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Systematic Reviews are rated as the ‘highest level of evidence’ in the evidence hierarchy pyramid.
The Cochrane Library is a database of systematic reviews and meta-‐analyses.
Using one database to search for information is best as this ensures you don’t mix your results.
PubMed only provides abstracts which are useful to then search for relevant studies elsewhere.
Common Boolean logic terms consist of AND, WITH & OR
There is no need to read the whole article because abstracts provide a complete summary of the content within.
Searching different databases with the same terms provides the same results.
Because they are often conducted with blinding, Randomised Control Trials (RCTs) provide the highest level of evidence. Because of this, using the filter to restrict results to only show RCTs provides you with the best evidence.
The use of the ‘OR’ operator narrows the amount of titles found.
‘Exploding’ a heading removes that heading from the search results.
MeSH terms are not always picked up when entered, so it is important to check and see that relevant items are being included.
PICO is the most reliable format for conducting a search as it highlights the keywords that can be entered into databases.
Before using a database, it is a good idea to research the terms to find possible synonyms.
The Cochrane Library provides access to Cochrane Systematics Reviews and to other forms of literature.
The library subscriptions provide access to more full text articles so logging in furthers your reach for finding good evidence.
Databases are a tool for finding information, but it is important to familiarise yourself with different databases to make searching as efficient as possible.
Using MeSH terms searches for like-terms and increases the chances that important research is captured.
Having a systematic approach to searching for evidence is a good way to ensure that you are not overwhelmed with information.
P values provide clinicians and patients with the information they most need.
Clinicians do not need to use confidence intervals to properly use research results in decision making processes.
Narrow Confidence intervals result from a large sample size and events which provide, a definitive conclusion about recommending therapy.
Statistical significance questions whether confidence intervals exclude the null value.
Statistical significance is used to inform clinical significance.
Treatments becomes clinically significant because the difference between treatments is statistically significant.
Clinical significance can be inferred from statistical significance if P value is ≥0.05
The P value measures the strength of the evidence that supports the null hypothesis.
Clinical significance asks whether any of the values in the confidence interval are big enough to care about
Huge samples create a more accurate P value.
P values are a tool for separating real effects from chance.
For studies with a negative result, clinicians should examine the lower boundary of the confidence interval.
To determine if the sample size in a study is inadequate, you examine the lower boundary of the confidence interval.
If the confidence interval overlaps the smallest treatment benefit, the study is not definitive and a larger study is needed.
P values ≤ 0.05 indicates strong evidence against the null hypothesis with 95% certainty.
P values ≥0.05 indicates strong evidence against the null hypothesis with 95% certainty.
Primary sources are the best source of information to use when conduction a search.
The PICO format is best technique used in evidenced based medicine to frame and answer for a clinical question.
Wikipedia is one of these best databases to use.
Combining searches is an effective way at finding relevant information to a clinical question.
When searching a database filters narrow the search to clinically important articles.
Databases allow you to choose which article types you want to search for.
When searching PubMed with a single term into the search box it automatically carries out both a textword and thesaurus search.
When having found a useful article in PubMed there is a related hyperlink that searches for similar items within the database.
Medline is the leading resource for systemic reviews.
The Cochrane library has a wide range of study types
The best way to search a database is to type in your complete question
When searching PubMed, the researcher must enter in all related terms as there is no textword or thesaurus search function
The P in PICO stands for population/patient.
Databases like PubMed, Medline and CINAHL allow you to search for studies within specific years.
A good literature search shouldn’t include unpublished work and studies with negative findings.
You only have to use 1 database when trying to answer a clinical question.
Confidence intervals are the range within which the true treatment effect might plausibly lie, when given the trial data.
In regards to confidence intervals, greater precision results from smaller sample sizes and small numbers of events.
When clinicians are trying to determine whether a trial with a positive effect is sufficiently large, they should focus on the upper boundary of the confidence interval.
A P value of equal to or less than 0.05 tells us that we can rule out the null effect/hypothesis with 95% certainty.
P values are not usually helpful for studies with large sample sizes.
Clinical significance asks whether any of the values in the confidence interval are big enough to care about.
Statistical significance can be inferred from clinical significance.
If the statistical power of a study is increased, the sample size is also increased.
The “Number-needed-to-treat” is an estimation of the number of patients that need to be treated in order to have an impact on one person.
Big sample sizes in trials means that small discrepancies will go undetected.
The Pearson correlation coefficient is a measure of strength of the association between 3 variables.
Differences in treatment groups less than the smallest effect of clinical interest are more like to be found statistically significant when the sample size is increased.
Is it important for clinicians to think about the smallest amount of benefit that would justify therapy when examining a new study?
In some cases, outcomes of a study and research may not be considered significant by the patients, especially if the new/changed intervention involves a considerable amount of time and effort on their behalf.
When calculating the sample size in clinical trials, the minimum power usually recommended to have is 70% or above.
Whenever an effect is insignificant, all values within the confidence interval will be on the same side of zero.
Case reports are high quality literature, according to most levels of evidence
It is not important for a researcher or clinician to know the difference between levels of evidence
Clinical trials are always the best type of study design in medical experiments
Exposure to confounding variables does not increase the potential risk of bias in a study design
Systematic reviews are often unreliable sources of information and should not be relied upon for clinical decision making
A researcher does not need to consider which study design is the most appropriate to answer their question when planning their investigation
Sources of evidence higher on the hierarchy of evidence usually only investigate small populations of patients for a particular outcome
Those sources higher up on the hierarchy of evidence are always superior to those below them
Levels of evidence are a method of grading literature quality
Debate exists about the rigidity of the hierarchy of evidence
Different levels of evidence are appropriate for use depending on the setting and intended audience involved
Each study design must be considered for its own strengths and weaknesses prior to selection
Several models exist for the hierarchy of evidence
Expert opinions are considered to be poorer quality evidence, according to most hierarchies
The design of a study affects its position on the hierarchy of evidence
The term 'levels of evidence' was first used and described within a 1979 report by the Canadian Health Task Force on Periodic Health Examination
CINAHL stands for ‘Cumulative Index to Nursing and Allied Health Literature’.
Systematic reviews and meta-analyses are the most reliable forms of evidence.
Randomised controlled trials are the best form of evidence in non-synthesised medical information.
Expert opinion has a lot of bias and is therefore located at the bottom of the hierarchy of evidence.
Studies that limit bias to a greater extent are considered to be better sources of evidence compared to those which don’t.
Randomised control trials aren't always practical or feasible.
A randomised control study in which participants and researchers are blinded gives a higher level of evidence and is a more reliable source.
Cochrane Reviews are systematic reviews of primary research in the health industry and are recognised as the highest standard and most reliable of sources in evidence-based health care resources.
Clinical trials and cohort studies are more reliable sources than expert opinion.
Double blinding lowers a sources evidence strength.
Randomising participants in a randomised control study makes the study less reliable as a source.
The levels of evidence hierarchy is very rigid and studies which are higher on the hierarchy are always better than those which are lower.
Meta-analyses tend to have more bias than cohort studies.
Meta-analyses tend to have more bias than case studies.
Study design has no effect on a studies’ evidence strength.
Expert opinion is the most reliable form of evidence.
There are more meta-analyses available than there are randomised control studies.
CINAHL stands for ‘ Cumulative Index to Nursing and Allied Health Literature’.
The ‘C’ term within ‘PICO’ stands for comparison.
The TRIP database has a ‘PICO’ search option, which allows users to create a structured clinical question.
To conduct a comprehensive search more than one database should be used.
The ‘wildcard’ symbol can be used to find words with the same stem in order to increase the scope of successful searching.
‘MeSH’ is an indexing feature that stands for Medical Subject Headings.
‘AND’, ‘ OR’ and ‘NOT’ are terms that should never be used while searching medical databases
It is often only necessary to use one database, as they are all linked and have the same results.
Cohort studies are rated as the ‘highest level of evidence’ in the evidence hierarchy pyramid.
Randomized Control Trials often provide unreliable evidence and should be overlooked when conducting searches.
It is always necessary to have a comparison when conducting a ‘PICO’ search.
Conducting a thorough search should only take around half an hour.
‘MeSH’ is the abbreviation for methanethiol and is irrelevant to the field of evidence-‐based medicine.
Online databases are updated infrequently and as a result textbooks are often more reliable when searching for examples.
The P in PICO stands for Patient.
In PICO the outcome is the end point of interest to you or your patient.
In PICO the comparison is the intervention against which the intervention is measured
A fifth element time is often added to the PICO list.
5. The strongest design for evaluation of a clinical question is a systematic review of multiple randomised clinical trials.
6. You can further filter your search by language, year, or age group.
7. Choosing the right key words and search strategy and using appropriate databases are essential starting points. 8. Advanced searching includes the use of the medical subject headings thesaurus and other strategies to refine and focus the search.
What matters to the practitioner are the most important outcomes.
PICO stands for Patient, Interaction, Comparison and Outcome.
PubMed is not a credible source when researching an article.
Using Mesh headings are irrelevant to the search strategy.
CINAHL is not useful when studying nursing as a prime database.
Having the same search strategy across databases is not necessary.
Endnote is a good database when looking for a systematic review.
When searching for a article filters are unnecessary and time consuming.
The database for nursing and allied health studies is called CINAHL.
The outcome in the ‘P I C O’ principle refers to patient-‐relevant consequences of the intervention.
The AND operator is used when you wish to recall those records containing both search terms.
The intervention in the ‘P I C O’ principle refers to the management strategy of interest.
Medical subject headings (MeSH terms) are a controlled vocabulary device used by the National Library of Medicine to cross-‐reference every Medline article.
The OR operator is used when at least one of the terms must appear in the record, broadening the search and increasing the number of citations received.
The wildcard symbol can be used to find all of the words with the same stem.
Boolean instructions, such as AND, OR, and NOT, operate within most databases and must be typed in upper case.
Finding all relevant studies that have addressed a single question is an easy task.
The NOT operator is used to retrieve records containing both search terms.
PubMed does not retain previous search results on the ‘history’ function on the features bar.
Additional terms cannot be added to an existing search, and therefore multiple searches cannot be combined.
The population in the ‘P I C O’ principle refers to the total population in the patient’s household.
The abstract must not be used as a ‘starting point’ to assist the reader in determining the relevance of the study.
All research questions must contain the comparison component of the ‘P I C O’ principle.
There is no database for psychological studies.
Statistical significance tells us how confident we can be when an effect of an intervention is true/real.
Statistical significance does not tell us if the impact is large enough to be implemented.
Statistical significance is a mathematical phenomenon.
Statistical significance depends on sample size, precision of data and effect size.
Statistical significance looks at the 95% confidence interval.
p values and confidence intervals (CI) are the most commonly used measures of statistical significance.
If a small effect size is found, the treatment may not be clinically important.
The null hypothesis is the basis for formal testing of statistical significance
Clinical significance does not measure how large the differences in treatment effects in clinical practice.
The 35% CI is used to measure statistical significance.
If the sample size is large, the clinical significance will always be large.
The higher the statistical significance the higher the clinical outcome.
Clinical significance is not of importance to a treatment effect.
Statistical significance equates to clinical usefulness.
To be clinically useful, the therapy must do more harm than good.
If a hazard ratio is less than 1,it is not statistically significant.
When a sample size is large, differences that are minute can be detected.
When judging clinical significance 95% confidence intervals should be considered over p-‐ values for large sample sizes.
Clinical significant results make enough of a difference to change the method of practice.
Clinical significance is judging whether the values in the confidence intervals are large enough to care about.
When studies have very large sample sizes, p-‐values can be considered almost obsolete.
Any effect no matter how small, can be seen as statistically significant if the sample size is large enough.
A clinician should decide that the study was large enough and the confidence intervals were small enough to warrant clinical significance.
To determine whether a positive result is clinically significant, the lower boundary of the confidence interval should be looked at.
When a p-‐value is <0.05 the result is considered clinically significant.
A clinical board must reach a unanimous decision to define a result as clinically significant.
Statistical significance shows whether confidence intervals include the null value.
Statistical p-‐values are most helpful for finding clinical significance, when looking at huge sample sizes.
The larger a sample size is the wider a confidence interval becomes, reducing the relevance of statistical significance.
P-‐values depend on the overall sample size, proving clinical significance with large enough numbers.
As huge studies become more prevalent, the difference between clinical significance and statistically significance are becoming irreverent.
Thresholds which patients would consider important in terms of treatment, can not define whether a result is clinically significant.
RCT’s are not always practical. This may be due to ethical issues.
An example of a retrospective study design is a case-‐control study.
The hierarchy of evidence provides a guide towards categorising clinical research.
Studies that limit bias to the greatest extent are higher levels of evidence.
The first step in assessing the validity of a research study is to determine study design.
A systematic review would be an effective trial design to research which NSAID is the least likely to cause a heart attack.
Strengths of case reports and case series study designs are that they are cheap and relatively easy do with existing medical records.
A limitation when using a cohort study design for rare diseases may be that there are not enough patients to be statistically or clinically significant.
RCT’s are generally very inexpensive study designs.
Expert opinion is a higher level of evidence than a case report.
The strength of a case-‐control study design is that you can study a number of diseases and outcomes at any given time.
Cohort studies are not ideal for etiology, harm or prognosis.
Using the term 'safe' to a consumer is preferred rather than using the term 'low risk' as it gives consumer 100% confidence.
It is not appropriate to ask a patient if there is a particular side effect they are concerned about, always list every possible side effect.
Clinical trials never involve human experiments.
Case reports, case series and cross-‐sectional studies are all longitudinal studies.
Systematic reviews is used as a stronger evidence as compared to the expert opinions.
All health professionals should use appropriate language for communication that is understandable to all level of patients.
Visual demonstration is the convenient way to convey the health message across the patients with poor literacy level.
It is the responsibility of the health care provider to provide the effective treatment to the patient.
Strong research method will not only help to get the better outcomes but it also prevent from getting the misleading result, which might be harmful for the patient.