[ANSWERED 2023] Submit a summary of six of your articles on the discussion board. Discuss one strength and one weakness to each of these six articles

Expert Answer and Explanation

Evaluation Methods

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.

References

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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FAQs

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:

1. Formulating research questions: This involves defining the research questions to be answered by the evaluation and the outcomes that will be measured.
2. Conducting a literature review: This refers to reviewing the existing research literature to identify the best available evidence on the effectiveness of similar interventions.
3. Selecting appropriate research designs: This entails selecting appropriate research designs, such as randomized controlled trials or quasi-experimental designs, to answer the research questions.
4. 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.
5. 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:

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.

1. 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.
2. 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.
3. 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.
4. 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.

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.

1. 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.
2. 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.
3. 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.
4. 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.

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