before midterm

Question 1

CH 7: SINGLE SUBJECT (N=1) DESIGNS

Answer 1

Group comparisons – can give evidence on general disease causes or treatment effectiveness
Health professionals – most often work with individual patients, causes of problems, effectiveness of treatment
N=1 designs – employing research principles in everyday practice
similar to quasi-experimental designs (ie. have control over treatment and time of introduction)

Question 2

AB DESIGNS

Answer 2

Eg. patient admitted with high temperature
monitor temperature every 15 min for 2 hours
give medication
monitor temperature
if temperature falls in time consistent with medication, shows/suggests effective

Graph
	   -y-axis = dependent variable
x-axis = time
period A = control (baseline) level of 				dependent variable
period B = measurements after treatment

Question 3

AB DESIGNS (cont.)
several threats to validity in AB designs

Answer 3

Eg. Previous example:
maturation- patients’s temperature already going down

history- other influences cause temperature to decrease eg. Air conditioner

Question 4

ABAB DESIGNS

Answer 4

stronger control for extraneous variables
introduce reversal condition ie. re-introduce A conditions (withdraw treatment) and then B again
useful in some cases
not useful if variable irreversible eg. antibiotic cures condition so no re-emergence when withdraw
may not be ethical to withdraw treatment if produced desired effects

Question 5

MUTIPLE-BASELINE DESIGNS

Answer 5

concurrent observations to generate two or more baselines
eg. brain-damaged client with aggressive behaviors that disrupt occupational and speech therapies
introduce behavioral treatment strategy (eg. snack) to decrease aggressive outbursts
monitor frequency of outbursts in both sessions
introduce treatment first in occupational therapy sessions and later in speech sessions
ie. continue baseline in speech sessions after initiate treatment in occupational therapy sessions
helps control for extraneous factors that may influence dependent variable(s)

alternatively can generate baselines for 2 or more individuals or outcomes
eg. Two people with gout in extended care home
monitor acute attacks
introduce functional food (eg. bananas) in diet of one and later in diet of other
controls for other changes in diet
eg. Person with hypertension and diabetes
monitor blood pressure and blood glucose
introduce bananas and later flaxseed in diet
controls for negative or no influence

Question 6

INTERPRETATION OF RESULTS FOR N=1 DESIGNS

Answer 6

• when intend to show intervention causally related to beneficial outcome
• Eg. young man (John) who broke leg in a motorcycle accident – has severe pain except with narcotic analgesics
  
  • previous research shows that in some cases can control pain with transcutaneous electrical stimulation (TENS)
• but not equally effective for all patients
• also may get placebo effect

Question 7

2 questions:

	1. is TENS effective in reducing John’s pain?
	2. is pain reduction caused by TENS?

Answer 7

independent variable (IV) = TENS - select two levels:
A – output level known physiologically ineffective (placebo)
B – output known to be effective
dependent variable (DV) = pain intensity on 10-point scale

Question 8

VALIDITY OF N=1 DESIGNS

Answer 8

basic requirement = establish stable baseline
otherwise difficult to interpret results
but sometimes unethical to withhold treatment
can use baseline and treatment phases of different duration (eg. to limit time without treatment)
treatment time must be sufficient for effect to emerge
need valid and reliable measure of dependent variable

n=1 designs try to control for extraneous variables
can show causality
but may only relate to controlled setting
therefore evaluate sources of invalidity for each n=1 study
no matter how sophisticated, results may not generalize to other cases
sometimes can use meta-analysis of several n=1 studies to indicate overall trends