Directions for completing this assignmentIn this assignment, .docx

Directions for completing this assignment:
In this assignment, you will analyze the Student Computer Lab
case study (towards the end of this document). To effectively
meet the requirements of this assignment, analyze the
qualitative data derived from the primary research found in the
case study scenario.
To successfully complete this assignment, write a 3 page
critical essay in APA style format covering the following
topics:
1. Determine overall student satisfaction with the computer lab.
2. Do you think it was wise to have a group with both graduate
and undergraduate students included?
3. Analyze the focus group transcript very thoroughly. Make a
list of problems and ideas generated for the student computer
lab.
4. What do you see as the benefits and limitations of the focus
group findings? Do you think the task force plan for utilizing
the focus groups is appropriate?
5. What changes would you make to improve the problems or to
capitalize on the opportunities identified in the primary
research? Collect and describe student recommendations for
improvements.
Additional Requirements:
-APA citation
-Double-spaced
-Font size: 12
-Font: Time New Roman
-Title and Reference page

Case Scenario
Student Computer Lab
A major university served over 2,000 undergraduate and
graduate students majoring in business administration. The
large number of students enrolled in the Business School
coupled with increasing use of computer technology by faculty
and students created overwhelming demands on the Business
School’s computer center. In order to respond, the Business
School decided to upgrade its computer facilities.
Rod Stevenson, director of the Student Computer Center (SCC),
opened a new computer lab in the fall of 2007. The new lab
offered specialized software required by student courses and the
latest technology in hardware and software.
Computer Lab Project
After operating for six months, Stevenson recognized some
potential problems with the new computer lab. Although the
number of computers had doubled, student suggestions and
complaints indicated that the demand for computers at times
exceeded the available resources. To address this problem,
Stevenson established a task force to investigate the level of
student satisfaction with the computer lab. The task force was
made up of four graduate students and was established in
January 2008. The task force aimed to help the computer lab
identify student needs and provide suggestions on how those
needs could be most effectively met.

The first activity of the task force was to examine available
information on the lab and its functions and resources. Services
offered by the computer lab included network and printer
access. The lab usually had three to four lab monitors to collect
money for printouts and answer any of the student’s questions.
Lab hours were 8:00 a.m. to 9:30 p.m. on weekdays and 8:00
a.m. to 5:00on Saturdays and Sundays.
After reviewing available information on the lab, the task force
decided it needed to conduct some research before making
recommendations on the services offered. Exhibit 1 displays a
proposal written by the task force outlining the information to
be obtained and the time frame for the research.
Focus Group Study
Stevenson received the proposal and approved it. He agreed
with the task force’s use of focus groups to gain a
preliminary understanding of the students’ attitudes. The
focus groups would identify existing problems better than
secondary research, although the process of collecting and
analyzing the data would be more time consuming. After
receiving approval, the task force posted information around
the Business School to alert students that focus groups were
being conducted. Free laser copies were offered as an incentive
for participation. Students were selected based on their
interest. The student focus group was held on March 10, 2008.
Seven students participated, five graduate and two undergradu-
ate. Transcripts are provided in Exhibit 2.
Because one of the responsibilities of the lab monitors is to
assist students with questions and problems, separate focus
groups were also conducted on March 9, 2008, and March 11,
2008, with eight lab monitors. Information from both the
student and lab monitor focus groups was used as a guide
to develop questions for the second phase, a student survey.
Information from the focus groups was reduced to a list of key

issues, which were then categorized. An exhaustive list of state-
ments was devised to address potential user attitudes with
respect to each issue. When the list was complete, statements
were revised, combined, or eliminated to a set that succinctly
covered the original key issue categories. The questionnaire
was then pretested and finally administered to a sample of
students attending class in the Business School.
QuestionsDid the moderator do an adequate job of getting the
information needed by the SCC?Do you think it was wise to
have a group with both graduate and undergraduate students
included?Analyze the focus group transcript very thoroughly.
Make a list of problems and ideas generated for the student
computer lab.What do you see as the benefits and limitations of
the focus group findings? Do you think the task force plan for
utilizing the focus groups is appropriate?
1The contributions of Monika E. Wingate to the development of
this case are gratefully acknowledged. © Cengage Learning
Exhibit 1 Task Force Proposal
DATE: February 1, 2008 TO: Rod Stevenson
FROM: Computer Center Improvement Task Force RE:
Computer Lab Research Proposal
Background: In 2007, the Business School opened a new student
computer lab. Through suggestions and complaints, the SCC
realizes that there is a service delivery problem in that student
demand for computers at times exceeds available resources.
The aim of this research is to help the SCC identify student
needs and provide suggestions on how those needs can be most
effectively met. The results of this research will be limited to

the student computer lab. Other Business School computer
facilities, such as the computer classrooms and the multimedia
lab, are outside the scope of this project.
Objectives: The research objectives are as follows:Determine
overall student satisfaction with the labIdentify current problem
areasCollect student recommendations for improvements
Methodology: The research design is divided into two parts,
exploratory research followed by descriptive research. The
exploratory research would attempt to gain a better
understanding of students’ perceptions of the computer lab and
to identify the issues that concern them. The student survey
would aim to quantify the magnitude of these problems and to
develop recommendations.
Focus Groups: The task force feels that focus groups would be
the most appropriate method for exploratory research. Two sets
of focus groups are recommended. One set will focus on
students who use the computer lab, while the other will address
the lab monitors who deal with student problems on a daily
basis.
Student Survey: The focus group information would be used to
develop questions for a subsequent survey. Since the population
of interest is students enrolled in the Business School, this
survey would be administered to students attending classes
within the Business School, both graduates and undergraduates.
Time Schedule Completed By
Focus Groups March 11
Questionnaire Design April 2
Pretest Questionnaire April 9
Survey April 23
Data Analysis May 10

Exhibit 2
Student Focus Group Transcript
Moderator: I’m Robert from Professional Interviewing. I really
appreciate your participation in this group session. As you can
see, I am taping this session so I can review all of your
comments. We are here tonight to talk about the computer lab at
the Business School. As business students, you all have access
to the lab for your class assignments. How do you think the
computer lab is meeting your needs?
Lisa: I think there is a problem with the lab because the folks
who are using computers don’t know about computers. That’s
been reflected in the fact that you go to one computer and you
pick up a virus. These people don’t know anything about
viruses, they’re transmitting them all over the place, nobody is
scanning for viruses, and there’s something that could easily be
put on the systems.
Oliver: I think there has to be training for the people who are
watching the computers. They are ignorant. You ask them any
question and they can’t answer it. It’s a computer lab and this
computer doesn’t seem to be doing the thing that it should be
doing, why? Why is this network different from the rest? How
are we supposed to handle this network? They don’t know.
Lisa: Not only that, they don’t know any of the software.
Oliver: Absolutely!
Lisa: This is like I have Word at home and this is WordPerfect,
‘‘How do I do XYZ in WordPerfect?’’ They don’t know. They
say, let
me go check with John and it takes three of them to try to
answer the question. (Continued)
case 5 519

Exhibit 2
Student Focus Group Transcript (Continued)
Marion: And there are three of them!
Lisa: I know!
Oliver: There is always a big queue so you cannot get onto a
Windows machine; you have to go to Pagemaker Plus if you
need to make a presentation. You cannot go to these
WordPerfect machines that have just keyboard entries. But there
are very few computers and a lot of lines in the peak times and
they are just not equipped to handle it. They have so many staff
over there, five people, all of these people, but not one of them
will help anyone.
Moderator: How about you, Jennifer, have you experienced
this?
Jennifer: Yeah, I even had it today. I just don’t have time to
wait in line to get a computer. It’s a half hour sometimes to go
in and get one.
Lisa: And that’s now. At the end of the semester it’s worse.
Jennifer: Yeah, it gets worse.
Lisa: It takes an hour and there’s no sign-up. There’s no regular
sign-up.
Mike: They truncated the hours the last two weeks of the
semester.
Jennifer: You could take these four people and turn that into
one educated person, or take the four people and have one
uneducated person there 24 hours a day. That would be nice. If
all they’re going to do is take your card and give you your copy,
why do you have to have four of them? That’s all they’re doing.
And studying.
Moderator: How about you, I didn’t get your name?

Tammy: Tammy.
Moderator: Welcome, Tammy, how about you. What kind of
things have you come across?
Tammy: What I’m hearing are a lot of the problems I’ve seen,
too. I just think there needs to be more computers in the lab and
the hours need to be longer.
Mike: I don’t think they need more computers. They just need to
expand the hours and the computing labs.
Oliver: I had an idea where they don’t need more computers.
One suggestion I already put in the suggestion box is to have
people bring their own computers. Why doesn’t a grad student
who is going to be here for two years, going to interface with
technology when he leaves here, spend a thousand dollars and
go buy his own system? They should do that. Have your own
computer here, I’m saying it’s a requirement. It’s a requirement
at a lot of universities that you come with your own system.
Then you don’t have to worry, you don’t need access to our
labs. Now for undergraduates we still have similar problems,
but it would put less stress on the system.
Moderator: What would you suggest for people who would say,
okay I can get this computer system, but I have to get this
software for this class, and this software for this class, and this
software. That is a lot of money.
Oliver: Yeah, we can already jump into the network from home.
All you need is the software.
Lisa: I don’t think so.
Oliver: You can get in. I can check my mail and stuff.
Lisa: But not software.
Oliver: Oh, software. I haven’t tried, so I don’t know.
Tammy: Getting back to the machine. I’d love to have my own
machine but I don’t want to have it if I don’t have to. As long
as we have all these other computers, why not use what we’ve
got?
Mike: I can’t afford it. If you want to buy a good computer, a
decent printer, a decent monitor, you are still going to spend
between

$1,600 and $2,000.
Oliver: I think while we’re in school the school should support
us with computers.
Mike: I think one of the reasons there aren’t enough computers
is that people who aren’t enrolled in the Business School have
access to the lab. In the old building, they always checked your
ID.
Tammy: Yeah. Why don’t we use the card machines? They were
working, weren’t they? They had the doors closed and you used
a key card.
Oliver: I think the old lab was better because they controlled
people coming and going.
520 case 5
Exhibit 2
Mike: Yeah. Gatekeeping.
Tammy: They had hours when only graduate students could
come in. I think that’s something that should be started again
because they have a lot more papers to type up.
Mike: I don’t see why this lab isn’t open 24 hours. I really
don’t. Why aren’t the labs open 24 hours?
Lisa: Monitor problem, they need someone to monitor them, to
work with them.
Jennifer: Three people, three eight-hour shifts.
Mike: They don’t have a budget to increase their hours. They
need to double the hours, like not having four monitors at one
time.
Moderator: There are peak hours and there are hours that there

are a lot of open computers, where people don’t generally come
in. If there was a way to monitor those times and put a schedule
up, people could come in and indicate a time when we could go
there. Continually monitor that, what do you think about that?
Mike: Every hour is a peak hour, particularly at the end of the
semester.
Oliver: I think it would be a good way of trying to smooth it
out, because that’s what you are trying to do. Have people go
there when it’s not so busy. But then what about times like
today? I happened to get out of class one-half hour early and
went downstairs and used it. But if I hadn’t signed up early,
there were a million folks in there. There are some trade-offs,
but I think it’s a great idea to try and smooth it out. This
morning there were four of us in there at 8:00 or 8:15 when it
opened, and I don’t think anybody else showed up until 10:00.
Mike: Another problem in the lab right now is that there are a
lot of computers that are broken at one time.
Oliver: Oh yeah!
Mike: There are six of them right now that aren’t working.
Oliver: That’s from people not knowing what they are doing. I
was sitting down there on one of the old machines and there was
a gentleman sitting next to me who couldn’t figure out why it
wouldn’t work. He took his disk out and shut the computer off.
When it came back on it got a boot error. Then he got scared
and he just left. He didn’t go tell anyone. The monitors are
looking from the other side, so they don’t know there is
anything wrong. Someone comes in, they just look around, and
see that the computer is broken, or it’s not booted up, and so on.
That’s why I am saying, it’s the students themselves. People
need to know how to use the system.
Ira: I think there should be a small note pasted next to the
computers with instructions as to how to use each computer.
Marion: Even a template for the word processing.
Ira: Even a small hint for troubleshooting, please don’t do this
and do this.
Tammy: I think an excellent model for this are the computer

labs in the dorms. The first time you use them, they scan your
ID to
be sure you are a dorm resident, they know if it’s the first time
you are using it, they ask you to make sure you know how to
use the software. They have a rack with every different kind of
title and anything you need to use the software. They tell you
exactly what’s going to come up on the machine and what you
have to do. I’m sure the Business School can get copies of it all
and
then just copy it.
Marion: We have no reference guides for the software.
Tammy: And then they have the guides there. The little orange
books.
Moderator: Are there any other concerns we haven’t talked
about?
Ira: Is there any way the cost for a laser print can be reduced?
Tammy: It kills me.
Ira: It should be 7 cents. It is 6 cents in the library.
Tammy: You used to have the option to go to a dot matrix
printer. They changed that this semester. The only way to go to
the dot matrix was to go to an AT&T machine. Don’t tell me
someone is looking at cost.
Ira: I think the initial cost is pretty high, that is why they’re
keeping it at 10 cents.
Jennifer: If they are planning on getting more printers, I think
they should have at least one or two individual print stations
where you can grab your stuff. If you’re working on your
resume and you want to print on bond paper or do envelopes,
the people behind the desk won’t let you do it because they
don’t know if other people are going to send before you do, they
don’t know
what is going to come out. (Continued)
case 5 521

Exhibit 2
Oliver: Or they waste your paper because they can’t coordinate
it.
Jennifer: So I think there should be some individual
workstations.
Oliver: I have something to say and maybe I’m the only one
with this problem. I always find that when I go there and I am
working alone, other groups are creating a racket, so it’s really
frustrating. I’m working on a project, I need to think. I don’t
need this kind of heavy distraction, this loud talk. I go and work
in groups too, we try to whisper. There should be some kind of
discipline in the computer lab. I think I may be the only one
being that sensitive, but I think silence has to be maintained. It
is a computer lab,
it is a place for people working, if you’re having a fun time go
have it outside.
Moderator: How effective do you think their waiting lists
system is?
Tammy: It stinks.
Ira: I didn’t even know they had one.
Tammy: It would be better to set up a physical waiting list
where there would be chairs or a bench or something like that.
Ira: Or like a number.
Tammy: Or six chairs in a row and you sit down next to the
computers and that means you are next to get on; then if you
leave the next person can move down and then you can see that
no one is getting in front of you.
Oliver: It worked pretty well for me. Every time I used the
waiting list I had to wait for maybe a half hour and my name
was called and I could get a computer. I have no complaints.

This happened every time. There was no problem. I had no
problems at all.
Mike: Until now I didn’t even know there was a waiting list. If
there was an open computer, I would just sit down.
Tammy: I found out the hard way, I went down and sat down
and someone told me.
The paper only needs to be 1 page
•Provide a brief summary of the study.
•Describe the main findings.
•Discuss how this research advances the study of PNI
•Discuss what kind of follow-up research you think is needed in
this area.
•Be sure to include the full reference for the article you chose in
APA format.
REVIEW ARTICLE
Resources, Stress, and Immunity: An Ecological Perspective
on Human Psychoneuroimmunology
Suzanne C. Segerstrom, Ph.D.
Published online: 5 June 2010
# The Society of Behavioral Medicine 2010
Abstract Ecological immunology provides a broad theoret-

ical perspective on phenotypic plasticity in immunity, that is,
changes related to the value of immunity across different
situations, including stressful situations. Costs of a maxi-
mally efficient immune response may at times outweigh
benefits, and some aspects of immunity may be adaptively
suppressed. This review provides a basic overview of the
tenets of ecological immunology and the energetic costs of
immunity and relates them to the literature on stress and
immunity. Sickness behavior preserves energy for use by the
immune system, acute stress mobilizes “first-line” immune
defenders while suppressing more costly responses, and
chronic stress may suppress costly responses in order to
conserve energy to counteract the resource loss associated
with stress. Unexpected relationships between stress “buf-
fers” and immune functions demonstrate phenotypic plastic-
ity related to resource pursuit or preservation. In conclusion,
ecological models may aid in understanding the relationship
between stress and immunity.
Keywords Ecology. Optimism . Psychoneuroimmunology.
Sickness behavior. Social . Stress
Introduction
The days of belief that the immune system operates
autonomously are over. Demonstrations that the immune
system can be classically conditioned, that it is innervated
by the sympathetic nervous system, that it responds to
hormonal changes, that it has both circadian and circannual
rhythms, and that its changes correlate with changes in
psychological states such as emotion have all led to the
abandonment of the model of a “shielded” immune system
and the development of the field of psychoneuroimmunol-
ogy, the study of interrelationships among the mind,

nervous system, and immune system [1].
Immune changes that accompany stressful events have
perhaps garnered more scientific scrutiny than any other
topic in human psychoneuroimmunology. Meta-analytic
findings support the principle that psychologically stressful
events lasting anywhere from minutes to years associate
with changes in the immune system [2]. Ecological
immunology provides a broad theoretical perspective on
these changes. From the ecological perspective, the well-
being of an organism is maintained by efficiently matching
biological and behavioral priorities to the demands of the
environment. Unlike some other organs, the immune
system is necessary for survival mainly when an immuno-
logical challenge such as infection is present. In fact,
evidence suggests that too much tonic immunological
activity can lead to poor long-term health outcomes such
as the development of heart disease, Alzheimer’s disease,
frailty, and some kinds of cancer [3–5]. Therefore, robust
immune activity is undesirable except during immunolog-
ical challenge, and prioritizing immune function across all
situations may not be adaptive. Specifically, it may not
always be the fittest response to prioritize the immune
system’s demands for physiological resources1—which can
1 I will use the term “energy” to stand in for these physiological
resources so as to avoid confusion with the psychosocial
resources
that are the focus of the latter half of this review. However, it
should
be understood that this is a broad use of the term that could
encompass
not only physiological resources that are literally understood as
energy
(e.g., glucose, fatty acids) but also other proposed mediators
such as

proteins that act as transporters for these forms of physiological
fuel
(e.g., apolipophorin III; [89]).
S. C. Segerstrom (*)
Department of Psychology, University of Kentucky,
115 Kastle Hall,
Lexington, KY 40506-0044, USA
e-mail: [email protected]
ann. behav. med. (2010) 40:114–125
DOI 10.1007/s12160-010-9195-3
be considerable—above other potential demands. Under
some circumstances, suppressing immune function below
optimal levels in terms of protection against pathogens may
actually be to the overall benefit of the organism [6]. An
ecological perspective that places the functioning of the
immune system in an array of potential uses of energy has
the potential to explain the effects of immune activation on
motivation and behavior as well as diverse effects of
motivation and behavior on immune function in humans.
An ecological perspective is particularly useful in
understanding cases in which individual differences that
should act as buffers against stress sometimes act as
vulnerabilities. For example, epidemiological evidence
correlating smaller social networks with increased all-
cause mortality supports the idea that social relationships
buffer against stress and improve health [7]. There are,
however, some unusual and perplexing findings with regard
to the effects of social networks on immune function.
Larger social networks have associated with poorer cellular
immunity in healthy young adults and HIV patients [8, 9].
One study found that the increased risk of upper respiratory

infection that accompanies severe life stressors increased
further for those people with large social networks [10].
Social relationships are not the only “buffer” to predict
worse immunity. Dispositional optimism, the tendency to
expect more good events than bad in the future, often
predicts better cellular immune function during stressors
but almost equally often predicts worse function, usually
when stressors are more difficult or severe [11].
The Immune System and Its Energetic Costs
A comprehensive review of the immune system is beyond
the scope of this paper; the interested reader is referred to
immunology sources (e.g., Refs. [12, 13]) for more detailed
discussion of the immune components reviewed below. For
the purposes of this paper, it is most important to
understand the basic components of the immune system,
their functions, and the relative costs associated with those
functions [14].
The human immune system is made up of cells and
organs that protect the body against foreign invaders as well
as traitors within the ranks, that is, some types of cancerous
cells. Its first line of defense is the innate immune system, a
phylogenetically primitive subgroup of cells such as
neutrophils and macrophages that respond to nonspecific
signals of invasion such as tissue damage with an equally
nonspecific defense, inflammation. Inflammation is pro-
moted by proteins called cytokines, which are secreted by
these cells. Proinflammatory cytokines, including tumor
necrosis factor-α, interleukin (IL)-1, and IL-6, promote
local responses such as vasodilation and infiltration of
circulating immune cells into the affected tissue, as well as
systemic responses such as fever.

Although the inflammatory response is important for
early responses to infection, it is inadequate to control most
infections to the point of clearing them. A second line of
defense, the acquired2 immune system, is required. The
acquired immune system comprises groups of cells that
respond to specific antigenic stimulation, that is, specific
and unique signatures—antigens—expressed or produced
by invaders. For example, an antigen might be a viral
protein, a component of bacterial cell wall, or a bacterial
toxin. The antigen-specific lymphocytes that respond
include helper T cells, which release cytokines such as IL-
2, IL-4, IL-5, and IL-10 to activate and direct other immune
cells; cytotoxic T cells, which have the capacity to kill
compromised cells such as an epithelial cell infected by a
virus; and B cells, which produce antibody. Antibody can
attach to an invader and either inactivate it or target it for
killing by other cells.
Both innate and acquired immunities entail energetic
costs. Perhaps the best-recognized cost of innate immunity
is fever. It has been recognized for almost a century that
increases in body temperature come at metabolic costs,
estimated at 7–13% of daily metabolism per degree Celsius
[15–17]. The daily metabolic cost for mild (i.e., 1°C) fever
is comparable to the metabolic demands of the brain and
the heart [16].
In addition to the well-known cost of fever, two other
immune functions are particularly energetically costly:
protein production and clonal proliferation [18]. Immune
responses require cells to produce and secrete various
proteins including cytokines, cytotoxic proteins that will
effect the death of target cells, and antibody. In vitro,
stimulated cells increase oxygen consumption, an index of
metabolic rate, for the purpose of protein production by
70% [18]. In vivo, mice vaccinated with a benign antigen to

produce antibody increased their metabolic rate by 20–30%
in the absence of fever. In general, vaccination results in
15–30% increases in metabolic rate [15, 17]. Protein
production therefore entails significant energetic costs.
The costs of clonal proliferation are also significant. The
number of antigens for which a responsive T cell exists is
estimated in the millions, but there are not enough cells
with each antigen specificity present to effectively respond
to a challenge. As a consequence, when an antigen is
detected, the stimulated cell makes copies of itself, creating
an expanded population of cells capable of responding.
With regard to the costs of creating these cells, DNA
2 Also known as the adaptive branch of the immune system. The
term
“acquired” is used here to avoid confusion with the term
“adaptive” as
implied by evolutionary theory, that is, increasing fitness.
ann. behav. med. (2010) 40:114–125 115
replication alone increases in vitro oxygen consumption in
stimulated immune cells by 17% [18].
In sum, almost every function of immune cells requires
energy. As a consequence of the energetic demands of
immunity, energy availability significantly impacts immune
function. Although more work with humans is needed [19],
in animal models, caloric restriction in the diet and
reductions in body fat led to reduced expression of genes
associated with antigen processing and presentation and
antibody-mediated immune responses3, suppression of
immune functions, and increased risk of infection (see

Refs. [15, 17, 20] for reviews). Experimental surgical
removal of body fat from rodents caused them to respond
less effectively to vaccine than control animals. If they
regained body fat, their response returned to normal [21].
Suppression of costly immune functions is likely to be
an adaptive mechanism to preserve energy when it is at a
premium. Although it is not ideal to gamble with immunity,
it is possible for an organism to do so and survive,
particularly if the risk for infection is low and if energy
can be diverted to other systems or activities more
important to survival. In fact, organisms that fail to gamble
immunity may pay an even greater cost. One study
activated bumblebee immune systems with a benign
antigen, lipopolysaccharide (LPS). Under starvation con-
ditions, immune activation significantly shortened survival
time compared with control bumblebees. In short, energy
used by an activated immune system accelerated time to
death from starvation [22].
Ecological Immunology
An evolutionary, ecological perspective on behavior and
immunity predicts trade-offs between the costs and benefits
of immune activity. The basic principles are as follows (cf.,
Ref. [23]). Optimal immune responsiveness maximizes the
cost/benefit ratio. Circumstances can, of course, change
costs and benefits and therefore the optimum for immune
activity. Immunity is therefore expected to show “pheno-
typic plasticity” or “reaction norms”, that is, variability that
occurs when “the value of a trait ... varies in relationship to
one or more environmental variables” ([24], p. 1590).
Phenotypic plasticity is provided by the organism’s if–then
reaction norms: genetically encoded reactions to the
environment that can include changes in behavior and

immunity [24]. Reaction norms provide the flexibility to
respond to changing environmental circumstances and the
reordering of the organism’s priorities.
When an infection is present, the benefit of immune
activity increases, so optimal immune responsiveness
should increase. Likewise, when the cost of immune
activity increases, optimal immune responsiveness should
decrease. What are the costs of immunity? One that plays
an important role in ecological models is the opportunity
cost of the energy used by immune activity, that is, other
activities that could be pursued with the energy used by the
immune system. For example, maintaining immune func-
tion but failing to escape from a predator could impose a
very steep opportunity cost. Optimal immune function
could decrease in the presence of opportunities as well as
threats. Behavioral goal pursuit both demands energy and
improves reproductive opportunities, particularly when the
goal involves gaining status and resources that could
increase one’s value as a mate [25, 26]. When the
opportunity to gain such resources presents itself, the
opportunity costs of other energetic uses, such as immunity,
increase and optimal immune function should decrease,
particularly if both energy and resources are limited. The
range of situations that fall under the rubric of “stress” may
encompass more than one of these circumstances, so any
understanding of immunological responses to “stress”
needs to consider the potential priorities of the organism
in each specific situation. This paper will consider three
such situations: infection, acute or “fight or flight”
stressors, and chronic stressors. In each case, immunolog-
ical adaptations may maximize the cost/benefit ratio.
When Immunity is a Priority: Sickness Behavior
In the face of infection, the best chance of survival comes

from making energy available to the immune system. In a
practical sense, this means reducing other activities com-
peting for that energy. When infection is not a threat,
energy is well used by foraging for food, competing for and
attracting mates, and forming social bonds, and animals
(including humans) are motivated to engage in these
activities. When an infection is present, however, motiva-
tion and priorities should and do change.
A substantial body of evidence from nonhuman animals
demonstrates that when proinflammatory cytokines are
stimulated by the injection of LPS or are directly
administered, a series of behavioral changes ensues.
Affected animals reduce their activity levels and stop
exploring their environments, reduce their food intake and
grooming, lose interest in investigating new conspecifics in
3 The increases in longevity associated with long-term caloric
restriction do not appear to be mediated by improved immunity;
in
fact, caloric restriction is associated with poorer immunity.
Instead,
increased expression of tumor suppressor genes points to
decreased
rates of cancer as the major mechanism by which caloric
restriction
increases longevity. Increased expression of genes protective
against
oxidative stress may also play a role in the decreased rates of
neurodegenerative disorders and cardiovascular disease
observed with
caloric restriction [20].
116 ann. behav. med. (2010) 40:114–125

their environments, decrease sexual receptivity and behav-
ior (particularly in females), and increase sleep (particularly
non-rapid eye movement sleep) [27, 28]. One consequence
of these behavioral changes is less energy expended in
motivated behavior to acquire food, friends, and mates, and
more energy available to the immune system. Although low
motivation to eat may seem to work against the goal of
providing energy to the immune system, the energetic costs
of foraging may be more consequential during illness, food
metabolism may compete with immune function [29], or
some combination thereof. Therefore, it may be more
efficient to rely on stored energy during illness.
Sickness behavior is observed in humans who have high
levels of proinflammatory cytokines either from exogenous
administration as medical treatment or endogenous produc-
tion as a consequence of infection. Administration of
chemotherapeutic cytokines such as interferon-α stimulates
the release of endogenous proinflammatory cytokines. A
substantial number of patients receiving interferon-α
experience moderate to severe symptoms of sickness
behavior such as anhedonia, appetite disturbance, sleep
disturbance, and especially fatigue [30]. Acute, febrile
infections that are characterized by proinflammatory cyto-
kine production also produce sickness behavior. Patients
infected with pathogens such as Ross River virus, Epstein–
Barr virus, or Q fever reported even higher frequency of
sickness behavior than patients receiving interferon-α, with
over half reporting malaise, loss of appetite, and fatigue,
and all reporting anhedonia. Cells from patients with severe
symptoms also produced more proinflammatory cytokines
in culture than those from patients with mild symptoms,
consistent with the experimental evidence linking these
cytokines to sickness behavior [31].

At a phenomenological level, these changes may be the
consequence of anhedonia, so ordinarily rewarding activi-
ties such as eating, socializing, and sex are no longer of
interest to the sick individual. Anhedonia had the highest
correlation with proinflammatory cytokine production by
cells from pathogen-infected patients [31]. This and other
studies (e.g., Ref. [32]) suggest that infection decreases
appetitive motivations that might otherwise be priorities for
the animal, promoting energy-conserving behavior such as
sleep and withdrawal [33].
There is evidence that sickness behavior shows pheno-
typic plasticity. In this case, the “trait” of sickness behavior
varies in relationship to an evolutionarily important
situation: threats to young. Mouse dams were injected with
LPS. The resulting sickness behavior included deficits in
nest-building and time to retrieve pups removed from the
nest. However, these deficits were reversed by lowering the
ambient temperature [34]. Because mouse pups depend on
the nest to regulate their body temperature, their survival is
threatened if they are outside the nest when temperatures
drop. Under those circumstances, the dam’s sickness
behavior took a back seat to her motivation to protect her
offspring (as reflected in renewed alacrity in nest-building
and pup-retrieving).
When Survival is a Priority: Fight or Flight
When infection is present or the risk of infection is high, a
physiological shift that prioritizes availability of energy for
an immune response seems most adaptive. However, some
circumstances that pose a high risk of infection also
produce competing demands for energy. Such competition
occurs during acute stress responses, commonly described
as fight-or-flight responses.

The label “fight or flight” describes the behavioral
responses available when confronting situations such as
predation, storms, fires, or hostile peers, to name a few
likely stressors for early humans as well as other animals.
Both fighting and fleeing entail significant energetic
demand. In order to support this behavior, well-described
metabolic and physiological changes occur that support the
important actors in fight or flight: the muscles. Sympathetic
nervous system activation increases respiratory and heart
rates and directs blood to the heart and large muscles. With
increasing exertion, blood flow in the muscles increases
from 1,200 to 22,000 mm/min. Blood flow in the viscera,
however, decreases markedly. Blood flow to the kidney, for
example, decreases from 1,100 to 250 mm/min [35].
Sympathetic activation also provides increased fuel to
working muscles. Catecholamines mobilize stores of
glycogen and triacylglycerol to glucose and fatty acids that
can be used by muscles. Activation of the HPA axis and
secretion of cortisol also promotes conversion of glycogen
to glucose, although cortisol also inhibits the uptake of
glucose by muscle [36].
Along with changes in blood flow and metabolism come
changes in the immune system. The energetic costs of
fighting and fleeing would seem to dictate the opposite
pattern from that seen in sickness behavior: energy should
be directed away from the immune system and made
available to the heart and muscles. On the other hand, this
might not be the most ecologically adaptive response
because the circumstances that dictate fighting or fleeing
also increase risk of infection [2, 37]. Targets of predators
or human enemies, if they survive, would be likely to incur
scratches, punctures, or bites. Headlong flight from a storm
or flood might also involve injury such as scrapes from tree
branches. Any wound that breaks the barrier of the skin or

allows pathogens entry into the bloodstream is a candidate
for infection. Bacteria, for example, are omnipresent in the
environment, and most wounds are therefore contaminated
by definition [38]. Infections of wounds acquired during
ann. behav. med. (2010) 40:114–125 117
fight or flight were a common cause of death in ancestral
environments [39].
Acute stressors therefore pose a conundrum for the
organism. Provide too little energy to the muscles and risk
the possibility of death by predation, attack, or natural
disaster, or provide too little energy to the immune system
and risk the possibility of death by infection. Examination
of the kind of immune changes that occur during acute
stressors illustrates how this conundrum is solved. A meta-
analysis of studies of human participants challenged with
acute stressors indicated that there are a number of reliable
changes in the immune system during such tasks [2]. These
changes are energetically conservative but could provide
increased short-term protection against infection incurred
during fight or flight.
First, cells and proteins are redistributed. In particular,
there is a dramatic increase in the number of neutrophils
and natural killer cells in the blood. Neutrophils and natural
killer cells have in common their roles as innate first-line
defenders. Neutrophils are the first cells to respond to injury
or infection in the tissues and initiate further inflammatory
responses; natural killer cells contain viral infections until
antigen-specific T cell-mediated responses are possible.
Therefore, during acute stress, the blood becomes more
highly populated with cells that provide first-line defense. It

is important to note that there is little evidence that these
cells individually become more potent. For example,
natural killer cell cytotoxicity on the level of an individual
cell does not increase with acute stress [2].
Another potentially important redistribution involves the
release of antibody into secretions, particularly saliva.
Although the time frame of acute stressors is often too
short to permit the de novo synthesis of antibody,
preformed antibody is secreted at a faster rate, increasing
the density of potentially protective antibody in saliva.
Redistribution is perhaps the least energetically costly of
immune functions; by loading blood and saliva with first
responders, the immune system prepares itself for challenge
in an energetically conservative way.
Second, lymphocyte proliferation, particularly among T
cells, reliably decreases. Because proliferation is a costly
response of antigen-specific cells, it is not relevant to the
short-term, nonspecific responses that would be most
critical during acute threat of infection. Decreased prolifer-
ation during acute stressors could also be due to redistri-
bution, since not all T cells have equal proliferative
capacity. T cells are capable of a finite number of
replications; once that number has been reached, the cells
maintain their cytotoxic and cytokine-producing capabili-
ties but lose co-stimulatory molecules and the ability to
proliferate [40]. One possibility to explain the decrease in
T-cell proliferation during acute stress is that these cells are
distributed into the blood because they offer potential for
protection without the cost of proliferation. Supporting this
possibility, acute exercise differentially mobilized T cells
with restricted proliferative ability [41]. This redistribution
means that proliferative capabilities in other immune
compartments such as lymph nodes might be preserved or

even enhanced (as cells with low proliferative ability are
distributed out of the lymph nodes into the blood).
Compared with blanket suppression of T-cell proliferation,
a redistribution of T cells would be more adaptive insofar as
it preserves capacity for later antigen-specific responses in
immune compartments other than the blood.
Typical “fight or flight” stressors such as predation,
storms, fires, or fights, carry with them both the energetic
demand of fighting or fleeing (or both) and an increased
risk for infection. In this case, humans appear to have
adapted by associating acute stressors with immune
changes that could potentially provide better first-line
defense against infection at a low cost.
When Resources are a Priority: Sacrificing Immunity?
Unlike acute stressors, chronic stressors—those that last
from days to years—are not associated with changes in the
immune system that could lead to more robust immune
responses. Instead, these changes mostly involve decre-
ments in immune cell functions including proliferation,
cytotoxicity, cytokine production and secretion, and anti-
body production. These changes are seen during stressors
ranging in both severity and duration from academic
examinations to caring for a loved one with dementia.
The longer the stressor, the broader the changes, so that
stressors that last only a few days are more likely to affect
cellular (i.e., killer cell-mediated or Th1 functions), whereas
those that last months or years appear to affect both cellular
and humoral (i.e., antibody-mediated or Th2) functions [2].
Although acquired immunity appears to decrease during
chronic stress, innate immunity—particularly the produc-
tion of proinflammatory cytokines—may be increased [42].
One possibility is that innate immunity is being mustered to
provide a potentially less costly compensation for decreased

acquired immunity; another possibility, considered in more
detail later, is that the process of containing acquired
immunity results in innate immunity “escaping” from that
containment.
The dominant perspective on these changes is that
chronic stress perturbs homeostatic mechanisms in the
body and results in poorer immune functions in the cellular
arm, the humoral arm, or both. When the fight-or-flight
response, which was designed to meet short-term energetic
demands, is prolonged, undesirable consequences ensue
[43]. Changes in the immune system under chronic stress
therefore reflect maladaptive, chronic use of a system
118 ann. behav. med. (2010) 40:114–125
adapted to respond to acute threat and distress. This is a
reasonable and useful perspective as evidenced by its
influence and longevity in psychoneuroimmunology re-
search. However, it is not the only potential explanation
and, in fact, more than one mechanism may be acting at
once to influence the immune system during chronic stress.
From an ecological perspective, immunological changes
during chronic stress may reflect a change in priorities in
which the pursuit, protection, or restoration of resources
becomes more important, and optimal immunity becomes
less important.
An Ecological Perspective on Chronic Stress and Immunity
An ecological perspective does not assume that immuno-
logical responses to chronic stressors are necessarily
maladaptations. Instead, there may be a range of optima
in terms of immunocompetence depending on the circum-

stances. From this perspective, suppression of costly
immune functions such as decreased cytotoxicity or
antibody production can be adaptive because immunity is
located in an array of potential uses of energy, some of
which may be more important to the organism’s long-term
well-being, survival, or reproductive capacity. In fact, from
an evolutionary perspective, the ultimate measure of an
organism’s adaptive quality is not how well it fights
infection but how well it transmits genes to the next
generation. Fighting infection is important, but not at the
cost of reproductive opportunities or protection of off-
spring. As an example, Bateman’s principle of life-history
strategies states that longevity is more important to females’
fitness, whereas increasing mating rates are more important
to males’ fitness. This principle may explain the finding in
many species that females have stronger immune responses
than males [44].
Resources other than mating opportunities may “trump”
immunity. In murine models, pursuing as well as protecting
ecologically important social and environmental resources
were associated with poorer immunity against experimental
parasite exposure. Scent exposure that signaled upcoming
competition or a mating opportunity with another mouse
increased infection severity and duration [45]. Importantly,
olfactory signals of both the need to protect an existing
resource (in this case, social dominance protected from
another male mouse) and the opportunity to gain a new
resource (in this case, mating opportunity gained with a
female mouse) were associated with worse immunity
against the parasite. Another study randomly assigned
group-housed male mice to cages that were or were not
equipped with shelves and nestboxes, examining the effects
of providing “defendable resources” ([46], p. 1224).
Greater parasitic burden and longer infection occurred in
mice provided with these environmental resources. There-

fore, phenotypic plasticity in immunity against parasites
appears to occur in response to the need to both pursue and
protect social and environmental resources.
Decreases in costly immune responses in the service of
protecting threatened resources does not necessarily con-
tradict usual models of stress, since the “threat” of losing
resources could be appraised as stressful and result in
immune changes. Such decreases in the service of pursuing
possible new resources, however, provoke a broader
perspective in which this change takes place as “part of
an adaptive mechanism of physiological and behavioural
decision-making, rather than as simply an unwelcome
incidental cost” ([46], p. 1223).
Human Resources and Ecology
Important human resources overlap significantly with
important mouse resources. On the most basic level,
humans and mice share with many other organisms their
needs for physical energy, the means to replenish that
energy (e.g., food), and the ability to protect their physical
integrity (e.g., shelter). Among social species, acceptance
into a social group can mean sharing food and shelter, as
well as providing mutual protection from predators, so
social resources facilitate access to basic resources. Finally,
within a social group, status can provide more access to
food, shelter, and protection. Basic resources, social
resources, and status resources all contribute to the ultimate
outcome from an evolutionary perspective: representation
of one’s genes in subsequent generations.
Resource loss either implicitly or explicitly plays a role
in most theories of stress. Stress appraisal models accord a
lesser role to resources, predicting that stress occurs only

when demands tax or exceed available resources [47]. If
one has enough resources to “spend” in compensating for a
stressful event, these models propose that it is possible to
counteract the demands of stress. However, resource-
focused models are more expansive than appraisal models
in that they propose that any net resource loss is stressful
[48, 49]. Even if resources can be mustered to address the
stressor itself, the process of that mustering also creates
stress. Such loss may be felt acutely if resources in that
domain are already scarce; that is, loss is felt proportion-
ately to available resources [48, 50]. This model accounts
for some phenomena related to stress, resources, and health.
First, in the realm of status resources, there is a
continuous gradient between SES and health [51]. If the
protective value of income arose from having enough
money available to meet the demands of stressors, there
should be a nonlinear relationship between income and
health in which the greatest benefit comes with having
enough income to counteract common stressors (such as
parking tickets) or meet basic needs (such as living in a safe
ann. behav. med. (2010) 40:114–125 119
neighborhood). Living in a safe, luxurious neighborhood
should not provide much benefit above and beyond
living in a safe, middle-class neighborhood. The resource
model, however, predicts that stressors are felt—albeit
differentially—across the income spectrum. At the lower
end, a ticket that costs 10% of one’s monthly income is
more stressful than one that costs 5%, but likewise, at the
upper end, one that costs 0.05% is more stressful than
one that costs 0.01%.

Second, in the realm of social relationships, using social
resources does not buffer stress as well as having social
resources. Available social support is a better predictor of
health than received social support [52]; receiving social
support alleviates distress only to the extent that the
recipient is unaware of it [53]; and providing support to
others may be healthier than receiving support from others
[54]. One case in which receiving social support does seem
to be protective is when the recipient has a high level of
available resources [55]; as in the parking ticket example,
spending resources is healthier when doing so depletes a
smaller proportion of the resource pool. Social resources
seem to counteract stress and protect health to the extent
that individuals have them rather than spend them. This is
consistent with a resource model that proposes that building
resources rather than spending them buffers against
stressors.
In order to minimize stress, then, humans must expend
energy to maintain and pursue their resources. From the
perspective of ecological immunology, pursuit of goals and
resources reasonably and rationally changes optimum
immune function. If chronic stress can be effectively
defined as resource loss, immunosuppression under these
circumstances might be a mechanism that makes energy
available to preserve and renew lost resources.
Resources and Immunity: Evidence That More
is Sometimes Less
The basic premise of ecological immunology is that
immunity can be reduced in the service of other beneficial
uses of energy. In many vertebrates, chronic stressors
involve increased energy expenditure, decreased energy
sources, or both. During migration, drought, or famine,
animals may travel long distances to find scarce food or

water sources. Even chronic social conflict may compro-
mise an animal’s ability to acquire food, as when a
subordinate animal has food taken from it by a dominant
animal. These chronically stressful situations involve
energy imbalance arising from decreased energy availabil-
ity coupled with increased energy demand in trying to find
(and keep) food. Under such circumstances, it would be
adaptive to cut back on nonessential spending, especially
on costly projects such as immunity and reproduction.
Therefore, costly aspects of human immunity might be
adaptively suppressed during chronic stressors as a con-
served response to ancestral chronic stressors, which
usually and explicitly involved energy shortages.
If one also considers chronic stress to involve the
scarcity or loss of resources other than food and water,
human immunity might also be adaptively suppressed
during chronic stressors in order to protect, maintain, and
pursue those resources. For many vertebrates, these
activities might involve physical acts such as retrieving
offspring, competing for mates, and acquiring and defend-
ing territory such as a nestbox [34, 45, 46]. For humans,
these activities might involve the pursuit of maintaining and
acquiring resources such as socioeconomic status or social
integration. When resources are lost or threatened through
social conflict, bereavement, unemployment, and the like,
an adaptive response would be to redirect energy toward
rebuilding or compensating for those resources. This
response could account for some of the decreases in
immune function (e.g., in proliferation, protein production,
and cytotoxicity) observed during stressors such as marital
conflict, bereavement, and unemployment [2]. It might also
create empirical relationships that are unexpected: people
making stronger efforts to maintain or accumulate resources
might have poorer immune function than those making

weaker efforts, particularly if they are facing multiple
demands on their energy. In fact, several examples of just
such relationships exist. The largest number of examples
examines the relationships among stressors, social net-
works, and immune function, but there is also evidence that
personality factors associated with persistent goal pursuit
can yield similar findings.
Social Networks, Energy, and Immunity
Large and diverse social networks generally associate with
better immunity and longevity [7, 56]. They also take time
and energy to maintain. The number of social contacts
received and available social support are directly related to
efforts to initiate social contacts and provide social support
[57, 58]. Social resources, like other resources, are actively
built and maintained.
These building and maintenance activities, when com-
bined with other demands, may come at an energetic and
immunological cost. In a review of the literature on social
relationships and HIV infection, perceived availability of
social support was often associated with higher number of
CD4+ T cells (the cells selectively infected and destroyed
by the HIV virus), higher natural killer cell cytotoxicity,
later symptom onset, and longer survival [8]. This is
consistent with the finding that perceived social support is
the most salubrious kind [52]. Other social parameters, such
as social network size, were either unrelated to immunity
120 ann. behav. med. (2010) 40:114–125
and health or had negative consequences, particularly in
prospective studies. More anticipated social activity, greater

affinity with social networks, larger social networks, and
less loneliness were associated with faster CD4+ T-cell
decline, earlier symptom onset, and greater mortality [8].
The energetic costs of maintaining or even interacting with
large social networks may be detrimental to immunity and,
therefore, health in the context of chronic infection.
Paradoxical effects of social network size on immunity
have also been observed in healthy, young adults. For first-
year law students, one of the major challenges is balancing
curricular demands with extracurricular interests and activ-
ities, and finding time and energy to interact with
significant others such as friends and family is a significant
concern. Among first-year law students, relocation to attend
law school and attendant separation from established social
networks was associated with better cellular immunity as
measured by delayed-type hypersensitivity (DTH) testing.
Within-person changes in social network size across the
first six months of law school paralleled this between-
person finding: at those assessment points when a student
had more social contacts, he or she also had poorer cellular
immunity [9]. Although there might be a psychological
benefit to tonic and phasic engagement with one’s social
network, there also appears to be an immunological cost
associated with maintaining network contacts while also
meeting the demands of law school.
Finally, ecologically motivated changes in immunity
may have health consequences. A diary study of students
found that life events were associated with higher numbers
of clinically verified upper respiratory infections only
among students with large social networks [10]. One
potential explanation for this interaction among social
networks, stress, and infectious disease is that social
networks provide more opportunities for infection. Howev-
er, this explanation cannot suffice to explain differences in

response to DTH testing or studies of HIV infection in
which controls for potential reexposure were included (e.g.,
Ref. [59]).
Optimism, Energy, and Immunity
The potential energetic and immunological costs of social
networks are also evident in a series of studies focusing on
the consequences of stress and dispositional optimism.
Dispositional optimism reflects generalized expectations for
a positive future [60]. In turn, positive expectations result in
more goal-directed motivation and persistence both in and
out of the lab [61–64]. In law students, more optimistic
students should be expected to engage conflicts between
academic and social demands while their pessimistic
counterparts reduce their effort to meet curricular demands,
extracurricular demands, or both [63].
In three separate samples, optimism was negatively
correlated with cellular immunity (again, as measured by
DTH testing) in students who did not move away to attend
law school and positively correlated with cellular immunity
in students who did [65, 66]. These results reflect
phenotypic plasticity in response to energetic cost of goal
pursuit under demanding circumstances. In this case, the
cost is observed among individuals in the most demanding
context and with the greatest propensity to pursue and
protect goals and resources (i.e., optimists). A similar effect
has been observed in community-dwelling women. In this
sample, during short-term stressors (i.e., less demanding
circumstances), dispositional optimism correlated with
higher numbers of T cells. During long-term stressors (i.e.,
more demanding circumstances), however, dispositional
optimism correlated with lower numbers of T cells [67].
Similarly, in laboratory studies, dispositional optimism
predicted higher immune parameters (such as natural killer

cell cytotoxicity or skin test response) after less demanding
stressors or rest, but lower immune parameters after more
demanding stressors [68, 69]. In demanding circumstances,
optimists’ energetic efforts to overcome or master difficulties
and stressors appear to result in lower cellular immune
function than the withdrawal more typical of their pessimis-
tic counterparts.
These effects are, however, potentially interpretable in
another light. Specifically, it has been suggested that when
positive expectations are not borne out, optimism can result
in disappointment and distress and thereby compromise
immunity [67, 69, 70]. However, there is little evidence to
support this mechanism. Explicit tests of the effects of
disappointing situations do not show that optimists are
vulnerable relative to pessimists [66, 71, 72] or that
affective pathways mediate between optimism and DTH
responses [66].
Further Considerations
Can Traditional and Ecological Models Coexist?
Ecological effects do not eliminate the need for traditional
views of stress and stress buffers, and vice versa. For
example, the interaction between dispositional optimism
and social demands (as indexed by relocation) predicted
number of T cells and the immune response to DTH testing
in a manner consistent with the ecological model [65, 66],
but in the same samples, appraisals of law school as more
stressful correlated with lower natural killer cell cytotox-
icity and poorer response to DTH testing, more negative
daily mood correlated with poorer immune responses to
DTH testing, and more positive daily mood correlated with
more robust responses [66, 73, 74].

ann. behav. med. (2010) 40:114–125 121
Ideally, psychoneuroimmunology research should begin
to combine these perspectives to best understand changes in
the immune system that accompany stressors. Many
investigations into the relationship between stressors and
immunity have assessed stress appraisals or negative moods
directly, but the assessment of resources is rare. Resource
assessments for PNI studies could be standardized, as in the
Conservation of Resources Evaluation [50]; idiosyncratic to
situation, as in loss of possessions after an earthquake [75];
or idiographic, as in self-nominated resources pertinent to
current goals [76]. In any case, combining assessments of
resources and distress may yield fruitful insights into the
relationship between stress and immunity. These effects
may be additive: among hospital workers who experienced
the Northridge earthquake, both distress and resource loss
were independently associated with number of T cells [75].
It may also be important to examine the construct of
stress through an evolutionary or ecological lens in order to
determine what kind of response is demanded by the
stressor and what the adaptive response might be. One
principle of evolutionary science is that adaptations emerge
in response to specific challenges in the environment. The
nonspecificity of the term “stress” disguises the variety of
environmental challenges. Equating stress with threat and
the “fight or flight” response supposes that stressors should
invariably result in increased energy directed to the
periphery (through autonomic and neuroendocrine mecha-
nisms described above), particularly the muscles. Behavior
is the prioritized response. However, stress can also result
from an internal threat such as infection, in which case the
“protein production and proliferation” response of the

immune system should result and behavior will be
inhibited. Immunity is the prioritized response. Finally,
stress may also result from opportunities to acquire resources
that require self-regulatory responses. In this case, the needs
of the brain to “pause and plan” may take priority, with
energy directed away from the periphery [77]. Definitions of
stress as equivalent to threat may not be broad enough to
encompass all important situations in human ecology.
Chronic Stress and Proinflammatory Cytokines
Although stressors typically associate with decrements in
immunity in the cellular and humoral compartments, recent
evidence demonstrates that stressors, both acute and
chronic, are associated with higher levels of proinflamma-
tory cytokines [42, 78]. How does a potentially energy-
conserving mechanism (ecologically driven suppression of
immune functions such as cell proliferation and antibody
production during chronic stress) account for increased
levels of proinflammatory cytokines? One possibility is that
the mechanism by which acquired immunity is contained
eventually allows innate immunity to escape this contain-
ment. Tonic and phasic control over immune activity is
likely to be achieved via immunosuppressive mechanisms
such as corticosteroids. In animal models, withdrawing
corticosteroids via adrenalectomy results in a pathological
level of immune activity that can result in mortality from
autoimmunity or septic shock [79, 80]. Humans with
insufficient endogenous production of cortisol are also at
higher risk for death from septic shock, a risk that can be
ameliorated by administration of exogenous corticosteroids
[81]. Titration of immune activity to meet optimal levels is
likely to be achieved by greater or lesser degrees of
suppression, not by immune enhancement—the effects of
a merely unrestricted immune system are potent enough.

Prolonged exposure to elevated cortisol can alter the
sensitivity of receptors on immune cells and blunt its anti-
inflammatory potential [82]. These findings suggest that
after some time, ecologically titrated containment of the
immune system may fail. A similar failure as a consequence
of frequent or prolonged “fight or flight” responses has
been implied in the development of allostatic load (i.e., “the
wear and tear that results from chronic overactivity” of
stress response systems; [83], p. 171). The time course of
the progress from ecological allostasis to pathological
allostatic load will be an important area of further
investigation. The clinical implications of this failure are
not trivial, insofar as inflammatory escape can increase
health risk associated with proinflammatory cytokines such
as IL-6 [3–5], the energetic costs of this escape may reduce
availability of energetic resources for other systems (cf.
Ref. [22]), or both.
The Ecological Model and Long-term Implications
for Health
The basic premise of the ecological model is that costs (e.g.,
increased risk of infection) can be traded for benefits (e.g.,
resources or reproduction). Empirical tests of this proposition
in humans are needed, although the factors that are
associated with phasic reductions in immunity in healthy
adults (i.e., social network size and dispositional optimism)
in small-scale psychoneuroimmunology studies also tend to
be associated with better long-term health outcomes in
epidemiological and meta-analytic studies (e.g., Refs. [7,
84]). Therefore, the long-term health evidence suggests that
the immunological cost associated with protecting or
building resources may be more than offset by the longer-
term health advantage of having those resources.

Adamo [85] lists major problems in interpreting immune
function in light of disease resistance and health:
(1) correlations between assays of immunity and
disease resistance are typically pathogen specific, (2)
correlations between assays of immunity and disease
122 ann. behav. med. (2010) 40:114–125
resistance are sometimes weak or nonexistent, (3)
research suggests that some immune components
have a threshold value such that changes above that
threshold value may have no biological significance
(p. 1443).
These problems raise interesting questions about eco-
logical effects on immunity and their consequences for
health. For example, life history of pathogen exposure, as a
signal of what kinds of infectious threats exist in the
environment, might affect which immune components are
more or less susceptible to ecological effects. Immune
components that have been called into use may be less
susceptible. As another example, different populations may
differ in their “threshold value”, such that ecological effects
have health consequences for some populations (e.g., HIV
patients or the elderly) but not others (e.g., healthy children
or young adults).
Mechanisms of Ecological Effects on Immunity
Further investigations into the role of energy in stress-
related immune change and especially the mechanisms
involved are needed. Schmid-Hempel [86] noted that in the
ecological immunology literature, survival costs or reduc-

tion in physical condition during immune responses
become apparent only when additional energy challenge is
present (e.g., starvation), possibly because up to a point it is
possible to compensate for energetic demands (e.g., through
additional food intake). Hormonal pathways directly related
to energy and energy mobilization (e.g., cortisol) are
therefore obvious potential mediators between ecological
demands and immunological responses. However, others
have been proposed. Lessells [24] points out that energy
starvation per se may act as a mediator of ecologically
motivated immunosuppression, but it is “better to shut [the
immune system] down in an orderly fashion that allows
remaining resources to be used to maximum effect than to
starve it into inactivity” (p. 1593). The neuroendocrine
system is likely to provide signals about resources that
mediate ecological trade-offs with immunity. Testosterone
may account for immunological differences between the
sexes that conform to the Bateman principle, although such
sex differences also exist in invertebrates that lack
testosterone [44]. Leptin, a hormone secreted by adipose
tissue (i.e., body fat), has been suggested as a signal to the
immune system about the amount of energy available to the
organism [15]. Melatonin has been proposed to signal
energetic trade-offs related to the seasons, including
immunological trade-offs [87]. Finally, others (e.g., Refs.
[88]) have argued that lack of energy may not entirely
mediate the negative effects of stress on the immune
system. Rather, an increase in energy turnover or metabolic
rate during stress could increase the production of free
radicals that damage the immune system and prevent it
from functioning effectively.
Conclusion
An ecological approach to the relationship between stress

and immune function specifies that immune function may
be sacrificed to meet other goals, a process that does not
necessary imply threat but incorporates the idea of limited
energetic resources. This approach can account for immune
responses to both acute and chronic stressors, as well as
seemingly paradoxical effects of stress buffers such as
social network size and optimism on immune function.
Acknowledgements The author thanks David Westneat and
Gregory
E. Miller for their helpful comments on an earlier version of the
manuscript.
References
1. Ader R, Felten DL, Cohen N. Psychoneuroimmunology. 3rd
ed.
San Diego: Academic Press; 2001.
2. Segerstrom SC, Miller GE. Psychological stress and the
human
immune system: A meta-analytic study of 30 years of inquiry.
Psychol Bull. 2004;130:601-630.
3. Ershler WB, Keller ET. Age-associated increased interleukin-
6
gene expression, late-life diseases, and frailty. Ann Rev Med.
2000;51:245-270.
4. Kiecolt-Glaser JK, Glaser R. Depression and immune
function:
Central pathways to morbidity and mortality. J Psychosom Res.
2002;53:873-876.
5. Papanicolaou DA, Wilder RL, Manolagas SC, Chrousos GP.
The

pathophysiologic roles of interleukin-6 in human disease. Ann
Int
Med. 1998;128:127-137.
6. Viney ME, Riley EM, Buchanan KL. Optimal immune
responses:
Immunocompetence revisited. Trends Ecol Evol. 2005;20:665-
669.
7. House JS, Landis KR, Umberson D. Social relationships and
health. Science. 1988;241:540-545.
8. Miller GE, Cole SW. Social relationships and the progression
of
human immunodeficiency virus infection: A review of evidence
and possible underlying mechanisms. Ann Behav Med.
1998;20:181-189.
9. Segerstrom SC. Social networks and immunosuppression
during
stress: Relationship conflict or energy conservation? Brain
Behav
Imm. 2008;22:279-284.
10. Hamrick N, Cohen S, Rodriguez MS. Being popular can be
healthy or unhealthy: Stress, social network diversity, and
incidence of upper respiratory infection. Health Psychol.
2002;21:294-298.
11. Segerstrom SC. Optimism and immunity: Do positive
thoughts
always lead to positive effects? Brain Behav Imm. 2005;19:195-
200.
12. Clark WR. In defense of self: How the immune system
really

works. New York: Oxford University Press; 2008.
13. Rabin BS. Stress, immune function, and health: The
connection.
New York: Wiley; 1999.
ann. behav. med. (2010) 40:114–125 123
14. Lee KA. Linking immune defenses and life history at the
levels of
the individual and the species. Int Comp Biol. 2006;46:1000-
1015.
15. Demas GE. The energetics of immunity: A neuroendocrine
link
between energy balance and immune function. Horm Behav.
2004;45:173-180.
16. Elia M. Organ and tissue contribution to metabolic rate. In:
Kinney JM, Tucker HN, eds. Energy metabolism: Tissue
determinants and cellular corollaries. New York: Raven Press;
1992:61-79.
17. Lochmiller RL, Deerenberg C. Trade-offs in evolutionary
immu-
nology: Just what is the cost of immunity? OIKOS. 2000;88:87-
98.
18. Buttgereit F, Burmester GR, Brand MD. Bioenergetics of
immune
functions: Fundamental and therapeutic aspects. Immunol
Today.
2000;21:192-199.

19. Norgan NG. The beneficial effects of body fat and adipose
tissue
in humans. Int J Obesity. 1997;21:738-746.
20. Swindell WR. Comparative analysis of microarray data
identifies
common responses to caloric restriction among mouse tissues.
Mech Ageing Dev. 2008;129:138-153.
21. Demas GE, Drazen DL, Nelson RJ. Reductions in total body
fat
decrease humoral immunity. Proc Roy Soc London B.
2003;270:905-911.
22. Moret Y, Schmid-Hempel P. Survival for immunity: The
price of
immune system activation for bumblebee workers. Science.
2000;290:1166-1168.
23. Råberg L, Grahn M, Hasselquist D, Svensson E. On the
adaptive
significance of stress-induced immunosuppression. Proc Roy
Soc
London B. 1998;265:1637-1641.
24. Lessells CM. Neuroendocrine control of life histories: What
do we
need to know to understand the evolution of phenotypic
plasticity? Phil Trans R Soc B. 2008;363:1589-1598.
25. Barnard CJ, Behnke JM. From psychoneuroimmunology to
ecological immunology: Life history strategies and immunity
trade-offs. In: Ader R, Felton DL, Cohen N, eds. psychoneur-
oimmunology. 3rd ed. San Diego: Academic Press; 2001:35-47.
26. Kirkwood TBL. Repair and its evolution: Survival versus

reproduction. In: Townsend CR, Calow P, eds. Physiological
ecology: An evolutionary approach to resource use. Boston:
Blackwell Scientific; 1981:165-189.
27. Dantzer R, Bluthé RM, Castanon N, et al. Cytokine effects
on
behavior. In: Ader R, Felton DL, Cohen N, eds. Psychoneur-
oimmunology. 3rd ed. San Diego: Academic Press; 2001:703-
727.
28. Larson SJ, Dunn AJ. Behavioral effects of cytokines. Brain
Behav
Immun. 2001;15:371-387.
29. Adamo SA, Fidler TL, Forestell CA. Illness-induced
anorexia and
its possible function in the caterpillar, Manduca sexta. Brain
Beh
Immun. 2007;21:292-300.
30. Capuron L, Miller AH. Cytokines and psychopathology:
Lessons
from interferon-α. Biol Psychiatr. 2004;56:819-824.
31. Vollmer-Conna U, Fazou C, Cameron B, et al. Production of
pro-
inflammatory cytokines correlates with the symptoms of acute
sickness behavior in humans. Psychol Med. 2004;34:1289-1297.
32. Yirmiya R. Endotoxin produces a depressive-like episode in
rats.
Brain Res. 1996;711:163-174.
33. Dantzer R, Kelley KW. Twenty years of research on
cytokine-
induced sickness behavior. Brain Beh Imm. 2007;21:153-160.

34. Aubert A, Goodall G, Dantzer R, Gheusi G. Differential
effects of
lipopolysaccharide on pup retrieving and nest building in
lactating
mice. Brain Beh Immun. 1997;11:107-118.
35. Papillo JF, Shapiro D. The cardiovascular system. In:
Cacioppo
JT, Tassinary LG, eds. Principles of psychophysiology:
Physical,
social, and inferential elements. New York: Cambridge
University
Press; 1990:456-512.
36. Frayn KN. Metabolic regulation: A human perspective.
Malden,
MA: Blackwell; 2003.
37. O’Leary A. Stress, emotion, and human immune function.
Psychol Bull. 1990;108:363-382.
38. Williams NA, Leaper DJ. Infection. In: Leaper DJ, Harding
KG,
eds. Wounds: Biology and management. New York: Oxford
University Press; 1998:71-87.
39. Finch CE. Evolution of the human lifespan and diseases of
aging:
Roles of infection, inflammation, and nutrition. PNAS.
2010;107:1718-1724.
40. Effros RB, Pawelec G. Replicative senescence of T cells:
Does the
Hayflick limit lead to immune exhaustion? Immunol Today.
1997;18:450-454.

41. Campbell JP, Riddell NE, Burns VE, et al. Acute exercise
mobilizes CD8+ T lymphocytes exhibiting an effector-memory
phenotype. Brain Beh Immun. 2009;23:767-775.
42. Robles TF, Glaser R, Kiecolt-Glaser JK. Out of balance: A
new
look at chronic stress, depression, and immunity. Curr Dir
Psychol Sci. 2005;14:111-115.
43. Sapolsky RM. Why zebras don’t get ulcers: A guide to
stress,
stress-related diseases, and coping. New York: Freeman; 1994.
44. Rolff R. Bateman’s principle and immunity. Proc R Soc
Lond B.
2002;269:867-872.
45. Smith FV, Barnard CJ, Behnke JM. Social odours, hormone
modulation, and resistance to disease in male laboratory mice,
Mus musculus. Animal Beh. 1996;52:141-153.
46. Barnard CJ, Behnke JM, Sewell J. Environmental
enrichment,
immunocompetence, and resistance to Babesia microti in male
mice. Physiol Behav. 1996;60:1223-1231.
47. Lazarus RS, Folkman S. Stress, appraisal, and coping. New
York:
Springer; 1984.
48. Hobfoll SE. The ecology of stress. New York: Hemisphere;
1988.
49. Hobfoll SE. Conservation of resources: A new attempt at
conceptualizing stress. Amer Psychol. 1989;44:513-524.

50. Hobfoll SE. Stress, culture, and community: The psychology
and
philosophy of stress. New York: Plenum; 1998.
51. Gallo LC, Matthews KA. Understanding the association
between
socioeconomic status and physical health: Do negative emotions
play a role? Psychol Bull. 2003;129:10-51.
52. Smith C, Fernengel K, Holcroft C, Gerald K, Marien L.
Meta-
analysis of the associations between social support and health
outcomes. Ann Behav Med. 1994;16:352-362.
53. Bolger N, Zuckerman A, Kessler RC. Invisible support and
adjustment to stress. J Pers Soc Psychol. 2000;79:953-961.
54. Brown SL, Nesse RM, Vinokur AD, Smith DM. Providing
social
support may be more beneficial than receiving it: Results from a
prospective study of mortality. Psychol Sci. 2003;14:320-327.
55. Riley D, Eckenrode J. Social ties: Subgroup differences in
costs
and benefits. J Pers Soc Psychol. 1986;51:770-778.
56. Uchino BN, Cacioppo JT, Kiecolt-Glaser JK. The
relationship
between social support and physiological processes: A review
with emphasis on underlying mechanisms and implications for
health. Psychol Bull. 1996;119:488-531.
57. Epstein S. The stability of behavior: On predicting most of
the
people much of the time. J Pers Soc Psychol. 1979;37:1097-

1126.
58. Gottlieb BH. Social support and social participation among
residents of a married student housing complex. J Coll Student
Personnel. 1981; January: 46-52.
59. Miller GE, Kemeny ME, Taylor SE, Cole SW, Visscher B.
Social
relationships and immune processes in HIV seropositive gay and
bisexual men. Ann Behav Med. 1997;19:139-151.
60. Scheier MF, Carver CS. Optimism, coping, and health:
Assess-
ment and implication of generalized outcome expectancies.
Health
Psychol. 1985;4:219-247.
61. Carver CS, Blaney PH, Scheier MF. Reassertion and giving
up:
The interactive role of self-directed attention and outcome
expectancy. J Pers Soc Psychol. 1979;37:1859-1870.
124 ann. behav. med. (2010) 40:114–125
62. Scheier MF, Carver CS. Self-consciousness, outcome
expectancy,
and persistence. J Res Person. 1982;16:409-418.
63. Segerstrom SC. L. When goals conflict but people prosper:
The
case of dispositional optimism. J Res Pers. 2006;40:675-693.
64. SolbergNes L, Segerstrom SC, Sephton SE. Engagement and
arousal: Optimism’s effects during a brief stressor. Pers Socl

Psychol Bull. 2005;31:111-120.
65. Segerstrom SC. Optimism, goal conflict, and stressor-
related
immune change. J Behav Med. 2001;24:441-467.
66. Segerstrom SC. How does optimism suppress immunity?
Evalua-
tion of three affective pathways. Health Psychol. 2006;25:653-
657.
67. Cohen F, Kearney KA, Zegans LS, Kemeny ME, Neuhaus
JM,
Stites DP. Differential immune system changes with acute and
persistent stress for optimists vs. pessimists. Brain Beh Immun.
1999;13:155-174.
68. Segerstrom SC, Castaneda JO, Spencer TE. Optimism
effects on
cellular immunity: Testing the affective and persistence models.
Pers Ind Diff. 2003;35:1615-1624.
69. Sieber WJ, Rodin J, Larson L, et al. Modulation of human
natural
killer cell activity by exposure to uncontrollable stress. Brain
Beh
Imm. 1992;6:141-156.
70. Tennen H, Affleck G. The costs and benefits of optimistic
explanations and dispositional optimism. J Pers. 1987;55:377-
393.
71. Litt MD, Tennen H, Affleck G, Klock S. Coping and
cognitive
factors in adaptation to in vitro fertilization failure. J Behav
Med.

1992;15:171-187.
72. Stanton AL, Snider PR. Coping with a breast cancer
diagnosis: A
prospective study. Health Psychol. 1993;12:16-23.
73. Segerstrom SC, Sephton SE. Optimistic expectancies and
cell-
mediated immunity: The role of positive affect. Psychol Sci.
2010;21:448-455.
74. Segerstrom SC, Taylor SE, Kemeny ME, Fahey JL.
Optimism is
associated with mood, coping, and immune change in response
to
stress. J Pers Soc Psychol. 1998;74:1646-1655.
75. Solomon GF, Segerstrom SC, Grohr P, Kemeny M, Fahey J.
Shaking up immunity: Psychological and immunological
changes
after a natural disaster. Psychosom Med. 1998;59:114-127.
76. Diener E, Fujita F. Resources, personal strivings, and
subjective
well-being: A nomothetic and idiographic approach. J Pers Soc
Psychol. 1995;68:926-935.
77. Segerstrom SC, Hardy JK, Evans DR, Winters NF. “Pause
and
plan”: Self-regulation and the heart. In: Gendolla G, Wright R,
eds. Motivational Perspectives on Cardiovascular Response.
Washington, DC: American Psychological Association; in
press.
78. Steptoe A, Maner M, Chida Y. The effects of acute
psychological stress on circulating inflammatory factors in

humans: A review and meta-analysis. Brain Beh Imm.
2007;21:901-912.
79. Bertini R, Bianchi M, Ghezzi P. Adrenalectory sensitizes
mice to
the lethal effects of interleukin-1 and tumor necrosis factor. J
Exp
Med. 1988;167:1708-1712.
80. Webster JI, Tonelli L, Sternberg EM. Neuroendocrine
regulation
of immunity. Ann Rev Immunol. 2002;20:125-263.
81. Siraux V, De Backer D, Yalavatti G, et al. Relative adrenal
insufficiency in patients with septic shock: Comparison of low-
dose and conventional corticotropin tests. Crit Care Med.
2005;33:2479-2486.
82. Miller GE, Cohen S, Ritchey AK. Chronic psychological
stress and
the regulation of pro-inflammatory cytokines: A glucocorticoid-
resistance model. Health Psychol. 2002;21:531-541.
83. McEwen BS. Protective and damaging effects of stress
mediators.
New England J Med. 1998;338:171-179.
84. Rasmussen HN, Scheier MF, Greenhouse JB. Optimism and
physical health: A meta-analytic review. Ann Behav Med.
2009;37:239-256.
85. Adamo SA. How should behavioural ecologists interpret
measure-
ments of immunity? Animal Beh. 2004;68:1443-1449.
86. Schmid-Hempel P. Variation in immune defence as a

question of
evolutionary ecology. Proc Roy Soc London B. 2003;270:357-
366.
87. Nelson RJ. Seasonal immune function and sickness
responses.
Trends Immunol. 2004;25:187-192.
88. Svensson E, Råberg L, Koch C, Hasselquist D. Energetic
stress,
immunosuppression, and the costs of an antibody response.
Funct
Ecol. 1998;12:912-919.
89. Adamo SA, Roberts JL, Easy RH, Ross NW. Competition
between immune function and lipid transport for the protein
apolipophorin III leads to stress-induced immunosuppression in
crickets. J Exp Biol. 2008;211:531-538.
ann. behav. med. (2010) 40:114–125 125
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