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  
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  
Metaanalysis  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  
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  
Advantages of systematic reviews  Increased sample sizes Can control for betweenstudy variation  
Disadvantages of systematic reviews  • Not a primary study Limited by validity of individual studies Subject to bias  
Metaanalysis  Statistical analysis of results of several similar studies (aka quantitative synthesis) Type of quantitative systematic review, or included as part of systematic review  
Hierarchy of Evidence  1 Systematic review 2 Random Controlled Trials 3 Cohort 4 Casecontrol series 5 Case series 6 Case reports 7 Editorial and opinions 8 Animal research and lab studies  
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)  
Forest plots  Compares different studies Statistically different when 95% confidence intervals cross effect line  
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  
Narrative reviews disadvantages  May not provide the best available answers Findings are less reliable  
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  
Systematic reviews disadvantages  Specialized expertise of reviewers is required Involve a formal research protocol Findings are only relevant to a single question  
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  
Study homogeneity  Similarity between studies, increases their ability to be compared  
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  
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 metaanalysis  
IMRaD  Introduction (What was asked) Methods (How was it studied) Results (What was found) and Discussion  
Introduction  Objective = the exact questions asked  
Methods  Design Setting Patients Interventions Main outcome  
Results  Key findings  
Discussion  Conclusion = key conclusions including direct clinical application  
Incidence  # of new cases in time period/population x 100,000  
Risk  estimate of proportion of unaffected person who will develop the disease of interest over a specified period of time  
Odds Ratio (OR)  odds of developing disease in exposed group / odds of developing disease in unexposed group  
Prevalence  # of existing cases in a time period / population x 100,000  
Point prevalence  proportion of population with disease at a given time (can miss episodic conditions)  
Period prevalence  proportion of population that has disease within a defined period of time  
Causation in epidemiology  3 key criteria: Temporality (temporal precedence) Consistency Doseresponse  
Temporality  A causes B or B causes A or X causes A + B A not related to B; occurrence is a mere chance  
Consistency  Reproduction of study results in different populations  
Dose response  Greater exposure to risk factor leads to greater effect on health  
Bradford Hill's Criteria of Causation  Strength of Association Consistency Specificity in the case Temporality Doseresponse relationship = increase dose > increase occurrence Plausibility Coherence Experimental evidence Analogy  
Cohort studies  Longitudinal Prospective = know patient's exposure, observing ahead for disease Retrospective = know patient's exposure, looking back in time for disease  
Casecontrol 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)  
For casecontrol studies you must calculate ________ and not __________  Odds Ratio (OR), risk  
OR formula  ad/bc a=exposed cases b=exposed controls c=nonexposed cases d=nonexposed controls  
Casecontrol 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  
Casecontrol 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  
Recall bias  systematic differences between cases and controls in ability to recall past exposures  
Berkson's bias  (Admission rate bias) type of selection bias where hospitalized cases are different than hospitalized controls  
Stratified analysis  Cnsiders confounding variable (e.g. alcohol consumption and lung cancer) Looks at effect each independent variable has on outcome separately  
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  
Discreet vs Continuous variables  Discreet> smokers vs. nonsmokers Continuous> cholesterol levels  
Inception cohort study  Tracking cohort with early stage of chronic condition  
Cohort studies  Less subject to bias than casecontrol 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  
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  
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)  
Attributable risk (AR) in cohort studies AND Absolute risk reduction (ARR) in cohort studies  AR or ARR= a/(a+b)  c/(c+d)  
Relative risk reduction (RRR) in cohort studies  Comparative reduction in rates of bad outcomes between experimental and control groups............RRR = ARR // c/(c+d)  
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  
Cohort studies advantages  Portray the natural history of disease Don not rely on patient recall Better for establishing a cause and effect relationship than casecontrol studies Less vulnerability to bias or chance Permit calculation of true disease rates in the population  
Cohort studies disadvantages  Typically very expensive Many people must be followed to obtain enough with the disease Very timeconsuming Subjects frequently drop out of study over time Difficult to generate a control group to study very common conditions  
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)  
4 types of case studies  1) Unique case 2) Unexpected association 3) Unexpected development 4) Unusual presentation  
Is a case study the same thing as a case report?  NO, a case study is more in depth  
Purposes of case reports  Detect rare conditions Educational value Learn how other doctors manage certain cases  
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  
Case series  Are especially prone to: Selection, observation, and publication bias (can be subjected to meta analysis)  
SSTSDs  Single subject time series design (aka N=1 design)............AB, ABA (withdrawal design), ABAB variants, ABAC (comparing 2 treatments  
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  
Trendline examples  Stable downward and accelerating downward trend  
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  
Descriptive statistics  Usually retrospective, can be prospective, low validity but high clinical relevance  
4 types of descriptive statistics  1) Unique case 2) Unexpected association 3) Unexpected development 4) Unusual presentation  
Frequency distribution  Usually in a histogram  
Measure of central tendency in descriptive statistics  Mean of a sample or mean of a population  
Levels of measurement  Nominal, ordinal, interval, ratio  
Nominal  Counting, central tendency=MODE, example=NUMBERS  
Ordinal  Greater or less than operations, central tendency=MEDIAN, example=MILITARY RANK  
Interval  Addition or subtraction, central tendency=(symmetrical) MEAN / (skewed) MEDIAN, example=Fahrenheit  
Ratio  Addition, subtraction, multiplication, and division, central tendency=(symmetrical) MEAN / (skewed) MEDIAN, example=Kelvin, R.O.M.  
Normal distribution  Symmetrical, unimodal histogram where the Mean=Median=Mode (they are in the same position, in the center of the Bell curve)  
Modal Division  Unimodal = 1 peak, Bimodal = 2 peaks, Multimodal = < 2 peaks  
Standard error of the mean  SE(n) = S/(square root of n)  
1 standard deviation from the mean  68.3% confidence interval  
2 standard deviations from the mean  95.5% confidence interval  
3 standard deviations from the mean  99.7% confidence interval  
The wider the bars on the histogram are distributed...  the higher the standard deviation (larger spread)  
The narrower the bars on the histogram are distributed...  the lower the standard deviation (smaller spread)  
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  
Know how to calculate zscore  Zscore is the percentage to the left of the point in question, to find the other side, subject that percentage from 100%  
True H(o) > Reject H(o)  Type 1 error, the odds of saying the hypothesis is true when it is actually false  
False H(o) > Reject H(o)  CORRECT DECISION, the odds of saying the hypothesis is false when it actually is false  
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  
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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Created by:
reeseochoa
on 20101118