Assignment week 5 review

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Assignment in Word document. Power points are attached 

The purpose of the assignment is to compare and contrast integrative reviews and systematic reviews. After reviewing the chapters and PowerPoints for this week, please pick a topic and compare and contrast what the possible pros and cons are of an integrative review compared with a systematic review for that topic. You can dig deeper and find actual published work regarding your topic or use the review examples in Box 11.4

Please submit a summary of your findings (approximately 250 words). Include a title page and reference page in APA style. These do not count towards the minimum word count for this assignment. Use the appropriate APA style in-text citations and references for all resources utilized to answer the questions.

Chapter 11

Systematic Reviews and Clinical Practice Guidelines

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  • Systematic review is the summation and assessment of research studies found in the literature based on a clearly focused question that uses systematic and explicit methods to identify, select, critically appraise, and analyze relevant data from the selected studies to summarize the findings in a focused area.

Systematic Review

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  • A review of studies using statistical methods
  • Statistically analyzes and integrates the results of many studies
  • Provides level I evidence, the highest level of evidence

Meta-Analysis

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  • Critically appraises the literature in an area, but without a statistical analysis
  • Broadest category of review

Integrative Review

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  • Summary of the quantitative research literature that used similar designs based on a focused clinical question
  • Brings together all the studies concerning a focused clinical question and, using rigorous inclusion and exclusion criteria, assesses the strength and quality of the evidence provided by the chosen studies in relation to:
  • Sampling issues
  • Internal validity (bias) threats
  • External validity
  • Data analysis

Systematic Review

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  • Systematic summary using statistical techniques to assess and combine studies of the same design to obtain a precise estimate of effect
  • Statistically analyzes the data from each of the studies

Meta-Analysis

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  • Phase I: The data are extracted (i.e., outcome data, sample sizes, and measures of variability from the identified studies).
  • Phase II: The decision is made as to whether or not it is appropriate to calculate what is known as a pooled average result (effect) of the studies reviewed.

Phases of Meta-Analysis

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  • Effect sizes are calculated using the difference in the averages scores between the intervention and control groups from each study.
  • Thus, the effect size is an estimate of how large of a difference there is between intervention and control groups in the summarized studies.

Effect Size

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  • Sometimes called a “blobbogram”
  • Graphically depicts the results of analyzing a number of studies

Forest Plot

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Forest Plot (Cont.)

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  • Largest repository of meta-analyses.
  • Cochrane Collaboration is an international organization that prepares and maintains a body of systematic reviews that focus on health care interventions.

Cochrane Collaboration

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  • Critical reviews of an area of research without a statistical analysis or a theory synthesis
  • Broadest category of review
  • Can include theoretical literature, research literature, or both
  • Can include both quantitative or qualitative research

Integrative Review

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  • PRISMA (Preferred Reporting for Systematic Reviews and Meta-analyses)
  • MOOSE (Meta-analysis of Observational Studies in Epidemiology

Reporting Guidelines: Systematic Reviews and Meta-Analysis

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  • The Center for Evidence Based Medicine (CEBM)
  • Questions
  • Does this study address a clearly focused question?
  • Did the study use valid methods to address the question
  • Are the valid results of the study important?
  • Are these valid, important results applicable to my patient or population?

Tools for Evaluating Individual Studies

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  • Systematically developed statements or recommendations that link research and practice and serve as a guide for practitioners.
  • Guidelines are developed by professional organizations, government agencies, institutions, or convened expert panels.
  • Guidelines provide clinicians with an algorithm for clinical management, or decision making for specific diseases.

Clinical Practice Guidelines

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  • Evidence-based practice guidelines are developed using a scientific process.
  • Expert-based guidelines: agreement of a group of nationally known experts in the field who meet and solely use opinions of experts along with whatever research evidence is developed to date.

Clinical Practice Guidelines (Cont.)

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  • National organizations develop clinical practice guidelines
  • Appraisal of Guidelines Research and Evaluation II (AGREE II)—one of the most widely used to evaluate the applicability of a guideline to practice

Evaluating Clinical Practice Guidelines

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  • AGREE II—Developed to assist in evaluating guideline quality, provide a methodological strategy for guideline development, and inform practitioners about what information should be reported in guidelines and how it should be reported.

Evaluating Clinical Practice Guidelines (Cont.)

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  • Does the PICO question used as the basis of the review match the studies included in the review?
  • Are the review methods clearly stated and comprehensive?
  • Are the dates of the review’s inclusion clear and relevant to the area reviewed?
  • Are the inclusion and exclusion criteria for studies in the review clear and comprehensive?
  • What criteria were used to assess each of the studies in the review for quality and scientific merit?
  • If studies were analyzed individually were the data clear?
  • Were the methods of study combination clear and appropriate?
  • If the studies were reviewed collectively, how large was the effect?
  • Are the clinical conclusions drawn from the studies relevant and supported by the review?

Critiquing Criteria—Systematic Reviews

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  • Is the date of publication or release current?
  • Are the authors of the guideline clear and appropriate to the guideline?
  • Is there a clinical problem and purpose clear in terms of what the guideline covers and patient groups for which it was designed?
  • What types of evidence (research, nonresearch) were used in formulating the guideline and were they appropriate to the topic?
  • Is there a description of the methods used to grade the evidence?
  • Were the search terms and retrieval methods used to acquire research and nonresearch evidence used in the guideline clear and relevant?
  • Is the guideline well referenced and comprehensive?
  • Are the recommendations in the guideline sourced according to the level of evidence for its basis?
  • Has the guideline been reviewed by experts in the area?
  • Who funded the guideline development?

Critiquing Guidelines—Systematic Reviews

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Human subjects

Pretest and posttest design

Statistical methods

Qualitative analysis

The only review type that can be labeled meta-analysis is one that reviewed studies using what?

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Answer: C

Rationale: The only review type that can be labeled a meta-analysis is one that reviewed studies using statistical methods.

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Level I

Level II

Level III

Level IV

Meta-analysis provides which level of evidence?

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Answer: A

Rationale: Meta-analysis provides Level I evidence, the highest level of evidence as it statistically analyzes and integrates the results of many studies.

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A systematic review:

is summary of the qualitative research literature

summarizes studies with different designs

provides an analysis of the studies

reports the most current and valid research on intervention effectiveness

Which statement about systematic review does the nurse identify as being true?

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Answer: D

Rationale: A systematic review is a summary of the quantitative research literature that used similar designs based on a focused clinical question. The goal is to bring together all of the studies concerning a focused clinical question and, using rigorous inclusion and exclusion criteria, assess the strength and quality of the evidence provided by the chosen studies.

The purpose is to report, in a consolidated fashion, the most current and valid research on intervention effectiveness and clinical knowledge, which will ultimately inform evidence-based decision making about the applicability of findings to clinical practice.

The components of a systematic review are the same as a meta-analysis except for the analysis of the studies.

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AGREE II Guideline

Cochrane Collaboration/Review

National Institutes of Health

Centers for Disease Control and Prevention

The largest repository of meta-analyses is what?

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Answer: B

Rationale: The largest repository of meta-analyses is the Cochrane Collaboration/Review.

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Chapter 12

Sampling

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  • Process of selecting representative units of a population for study in a research investigation
  • Usually found in the methods section

Sampling

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  • Population
  • Well-defined set with specific properties
  • May be humans, medical records, specimens

Sampling Concepts

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  • Target population
  • The entire set of cases about which the researcher would like to make generalizations

Sampling Concepts (Cont.)

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  • Accessible population
  • Available population that meets the criteria

Sampling Concepts (Cont.)

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  • Inclusion and exclusion criteria
  • Inclusion criteria, also called eligibility criteria
  • Exclusion criteria, also called delimitations

Sampling Concepts (Cont.)

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  • Inclusion and exclusion criteria
  • Determine the subjects used in a study by defining the criteria used to include or exclude a subject from a study
  • Must be explained by the researcher
  • Control for extraneous variables or bias

Sampling Concepts (Cont.)

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  • Sampling: the process of selecting a portion or subset of the designated population
  • Sample: a set of elements that make up the population

Samples and Sampling

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  • Element: the most basic unit about which information is collected
  • In nursing research, “elements” are usually individuals.

Samples and Sampling (Cont.)

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  • Purpose: to be more efficient; it is not cost-effective, or even feasible, to study an entire population
  • Should be representative; a representative sample has the same key characteristics as the entire population

Samples and Sampling (Cont.)

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Types of Sampling

  • Nonprobability
  • Inclusion in a group is NOT random
  • Less generalizable
  • Less representative
  • Three types:
  • Convenience
  • Quota
  • Purposive
  • Probability sampling
  • Uses randomization to assign elements
  • More generalizable
  • More representative
  • Three types:
  • Simple random sampling
  • Stratified random sampling
  • Cluster sampling

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  • Convenience
  • Use of the most readily accessible persons or objects as subjects in a study
  • Easy to recruit subjects
  • Risk of bias greatest in this type of sample
  • Used most with quantitative nonexperimental or qualitative studies

Nonprobability Sampling

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  • Quota
  • Knowledge about characteristics of the population of interest used to build representativeness into the sample
  • Identifies the strata of the population and proportionally represents the strata in the sample

Nonprobability Sampling (Cont.)

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  • Purposive
  • Subjects selected who are considered to be typical of the population
  • Useful in studying populations with unusual/rare characteristics
  • Assumes that errors of judgment in overrepresenting or underrepresenting characteristics of the population in the sample will tend to balance out

Nonprobability Sampling (Cont.)

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  • Network sampling (Snowballing)—used for locating samples that are difficult or impossible to locate in other ways
  • Use of social networks

Nonprobability Sampling (Cont.)

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  • Critiquing convenience samples
  • What motivated some of the people to participate and others not to participate (self-selection)?
  • What kind of data would have been obtained if nonparticipants had also responded?

Nonprobability Sampling (Cont.)

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  • Critiquing convenience samples
  • How representative are the people who did participate in relation to the population?
  • What kind of confidence can you have in the evidence provided by the findings?

Nonprobability Sampling (Cont.)

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  • Uses random selection
  • Each element of the population has an equal and independent chance of being included in the sample.
  • Strongest type of sampling strategy
  • Used in experimental and quasi-experimental studies

Probability Sampling

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  • Simple random sampling
  • Researcher defines the population (a set), lists all the units of the population (a sampling frame), and selects a sample of units (a subset) from which the sample will be chosen.

Probability Sampling (Cont.)

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  • Advantages: simple random sampling
  • Sample selection is not subject to conscious biases.
  • Representativeness of the sample is maximized.

Probability Sampling (Cont.)

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  • Advantages: simple random sampling
  • Differences in the characteristics of the sample and the population are purely a function of chance.
  • Probability of choosing a nonrepresentative sample decreases as the size of the sample increases.

Probability Sampling (Cont.)

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  • Disadvantages: simple random sampling
  • Time consuming and usually inefficient method of obtaining a random sample

Probability Sampling (Cont.)

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  • Stratified random sampling
  • Population divided into homogeneous strata or subgroups
  • Allows more representativeness

Probability Sampling (Cont.)

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Probability Sampling (Cont.)

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  • Advantages: stratified random sampling
  • Enhanced representativeness of the sample
  • Makes comparisons among subsets
  • Disproportionately small stratum oversampled to adjust for underrepresentation

Probability Sampling (Cont.)

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  • Disadvantages: stratified random sampling
  • It is difficult to obtain a population list containing complete critical variable information.
  • It is time consuming.
  • Enrolling proportional strata is challenging.
  • A large-scale study is costly and takes time.

Probability Sampling (Cont.)

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  • Multistage (cluster) sampling
  • A successive random sampling of units (clusters) that progress from large to small
  • Sampling units or clusters that can be selected by simple random or stratified random sampling methods

Probability Sampling (Cont.)

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  • Multistage (cluster) sampling
  • Advantages
  • More economical in terms of time and money
  • Disadvantages
  • More sampling errors tend to occur than with simple random or stratified random sampling.
  • Appropriate handling of the statistical data from cluster samples is complex.

Probability Sampling (Cont.)

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Sampling Strategies

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  • Largest sample size possible
  • Data saturation
  • Pilot study

Sample Size

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  • Have the sample characteristics been completely described?
  • Can the parameters of the study population be inferred from the description of the sample?

Sampling Critiquing Criteria

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  • To what extent is the sample representative of the population?
  • Are the criteria eligibility in the sample specifically identified?
  • Have sample delimitations been established?

Sampling Critiquing Criteria (Cont.)

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  • Would it be possible to replicate the study population?
  • How was the sample selected? Is the method of sample selection appropriate?
  • What kind of bias, if any, is introduced by this method?

Sampling Critiquing Criteria (Cont.)

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  • Is the sample size appropriate? How is it substantiated?
  • Are there indications that rights of subjects have been ensured?
  • Does the researcher identify the limitations in generalizability of the findings?

Sampling Critiquing Criteria (Cont.)

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  • Is the sampling strategy appropriate for the design and level of evidence provided by the design?
  • Does the researcher indicate how replication of the study with other samples would provide increased support for the findings?

Sampling Critiquing Criteria (Cont.)

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When calculating sample size using power analysis, the total sample size needs to consider that attrition or dropouts will occur.

10%

15%

25%

30%

Approximately what percent of extra subjects are needed to ensure the ability to detect differences between groups or that the effect of an intervention remains intact?

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ANSWER: B

RATIONALE: When calculating sample size using power analysis, the total sample size needs to consider that attrition, or dropouts, will occur and build in approximately 15% extra subjects to make sure that the ability to detect differences between groups or the effect of an intervention remains intact. When expected differences are large, it does not take a very large sample to ensure that differences will be revealed through statistical analysis. When an appropriate sample size, including power analysis for calculation of sample size and sampling strategy have been used, the researcher can feel more confident that the sample is representative of the accessible population rather than biased.

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50

68

112

480

To determine ethnic differences in cancer pain among four ethnic groups in the United States, what is the appropriate number of patients per ethnic group that should be used in the study?

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ANSWER: B

RATIONALE: Using power analysis, the researcher must estimate how large of a difference will be observed among the four ethnic groups (i.e., to test differences in cancer pain, symptoms accompanying pain, and functional status). If a moderate difference is expected, a conventional effect size of 0.20 is assumed. With a significance level of 0.05, a minimum of 68 participants per ethnic group would be needed to detect a statistically significant difference between the groups with a power of 0.80.

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When comprehensive results are desired

To increase generalizability of the findings

When the population size is very small

When the study is highly funded

When might an entire population be used in a research study?

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ANSWER: C

RATIONALE: When the population size is very small. The only time it makes sense to use an entire population is when the population is very narrowly identified and thus very small and accessible.

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Snowball sampling

Simple random sampling

Cluster sampling

Matching

What type of sampling includes using the Internet and social networking to locate samples that are otherwise difficult or impossible to locate?

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ANSWER: A

RATIONALE: Snowball sampling; networking sampling, sometimes referred to as snowballing, is a strategy used for locating samples that are difficult or impossible to locate in other ways.

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