AH 4239

false consensus effect

tendency for people to overestimate how much other people share their beliefs attitudes and behaviors

because of the false consensus effect our goal in research is to

avoid casual observations
use systematic approach instead

what is research?

a critical process for asking and attempting to answer questions about the world

ways of learning about behavior

custom and tradition
intuition
logical reasoning
authority
pseudoscience
scientific approach- empiricism

characteristics of intuition

gut feelings
basic observation
common sense
accept info w/o skepticism

limitations of intuition

assumes facts without finding proof
not full picture
no strong foundation of evidence

logical reasoning uses the

problem solving method

inductive reasoning is when you

develop generalizations from specific observations

example of inductive reasoning

nurse observes anxious behavior children in one hospital
conclusion that in general child's separation from parent is stressful

deductive reasoning is when you

develop specific predictions from general principles

deductive reasoning example

assume separation anxiety happens in general
conclusion that children in local hospital whos parents leave will have 5x stress

limitation of logical reasoning

validity of reasoning depends on accuracy of info used to create predictions

learning by authority is when

turn to specialized sources
leaders say it's the answer

limitation of learning by authority

need to consider your source

phrenology is an example of

pseudoscience

phrenology claims to be able to

determine character and personality based on shape of head

limitations of phrenology and pseudoscience

lack of evidence

pseudoscience tends to

pick favorable evidence
tends to be dogmatic and unyielding

scientific method defintion

systematic
empirical
controlled
critical examination of hypothetical propositions

systematic means there is

a sense of order
ID problem
Collect evidence
Analyze data
Interpret findings

empiricism is

knowledge must be based on observation

falsifiability is when

research fails to provide support of an idea

peer-review acts to

prevent poor quality research from becoming part of scientific literature

steps of scientific method

develop question
background research
construct hypothesis
develop method
test hypothesis
analyze data
communicate results

why does research matter?

understand and interpret new info
improve clinical practice
discover and validate scientific concepts

benefits of research

improves legislation
aids program development

goals of behavioral research

description of behavior
prediction of behavior
determine causes
explain behavior

data + methods \=

outcomes

research process

research idea
research design
collecting data
analyze data
publication process

non experimental research questions

descriptive
correlational
no intervention

example of descriptive research question

what beverages do college students consume daily?

example of correlational research question

what is the relationship between daily hours of studying and daily alcohol consumption?

example of experimental research question

does a low carb diet compared to an isocaloric low fat diet result in greater weight loss among college students

basic behavioral research acts to

examine nature of behavior
increases knowledge

applied behavioral research acts to

address issues and potential solutions
puts knowledge into action

experimental research designs

true experimental
within subjects experimental
quasi-experimental

key uses of non-experimental design

describe co-occurence
generate hypotheses
compare two methods
prediction

descriptive research describes

a developmental change in people over time without changing the environment

correlational research studies

the nature of existing relationships

correlational coefficient is the

numerical index of strength of relationship

epidemiological research is

non-experimental
study of health and disease in population and incidence of disease

example of epidemiological research

risk factors for heart disease
37% of adults report at least two of them

limitations of non experimental research

never cause and effect
third variable problem

key features of true experimental design

true control group
true random assignment
groups statistically equal
blind
sample size

pre-test/ post-test design example

effects of resistance exercise on elders with depression

factorial design means there is

more than one independent variable

factorial design example

effect of running vs walking on people with either low fat or normal diet

within subjects design is when there is

one group of subjects
subjects as their own control group

advantages of within subjects design

fewer participants
less money
conditions identical because person is own control group

disadvantages of within subjects design

fatigue effect
carryover effect (order effect)
practice effect

disadvantages of within subjects design fixed by

crossover design with random order and wash out period

quasi experimental design

no random assignment; uses pre existing or self selected groups
one group post test only
one group pre test post test

why sampling

economical
time efficient
potentially more accurate

goal of study is to

generalization

goal of sampling is to

represent population

our class vs. the uconn population

only a handful of majors
ratio of men vs women
age/ class standing
ratio of commuter vs. residential

steps in sampling process

ID target population
ID accessible population
Choose sampling procedure
define inclusion and exclusion criteria

inclusion criteria is the

main characteristics of target and accessible populations that will qualify someone as participant

exclusion criteria is the

characteristics that would prevent someone from being a participants

sampling bias is when

certain attributes of a sample that aren't representative of population

sampling bias means that the data you collect may

not be accurate or represent the population

sampling bias can occur any time your sample is

not random sample

sampling bias leads to

sampling error
deviation of sample from the population

probability sampling is

random selection
every unit has equal chance of being chosen
free of sampling error

disproportionate sampling is

non random
probability of selection isn't known
sampling error can't be estimated

disproportionate sampling is common in

clinical research
certain condition or intervention

stratified random sampling is

selecting randomly from intact groups ex: major
certain participant characteristics are important

in disproportionate sampling data are then

weighed meaning mathematically corrected due to sample having larger proportion than actual population

cluster sampling is done when

accessible population is too large

in cluster sampling sample is selected

using large units than smaller units
multi stage selection process

ex of cluster sampling

randomly select from all CT schools
then from all 8th graders
then from all latinos

NHANES is the \__ and they sample by

national health and nutrition examination survey
to sample combines interviews and physical examination

non probability sampling is done when

probability sampling isn't feasible
each person does NOT have an equal chance of being selected

in non probability sampling techniques are

arbitrary
population of interest may be defined but there's little effort to sample from it
sample can be very different from target population

types of non-probability sampling

convenience
purposive
snowball
quota

in convenience sampling it is \__ and potential for

done haphazard and based on availability
potential for bias of self selection
bonus it's very easy and inexpensive

in purposive sampling

recrutiment is based on specific criteria

in snowball sampling

there are hard to locate individuals
recruit similar subjects

selection in quota sampling

select subjects until number need is met
ex: need a certain number of muslims for a study but isn't accurate to actual population proportions in the population

quota sampling may limit

generalizing to the state population

concepts are

mental representations
an abstract idea
terms we know the definition of as a society

example of concepts

food
father
weight
wheelchair

constructs are

a concept created for a scientific purpose to be measured

example of constructs

IQ
shyness
health
pain
love

types of variables

continuous
discrete

continuous variables are

any value along a continuum
can't be exactly measure and depends on degree of precision

example of continuous variables

distance
weight

discrete variables are

categorical
described as whole unit

example of discrete variable

heart rate
population

levels of measurement

nominal
ordinal
interval
ratio

nominal is a

classification
category label
ex: sex nationality blood type

ordinal is

rank order
ex: pain, functional status

interval is

equal intervals between numbers with NO TRUE ZERO
ex: calendar years, IQ, temperature

ratio is

units with equal intervals measure from TRUE ZERO
ex: distance, length, age, time

reliability is the

extent to which a measurement is consistent

validity means measurement is

relatively free from error

goal of validity in research

to show using a sample of people that a change in the IV caused a change in the DV and that this relationship can be generalized to population

three types of validity

internal
external
construct

internal validity means

ability to accurately draw conclusions about causal relationships

external validity means

ability to generalize results to population and other settings