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# Dr. K RM Test 2

### Research Methods Test 2

Question | Answer |
---|---|

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 |

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 |

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 between-study variation |

Disadvantages of systematic reviews | • Not a primary study -Limited by validity of individual studies -Subject to bias |

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 |

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 |

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 meta-analysis |

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 Dose-response |

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 Dose-response 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 |

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) |

For case-control 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 |

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 |

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 |

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 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 |

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 case-control 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 time-consuming -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 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% |

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 |