Research Methods Test 2
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| Narrative Review | -Selective review of the literature that broadly covers a specific topic -Does not follow strict systematic methods to locate and synthesize articles
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| Systematic Review | -Utilizes exacting search strategies to make certain that the maximum extent of relevant research has been considered -Original articles are methodologically appraised and synthesized
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| Meta-analysis | -Quantitatively combines the results of studies that are the result of a systematic literature review -Capable of performing a statistical analysis of the pooled results of relevant studies
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| Systematic reviews | -Overview of primary studies which used explicit and reproducible results -Can be performed on group or single subject studies -Can include both quantitative and qualitative analyses
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| Advantages of systematic reviews | -Increased sample sizes -Can control for between-study variation
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| Disadvantages of systematic reviews | • Not a primary study -Limited by validity of individual studies -Subject to bias
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| Meta-analysis | Statistical analysis of results of several similar studies (aka quantitative synthesis) -Type of quantitative systematic review, or included as part of systematic review
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| Hierarchy of Evidence | 1 Systematic review
2 Random Controlled Trials
3 Cohort
4 Case-control series
5 Case series
6 Case reports
7 Editorial and opinions
8 Animal research and lab studies
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| Stages and phases involved in a systematic review | -Planning the review (ID of the need for a review, preparation of a proposal for review, and development of a review protocol) -Conducting the review (ID of research, selection of studies, study quality assessment, data extraction and synthesis)
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| Forest plots | -Compares different studies -Statistically different when 95% confidence intervals cross effect line
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| Narrative reviews advantages | -Present a general overview covering a specific topic that provides primary information or an update, or both -Fairly easy for novice authors to prepare
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| Narrative reviews disadvantages | -May not provide the best available answers -Findings are less reliable
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| Systematic reviews advantages | -Present a comprehensive review of the literature based on all available research with regard to a focused research question -Provide an estimate of the "true" answer to the research question
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| Systematic reviews disadvantages | -Specialized expertise of reviewers is required -Involve a formal research protocol -Findings are only relevant to a single question
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| Publication bias | -File Drawer Problem = only positive data presented, the rest are put in the file drawer -In situ = some parts of the studies published
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| Study homogeneity | Similarity between studies, increases their ability to be compared
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| Study heterogeneity | Differences between studies -Hinders comparison of subjects -Study design -Observed treatment effects more dissimilar than due to chance -Statistical test can estimate and account for this -Treatments that work across, elevate confidence
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| Study heterogeneity | -Subgroup analysis (older v younger)= may be more valid, reduce stat power -Meta regression analysis = analysis of hetero. between subgroups -Sensitivity analysis = considers variation between factors other than subjects -Cumulative meta-analysis
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| IMRaD | Introduction (What was asked)
Methods (How was it studied)
Results (What was found)
and
Discussion
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| Introduction | Objective = the exact questions asked
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| Methods | Design
Setting
Patients
Interventions
Main outcome
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| Results | Key findings
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| Discussion | Conclusion = key conclusions including direct clinical application
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| Incidence | # of new cases in time period/population x 100,000
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| Risk | estimate of proportion of unaffected person who will develop the disease of interest over a specified period of time
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| Odds Ratio (OR) | odds of developing disease in exposed group / odds of developing disease in unexposed group
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| Prevalence | # of existing cases in a time period / population x 100,000
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| Point prevalence | proportion of population with disease at a given time (can miss episodic conditions)
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| Period prevalence | proportion of population that has disease within a defined period of time
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| Causation in epidemiology | 3 key criteria:
Temporality (temporal precedence)
Consistency
Dose-response
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| Temporality | A causes B
or
B causes A
or
X causes A + B
A not related to B; occurrence is a mere chance
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| Consistency | Reproduction of study results in different populations
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| Dose response | Greater exposure to risk factor leads to greater effect on health
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| Bradford Hill's Criteria of Causation | Strength of Association
Consistency
Specificity in the case
Temporality
Dose-response relationship = increase dose -> increase occurrence
Plausibility
Coherence
Experimental evidence
Analogy
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| Cohort studies | Longitudinal
Prospective = know patient's exposure, observing ahead for disease
Retrospective = know patient's exposure, looking back in time for disease
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| Case-control study | Similar to retrospective cohort study Disease or condition is known, looking back in time for risk factors 2 Types: Prevalent case (includes all persons) and cumulative incidense (only new cases)
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| For case-control studies you must calculate ________ and not __________ | Odds Ratio (OR), risk
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| OR formula | ad/bc a=exposed cases b=exposed controls c=nonexposed cases d=nonexposed controls
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| Case-control studies advantages | -Good for investigating rare diseases -Can be performed quickly and inexpensively -Useful for studing disease with long latency periods -Facilitate study of multiple potential cases at once -Existing records can often be used
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| Case-control studies disadvantages | -Typically rely on patients recall of past exposure -Do not permit calulation of true disease rates in the population -Difficult to validate information on exposure -Other variables that may be associated with disease are not controlled
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| Recall bias | systematic differences between cases and controls in ability to recall past exposures
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| Berkson's bias | (Admission rate bias) type of selection bias where hospitalized cases are different than hospitalized controls
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| Stratified analysis | Cnsiders confounding variable (e.g. alcohol consumption and lung cancer) -Looks at effect each independent variable has on outcome separately
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| Cohort studies | -Follow a disease free group of subjects forward in time -Some subjects are exposed to a risk factor and some are not -Purpose is to see if there is a greater proportion of disease among those who are exposed to the risk factor
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| Discreet vs Continuous variables | Discreet--> smokers vs. nonsmokers Continuous--> cholesterol levels
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| Inception cohort study | Tracking cohort with early stage of chronic condition
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| Cohort studies | -Less subject to bias than case-control studies bc exposure levels evaluated before disease develops -Best design to determine risk level -Better for studying relatively common diseases -Most expensive type of epidemiological study, but cheaper than RCTs
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| When an outcome in a research study is common (occurs in more than 10% of the unexposed group)... | The odds ratio will tend to OVERESTIMATE the risk ratio
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| Relative Risk (RR) in cohort studies | RR = (a/(a+b)) // (c/(c+d))..........................RR > 1 = increase in incidence of disease in exposed group...................RR < 1 = protective effect of exposure (can be used to calculate placebo effect)
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| Attributable risk (AR) in cohort studies AND Absolute risk reduction (ARR) in cohort studies | AR or ARR= a/(a+b) - c/(c+d)
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| Relative risk reduction (RRR) in cohort studies | Comparative reduction in rates of bad outcomes between experimental and control groups............RRR = ARR // c/(c+d)
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| Number needed to treat (NNT) in cohort studies | # of patients would would need to be treated in order to prevent one additional bad outcome......NNT = 1/ARR........related term = NNH (number needed to harm
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| Cohort studies advantages | -Portray the natural history of disease -Don not rely on patient recall -Better for establishing a cause and effect relationship than case-control studies -Less vulnerability to bias or chance -Permit calculation of true disease rates in the population
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| Cohort studies disadvantages | -Typically very expensive -Many people must be followed to obtain enough with the disease -Very time-consuming -Subjects frequently drop out of study over time -Difficult to generate a control group to study very common conditions
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| Case studies | Usually retrospective, can be prospective, low validity but high clinical relevance, similar to IMRaD format but with case description rather than M & R (storied case report and evidence based case report)
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| 4 types of case studies | 1) Unique case 2) Unexpected association 3) Unexpected development 4) Unusual presentation
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| Is a case study the same thing as a case report? | NO, a case study is more in depth
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| Purposes of case reports | -Detect rare conditions -Educational value -Learn how other doctors manage certain cases
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| Limitations of case reports | -Susceptible to many biases -Unable to test hypotheses -Does not determine the effectiveness of an intervention - Unable to generalize results to other patients or practices
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| Case series | Are especially prone to: Selection, observation, and publication bias (can be subjected to meta analysis)
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| SSTSDs | Single subject time series design (aka N=1 design)............AB, ABA (withdrawal design), ABAB variants, ABAC (comparing 2 treatments
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| Suitable candidates for SSTSDs | -Condition is chronic -Condition is stable -Spontaneous remission is not likely -Previous treatment has had limited success -No concurrent treatment is involved
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| Trendline examples | Stable downward and accelerating downward trend
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| Multiple baseline design | Variant: Simultaneous replication design........-Patients begin studies at same time -Treatment administered sequentially to patients only after clear treatment effect is observed for prior patient
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| Descriptive statistics | Usually retrospective, can be prospective, low validity but high clinical relevance
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| 4 types of descriptive statistics | 1) Unique case 2) Unexpected association 3) Unexpected development 4) Unusual presentation
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| Frequency distribution | Usually in a histogram
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| Measure of central tendency in descriptive statistics | Mean of a sample or mean of a population
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| Levels of measurement | Nominal, ordinal, interval, ratio
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| Nominal | Counting, central tendency=MODE, example=NUMBERS
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| Ordinal | Greater or less than operations, central tendency=MEDIAN, example=MILITARY RANK
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| Interval | Addition or subtraction, central tendency=(symmetrical) MEAN / (skewed) MEDIAN, example=Fahrenheit
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| Ratio | Addition, subtraction, multiplication, and division, central tendency=(symmetrical) MEAN / (skewed) MEDIAN, example=Kelvin, R.O.M.
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| Normal distribution | Symmetrical, unimodal histogram where the Mean=Median=Mode (they are in the same position, in the center of the Bell curve)
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| Modal Division | Unimodal = 1 peak, Bimodal = 2 peaks, Multimodal = < 2 peaks
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| Standard error of the mean | SE(n) = S/(square root of n)
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| 1 standard deviation from the mean | 68.3% confidence interval
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| 2 standard deviations from the mean | 95.5% confidence interval
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| 3 standard deviations from the mean | 99.7% confidence interval
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| The wider the bars on the histogram are distributed... | the higher the standard deviation (larger spread)
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| The narrower the bars on the histogram are distributed... | the lower the standard deviation (smaller spread)
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| Skewed distributions | -Positive skews have tails extending to the right, where negative skews have tails to the left -Mean is drawn towards the tail -Mode is at the peak -Median is between
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| Know how to calculate z-score | Z-score is the percentage to the left of the point in question, to find the other side, subject that percentage from 100%
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| True H(o) ---> Reject H(o) | Type 1 error, the odds of saying the hypothesis is true when it is actually false
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| False H(o) ---> Reject H(o) | CORRECT DECISION, the odds of saying the hypothesis is false when it actually is false
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| True H(o) ---> Fail to reject H(o) | CORRECT DECISION, the odds of saying the hypothesis is true when it cannot be proven to be false
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| False H(o) ---> Fail to reject H(o) | Type 2 error, the odds of saying the hypothesis is false, when it cannot be proven to be false
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