Keywords

Randomized Controlled Trials

  • Has high internal validity

  • Reduced risk of confounding variable

  • Reduced external validity

  • Expensive, time-consuming variables

Cohort Studies

  • Useful for sequential events

  • Can study multiple outcomes from exposures

  • Retrospective: less expensive

  • Require large sample size

  • Risk of confounding variables

  • Difficult to study rare outcomes

  • Prospective: expensive

Case-Control Studies

  • Useful for rare outcomes

  • Can study several exposures

  • Inexpensive

  • Risk of confounding variables

Cross-Sectional Studies

  • Can study multiple outcomes and exposures

  • Cannot infer causality

  • Risk of confounding variables

  • Less useful for rare exposures or outcomes

Case Studies

  • Useful for rare outcomes

  • Convenient and inexpensive

  • Lack of a comparison group

  • Cannot infer causality

  • Risk of confounding variables

Systematic Reviews

  • Summarize existing studies descriptively

  • A descriptive results section summarizing the findings and addressing the qualities of the included studies

Meta-analyses

  • Use statistics to combine the results from each included study and generate a single summary statistic

    • Compilation of evidence that potentially has greater power to inform clinical decisions than would an individual study in the systematic review or meta-analysis

    • If the quality of the studies included in the systematic review or meta-analysis is poor, the summary conclusions are similarly inadequate

Case Reports

  • Aid in recognizing and describing new disease processes or rare manifestations

  • Describe the disease in the context of comorbidities and individual characteristics

  • Identify drug adverse effects

  • Help to illustrate the diagnostic process and help students apply the literature to an individual patient

  • Help identify emerging health conditions

  • Show how exposures and disease outcomes are related

  • Can stimulate important research questions and help guide hypotheses

  • Are purely descriptive and one of the weakest forms of evidence

  • Cannot be used to make inferences about the broader population

  • Cannot prove causality

Anecdotal Evidence

  • A clinician’s personal experience

  • Shares some characteristics with case reports

  • Lacks the strength of data collected via rigorous methodology that also involves significant numbers

    anecdotal evidence can suggest hypotheses and leads to the creation of credible studies

Descriptive Epidemiologic Studies

  • Follow up on case reports

  • Used to describe patterns of disease in the population according to person, place, and time

  • Do not test a predefined hypothesis or determine a cause-and-effect relationship

  • Used to develop hypotheses for subsequent analytic studies

  • Use a variety of tools, including surveillance reports, cross-sectional analyses, and surveys

Validity

  • Addresses whether an instrument or test actually measures what it is intended to measure

  • Criterion validity is the degree to which the measurement correlates with an external criterion or another instrument or test that is considered valid

    • Convergent validity is the degree to which independent measures of the same construct are highly correlated

    • Predictive validity is the ability of an instrument or test to predict some future criterion

    • Discriminant validity requires that an instrument or test shows little or no correlation with measures from which it differs

  • Content validity refers to the extent to which aspects of items that make up an instrument or test are representative of a particular construct

    • Face validity is a judgment about whether elements of an instrument make intuitive sense

    • Sampling validity refers to whether the instrument incorporates all of the aspects under study

Reliability

  • The consistency or repeatability of scores

  • Test–retest reliability assesses whether an instrument or test yields the same results each time it is used with the same study sample under the same study conditions

  • Internal consistency reliability is a measure of the consistency of the items within a test

  • Interrater reliability is the degree to which two raters independently score an observation similarly

Fig. 1
figure 1

Foursquare: TP true positive, FP false positive, FN false negative, TN true negative

Full size image

Sensitivity: Screening

  • Probability of correctly identifying those who truly have the disease

  • True positives/disease

  • TP/(TP + FN) (Fig. 1)

Specificity: Confirmation

  • Probability of correctly identifying those who do not have the disease

  • True negatives/disease

  • TN/(FP + TN)

Positive Predictive Value (PPV)

  • Probability of correctly identifying those who truly have the disease amongst those whose tests are positive

  • True positives/test

  • TP/(TP + FP)

Negative Predictive Value (NPV)

  • Probability of not having the disease given a negative test

  • True negatives/test

  • TN/(FN + TN)

Predictive values are dependent on the prevalence of the disease. The higher the prevalence of a disease, the higher the PPV of the test.

p Value

  • The p value is the probability of obtaining a test statistic result at least as extreme as the one that was actually observed, assuming that the null hypothesis is true.

  • A researcher will often “reject the null hypothesis” when the p value turns out to be less than a predetermined significance level, often 0.05 or 0.01. Such a result indicates that the observed result would be highly unlikely under the null hypothesis.

  • Many common statistical tests, such as chi-square test or Student’s t test, produce test statistics which can be interpreted using p values.

  • An informal interpretation of a p value, based on a significance level of about 10 %, might be:

    • p ≤ 0.01: very strong presumption against null hypothesis

    • 0.01 < p ≤ 0.05: strong presumption against null hypothesis

    • 0.05 < p ≤ 0.1: low presumption against null hypothesis

    • p > 0.1: no presumption against the null hypothesis

False Positive

  • A false positive occurs when the test reports a positive result for a person who is disease free.

False Negative

  • A false negative occurs when the test reports a negative result for a person who actually has the disease.

Odds Ratio (OR)

  • Calculates the relative risk (RR) if the prevalence of the disease is low. It can be calculated for case-control study (retrospective study)

  • The OR can be used to determine whether a particular exposure is a risk factor for a particular outcome and to compare the magnitude of various risk factors for that outcome

Relative Risk (RR)

  • Disease risk in the exposed group divided by disease risk in unexposed group. It can be calculated for cohort study (prospective study)

  • The 95 % confidence interval (CI) is used to estimate the precision of the OR

  • If the 95 % CI for OR or RR includes 1, the study is inconclusive

  • A large CI indicates a low level of precision of the OR, whereas a small CI indicates a higher precision of the OR

  • For a rare disease, OR approximates RR