starts with people in the present, following them into the future - prospective
measure dependent variable and covariables before/in present to determine baseline
follow them in time, whilst conducting a experimental manipulation (the independent variable)
after the experimental manipulation, measure the dependent variable again to see the affect of the independent variable on it
Inferring causation - problems
Confounding - other/extraneous variables that may have caused a change in symptoms/dependent variables
Regression to the mean - you may have got an extreme measurement they first time you measured, so the second time you measured it was a more normal result
Natural recovery
Placebo/non-specific effects
Hawthorne Effect (Observer) - people changing their behaviours because they know theyre being observed
Rosenthal Effect (Experimenter expectancy) - researchers biasing the changes they want to see
Confounding variables - Natural recovery:
symptoms naturally resolve over time, which can explain for the change in measured dependent variables
this would mean that the change in the dependent variable wasn't caused by the independent variable, which means it wasnt a causation