Topic 3 Flashcards
what are the components of a line graph?
- x (abscissa) and y-axis (ordinate) lines
- labels for axis
- numbers on axis
- data points and connecting with lines
- phase lines (if there are diff phases)
- phase labels (baseline, treatment and follow up)
what is a phase line?
vertical line on graph that indicates change in treatment
- data points do not connect across phase lines
what are the typical x and y axis for b-mod?
time and behavior
what are the do/don’t for graphs?
- client name (bottom right)
- data summary to go from raw data
- no legend
- no gridlines
- add title
- black axes and units
- no connection baseline phase curve to treatment phase curve
what is the purpose of research design?
determine whether treatment is responsible for observed change in target behavior and to rule out extraneous variables causing behavior to change
independent variable
treatment applied
- what researcher applied to manipulate to produce change in target behavior
dependent variable
target behavior measure
confounding variable
extraneous
- factor affecting behavior but not controlled
functional relationship
treatment procedure (IV) regularly causes change in target behaviour while other variables held constant
- need IV-DV behavior and replication
what is IV-DV relationship?
changing IV causes change in DV
what is replication in functional relationship?
consistent pattern of results
what does b-mod typically use?
single-subject research methods
does not employ much stats analysis
what is A-B design?
one baseline (A) and one treatment (B)
- baseline collect at least 3 points that do not show a trend (which would indicate behavior change)
- used to eval the effect of treatment on target behavior
- not a research design or purposes
what is the simplest graph used?
A-B design
where is A-B graph used?
applied nonresearch situation in which people are interested in demonstrating behavior change occurred
- self-management project
pros of A-B design
satisfactory for self-management
cons of A-B design
not a true research design- lacks replication, no cause and effect, change can be due to confounding variable
A-B-A-B design
- reversal design
- 1 person doing
- 2 baseline phases
- 2 treatment phases
- varied to include more than one kind of treatment
pro of A-B-A-B
establish cause and effect
cons of A-B-A-B
- unethical to withdraw beneficial intervention
- behavior may not revert back to second baseline
multiple baseline design
- more than one A-B carried out simultaneously
- baseline vary in length before treatment begins
- intervention phase is staggered across separate designs
- evidence that treatment is effective
multiple baseline across subjects
applied to diff people
- nurse wearing protective gloves with HIV-pos patients
multiple baseline across behaviors
apply treatment to several diff target behaviors
- pronounciation of th, z, zh
multiple baseline across settings
apply in diff settings
- stuttering at home, work, public
pros of multiple baseline
no reversals
if behavior occurs only when B phase starts in each condition so can conclude result was intervention
con of multiple baseline
treatment can spread across subjects, behaviors, settings during baseline
alternating treatments design
- multielement design
- baseline and treatment applied in rapid succession
- extraneous factors could affect results can be counterbalanced
- treatment effects shown by fractionation
- little overlap
what is fractionation?
consistent vertical separation between treatment curves
- one point connects 2 lines in treatment
pros of alternating treatment
extraneous variables less of effect
evaluates effects of diff treatments
con of alternating treatment
treatments can interact with each other
changing-criterion design
- criterion for successful treatment progressively changes
- uses A-B design
- goal for target behavior changes in treatment
- reaches level and then changes it
- work up to where they want to be
example of changing criterion
less caffeine = earn money, drank more = lost money. level below criterion because behavior changed each time performance criterion changes showing a function relationship
which design is the most complex?
changing-criterion
pros of changing-criterion
well-suited to behaviors that can be approximated gradually
cons of changing-criterion
unsuitable for behavior that may not change gradually
what are the features used to evaluate behavior change?
level
trend
variability
level
how high or low data are on y-axis
- lower level in intervention shows intervention was successful
trend
exists when behavior is increasing across a phase or decreasing across phase
- need data stable within phase before changing
variability
how high and low data points are away from the mean level in phase
low variability
data points are still close to the mean level in phase
high variability
many data points are far above and far below the means
it is easier to identify level difference between phases when there is high or low variability?
low
