
A placebo is an inactive substance or
condition that can cause people to
improve or change their behavior. Both
expectancy and learning contribute to
this effect.

The placebo effect is an advantage for
treatment, boosting its effectiveness. This
effect may be responsible for about 35% of
improvements, but some treatments (such
as antidepressant drugs) have higher
placebo effects than others (such as
treatment for broken bones). Placebos can
also produce negative effects, called the
nocebo effect. Both placebo and nocebo
effects are real and produce symptoms
and relief that are indistinguishable from the
effects obtained from drug and other
physical treatments.

The placebo effect presents problems for
research because they prevent a clear
interpretation of treatment effectiveness.
Researchers try to control for placebo
effects by designing single-blind and
double-blind designs, arranging for
participants and even researchers to be
unaware of which participants receive a
placebo and which get active
treatment.

For research to contribute to knowledge
about health, scientists should be familiar
with one another's work, use controlled
methods, try to keep personal biases from
contaminating results, make claims
cautiously, and replicate their studies. To
understand behaviors related to health and
disease, researchers use a variety of
methods, including correlational studies,
cross-sectional and longitudinal studies,
experimental designs, and ex post facto
designs.

Correlational studies indicate the degree of
relationship between two variables, such as
the number of stressful life events and the
risk of heart attack. This approach is one
type of descriptive research. In
correlational studies, the relationship
between two variables is expressed in terms
of correlation coefficients. Coefficients
range from -1.00 to +1.00, with numbers
closer to ±1.00 indicating stronger
relationships. Attributions of cause and
effect are not possible from correlational
studies.

Cross-sectional studies are
conducted at one point in time and
compare people of different ages, whereas
longitudinal studies follow participants over
an extended period of time. Cross-sectional
studies can show differences between
groups. An advantage of longitudinal
studies is their ability to reveal
developmental trends, but they have the
disadvantage of taking a long time and
being expensive.

Experimental designs can determine cause
and effect relationships by manipulating an
independent variable and observing the
effect on a dependent variable, for
example, comparing an experimental
group on a low-fat diet (treatment group)
to participants who maintain their regular
diet (control group) and then measuring
the development of cardiovascular disease
(the dependent variable) in the two groups.
Well-controlled experimental designs give
scientists their best method to determine
causation.

Ex post facto designs are similar to experimental
designs in that both use contrasting groups, but these
designs do not include manipulation of independent
variables. Instead, groups of participants differing on
some subject variable are contrasted to determine
differences in the dependent variable. For example,
contrasting people with different educational and
occupational levels to determine the varying degree
of coronary artery disease is an ex post facto study.
The finding that different educational levels relate to
different rates of coronary artery disease does not
demonstrate that education is causally related to
heart disease because ex post facto studies do not
manipulate an independent variable or control for
other factors.

Epidemiology is a branch of medicine that investigates
factors contributing to the occurrence of a disease in a
particular population. Epidemiology evolved into a
scientific discipline during the 19th century and played an
important role in the fight against infectious diseases.
Today, epidemiologists also study factors associated with
chronic illness, including its prevalence and incidence.
Prevalence is the proportion of the population affected by
a particular disease at a particular time, whereas
incidence is the number of new cases of a disease during
a particular time, usually one year. Research methods
used in epidemiology are similar to those employed by
psychologists. Epidemiology research falls into three broad
areas: observational methods, natural experiments, and
experimental investigations.

Observational methods parallel correlation studies in
psychology. The two types of observational methods
are retrospective and prospective. Prospective
studies are longitudinal designs that follow the
forward development of a cohort, a group of people
starting an experience together. Retrospective
studies begin with a group of people already
experiencing a disease and then look for
characteristics of these people that are different from
those of people who do not have that disease.
Retrospective studies are also called case-control
studies because cases (people with a disease) are
compared with controls (people not affected).

Randomized, controlled trials are
equivalent to experiments in psychology.
Clinical trials are randomized, controlled
trials designed to test the effectiveness of a
drug or treatment. Researchers assign
participants to groups randomly to control
for self-selection. Randomized, placebocontrolled double-blind designs are often
considered the zenith of research design,
but comparative research indicates that
observational studies can yield similarly
valid results

Natural experiments are similar to ex post
facto studies in psychology; both involve
the selection rather than the
manipulation of a variable. Natural
experiments can be conducted when
two similar groups of people naturally
divide themselves into those exposed
and those not exposed to a pathogen.

Epidemiology provides techniques for
taking a first look at a health-related
problem. Two examples of these
techniques are the classical work of John
Snow and the more recent Alameda
County Study.

A dramatic example of epidemiological
research is the pioneering work of John
Snow during the 1848 cholera epidemic
in London. Snow found that homes
receiving water from one part of the
Thames River had much higher rates of
cholera than those who got their water
from other sections of the river. To slow
the spread of the disease, he simply shut
off the supply of polluted water.

The Alameda County Study began in 1965 in
an effort to identify certain health practices
that relate to subsequent mortality and
morbidity. Alameda County researchers found
that people who practiced six or seven basic
health-related behaviors were less likely to die
than those who practiced zero to three of
these behaviors. These health practices
included (1) getting seven or eight hours of
sleep daily, (2) eating breakfast almost every
day, (3) rarely eating between meals, (4)
drinking alcohol in moderation or not at all, (5)
not smoking, (6) exercising regularly, and (7)
maintaining weight near the prescribed ideal.

Most epidemiological studies do not
prove causation, rather, they point to
specific risk factors that are associated
with a particular disease or disorder.

A risk factor is any characteristic or condition
that occurs with greater frequency in people
with a disease than it does in people free from
that disease. Although they do not determine
causation, risk factors can be used to estimate
the probability of developing a disease.
Scientists using the risk factor approach must
distinguish relative risk from absolute risk.
Relative risk is the ratio between the number of
people in an exposed group with a disease
and the number in an unexposed group with
the disease. Absolute risk refers to a person's
chance of developing a disease independent
of the risk for other people.


?
Epidemiologists have gradually uncovered
evidence linking cigarette smoking to lung
cancer and heart disease. Although
scientists have no evidence from
experimental designs proving that cigarette
smoking causes heart disease and lung
cancer in humans, the accumulation and
consistency of other evidence has led
researchers to conclude that cigarette
smoking causes both heart disease and
lung cancer.

This evidence is based on seven conditions for determining
causation from nonexperimental research and shows that: (1) a
dose-response relationship exists between smoking and the
disease; that is, the more cigarettes a person smokes, the
greater the risk for heart disease and lung cancer; (2) the
prevalence and incidence of heart disease declines when
people stop smoking; (3) cigarette smoking precedes heart
disease and lung cancer; (4) the relationship between cigarette
smoking and disease is consistent with other data and makes
sense from a biological viewpoint; (5) research in this area yields
a consistent pattern of results—a pattern that has been
established through meta-analysis, a statistical technique that
allows the combination of information from several studies into
one analysis; (6) the size of the relative risk is large—about 23.0
for lung cancer; and (7) the evidence is based on a number of
well-designed studies. A combination of these criteria can allow
epidemiologists to determine causality from nonexperimental
designs
Health Psychology, 6/E by Linda Brannon and Jess Feist
Copyright  2007 Wadsworth Publishing, a division of Thomson Learning. All rights
reserved.


Theories and psychometric methods are
tools that researchers use to determine
areas of inquiry and to measure
variables essential to their research.

A theory can be defined as a set of related
assumptions that allow scientists to use
logical deductive reasoning to formulate
testable hypotheses. Theories are not idle
speculations but are useful tools in any
scientific discipline. Theory-based models
allow researchers to (1) organize data, (2)
render them meaningful, (3) generate
descriptive research, (4) test a variety of
hypotheses, and (5) follow a guideline for
working through daily problems.

Health psychologists, like other scientists,
use measuring instruments to test their
hypotheses and to build their theories. To
be useful, measuring devices must be
both reliable (consistent) and valid
(accurate).


The reliability of any measuring tool is the
extent to which that tool measures in a
consistent fashion. Reliability can be
established through test-retest and
interrater methods. Reliability is usually
expressed in terms of correlation
coefficients.

Measuring instruments can be reliable
(consistent) and yet lack validity
(accuracy or truthfulness). Validity is the
extent to which a measuring instrument
measures what it is designed to measure.
Predictive validity is an estimate of an
instrument's ability to predict which
participants will develop a particular
condition and which ones will remain
disease-free.