrhs.info/index.php/jmrhs/article/view/131
Davis-Coan, C., Crawford, K., Lynch, T., Davis, R., Miller, T., & Santoro, T. J. (2016). OSF Saint Francis Medical Center and University of Illinois College of Medicine, Peoria, ILRates of Medical Errors and Adverse Events in a Medical ICU Following Implementation of a Standardized Computerized Handoff System. Ochsner Journal, 16(Spec AIAMC Iss), 38-39. http://www.ochsnerjournal.org/content/16/Spec_AIAMC_Iss/38.abstract
Lawson, N. D., Shanafelt, T. D., Tawfik, D. S., Morgenthaler, T. I., Satele, D. V., Sinsky, C., … & West, C. P. (2018, November). Burnout is Not Associated With Increased Medical Errors/In Reply. In Mayo Clinic Proceedings (Vol. 93, No. 11, pp. 1683-1684). Mayo Foundation for Medical Education and Research. DOI:10.1016/j.mayocp.2018.08.015
Pereira-Lima, K., Mata, D. A., Loureiro, S. R., Crippa, J. A., Bolsoni, L. M., & Sen, S. (2019). Association Between Physician Depressive Symptoms and Medical Errors: A Systematic Review and Meta-analysis. JAMA network open, 2(11), e1916097-e1916097. https://jamanetwork.com/journals/jamanetworkopen/article-abstract/2755851
Rahman, S. A., Sullivan, J. P., Barger, L. K., Hilaire, M. A. S., Stone, K. L., O’Brien, C. S., … & Wright, K. P. (2019). 0969 Attentional Failures Are Correlated With Serious Medical Errors In Resident Physicians. Sleep, 42(Supplement_1), A390-A390. https://doi.org/10.1093/sleep/zsz067.967
Tawfik, D. S., Profit, J., Morgenthaler, T. I., Satele, D. V., Sinsky, C. A., Dyrbye, L. N., … & Shanafelt, T. D. (2018, November). Physician burnout, well-being, and work unit safety grades in relationship to reported medical errors. In Mayo Clinic Proceedings (Vol. 93, No. 11, pp. 1571-1580). Elsevier. https://doi.org/10.1016/j.mayocp.2018.05.014
Topic 3 DQ 2
Name two different methods for evaluating evidence. Compare and contrast these two methods
Expert Answer and Explanation
Surveys and interviews will be used to evaluate the evidence. The survey is an evaluation method where one can evaluate the evidence by collecting outcome measures data. Järvelin and Kekäläinen (2017) mention surveys can be used to collect both qualitative and quantitative data through free-response or open-ended questions.
Checklists and questionnaires can be used to collect data through surveys. Through interviews, one can evaluate evidence by coding observations or interview responses. J. Phillips and P. Phillips (2016) define interview as a process of structuring questions in a systemic manner and providing interviewees space to answer the questions.
In this method, the participants will be required to answer documented questions. The similarity between these methods is that they can both be used to evaluate goal, outcome, and process-based measures. Also, the two approaches can help the researcher relate more with the participants in the study. They are both easy to analyze and administer.
The difference between the methods includes the following. First, surveys can allow the researcher to cover many topics in a short time. However, interviews need a lot of time, and thus the author may fail to tackle other relevant topics. Another difference is that surveys are done through questionnaires and checklists (J. Phillips & P. Phillips, 2016).
However, interviews are done face-to-face. The researcher is required to visit the participants personally or conduct the process through online applications. Moreover, interviews and surveys are different in that surveys need less time to complete compared to interviews. For instance, a researcher can develop a series of questionnaires and distribute them to the subjects in a short time. However, interviews require the researcher to meet the participants one by one. Lastly, a researcher can cover a large population using questionnaires compared to interviews.
Phillips, J. J., & Phillips, P. P. (2016). Handbook of training evaluation and measurement methods. Routledge.
Järvelin, K., & Kekäläinen, J. (2017, August). IR evaluation methods for retrieving highly relevant documents. In ACM SIGIR Forum (Vol. 51, No. 2, pp. 243-250). New York, NY, USA: ACM. https://doi.org/10.1145/3130348.3130374
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What is evidence based evaluation?
Evidence-based evaluation entails assessing the effectiveness of programs, policies, or interventions based on the best available evidence. The goal of evidence-based evaluation is to provide an objective and comprehensive assessment of the impact of a particular intervention or program on the target population.
The process of evidence-based evaluation typically involves the following steps:
- Formulating research questions: This involves defining the research questions to be answered by the evaluation and the outcomes that will be measured.
- Conducting a literature review: This refers to reviewing the existing research literature to identify the best available evidence on the effectiveness of similar interventions.
- Selecting appropriate research designs: This entails selecting appropriate research designs, such as randomized controlled trials or quasi-experimental designs, to answer the research questions.
- Collecting and analyzing data: This is basically collecting data on the program or intervention and analyzing the data to determine the effectiveness of the program or intervention.
- Drawing conclusions: This involves drawing conclusions based on the evidence gathered and making recommendations for future programs or interventions.
Evidence-based evaluation is a rigorous and systematic approach to evaluating the effectiveness of programs or interventions that can help to ensure that resources are used effectively and efficiently to achieve desired outcomes.
How to evaluate evidence in research
Evaluating evidence in research entails critically assessing the quality, relevance, and validity of the evidence to determine its reliability and usefulness in informing decisions. Here are some steps that can be taken to evaluate evidence in research:
- Assess the study design: The study design used in the research can have a significant impact on the quality of the evidence. Randomized controlled trials (RCTs) are generally considered the gold standard for evaluating the effectiveness of interventions, while observational studies may be more appropriate for investigating associations or risk factors.
- Evaluate the sample size: The sample size of a study can affect the reliability of the results. Studies with larger sample sizes are generally more reliable and have greater statistical power.
- Look at the quality of data collection: The quality of data collection methods used in the study can affect the accuracy and reliability of the evidence. The use of standardized and validated measures can increase the quality of data.
- Assess the statistical analysis: The statistical analysis used to analyze the data can have an impact on the validity of the findings. The use of appropriate statistical methods and tests can increase the validity of the findings.
- Consider the generalizability of the findings: The generalizability of the findings can depend on the characteristics of the study population and the setting in which the study was conducted. The findings may not be applicable to other populations or settings.
- Look for potential biases: Bias in research can affect the validity and reliability of the evidence. Common sources of bias include selection bias, measurement bias, and confounding.
- Evaluate the strength of the evidence: The strength of the evidence can be evaluated using a hierarchy of evidence that takes into account the study design, sample size, quality of data collection, statistical analysis, and potential biases.
Assessing evidence in research requires a critical and systematic approach to assessing the quality and relevance of the evidence. By doing so, it is possible to identify reliable and useful evidence that can inform decision-making.
Model used to evaluate level of research
There are several models that can be used to evaluate the level or quality of research. One commonly used model is the evidence hierarchy, which is often depicted as a pyramid. The evidence hierarchy is a way of ranking different types of research evidence based on their level of validity and reliability, with the highest quality evidence at the top of the pyramid. The evidence hierarchy is typically organized as follows, from highest to lowest quality of evidence:
- Systematic reviews and meta-analyses of randomized controlled trials (RCTs): These are considered the highest level of evidence because they involve a comprehensive and systematic review of multiple RCTs.
- Individual RCTs: These studies involve a comparison of an intervention to a control group in which participants are randomly assigned to the intervention or control group.
- Non-randomized studies: These include observational studies, such as cohort studies or case-control studies, which are less reliable than RCTs because they do not involve randomization.
- Case studies and case reports: These provide individual accounts of a specific patient or event, but do not involve comparison groups and therefore cannot provide strong evidence for causality.
The evidence hierarchy model is widely used to assess the level of evidence in healthcare research, but it can also be applied to research in other fields. However, it is important to note that the evidence hierarchy model is just one way of evaluating the quality of research evidence and should be used in combination with other methods, such as critical appraisal of individual studies and consideration of the broader context of the research question.
Melnyk levels of evidence
The Melnyk levels of evidence is a framework for categorizing different types of research evidence based on their strength and quality. This framework was developed by Dr. Bernadette Melnyk, a nurse researcher and expert in evidence-based practice. The Melnyk levels of evidence include the following:
Level I: Evidence from systematic reviews or meta-analyses of randomized controlled trials (RCTs)
Level II: Evidence from well-designed RCTs
Level III: Evidence from quasi-experimental studies
Level IV: Evidence from non-experimental studies, such as cohort or case-control studies
Level V: Evidence from systematic reviews of descriptive and qualitative studies
Level VI: Evidence from a single descriptive or qualitative study
Level VII: Evidence from the opinion of authorities or expert committees
The Melnyk levels of evidence are similar to the evidence hierarchy described in my previous response, but they include additional levels for qualitative and expert opinion evidence. The framework is commonly used in healthcare research and is often used to guide the development of evidence-based practice guidelines and decision-making. However, it is important to note that the quality of evidence within each level can vary widely and that the level of evidence alone should not be the sole determinant of decision-making. It is important to consider the quality and relevance of the evidence in relation to the specific clinical or research question at hand.
When is evidence too old
The relevance of evidence depends on the specific context in which it is being applied, as well as the quality and nature of the evidence itself. While there is no universally agreed upon definition of when evidence is too old, there are some factors to consider when evaluating the relevance of older evidence, such as:
- The rate of change in the field: Some fields, such as medicine and technology, are constantly evolving, and evidence that is just a few years old may be outdated in the face of new discoveries and advancements. In contrast, fields such as mathematics and philosophy may have evidence that is still relevant and applicable even after many years.
- The nature of the research question: Some research questions require more up-to-date evidence than others. For example, if the research question pertains to a current public health crisis, such as COVID-19, then recent evidence is likely to be more relevant than evidence from a decade ago.
- The quality of the evidence: Even if evidence is old, it may still be relevant if it is of high quality and has been replicated or supported by subsequent research. Conversely, more recent evidence may be less relevant if it is of low quality or has not been rigorously tested.
- The availability of newer evidence: Even if older evidence is still relevant, it may be worthwhile to seek out more recent evidence that can add to or enhance the understanding of the topic at hand.
Ultimately, the decision of when evidence is too old depends on a careful evaluation of the research question and the available evidence. It is important to use critical thinking and judgement when evaluating evidence, and to consider a variety of factors beyond just the age of the evidence.