Research Design and Behavioral Analysis

1. Research Design and Behavioral Analysis

2. Research methods • Correlation Research – used to determine if there is a relationship between two variables • Least amount of experimental control • Cannot be used to state cause and effect relationships

3. Research methods (cont.) • Experiment – provides most confidence in determining cause and effect relationships. Manipulate the independent variable to see if changes occur in the dependent variable (measure) • Amphetamine study as an example

4. Research methods (cont) • Quasi-experiment – similar to an experiment except the independent variable (IV) cannot be manipulated • IV is usually a subject variable • Subjects are assigned to groups for particular reason (gender, age, ethnic group, etc.) • Lack of random assignment reduces confidence in cause and effect statement • Modification of Amphetamine study as an example

5. Research methods (cont.) • The experimental design preferred in psychopharmacological research – most control and confidence in cause and effect • Measures are usually behavioral changes that the drug was intended to cause and physical changes (side effects) • Side effects not always bad – many drugs designed for one purpose, but later found to be useful for another because of unexpected actions

6. Experimental designs • All experiments begin with a control group and one or more experimental groups. The two principle experimental designs differ in how subjects are assigned to the groups

7. Within-subjects design • Only one group of subjects involved • All subjects receive all levels of treatment. They act as their own control and experimental group(s). Test before giving the drug – baseline, then give the drug and measure any changes • Advantages • Need fewer subjects • You know groups are equal because they are the same subjects • Disadvantages • Carry over effects – measuring independent variable to get baseline may change subjects in some way • Many times it requires more time – delays between treatments

8. Between-subjects design • Different subjects are randomly assigned to different groups. Groups are assumed to be equal because each subject had an equal chance of being assigned to any group • Advantages • No carry-over effects • Quick • Disadvantages • More variability – groups may not be equal by chance • More subjects required and you may not have many

9. Statistical analysis • Inferential statistics – what is the probability that the difference between groups is the result of chance variations? • Within subjects design – What is the probability that the difference in the baseline measure and the experimental trials was the result of chance? • Between groups – What is the probability that the difference between the control group and experimental group(s) was due to chance? • Convention says to use probability of 1 or 5 out of 100 (P<.01 or P<.05) • With drug research using a P < .01 is preferred

10. Validity • Internal validity – How valid is our measurement? Are we measuring what we say we are measuring? • External validity – How confident are we that we can generalize our results from our sample to a whole population? Is our sample truly representative of our population? Could it be biased?

11. Important issues with validity • 1. Within groups variability – the average of the subjects in the experimental group performed differently than the average of the subjects in the control group, but perhaps a sub-group of the subjects did not show a difference in performance. • Example: older subjects were very different, but younger subjects showed no change. Your study showed it worked for all subjects when it only affected older subjects

12. Important issues with validity (cont.) • 2. Use of a drug with a population not included in any of the samples used in the experiment. • Examples: • 1. women excluded from testing hypertension drugs because of fluctuating hormones. These drugs used to treat hypertension in women. • 2. Prozac used to treat children when only tested on adults

13. Important issues with validity (cont.) • Placebo – a pill or injection that has no medicinal value, but causes changes because of peoples expectations • Placebo effect – if people given something that is suppose to help them, it may have an effect when in reality the drug had no effect. Has to be controlled by having the control group receive a placebo while experiment group receives experimental drug

14. Important issues with validity (cont.) • Hawthorne Effect – people will sometimes improve because they get attention and feel that others are trying to help even if the drug they are given has no effect itself

15. Experimenter bias • A Person testing their drug has a strong desire for drug testing to be successful • They know what the desired effect is suppose to be • They may “see” the desired effect in the experimental group, and not see it in the control receiving the placebo because they know which group is which

16. Solution to experimenter bias • Use of multiple naïve observers who have no expectations about the which subjects should show a change • Use of double-blind techniques. Subjects are unaware if they are receiving the placebo or test drug (single-blind), and the experimenter is unaware of who was assigned to get the placebo and who is receiving the test drug.

17. Three group design • Most frequently used drug testing design • 1. experimental groups receives test drug • 2. control group 1 receives placebo • 3. control group 2 receives drug with known effects • Allows 3 different comparisons: • 1. placebo to established drug – was test sensitive enough to detect an effect • 2. placebo to experimental drug – was there an effect • 3. established drug and experimental drug – is new drug more effect or have fewer side effects

18. Dependent measures in psychopharmacological research • Changes in observed behavior – decrease in aggressive behaviors, decreased eating, etc. • Changes in human performance – cognitive and motor tests • Self-report by subjects – pain medication, “on a scale of 1 to 10 with 1 being very little and 10 being excruciating how do you rate your level of pain?”

19. Dependent measures in psychopharmacological research • Electroencephalogram (EEG) • Measure level of arousal of the cortex –small fast waves indicate higher levels of arousal than large slow waves • Measure REM sleep – deprivation of REM sleep has similar effect to total sleep deprivation. A side effect of some drugs is a disruption of REM sleep

20. Dependent measures in psychopharmacological research • Perceptual measures: • Sensory difference thresholds – how different do two stimuli have to before you are able to detect a difference – Does a drug make you more or less sensitive to these differences? • Critical frequency of fusion – How fast does a light have to flicker on and off before you see it as a continuous light

21. Dependent measures in psychopharmacological research (cont.) • Cognitive tests • Motor tests – sobriety test • Combination – driving tests

22. Measuring performance in nonhumans • Drug effects on the performance on operant conditioning and different schedules of reinforcement • Avoidance – escape tasks – animals learn to avoid an unpleasant stimuli or they learn to escape an unpleasant stimuli they can’t avoid • Anxiety reducing drugs decrease avoidance behavior but not escape behavior

23. Measuring performance in nonhumans • Use of punishment – anything that decreases magnitude or frequency of a behavior. Does the drug decrease the effectiveness of punishment. Sedatives do amphetamines do not • Drug discrimination paradigm – teach animal to discriminate between the effects of a placebo and the effects of a particular drug • Used to determine if a new drug has a similar effect as an older drug • Also if the two drugs have the same effect on the actions of neurotransmitters

24. Drug development and testing • Major issue with psychoactive drugs: • 1. we know most mental disorders involve biochemical imbalances • 2. we know that psychoactive drugs operate on the effect of neurotransmitter systems • 3. we do not know exactly what the specific biochemical imbalance is in most disorders so it is difficult to know what drug will work with what disorder • This results in extensive testing with nonhumans • This results in extensive testing with nonhumans

25. Nonhuman testing • Purpose: • Identification of exactly which neurotransmitter system or systems the drug effects and identifies possible side effects • Identification of effective versus toxic dosages based upon body weight – looking for drugs with the largest difference between the two • Obviously interspecies differences a problem

26. Human testing • Purpose: • Identify short-term and long-term effects in humans • Detailed analysis of aversive effects – never ending unless drug is discontinued